From 3df29bd654093e8507882022c6f1136e9f46994f Mon Sep 17 00:00:00 2001 From: HGSilveri Date: Thu, 13 Jul 2023 18:33:44 +0200 Subject: [PATCH 01/18] Bump version to 0.15dev0 --- VERSION.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION.txt b/VERSION.txt index a803cc22..0fc46372 100644 --- a/VERSION.txt +++ b/VERSION.txt @@ -1 +1 @@ -0.14.0 +0.15dev0 From f56a19fe0a8d8853bb43d3369387002497c85ae9 Mon Sep 17 00:00:00 2001 From: HGSilveri Date: Thu, 13 Jul 2023 18:48:01 +0200 Subject: [PATCH 02/18] Remove expired deprecations in pulser-pasqal --- pulser-pasqal/pulser_pasqal/__init__.py | 1 - pulser-pasqal/pulser_pasqal/job_parameters.py | 65 ---------- pulser-pasqal/pulser_pasqal/pasqal_cloud.py | 87 +------------ tests/test_pasqal.py | 117 +----------------- 4 files changed, 2 insertions(+), 268 deletions(-) delete mode 100644 pulser-pasqal/pulser_pasqal/job_parameters.py diff --git a/pulser-pasqal/pulser_pasqal/__init__.py b/pulser-pasqal/pulser_pasqal/__init__.py index 6f9c57bf..8f102053 100644 --- a/pulser-pasqal/pulser_pasqal/__init__.py +++ b/pulser-pasqal/pulser_pasqal/__init__.py @@ -17,5 +17,4 @@ from pulser_pasqal._version import __version__ from pulser_pasqal.backends import EmuFreeBackend, EmuTNBackend -from pulser_pasqal.job_parameters import JobParameters, JobVariables from pulser_pasqal.pasqal_cloud import PasqalCloud diff --git a/pulser-pasqal/pulser_pasqal/job_parameters.py b/pulser-pasqal/pulser_pasqal/job_parameters.py deleted file mode 100644 index d2ddb0a8..00000000 --- a/pulser-pasqal/pulser_pasqal/job_parameters.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright 2022 Pulser Development Team -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -"""Parameters to build a sequence sent to the PASQAL cloud plaftorm.""" -from __future__ import annotations - -import dataclasses -from typing import Dict, Mapping, Optional, Union - -from numpy.typing import ArrayLike - -from pulser.register import QubitId - -JobVariablesDict = Dict[str, Union[ArrayLike, Optional[Mapping[QubitId, int]]]] - - -class JobVariables: - """Variables to build the sequence.""" - - def __init__( - self, - qubits: Optional[Mapping[QubitId, int]] = None, - **vars: Union[ArrayLike, float, int], - ): - """Initializes the JobVariables class. - - Args: - qubits: A mapping between qubit IDs and trap IDs used to define - the register. Must only be provided when the sequence is - initialized with a MappableRegister. - vars: The values for all the variables declared in this Sequence - instance, indexed by the name given upon declaration. Check - ``Sequence.declared_variables`` to see all the variables. - """ - self._qubits = qubits - self._vars = vars - - def get_dict(self) -> JobVariablesDict: - """Creates a dictionary used by the Sequence building and the cloud.""" - return {"qubits": self._qubits, **self._vars} - - -@dataclasses.dataclass -class JobParameters: - """Parameters representing a job to build the sequence.""" - - runs: int - variables: JobVariables - - def get_dict(self) -> dict[str, Union[int, JobVariablesDict]]: - """Creates a dictionary to send to the cloud.""" - return dict( - runs=self.runs, - variables=self.variables.get_dict(), - ) diff --git a/pulser-pasqal/pulser_pasqal/pasqal_cloud.py b/pulser-pasqal/pulser_pasqal/pasqal_cloud.py index 1173e472..5d385f4e 100644 --- a/pulser-pasqal/pulser_pasqal/pasqal_cloud.py +++ b/pulser-pasqal/pulser_pasqal/pasqal_cloud.py @@ -16,9 +16,8 @@ import copy import json -import warnings from dataclasses import fields -from typing import Any, Optional, Type, cast +from typing import Any, Type, cast import backoff import numpy as np @@ -40,7 +39,6 @@ from pulser.devices import Device from pulser.json.abstract_repr.deserializer import deserialize_device from pulser.result import Result, SampledResult -from pulser_pasqal.job_parameters import JobParameters EMU_TYPE_TO_CONFIG: dict[pasqal_cloud.EmulatorType, Type[BaseConfig]] = { pasqal_cloud.EmulatorType.EMU_FREE: EmuFreeConfig, @@ -233,86 +231,3 @@ def _convert_configuration( pasqal_config_kwargs["dt"] = 1.0 / config.sampling_rate return emu_cls(**pasqal_config_kwargs) - - def create_batch( - self, - seq: Sequence, - jobs: list[JobParameters], - emulator: pasqal_cloud.EmulatorType | None = None, - configuration: Optional[pasqal_cloud.BaseConfig] = None, - wait: bool = False, - fetch_results: bool = False, - ) -> pasqal_cloud.Batch: - """Create a new batch and send it to the API. - - For Iroise MVP, the batch must contain at least one job and will be - declared as complete immediately. - - Args: - seq: Pulser sequence. - jobs: List of jobs to be added to the batch at creation. - emulator: TThe type of emulator to use. If set to None, the device - will be set to the one stored in the serialized sequence. - configuration: Optional extra configuration for emulators. - wait: Whether to wait for the batch to be done. - fetch_results: Whether to download the results. Implies waiting for the batch. # noqa: 501 - - Returns: - Batch: The new batch that has been created in the database. - """ - with warnings.catch_warnings(): - warnings.simplefilter("always", DeprecationWarning) - warnings.warn( - "'PasqalCloud.create_batch()' is deprecated and will be " - "removed after v0.14. To submit jobs to the Pasqal Cloud, " - "use one of the remote backends (eg QPUBackend, EmuTNBacked," - " EmuFreeBackend) with an open PasqalCloud() connection.", - category=DeprecationWarning, - stacklevel=2, - ) - - if emulator is None and not isinstance(seq.device, Device): - raise TypeError( - "To be sent to a real QPU, the device of the sequence " - "must be a real device, instance of 'Device'." - ) - - for params in jobs: - seq.build(**params.variables.get_dict()) # type: ignore - - return self._sdk_connection.create_batch( - serialized_sequence=seq.to_abstract_repr(), - jobs=[j.get_dict() for j in jobs], - emulator=emulator, - configuration=configuration, - wait=wait, - fetch_results=fetch_results, - ) - - def get_batch( - self, id: str, fetch_results: bool = False - ) -> pasqal_cloud.Batch: - """Retrieve a batch's data and all its jobs. - - Args: - id: Id of the batch. - fetch_results: Whether to load job results. - - Returns: - Batch: The batch stored in the database. - """ - with warnings.catch_warnings(): - warnings.simplefilter("always", DeprecationWarning) - warnings.warn( - "'PasqalCloud.get_batch()' is deprecated and will be removed " - "after v0.14. To retrieve the results from a job executed " - "through the Pasqal Cloud, use the RemoteResults instance " - "returned after calling run() on one of the remote backends" - " (eg QPUBackend, EmuTNBacked, EmuFreeBackend) with an open " - "PasqalCloud() connection.", - category=DeprecationWarning, - stacklevel=2, - ) - return self._sdk_connection.get_batch( - id=id, fetch_results=fetch_results - ) diff --git a/tests/test_pasqal.py b/tests/test_pasqal.py index ae670acf..5124c289 100644 --- a/tests/test_pasqal.py +++ b/tests/test_pasqal.py @@ -32,13 +32,11 @@ SubmissionStatus, ) from pulser.devices import Chadoq2 -from pulser.register import Register from pulser.register.special_layouts import SquareLatticeLayout from pulser.result import SampledResult from pulser.sequence import Sequence -from pulser_pasqal import BaseConfig, EmulatorType, Endpoints, PasqalCloud +from pulser_pasqal import EmulatorType, Endpoints, PasqalCloud from pulser_pasqal.backends import EmuFreeBackend, EmuTNBackend -from pulser_pasqal.job_parameters import JobParameters, JobVariables root = Path(__file__).parent.parent @@ -335,116 +333,3 @@ def test_emulators_run(fixt, seq, emu_cls, parametrized: bool): configuration=sdk_config, wait=False, ) - - -# Deprecated - - -def check_pasqal_cloud(fixt, seq, emulator, expected_seq_representation): - create_batch_kwargs = dict( - jobs=[JobParameters(runs=10, variables=JobVariables(a=[3, 5]))], - emulator=emulator, - configuration=BaseConfig( - extra_config={ - "dt": 10.0, - "precision": "normal", - } - ), - wait=True, - fetch_results=False, - ) - - expected_create_batch_kwargs = { - **create_batch_kwargs, - "jobs": [{"runs": 10, "variables": {"qubits": None, "a": [3, 5]}}], - } - - with pytest.warns(UserWarning, match="No declared variables named: a"): - fixt.pasqal_cloud.create_batch( - seq, - **create_batch_kwargs, - ) - assert pulser_pasqal.__version__ < "0.15" - - fixt.mock_cloud_sdk.create_batch.assert_called_once_with( - serialized_sequence=expected_seq_representation, - **expected_create_batch_kwargs, - ) - - get_batch_kwargs = dict( - id="uuid", - fetch_results=True, - ) - with pytest.deprecated_call(): - fixt.pasqal_cloud.get_batch(**get_batch_kwargs) - assert pulser_pasqal.__version__ < "0.15" - - fixt.mock_cloud_sdk.get_batch.assert_called_once_with(**get_batch_kwargs) - - -@pytest.mark.parametrize( - "emulator, device", - [ - [emulator, device] - for emulator in (EmulatorType.EMU_FREE, EmulatorType.EMU_TN) - for device in (test_device, virtual_device) - ], -) -def test_pasqal_cloud_emu(fixt, emulator, device): - reg = Register.from_coordinates( - [(0, 0), (0, 10)], center=False, prefix="q" - ) - seq = Sequence(reg, device) - - check_pasqal_cloud( - fixt=fixt, - seq=seq, - emulator=emulator, - expected_seq_representation=seq.to_abstract_repr(), - ) - - -def test_pasqal_cloud_qpu(fixt): - device = test_device - - reg = Register.from_coordinates([(0, 0), (0, 10)], prefix="q") - seq = Sequence(reg, device) - - check_pasqal_cloud( - fixt=fixt, - seq=seq, - emulator=None, - expected_seq_representation=seq.to_abstract_repr(), - ) - - -def test_virtual_device_on_qpu_error(fixt): - reg = Register.from_coordinates([(0, 0), (0, 10)], prefix="q") - device = Chadoq2.to_virtual() - seq = Sequence(reg, device) - - with pytest.deprecated_call(), pytest.raises( - TypeError, match="must be a real device" - ): - fixt.pasqal_cloud.create_batch( - seq, - jobs=[JobParameters(runs=10, variables=JobVariables(a=[3, 5]))], - emulator=None, - wait=True, - ) - - -def test_wrong_parameters(fixt): - reg = Register.from_coordinates([(0, 0), (0, 10)], prefix="q") - seq = Sequence(reg, test_device) - seq.declare_variable("unset", dtype=int) - - with pytest.warns( - UserWarning, match="No declared variables named: a" - ), pytest.raises(TypeError, match="Did not receive values for variables"): - fixt.pasqal_cloud.create_batch( - seq, - jobs=[JobParameters(runs=10, variables=JobVariables(a=[3, 5]))], - emulator=None, - wait=True, - ) From d5ac0207443c3a24d026aebacc9b4c09b5b9b371 Mon Sep 17 00:00:00 2001 From: Antoine Cornillot <61453516+a-corni@users.noreply.github.com> Date: Mon, 24 Jul 2023 15:12:32 +0200 Subject: [PATCH 03/18] Adding DetuningMap, DMM (#539) * adding dmm, draw to DetuningMap * Testing avoiding circular import * Refactoring to avoid circular imports * Fix broken UTs * Import sorting * Fixing plot DetuningMap * Serialization/Deserialization of DMM in device * Fixing typos * Testing DMM and DetuningMap * Fixing typo * adding xfails, fixing type * Remove DMM from devices and finish UTs * Take into account review comments * Add annotations * Error in Global and Local * Defining _DMMSchedule * Fixing nits * Fixing typo --------- Co-authored-by: HGSilveri --- pulser-core/pulser/channels/__init__.py | 1 + pulser-core/pulser/channels/base_channel.py | 20 +- pulser-core/pulser/channels/channels.py | 2 +- pulser-core/pulser/channels/dmm.py | 74 +++++++ pulser-core/pulser/devices/_device_datacls.py | 57 +++++- pulser-core/pulser/devices/_devices.py | 9 + pulser-core/pulser/devices/_mock_device.py | 1 + .../pulser/json/abstract_repr/deserializer.py | 12 +- .../pulser/json/abstract_repr/serializer.py | 2 +- pulser-core/pulser/register/_reg_drawer.py | 73 +++++-- pulser-core/pulser/register/base_register.py | 25 +++ pulser-core/pulser/register/mappable_reg.py | 17 ++ .../pulser/register/register_layout.py | 27 +++ pulser-core/pulser/register/weight_maps.py | 106 ++++++++++ pulser-core/pulser/sequence/_schedule.py | 6 + tests/test_abstract_repr.py | 41 ++++ tests/test_devices.py | 46 ++++- tests/test_dmm.py | 193 ++++++++++++++++++ 18 files changed, 677 insertions(+), 35 deletions(-) create mode 100644 pulser-core/pulser/channels/dmm.py create mode 100644 pulser-core/pulser/register/weight_maps.py create mode 100644 tests/test_dmm.py diff --git a/pulser-core/pulser/channels/__init__.py b/pulser-core/pulser/channels/__init__.py index 9645bddb..8fea9dee 100644 --- a/pulser-core/pulser/channels/__init__.py +++ b/pulser-core/pulser/channels/__init__.py @@ -14,3 +14,4 @@ """The various hardware channel types.""" from pulser.channels.channels import Microwave, Raman, Rydberg +from pulser.channels.dmm import DMM diff --git a/pulser-core/pulser/channels/base_channel.py b/pulser-core/pulser/channels/base_channel.py index 3afabd99..2edd2b5f 100644 --- a/pulser-core/pulser/channels/base_channel.py +++ b/pulser-core/pulser/channels/base_channel.py @@ -17,7 +17,7 @@ import warnings from abc import ABC, abstractmethod -from dataclasses import dataclass, field, fields +from dataclasses import MISSING, dataclass, field, fields from typing import Any, Literal, Optional, Type, TypeVar, cast import numpy as np @@ -94,7 +94,7 @@ def basis(self) -> str: def _internal_param_valid_options(self) -> dict[str, tuple[str, ...]]: """Internal parameters and their valid options.""" return dict( - name=("Rydberg", "Raman", "Microwave"), + name=("Rydberg", "Raman", "Microwave", "DMM"), basis=("ground-rydberg", "digital", "XY"), addressing=("Local", "Global"), ) @@ -262,6 +262,14 @@ def Local( min_avg_amp: The minimum average amplitude of a pulse (when not zero). """ + # Can't initialize a channel whose addressing is determined internally + for cls_field in fields(cls): + if cls_field.name == "addressing": + break + if not cls_field.init and cls_field.default is not MISSING: + raise NotImplementedError( + f"{cls} cannot be initialized from `Local` method." + ) return cls( "Local", max_abs_detuning, @@ -299,6 +307,14 @@ def Global( min_avg_amp: The minimum average amplitude of a pulse (when not zero). """ + # Can't initialize a channel whose addressing is determined internally + for cls_field in fields(cls): + if cls_field.name == "addressing": + break + if not cls_field.init and cls_field.default is not MISSING: + raise NotImplementedError( + f"{cls} cannot be initialized from `Global` method." + ) return cls("Global", max_abs_detuning, max_amp, **kwargs) def validate_duration(self, duration: int) -> int: diff --git a/pulser-core/pulser/channels/channels.py b/pulser-core/pulser/channels/channels.py index 390286b7..9a95a31e 100644 --- a/pulser-core/pulser/channels/channels.py +++ b/pulser-core/pulser/channels/channels.py @@ -41,7 +41,7 @@ class Rydberg(Channel): """Rydberg beam channel. Channel targeting the transition between the ground and rydberg states, - thus enconding the 'ground-rydberg' basis. See base class. + thus encoding the 'ground-rydberg' basis. See base class. """ eom_config: Optional[RydbergEOM] = None diff --git a/pulser-core/pulser/channels/dmm.py b/pulser-core/pulser/channels/dmm.py new file mode 100644 index 00000000..744fd2ee --- /dev/null +++ b/pulser-core/pulser/channels/dmm.py @@ -0,0 +1,74 @@ +# Copyright 2023 Pulser Development Team +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Defines the detuning map modulator.""" +from __future__ import annotations + +from dataclasses import dataclass, field +from typing import Literal, Optional + +from pulser.channels.base_channel import Channel + + +@dataclass(init=True, repr=False, frozen=True) +class DMM(Channel): + """Defines a Detuning Map Modulator (DMM) Channel. + + A Detuning Map Modulator can be used to define `Global` detuning Pulses + (of zero amplitude and phase). These Pulses are locally modulated by the + weights of a `DetuningMap`, thus providing a local control over the + detuning. The detuning of the pulses added to a DMM has to be negative, + between 0 and `bottom_detuning`. Channel targeting the transition between + the ground and rydberg states, thus encoding the 'ground-rydberg' basis. + + Note: + The protocol to add pulses to the DMM Channel is by default + "no-delay". + + Args: + bottom_detuning: Minimum possible detuning (in rad/µs), must be below + zero. + clock_period: The duration of a clock cycle (in ns). The duration of a + pulse or delay instruction is enforced to be a multiple of the + clock cycle. + min_duration: The shortest duration an instruction can take. + max_duration: The longest duration an instruction can take. + min_avg_amp: The minimum average amplitude of a pulse (when not zero). + mod_bandwidth: The modulation bandwidth at -3dB (50% reduction), in + MHz. + """ + + bottom_detuning: Optional[float] = field(default=None, init=True) + addressing: Literal["Global"] = field(default="Global", init=False) + max_abs_detuning: Optional[float] = field(init=False, default=None) + max_amp: float = field(default=1e-16, init=False) # can't be 0 + min_retarget_interval: Optional[int] = field(init=False, default=None) + fixed_retarget_t: Optional[int] = field(init=False, default=None) + max_targets: Optional[int] = field(init=False, default=None) + + def __post_init__(self) -> None: + super().__post_init__() + if self.bottom_detuning and self.bottom_detuning > 0: + raise ValueError("bottom_detuning must be negative.") + + @property + def basis(self) -> Literal["ground-rydberg"]: + """The addressed basis name.""" + return "ground-rydberg" + + def _undefined_fields(self) -> list[str]: + optional = [ + "bottom_detuning", + "max_duration", + ] + return [field for field in optional if getattr(self, field) is None] diff --git a/pulser-core/pulser/devices/_device_datacls.py b/pulser-core/pulser/devices/_device_datacls.py index 0e194087..2dca543b 100644 --- a/pulser-core/pulser/devices/_device_datacls.py +++ b/pulser-core/pulser/devices/_device_datacls.py @@ -24,6 +24,7 @@ from scipy.spatial.distance import pdist, squareform from pulser.channels.base_channel import Channel +from pulser.channels.dmm import DMM from pulser.devices.interaction_coefficients import c6_dict from pulser.json.abstract_repr.serializer import AbstractReprEncoder from pulser.json.abstract_repr.validation import validate_abstract_repr @@ -34,7 +35,8 @@ DIMENSIONS = Literal[2, 3] -ALWAYS_OPTIONAL_PARAMS = ("max_sequence_duration", "max_runs") +ALWAYS_OPTIONAL_PARAMS = ("max_sequence_duration", "max_runs", "dmm_objects") +PARAMS_WITH_ABSTR_REPR = ("channel_objects", "channel_ids", "dmm_objects") @dataclass(frozen=True, repr=False) @@ -49,6 +51,9 @@ class BaseDevice(ABC): channel_ids: Custom IDs for each channel object. When defined, an ID must be given for each channel. If not defined, the IDs are generated internally based on the channels' names and addressing. + dmm_objects: The DMM subclass instances specifying each channel in the + device. They are referenced by their order in the list, with the ID + "dmm_[index in dmm_objects]". rybderg_level: The value of the principal quantum number :math:`n` when the Rydberg level used is of the form :math:`|nS_{1/2}, m_j = +1/2\rangle`. @@ -83,6 +88,7 @@ class BaseDevice(ABC): reusable_channels: bool = field(default=False, init=False) channel_ids: tuple[str, ...] | None = None channel_objects: tuple[Channel, ...] = field(default_factory=tuple) + dmm_objects: tuple[DMM, ...] = field(default_factory=tuple) def __post_init__(self) -> None: def type_check( @@ -155,6 +161,16 @@ def type_check( for ch_obj in self.channel_objects: type_check("All channels", Channel, value_override=ch_obj) + for dmm_obj in self.dmm_objects: + type_check("All DMM channels", DMM, value_override=dmm_obj) + + # TODO: Check that device has dmm objects if it supports SLM mask + # once DMM is supported for serialization + # if self.supports_slm_mask and not self.dmm_objects: + # raise ValueError( + # "One DMM object should be defined to support SLM mask." + # ) + if self.channel_ids is not None: if not ( isinstance(self.channel_ids, (tuple, list)) @@ -174,6 +190,12 @@ def type_check( "When defined, the number of channel IDs must" " match the number of channel objects." ) + if set(self.channel_ids) & set(self.dmm_channels.keys()): + raise ValueError( + "When defined, the names of channel IDs must be different" + " than the names of DMM channels 'dmm_0', 'dmm_1', ... ." + ) + else: # Make the channel IDs from the default IDs ids_counter: Counter = Counter() @@ -203,7 +225,7 @@ def to_tuple(obj: tuple | list) -> tuple: # Turns mutable lists into immutable tuples for param in self._params(): - if "channel" in param: + if "channel" in param or param == "dmm_objects": object.__setattr__(self, param, to_tuple(getattr(self, param))) @property @@ -216,6 +238,13 @@ def channels(self) -> dict[str, Channel]: """Dictionary of available channels on this device.""" return dict(zip(cast(tuple, self.channel_ids), self.channel_objects)) + @property + def dmm_channels(self) -> dict[str, DMM]: + """Dictionary of available DMM channels on this device.""" + return { + f"dmm_{i}": dmm_obj for (i, dmm_obj) in enumerate(self.dmm_objects) + } + @property def supported_bases(self) -> set[str]: """Available electronic transitions for control and measurement.""" @@ -420,18 +449,26 @@ def _to_dict(self) -> dict[str, Any]: @abstractmethod def _to_abstract_repr(self) -> dict[str, Any]: - ex_params = ("channel_objects", "channel_ids") defaults = get_dataclass_defaults(fields(self)) params = self._params() - for p in ex_params: - params.pop(p, None) for p in ALWAYS_OPTIONAL_PARAMS: if params[p] == defaults[p]: params.pop(p, None) ch_list = [] for ch_name, ch_obj in self.channels.items(): ch_list.append(ch_obj._to_abstract_repr(ch_name)) - return {"version": "1", "channels": ch_list, **params} + # Add version and channels to params + params.update({"version": "1", "channels": ch_list}) + dmm_list = [] + for dmm_name, dmm_obj in self.dmm_channels.items(): + dmm_list.append(dmm_obj._to_abstract_repr(dmm_name)) + # Add dmm channels if different than default + if "dmm_objects" in params: + params["dmm_channels"] = dmm_list + # Delete parameters of PARAMS_WITH_ABSTR_REPR in params + for p in PARAMS_WITH_ABSTR_REPR: + params.pop(p, None) + return params def to_abstract_repr(self) -> str: """Serializes the Sequence into an abstract JSON object.""" @@ -541,7 +578,7 @@ def _specs(self, for_docs: bool = False) -> str: ) ch_lines = ["\nChannels:"] - for name, ch in self.channels.items(): + for name, ch in {**self.channels, **self.dmm_channels}.items(): if for_docs: ch_lines += [ f" - ID: '{name}'", @@ -556,6 +593,12 @@ def _specs(self, for_docs: bool = False) -> str: "\t" + r"- Maximum :math:`|\delta|`:" + f" {ch.max_abs_detuning:.4g} rad/µs" + ) + if not isinstance(ch, DMM) + else ( + "\t" + + r"- Bottom :math:`|\delta|`:" + + f" {ch.bottom_detuning:.4g} rad/µs" ), f"\t- Minimum average amplitude: {ch.min_avg_amp} rad/µs", ] diff --git a/pulser-core/pulser/devices/_devices.py b/pulser-core/pulser/devices/_devices.py index 85eac815..bbfe8f6d 100644 --- a/pulser-core/pulser/devices/_devices.py +++ b/pulser-core/pulser/devices/_devices.py @@ -56,6 +56,15 @@ max_duration=2**26, ), ), + # TODO: Add DMM once it is supported for serialization + # dmm_objects=( + # DMM( + # clock_period=4, + # min_duration=16, + # max_duration=2**26, + # bottom_detuning=-20, + # ), + # ), ) IroiseMVP = Device( diff --git a/pulser-core/pulser/devices/_mock_device.py b/pulser-core/pulser/devices/_mock_device.py index 28c05eca..206d0455 100644 --- a/pulser-core/pulser/devices/_mock_device.py +++ b/pulser-core/pulser/devices/_mock_device.py @@ -31,4 +31,5 @@ Raman.Local(None, None, max_duration=None), Microwave.Global(None, None, max_duration=None), ), + # TODO: Add DMM once it is supported for serialization ) diff --git a/pulser-core/pulser/json/abstract_repr/deserializer.py b/pulser-core/pulser/json/abstract_repr/deserializer.py index 8413d62a..48d74360 100644 --- a/pulser-core/pulser/json/abstract_repr/deserializer.py +++ b/pulser-core/pulser/json/abstract_repr/deserializer.py @@ -31,6 +31,7 @@ RydbergEOM, ) from pulser.devices import Device, VirtualDevice +from pulser.devices._device_datacls import PARAMS_WITH_ABSTR_REPR from pulser.json.abstract_repr.signatures import ( BINARY_OPERATORS, UNARY_OPERATORS, @@ -346,12 +347,19 @@ def _deserialize_device_object(obj: dict[str, Any]) -> Device | VirtualDevice: params: dict[str, Any] = dict( channel_ids=tuple(ch_ids), channel_objects=tuple(ch_objs) ) - ex_params = ("channel_objects", "channel_ids") + if "dmm_channels" in obj: + params["dmm_objects"] = tuple( + _deserialize_channel(dmm_ch) for dmm_ch in obj["dmm_channels"] + ) device_fields = dataclasses.fields(device_cls) device_defaults = get_dataclass_defaults(device_fields) for param in device_fields: use_default = param.name not in obj and param.name in device_defaults - if not param.init or param.name in ex_params or use_default: + if ( + not param.init + or param.name in PARAMS_WITH_ABSTR_REPR + or use_default + ): continue if param.name == "pre_calibrated_layouts": key = "pre_calibrated_layouts" diff --git a/pulser-core/pulser/json/abstract_repr/serializer.py b/pulser-core/pulser/json/abstract_repr/serializer.py index 5c2c0a3f..c76e196d 100644 --- a/pulser-core/pulser/json/abstract_repr/serializer.py +++ b/pulser-core/pulser/json/abstract_repr/serializer.py @@ -26,9 +26,9 @@ from pulser.json.abstract_repr.signatures import SIGNATURES from pulser.json.abstract_repr.validation import validate_abstract_repr from pulser.json.exceptions import AbstractReprError -from pulser.register.base_register import QubitId if TYPE_CHECKING: + from pulser.register.base_register import QubitId from pulser.sequence import Sequence from pulser.sequence._call import _Call diff --git a/pulser-core/pulser/register/_reg_drawer.py b/pulser-core/pulser/register/_reg_drawer.py index 7c6e3ae3..81a5cdea 100644 --- a/pulser-core/pulser/register/_reg_drawer.py +++ b/pulser-core/pulser/register/_reg_drawer.py @@ -18,14 +18,15 @@ from collections.abc import Mapping from collections.abc import Sequence as abcSequence from itertools import combinations -from typing import Optional +from typing import TYPE_CHECKING, Optional import matplotlib.pyplot as plt import numpy as np from matplotlib import collections as mc from scipy.spatial import KDTree -from pulser.register.base_register import QubitId +if TYPE_CHECKING: + from pulser.register.base_register import QubitId class RegDrawer: @@ -58,6 +59,7 @@ def _draw_2D( qubit_colors: Mapping[QubitId, str] = dict(), masked_qubits: set[QubitId] = set(), are_traps: bool = False, + dmm_qubits: Mapping[QubitId, float] = {}, ) -> None: ordered_qubit_colors = RegDrawer._compute_ordered_qubit_colors( ids, qubit_colors @@ -73,21 +75,34 @@ def _draw_2D( ax.scatter(pos[:, ix], pos[:, iy], alpha=0.7, **params) # Draw square halo around masked qubits - if masked_qubits: - mask_pos = [] + if ( + masked_qubits + and dmm_qubits + and masked_qubits != set(dmm_qubits.keys()) + ): + raise ValueError("masked qubits and dmm qubits must be the same.") + elif masked_qubits: + dmm_qubits = { + masked_qubit: 1.0 / len(masked_qubits) + for masked_qubit in masked_qubits + } + + if dmm_qubits: + dmm_pos = [] for i, c in zip(ids, pos): - if i in masked_qubits: - mask_pos.append(c) - mask_arr = np.array(mask_pos) + if i in dmm_qubits.keys(): + dmm_pos.append(c) + dmm_arr = np.array(dmm_pos) ax.scatter( - mask_arr[:, ix], - mask_arr[:, iy], + dmm_arr[:, ix], + dmm_arr[:, iy], marker="s", s=1200, - alpha=0.2, + alpha=0.2 + * np.array(list(dmm_qubits.values())) + / max(dmm_qubits.values()), c="black", ) - axes = "xyz" ax.set_xlabel(axes[ix] + " (µm)") @@ -106,6 +121,7 @@ def _draw_2D( i = 0 bbs = {} final_plot_ids: list[str] = [] + final_plot_det_map: list = [] while i < len(plot_ids): r = plot_pos[i] j = i + 1 @@ -120,26 +136,41 @@ def _draw_2D( else: j += 1 # Sort qubits in plot_ids[i] according to masked status + det_map = [ + q for q, weight in dmm_qubits.items() if weight > 0.0 + ] plot_ids[i] = sorted( plot_ids[i], - key=lambda s: s in [str(q) for q in masked_qubits], + key=lambda s: s in det_map, ) - # Merge all masked qubits - has_masked = False + # Merge all masked qubits with their detuning + # if the detunings are not all the same (masked qubits then) + has_det_map = False + is_mask = len(set([dmm_qubits[q] for q in det_map])) == 1 for j in range(len(plot_ids[i])): - if plot_ids[i][j] in [str(q) for q in masked_qubits]: - plot_ids[i][j:] = [", ".join(plot_ids[i][j:])] - has_masked = True + if plot_ids[i][j] in [str(q) for q in det_map]: + qubit_det = [] + for q in plot_ids[i][j:]: + extra_label = ( + f": {dmm_qubits[int(q)]:.2f}" + if not is_mask + else "" + ) + qubit_det.append(q + extra_label) + plot_ids[i][j:] = [", ".join(qubit_det)] + has_det_map = True break # Add a square bracket that encloses all masked qubits - if has_masked: + if has_det_map: plot_ids[i][-1] = "[" + plot_ids[i][-1] + "]" + # Lower the fontsize if detuning is shown (not a mask) + if not is_mask: + final_plot_det_map.append(i) # Merge what remains final_plot_ids.append(", ".join(plot_ids[i])) bbs[final_plot_ids[i]] = overlap i += 1 - - for q, coords in zip(final_plot_ids, plot_pos): + for i, (q, coords) in enumerate(zip(final_plot_ids, plot_pos)): bb = ( dict(boxstyle="square", fill=False, ec="gray", ls="--") if bbs[q] @@ -154,7 +185,7 @@ def _draw_2D( va=v_al, wrap=True, bbox=bb, - fontsize=12, + fontsize=12 if i not in final_plot_det_map else 8.3, multialignment="right", ) txt._get_wrap_line_width = lambda: 50.0 diff --git a/pulser-core/pulser/register/base_register.py b/pulser-core/pulser/register/base_register.py index 1062bf25..473b10a8 100644 --- a/pulser-core/pulser/register/base_register.py +++ b/pulser-core/pulser/register/base_register.py @@ -33,6 +33,7 @@ from numpy.typing import ArrayLike from pulser.json.utils import obj_to_dict +from pulser.register.weight_maps import DetuningMap if TYPE_CHECKING: from pulser.register.register_layout import RegisterLayout @@ -204,6 +205,30 @@ def _validate_layout( " register's coordinates." ) + def define_detuning_map( + self, detuning_weights: Mapping[QubitId, float] + ) -> DetuningMap: + """Defines a DetuningMap for some qubits of the register. + + Args: + detuning_weights: A mapping between the IDs of the targeted qubits + and detuning weights (between 0 and 1, their sum must be equal + to 1). + + Returns: + A DetuningMap associating detuning weights to the trap coordinates + of the targeted qubits. + """ + if not set(detuning_weights.keys()) <= set(self.qubit_ids): + raise ValueError( + "The qubit ids linked to detuning weights have to be defined" + " in the register." + ) + return DetuningMap( + [self.qubits[qubit_id] for qubit_id in detuning_weights], + list(detuning_weights.values()), + ) + @abstractmethod def _to_dict(self) -> dict[str, Any]: """Serializes the object. diff --git a/pulser-core/pulser/register/mappable_reg.py b/pulser-core/pulser/register/mappable_reg.py index 29c789c2..d11f5a06 100644 --- a/pulser-core/pulser/register/mappable_reg.py +++ b/pulser-core/pulser/register/mappable_reg.py @@ -23,6 +23,7 @@ if TYPE_CHECKING: from pulser.register.base_register import BaseRegister, QubitId from pulser.register.register_layout import RegisterLayout + from pulser.register.weight_maps import DetuningMap class MappableRegister: @@ -122,6 +123,22 @@ def find_indices(self, id_list: abcSequence[QubitId]) -> list[int]: ) return [self.qubit_ids.index(id) for id in id_list] + def define_detuning_map( + self, detuning_weights: Mapping[int, float] + ) -> DetuningMap: + """Defines a DetuningMap for some trap ids of the register layout. + + Args: + detuning_weights: A mapping between the IDs of the targeted traps + and detuning weights (between 0 and 1, their sum must be equal + to 1). + + Returns: + A DetuningMap associating detuning weights to the trap coordinates + of the targeted traps. + """ + return self._layout.define_detuning_map(detuning_weights) + def _to_dict(self) -> dict[str, Any]: return obj_to_dict(self, self._layout, *self._qubit_ids) diff --git a/pulser-core/pulser/register/register_layout.py b/pulser-core/pulser/register/register_layout.py index a8aa8143..22d0917b 100644 --- a/pulser-core/pulser/register/register_layout.py +++ b/pulser-core/pulser/register/register_layout.py @@ -15,10 +15,12 @@ from __future__ import annotations +from collections.abc import Mapping from collections.abc import Sequence as abcSequence from dataclasses import dataclass from functools import cached_property from hashlib import sha256 +from operator import itemgetter from typing import Any, Optional, cast import matplotlib.pyplot as plt @@ -31,6 +33,7 @@ from pulser.register.mappable_reg import MappableRegister from pulser.register.register import Register from pulser.register.register3d import Register3D +from pulser.register.weight_maps import DetuningMap COORD_PRECISION = 6 @@ -185,6 +188,30 @@ def define_register( reg = reg_class(qubits, layout=self, trap_ids=trap_ids) return reg + def define_detuning_map( + self, detuning_weights: Mapping[int, float] + ) -> DetuningMap: + """Defines a DetuningMap for some trap ids of the register layout. + + Args: + detuning_weights: A mapping between the IDs of the targeted traps + and detuning weights (between 0 and 1, their sum must be equal + to 1). + + Returns: + A DetuningMap associating detuning weights to the trap coordinates + of the targeted traps. + """ + if not set(detuning_weights.keys()) <= set(self.traps_dict): + raise ValueError( + "The trap ids of detuning weights have to be integers" + f" between 0 and {self.number_of_traps}." + ) + return DetuningMap( + itemgetter(*detuning_weights.keys())(self.traps_dict), + list(detuning_weights.values()), + ) + def draw( self, blockade_radius: Optional[float] = None, diff --git a/pulser-core/pulser/register/weight_maps.py b/pulser-core/pulser/register/weight_maps.py new file mode 100644 index 00000000..2e3e1fd2 --- /dev/null +++ b/pulser-core/pulser/register/weight_maps.py @@ -0,0 +1,106 @@ +# Copyright 2023 Pulser Development Team +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Defines weight maps on top of traps.""" + +from __future__ import annotations + +from dataclasses import dataclass +from typing import Optional, cast + +import matplotlib.pyplot as plt +import numpy as np +from matplotlib.axes import Axes +from numpy.typing import ArrayLike + +from pulser.register._reg_drawer import RegDrawer + + +@dataclass +class WeightMap(RegDrawer): + """Defines a generic map of weights on traps. + + The sum of the provided weights must be equal to 1. + + Args: + trap_coordinates: An array containing the coordinates of the traps. + weights: A list weights to associate to the traps. + """ + + trap_coordinates: ArrayLike + weights: list[float] + + def __post_init__(self) -> None: + if len(cast(list, self.trap_coordinates)) != len(self.weights): + raise ValueError("Number of traps and weights don't match.") + if not np.all(np.array(self.weights) >= 0): + raise ValueError("All weights must be non-negative.") + if not np.isclose(sum(self.weights), 1.0, atol=1e-16): + raise ValueError("The sum of the weights should be 1.") + + def draw( + self, + with_labels: bool = True, + fig_name: str | None = None, + kwargs_savefig: dict = {}, + custom_ax: Optional[Axes] = None, + show: bool = True, + ) -> None: + """Draws the detuning map. + + Args: + with_labels: If True, writes the qubit ID's + next to each qubit. + fig_name: The name on which to save the figure. + If None the figure will not be saved. + kwargs_savefig: Keywords arguments for + ``matplotlib.pyplot.savefig``. Not applicable if `fig_name` + is ``None``. + custom_ax: If present, instead of creating its own Axes object, + the function will use the provided one. Warning: if fig_name + is set, it may save content beyond what is drawn in this + function. + show: Whether or not to call `plt.show()` before returning. When + combining this plot with other ones in a single figure, one may + need to set this flag to False. + """ + pos = np.array(self.trap_coordinates) + if custom_ax is None: + _, custom_ax = self._initialize_fig_axes(pos) + + super()._draw_2D( + custom_ax, + pos, + [i for i, _ in enumerate(cast(list, self.trap_coordinates))], + with_labels=with_labels, + dmm_qubits=dict(enumerate(self.weights)), + ) + + if fig_name is not None: + plt.savefig(fig_name, **kwargs_savefig) + + if show: + plt.show() + + +@dataclass +class DetuningMap(WeightMap): + """Defines a DetuningMap. + + A DetuningMap associates a detuning weight to the coordinates of a trap. + The sum of the provided weights must be equal to 1. + + Args: + trap_coordinates: an array containing the coordinates of the traps. + weights: A list of detuning weights to associate to the traps. + """ diff --git a/pulser-core/pulser/sequence/_schedule.py b/pulser-core/pulser/sequence/_schedule.py index f2cad62e..816c5c91 100644 --- a/pulser-core/pulser/sequence/_schedule.py +++ b/pulser-core/pulser/sequence/_schedule.py @@ -24,6 +24,7 @@ from pulser.channels.base_channel import Channel from pulser.pulse import Pulse from pulser.register.base_register import QubitId +from pulser.register.weight_maps import DetuningMap from pulser.sampler.samples import ChannelSamples, _PulseTargetSlot from pulser.waveforms import ConstantWaveform @@ -247,6 +248,11 @@ def __iter__(self) -> Iterator[_TimeSlot]: yield slot +@dataclass +class _DMMSchedule(_ChannelSchedule): + detuning_map: DetuningMap + + class _Schedule(Dict[str, _ChannelSchedule]): def __init__(self, max_duration: int | None = None): self.max_duration = max_duration diff --git a/tests/test_abstract_repr.py b/tests/test_abstract_repr.py index e37afab4..1e7307cd 100644 --- a/tests/test_abstract_repr.py +++ b/tests/test_abstract_repr.py @@ -27,6 +27,7 @@ from pulser import Pulse, Register, Register3D, Sequence, devices from pulser.channels import Rydberg +from pulser.channels.dmm import DMM from pulser.channels.eom import RydbergBeam, RydbergEOM from pulser.devices import AnalogDevice, Chadoq2, Device, IroiseMVP, MockDevice from pulser.json.abstract_repr.deserializer import ( @@ -235,6 +236,46 @@ def test_optional_channel_fields(self, ch_obj): dev_str = device.to_abstract_repr() assert device == deserialize_device(dev_str) + @pytest.fixture + def chadoq2_with_dmm(self): + # TODO: Delete once Chadoq2 actually has a DMM + dmm = DMM( + bottom_detuning=-1, + clock_period=1, + min_duration=1, + max_duration=1e6, + mod_bandwidth=20, + ) + return replace(Chadoq2, dmm_objects=(dmm,)) + + @pytest.mark.xfail( + raises=jsonschema.exceptions.ValidationError, strict=True + ) + def test_abstract_repr_dmm_serialize(self, chadoq2_with_dmm): + chadoq2_with_dmm.to_abstract_repr() + + @pytest.mark.xfail(raises=DeserializeDeviceError, strict=True) + @pytest.mark.parametrize( + "skip_validation", + [ + False, # Fails validation + True, # Fails because the DMM channel is deserialized as Rydberg + ], + ) + def test_abstract_repr_dmm_deserialize( + self, chadoq2_with_dmm, monkeypatch, skip_validation + ): + ser_device = json.dumps(chadoq2_with_dmm, cls=AbstractReprEncoder) + if skip_validation: + + def dummy(*args, **kwargs): + return True + + # Patches jsonschema.validate with a function that returns True + monkeypatch.setattr(jsonschema, "validate", dummy) + device = deserialize_device(ser_device) + assert device == chadoq2_with_dmm + def validate_schema(instance): with open( diff --git a/tests/test_devices.py b/tests/test_devices.py index c9981bdc..1214aa32 100644 --- a/tests/test_devices.py +++ b/tests/test_devices.py @@ -13,7 +13,7 @@ # limitations under the License. import re -from dataclasses import FrozenInstanceError +from dataclasses import FrozenInstanceError, replace from unittest.mock import patch import numpy as np @@ -21,6 +21,7 @@ import pulser from pulser.channels import Microwave, Raman, Rydberg +from pulser.channels.dmm import DMM from pulser.devices import Chadoq2, Device, VirtualDevice from pulser.register import Register, Register3D from pulser.register.register_layout import RegisterLayout @@ -74,6 +75,11 @@ def test_params(): "'interaction_coeff_xy' must be a 'float'," " not ''.", ), + ( + "dmm_objects", + ("DMM(bottom_detuning=-1)",), + "All DMM channels must be of type 'DMM', not 'str'", + ), ("max_sequence_duration", 1.02, None), ("max_runs", 1e8, None), ], @@ -130,6 +136,16 @@ def test_post_init_value_errors(test_params, param, value, msg): VirtualDevice(**test_params) +# TODO: Add test of comptability SLM-DMM once DMM is added for serialization +# def test_post_init_slm_dmm_compatibility(test_params): +# test_params["supports_slm_mask"] = True +# test_params["dmm_objects"] = () +# with pytest.raises(ValueError, +# match="One DMM object should be defined to support SLM mask." +# ): +# VirtualDevice(**test_params) + + potential_params = ["max_atom_num", "max_radial_distance"] always_none_allowed = ["max_sequence_duration", "max_runs"] @@ -384,3 +400,31 @@ def test_device_params(): assert set(all_params) - set(all_virtual_params) == { "pre_calibrated_layouts" } + + +def test_dmm_channels(): + dmm = DMM( + bottom_detuning=-1, + clock_period=1, + min_duration=1, + max_duration=1e6, + mod_bandwidth=20, + ) + device = replace(Chadoq2, dmm_objects=(dmm,)) + assert len(device.dmm_channels) == 1 + assert device.dmm_channels["dmm_0"] == dmm + with pytest.raises( + ValueError, + match=( + "When defined, the names of channel IDs must be different" + " than the names of DMM channels 'dmm_0', 'dmm_1', ... ." + ), + ): + device = replace( + Chadoq2, + dmm_objects=(dmm,), + channel_objects=(Rydberg.Global(None, None),), + channel_ids=("dmm_0",), + ) + assert not dmm.is_virtual() + assert DMM().is_virtual() diff --git a/tests/test_dmm.py b/tests/test_dmm.py new file mode 100644 index 00000000..22055dd6 --- /dev/null +++ b/tests/test_dmm.py @@ -0,0 +1,193 @@ +# Copyright 2020 Pulser Development Team +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from typing import cast +from unittest.mock import patch + +import numpy as np +import pytest + +from pulser.channels.dmm import DMM +from pulser.register.base_register import BaseRegister +from pulser.register.mappable_reg import MappableRegister +from pulser.register.register_layout import RegisterLayout +from pulser.register.weight_maps import DetuningMap + + +@pytest.fixture +def layout() -> RegisterLayout: + return RegisterLayout([[0, 0], [1, 0], [0, 1], [1, 1]]) + + +@pytest.fixture +def register(layout: RegisterLayout) -> BaseRegister: + return layout.define_register(0, 1, 2, 3, qubit_ids=(0, 1, 2, 3)) + + +@pytest.fixture +def map_reg(layout: RegisterLayout) -> MappableRegister: + return layout.make_mappable_register(4) + + +@pytest.fixture +def det_dict() -> dict[int, float]: + return {0: 0.7, 1: 0.3, 2: 0} + + +@pytest.fixture +def det_map(layout: RegisterLayout, det_dict: dict[int, float]) -> DetuningMap: + return layout.define_detuning_map(det_dict) + + +@pytest.fixture +def slm_dict() -> dict[int, float]: + return {0: 1 / 3, 1: 1 / 3, 2: 1 / 3} + + +@pytest.fixture +def slm_map(layout: RegisterLayout, slm_dict: dict[int, float]) -> DetuningMap: + return layout.define_detuning_map(slm_dict) + + +@pytest.mark.parametrize("bad_key", [{"1": 1.0}, {4: 1.0}]) +def test_define_detuning_att( + layout: RegisterLayout, + register: BaseRegister, + map_reg: MappableRegister, + bad_key: dict, +): + for reg in (layout, map_reg): + with pytest.raises( + ValueError, + match=( + "The trap ids of detuning weights have to be integers" + " between 0 and 4" + ), + ): + reg.define_detuning_map(bad_key) # type: ignore + with pytest.raises( + ValueError, + match=( + "The qubit ids linked to detuning weights have to be defined in" + " the register." + ), + ): + register.define_detuning_map(bad_key) + + +def test_bad_init( + layout: RegisterLayout, + register: BaseRegister, + map_reg: MappableRegister, +): + with pytest.raises( + ValueError, match="Number of traps and weights don't match." + ): + DetuningMap([(0, 0), (1, 0)], [0]) + + bad_weights = {0: -1.0, 1: 1.0, 2: 1.0} + bad_sum = {0: 0.1, 2: 0.9, 3: 0.1} + for reg in (layout, map_reg, register): + with pytest.raises( + ValueError, match="All weights must be non-negative." + ): + reg.define_detuning_map(bad_weights) # type: ignore + with pytest.raises( + ValueError, match="The sum of the weights should be 1." + ): + reg.define_detuning_map(bad_sum) # type: ignore + + +def test_init( + layout: RegisterLayout, + register: BaseRegister, + map_reg: MappableRegister, + det_dict: dict[int, float], + slm_dict: dict[int, float], +): + for reg in (layout, map_reg, register): + for detuning_map_dict in (det_dict, slm_dict): + detuning_map = cast( + DetuningMap, + reg.define_detuning_map(detuning_map_dict), # type: ignore + ) + assert np.all( + [ + detuning_map_dict[i] == detuning_map.weights[i] + for i in range(len(detuning_map_dict)) + ] + ) + assert np.all( + [ + layout.coords[i] + == np.array(detuning_map.trap_coordinates)[i] + for i in range(len(detuning_map_dict)) + ] + ) + + +def test_draw(det_map, slm_map, patch_plt_show): + for detuning_map in (det_map, slm_map): + detuning_map.draw(with_labels=True, show=True, custom_ax=None) + with patch("matplotlib.pyplot.savefig"): + detuning_map.draw(fig_name="det_map.pdf") + with pytest.raises( + ValueError, match="masked qubits and dmm qubits must be the same." + ): + slm_map._draw_2D( + slm_map._initialize_fig_axes(np.array(slm_map.trap_coordinates))[ + 1 + ], + np.array(slm_map.trap_coordinates), + [i for i, _ in enumerate(cast(list, slm_map.trap_coordinates))], + with_labels=True, + dmm_qubits=dict(enumerate(slm_map.weights)), + masked_qubits={ + 1, + }, + ) + + +def test_DMM(): + dmm = DMM( + bottom_detuning=-1, + clock_period=1, + min_duration=1, + max_duration=1e6, + mod_bandwidth=20, + ) + assert dmm.basis == "ground-rydberg" + assert dmm.addressing == "Global" + assert dmm.bottom_detuning == -1 + assert dmm.max_amp == 1e-16 + for value in ( + dmm.max_abs_detuning, + dmm.min_retarget_interval, + dmm.fixed_retarget_t, + dmm.max_targets, + ): + assert value is None + with pytest.raises(ValueError, match="bottom_detuning must be negative."): + DMM(bottom_detuning=1) + with pytest.raises( + NotImplementedError, + match=f"{DMM} cannot be initialized from `Global` method.", + ): + DMM.Global(None, None, bottom_detuning=1) + with pytest.raises( + NotImplementedError, + match=f"{DMM} cannot be initialized from `Local` method.", + ): + DMM.Local(None, None, bottom_detuning=1) From 0d8d4b1837a987a1de8cc73258acf6068abde9af Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Henrique=20Silv=C3=A9rio?= Date: Wed, 2 Aug 2023 09:50:20 +0200 Subject: [PATCH 04/18] Comply with latest style guidelines (#567) --- pulser-core/pulser/json/coders.py | 2 +- pulser-core/pulser/sequence/sequence.py | 2 +- tests/test_json.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/pulser-core/pulser/json/coders.py b/pulser-core/pulser/json/coders.py index 3d1a2dc0..989996f8 100644 --- a/pulser-core/pulser/json/coders.py +++ b/pulser-core/pulser/json/coders.py @@ -34,7 +34,7 @@ def default(self, o: Any) -> dict[str, Any]: """Handles JSON encoding of objects not supported by default.""" if hasattr(o, "_to_dict"): return cast(dict, o._to_dict()) - elif type(o) == type: + elif type(o) is type: return obj_to_dict(o, _build=False, _name=o.__name__) elif isinstance(o, np.ndarray): return obj_to_dict(o, o.tolist(), _name="array") diff --git a/pulser-core/pulser/sequence/sequence.py b/pulser-core/pulser/sequence/sequence.py index 35e47e58..72ba03ee 100644 --- a/pulser-core/pulser/sequence/sequence.py +++ b/pulser-core/pulser/sequence/sequence.py @@ -514,7 +514,7 @@ def check_retarget(ch_obj: Channel) -> bool: # We verify the channel class then # check whether the addressing is Global or Local - type_match = type(old_ch_obj) == type(new_ch_obj) + type_match = type(old_ch_obj) is type(new_ch_obj) basis_match = old_ch_obj.basis == new_ch_obj.basis addressing_match = ( old_ch_obj.addressing == new_ch_obj.addressing diff --git a/tests/test_json.py b/tests/test_json.py index 9764c84e..35a94c95 100644 --- a/tests/test_json.py +++ b/tests/test_json.py @@ -112,7 +112,7 @@ def test_register_numbered_keys(reg): j = json.dumps(reg, cls=PulserEncoder) decoded_reg = json.loads(j, cls=PulserDecoder) assert reg == decoded_reg - assert all([type(i) == int for i in decoded_reg.qubit_ids]) + assert all([type(i) is int for i in decoded_reg.qubit_ids]) def test_mappable_register(): From f742f5c348d552ec706329ce9c0e1b4965ed11c2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Henrique=20Silv=C3=A9rio?= Date: Tue, 29 Aug 2023 11:16:06 +0200 Subject: [PATCH 05/18] Update to jsonschema > 4.18, Sphinx < 7 (#572) * Update to jsonschema > 4.18 * Try Sphinx < 7 --- docs/requirements.txt | 2 +- pulser-core/pulser/json/abstract_repr/validation.py | 10 +++++----- pulser-core/requirements.txt | 2 +- tests/test_abstract_repr.py | 4 ++-- 4 files changed, 9 insertions(+), 9 deletions(-) diff --git a/docs/requirements.txt b/docs/requirements.txt index 04444904..9a81cc89 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,5 +1,5 @@ # For generating documentation. -Sphinx +Sphinx < 7 sphinx-rtd-theme # documentation theme sphinx_autodoc_typehints == 1.21.3 nbsphinx diff --git a/pulser-core/pulser/json/abstract_repr/validation.py b/pulser-core/pulser/json/abstract_repr/validation.py index 09bd7f06..9b8cd7ec 100644 --- a/pulser-core/pulser/json/abstract_repr/validation.py +++ b/pulser-core/pulser/json/abstract_repr/validation.py @@ -16,12 +16,12 @@ from typing import Literal import jsonschema +from referencing import Registry, Resource -from pulser.json.abstract_repr import SCHEMAS, SCHEMAS_PATH +from pulser.json.abstract_repr import SCHEMAS -RESOLVER = jsonschema.validators.RefResolver( - base_uri=f"{SCHEMAS_PATH.resolve().as_uri()}/", - referrer=SCHEMAS["sequence"], +REGISTRY: Registry = Registry().with_resources( + [("device-schema.json", Resource.from_contents(SCHEMAS["device"]))] ) @@ -37,5 +37,5 @@ def validate_abstract_repr( obj = json.loads(obj_str) validate_args = dict(instance=obj, schema=SCHEMAS[name]) if name == "sequence": - validate_args["resolver"] = RESOLVER + validate_args["registry"] = REGISTRY jsonschema.validate(**validate_args) diff --git a/pulser-core/requirements.txt b/pulser-core/requirements.txt index 40cee3bf..69fa4291 100644 --- a/pulser-core/requirements.txt +++ b/pulser-core/requirements.txt @@ -1,4 +1,4 @@ -jsonschema < 4.18 +jsonschema >= 4.18 matplotlib # Numpy 1.20 introduces type hints, 1.24.0 breaks matplotlib < 3.6.1 numpy >= 1.20, != 1.24.0 diff --git a/tests/test_abstract_repr.py b/tests/test_abstract_repr.py index 1e7307cd..745452de 100644 --- a/tests/test_abstract_repr.py +++ b/tests/test_abstract_repr.py @@ -38,7 +38,7 @@ AbstractReprEncoder, abstract_repr, ) -from pulser.json.abstract_repr.validation import RESOLVER +from pulser.json.abstract_repr.validation import REGISTRY from pulser.json.exceptions import AbstractReprError, DeserializeDeviceError from pulser.parametrized.decorators import parametrize from pulser.parametrized.paramobj import ParamObj @@ -282,7 +282,7 @@ def validate_schema(instance): "pulser-core/pulser/json/abstract_repr/schemas/" "sequence-schema.json" ) as f: schema = json.load(f) - jsonschema.validate(instance=instance, schema=schema, resolver=RESOLVER) + jsonschema.validate(instance=instance, schema=schema, registry=REGISTRY) class TestSerialization: From 2315989dbfbf0e90a8701e9e7b537f18388b404a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Henrique=20Silv=C3=A9rio?= Date: Tue, 29 Aug 2023 15:07:10 +0200 Subject: [PATCH 06/18] Give access to all EOM block parameters and allow for phase drift correction (#566) * Isolate detuning off calculation * Adding option to correct for phase drift in EOM mode * Add UTs for phase drift correction * Abstract repr support * Include phase drift correctin in the EOM tutorial --- pulser-core/pulser/channels/eom.py | 16 ++++ .../pulser/json/abstract_repr/deserializer.py | 7 +- .../schemas/sequence-schema.json | 12 +++ .../pulser/json/abstract_repr/serializer.py | 31 ++++++- pulser-core/pulser/sequence/_schedule.py | 30 +++++- pulser-core/pulser/sequence/sequence.py | 91 ++++++++++++++++--- tests/test_abstract_repr.py | 84 ++++++++++++----- tests/test_sequence.py | 54 ++++++++++- .../Output Modulation and EOM Mode.ipynb | 14 +-- 9 files changed, 286 insertions(+), 53 deletions(-) diff --git a/pulser-core/pulser/channels/eom.py b/pulser-core/pulser/channels/eom.py index 56455b6d..9409a259 100644 --- a/pulser-core/pulser/channels/eom.py +++ b/pulser-core/pulser/channels/eom.py @@ -180,6 +180,22 @@ def __post_init__(self) -> None: f" enumeration, not {self.limiting_beam}." ) + def calculate_detuning_off( + self, amp_on: float, detuning_on: float, optimal_detuning_off: float + ) -> float: + """Calculates the detuning when the amplitude is off in EOM mode. + + Args: + amp_on: The amplitude of the EOM pulses (in rad/µs). + detuning_on: The detuning of the EOM pulses (in rad/µs). + optimal_detuning_off: The optimal value of detuning (in rad/µs) + when there is no pulse being played. It will choose the closest + value among the existing options. + """ + off_options = self.detuning_off_options(amp_on, detuning_on) + closest_option = np.abs(off_options - optimal_detuning_off).argmin() + return cast(float, off_options[closest_option]) + def detuning_off_options( self, rabi_frequency: float, detuning_on: float ) -> np.ndarray: diff --git a/pulser-core/pulser/json/abstract_repr/deserializer.py b/pulser-core/pulser/json/abstract_repr/deserializer.py index 48d74360..9ce6f86b 100644 --- a/pulser-core/pulser/json/abstract_repr/deserializer.py +++ b/pulser-core/pulser/json/abstract_repr/deserializer.py @@ -263,6 +263,7 @@ def _deserialize_operation(seq: Sequence, op: dict, vars: dict) -> None: optimal_detuning_off=_deserialize_parameter( op["optimal_detuning_off"], vars ), + correct_phase_drift=op.get("correct_phase_drift", False), ) elif op["op"] == "add_eom_pulse": seq.add_eom_pulse( @@ -273,9 +274,13 @@ def _deserialize_operation(seq: Sequence, op: dict, vars: dict) -> None: op["post_phase_shift"], vars ), protocol=op["protocol"], + correct_phase_drift=op.get("correct_phase_drift", False), ) elif op["op"] == "disable_eom_mode": - seq.disable_eom_mode(channel=op["channel"]) + seq.disable_eom_mode( + channel=op["channel"], + correct_phase_drift=op.get("correct_phase_drift", False), + ) def _deserialize_channel(obj: dict[str, Any]) -> Channel: diff --git a/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json b/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json index ee0153c8..21d0900c 100644 --- a/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json +++ b/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json @@ -449,6 +449,10 @@ "$ref": "#/definitions/ChannelName", "description": "The name of the channel to take out of EOM mode." }, + "correct_phase_drift": { + "description": "Performs a phase shift to correct for the phase drift that occured since the last pulse (or the start of the EOM mode, if no pulse was added).", + "type": "boolean" + }, "op": { "const": "disable_eom_mode", "type": "string" @@ -467,6 +471,10 @@ "$ref": "#/definitions/ChannelName", "description": "The name of the channel to add the pulse to." }, + "correct_phase_drift": { + "description": "Performs a phase shift to correct for the phase drift that occured since the last pulse (or the start of the EOM mode, if adding the first pulse).", + "type": "boolean" + }, "duration": { "$ref": "#/definitions/ParametrizedNum", "description": "The duration of the pulse (in ns)." @@ -514,6 +522,10 @@ "$ref": "#/definitions/ChannelName", "description": "The name of the channel to put in EOM mode." }, + "correct_phase_drift": { + "description": "Performs a phase shift to correct for the phase drift incurred while turning on the EOM mode.", + "type": "boolean" + }, "detuning_on": { "$ref": "#/definitions/ParametrizedNum", "description": "The detuning of the EOM pulses (in rad/µs)." diff --git a/pulser-core/pulser/json/abstract_repr/serializer.py b/pulser-core/pulser/json/abstract_repr/serializer.py index c76e196d..ac5eb0ef 100644 --- a/pulser-core/pulser/json/abstract_repr/serializer.py +++ b/pulser-core/pulser/json/abstract_repr/serializer.py @@ -180,6 +180,15 @@ def get_all_args( } return {**default_values, **params} + def remove_kwarg_if_default( + data: dict[str, Any], call_name: str, kwarg_name: str + ) -> dict[str, Any]: + if data.get(kwarg_name, None) == get_kwarg_default( + call_name, kwarg_name + ): + data.pop(kwarg_name, None) + return data + operations = res["operations"] for call in chain(seq._calls, seq._to_build_calls): if call.name == "__init__": @@ -269,9 +278,18 @@ def get_all_args( res["slm_mask_targets"] = tuple(seq._slm_mask_targets) elif call.name == "enable_eom_mode": data = get_all_args( - ("channel", "amp_on", "detuning_on", "optimal_detuning_off"), + ( + "channel", + "amp_on", + "detuning_on", + "optimal_detuning_off", + "correct_phase_drift", + ), call, ) + data = remove_kwarg_if_default( + data, call.name, "correct_phase_drift" + ) operations.append({"op": "enable_eom_mode", **data}) elif call.name == "add_eom_pulse": data = get_all_args( @@ -281,15 +299,20 @@ def get_all_args( "phase", "post_phase_shift", "protocol", + "correct_phase_drift", ), call, ) + data = remove_kwarg_if_default( + data, call.name, "correct_phase_drift" + ) operations.append({"op": "add_eom_pulse", **data}) elif call.name == "disable_eom_mode": - data = get_all_args(("channel",), call) - operations.append( - {"op": "disable_eom_mode", "channel": data["channel"]} + data = get_all_args(("channel", "correct_phase_drift"), call) + data = remove_kwarg_if_default( + data, call.name, "correct_phase_drift" ) + operations.append({"op": "disable_eom_mode", **data}) else: raise AbstractReprError(f"Unknown call '{call.name}'.") diff --git a/pulser-core/pulser/sequence/_schedule.py b/pulser-core/pulser/sequence/_schedule.py index 816c5c91..5cfb8bc9 100644 --- a/pulser-core/pulser/sequence/_schedule.py +++ b/pulser-core/pulser/sequence/_schedule.py @@ -47,6 +47,16 @@ class _EOMSettings: tf: Optional[int] = None +@dataclass +class _PhaseDriftParams: + drift_rate: float # rad/µs + ti: int # ns + + def calc_phase_drift(self, tf: int) -> float: + """Calculate the phase drift during the elapsed time.""" + return self.drift_rate * (tf - self.ti) * 1e-3 + + @dataclass class _ChannelSchedule: channel_id: str @@ -350,8 +360,16 @@ def add_pulse( channel: str, phase_barrier_ts: list[int], protocol: str, + phase_drift_params: _PhaseDriftParams | None = None, ) -> None: - pass + def corrected_phase(tf: int) -> float: + phase_drift = ( + phase_drift_params.calc_phase_drift(tf) + if phase_drift_params + else 0 + ) + return pulse.phase - phase_drift + last = self[channel][-1] t0 = last.tf current_max_t = max(t0, *phase_barrier_ts) @@ -368,7 +386,7 @@ def add_pulse( ) last_pulse = cast(Pulse, last_pulse_slot.type) # Checks if the current pulse changes the phase - if last_pulse.phase != pulse.phase: + if last_pulse.phase != corrected_phase(current_max_t): # Subtracts the time that has already elapsed since the # last pulse from the phase_jump_time and adds the # fall_time to let the last pulse ramp down @@ -392,6 +410,14 @@ def add_pulse( ti = t0 + delay_duration tf = ti + pulse.duration self._check_duration(tf) + # dataclasses.replace() does not work on Pulse (because init=False) + if phase_drift_params is not None: + pulse = Pulse( + amplitude=pulse.amplitude, + detuning=pulse.detuning, + phase=corrected_phase(ti), + post_phase_shift=pulse.post_phase_shift, + ) self[channel].slots.append(_TimeSlot(pulse, ti, tf, last.targets)) def add_delay(self, duration: int, channel: str) -> None: diff --git a/pulser-core/pulser/sequence/sequence.py b/pulser-core/pulser/sequence/sequence.py index 72ba03ee..9d22a2be 100644 --- a/pulser-core/pulser/sequence/sequence.py +++ b/pulser-core/pulser/sequence/sequence.py @@ -55,7 +55,12 @@ from pulser.register.mappable_reg import MappableRegister from pulser.sequence._basis_ref import _QubitRef from pulser.sequence._call import _Call -from pulser.sequence._schedule import _ChannelSchedule, _Schedule, _TimeSlot +from pulser.sequence._schedule import ( + _ChannelSchedule, + _PhaseDriftParams, + _Schedule, + _TimeSlot, +) from pulser.sequence._seq_drawer import Figure, draw_sequence from pulser.sequence._seq_str import seq_to_str @@ -774,6 +779,7 @@ def enable_eom_mode( amp_on: Union[float, Parametrized], detuning_on: Union[float, Parametrized], optimal_detuning_off: Union[float, Parametrized] = 0.0, + correct_phase_drift: bool = False, ) -> None: """Puts a channel in EOM mode operation. @@ -806,6 +812,8 @@ def enable_eom_mode( optimal_detuning_off: The optimal value of detuning (in rad/µs) when there is no pulse being played. It will choose the closest value among the existing options. + correct_phase_drift: Performs a phase shift to correct for the + phase drift incurred while turning on the EOM mode. """ if self.is_in_eom_mode(channel): raise RuntimeError( @@ -822,29 +830,35 @@ def enable_eom_mode( channel_obj.validate_pulse(on_pulse) amp_on = cast(float, amp_on) detuning_on = cast(float, detuning_on) - - off_options = cast( - RydbergEOM, channel_obj.eom_config - ).detuning_off_options(amp_on, detuning_on) - + eom_config = cast(RydbergEOM, channel_obj.eom_config) if not isinstance(optimal_detuning_off, Parametrized): - closest_option = np.abs( - off_options - optimal_detuning_off - ).argmin() - detuning_off = off_options[closest_option] + detuning_off = eom_config.calculate_detuning_off( + amp_on, detuning_on, optimal_detuning_off + ) off_pulse = Pulse.ConstantPulse( channel_obj.min_duration, 0.0, detuning_off, 0.0 ) channel_obj.validate_pulse(off_pulse) if not self.is_parametrized(): + phase_drift_params = _PhaseDriftParams( + drift_rate=-detuning_off, ti=self.get_duration(channel) + ) self._schedule.enable_eom( channel, amp_on, detuning_on, detuning_off ) + if correct_phase_drift: + buffer_slot = self._last(channel) + drift = phase_drift_params.calc_phase_drift(buffer_slot.tf) + self._phase_shift( + -drift, *buffer_slot.targets, basis=channel_obj.basis + ) @seq_decorators.store @seq_decorators.block_if_measured - def disable_eom_mode(self, channel: str) -> None: + def disable_eom_mode( + self, channel: str, correct_phase_drift: bool = False + ) -> None: """Takes a channel out of EOM mode operation. For channels with a finite modulation bandwidth and an EOM, operation @@ -867,11 +881,24 @@ def disable_eom_mode(self, channel: str) -> None: Args: channel: The name of the channel to take out of EOM mode. + correct_phase_drift: Performs a phase shift to correct for the + phase drift that occured since the last pulse (or the start of + the EOM mode, if no pulse was added). """ if not self.is_in_eom_mode(channel): raise RuntimeError(f"The '{channel}' channel is not in EOM mode.") if not self.is_parametrized(): self._schedule.disable_eom(channel) + if correct_phase_drift: + ch_schedule = self._schedule[channel] + # EOM mode has just been disabled, so tf is defined + last_eom_block_tf = cast(int, ch_schedule.eom_blocks[-1].tf) + drift_params = self._get_last_eom_pulse_phase_drift(channel) + self._phase_shift( + -drift_params.calc_phase_drift(last_eom_block_tf), + *ch_schedule[-1].targets, + basis=ch_schedule.channel_obj.basis, + ) @seq_decorators.store @seq_decorators.mark_non_empty @@ -883,6 +910,7 @@ def add_eom_pulse( phase: Union[float, Parametrized], post_phase_shift: Union[float, Parametrized] = 0.0, protocol: PROTOCOLS = "min-delay", + correct_phase_drift: bool = False, ) -> None: """Adds a square pulse to a channel in EOM mode. @@ -913,6 +941,11 @@ def add_eom_pulse( immediately after the end of the pulse. protocol: Stipulates how to deal with eventual conflicts with other channels (see `Sequence.add()` for more details). + correct_phase_drift: Adjusts the phase to correct for the phase + drift that occured since the last pulse (or the start of the + EOM mode, if adding the first pulse). This effectively + changes the phase of the EOM pulse, so an extra delay might + be added to enforce the phase jump time. """ if not self.is_in_eom_mode(channel): raise RuntimeError(f"Channel '{channel}' must be in EOM mode.") @@ -936,7 +969,14 @@ def add_eom_pulse( phase, post_phase_shift=post_phase_shift, ) - self._add(eom_pulse, channel, protocol) + phase_drift_params = ( + self._get_last_eom_pulse_phase_drift(channel) + if correct_phase_drift + else None + ) + self._add( + eom_pulse, channel, protocol, phase_drift_params=phase_drift_params + ) @seq_decorators.store @seq_decorators.mark_non_empty @@ -1446,6 +1486,7 @@ def _add( pulse: Union[Pulse, Parametrized], channel: str, protocol: PROTOCOLS, + phase_drift_params: _PhaseDriftParams | None = None, ) -> None: self._validate_add_protocol(protocol) if self.is_parametrized(): @@ -1475,7 +1516,13 @@ def _add( self._basis_ref[basis][q].phase.last_time for q in last.targets ] - self._schedule.add_pulse(pulse, channel, phase_barriers, protocol) + self._schedule.add_pulse( + pulse, + channel, + phase_barriers, + protocol, + phase_drift_params=phase_drift_params, + ) true_finish = self._last(channel).tf + pulse.fall_time( channel_obj, in_eom_mode=self.is_in_eom_mode(channel) @@ -1590,6 +1637,24 @@ def _phase_shift( for qubit in target_ids: self._basis_ref[basis][qubit].increment_phase(phi) + def _get_last_eom_pulse_phase_drift( + self, channel: str + ) -> _PhaseDriftParams: + eom_settings = self._schedule[channel].eom_blocks[-1] + try: + last_pulse_tf = ( + self._schedule[channel] + .last_pulse_slot(ignore_detuned_delay=True) + .tf + ) + except RuntimeError: + # There is no previous pulse + last_pulse_tf = 0 + return _PhaseDriftParams( + drift_rate=-eom_settings.detuning_off, + ti=max(eom_settings.ti, last_pulse_tf), + ) + def _to_dict(self, _module: str = "pulser.sequence") -> dict[str, Any]: d = obj_to_dict( self, diff --git a/tests/test_abstract_repr.py b/tests/test_abstract_repr.py index 745452de..3558c705 100644 --- a/tests/test_abstract_repr.py +++ b/tests/test_abstract_repr.py @@ -732,32 +732,48 @@ def test_mappable_register(self, triangular_lattice): ] assert abstract["variables"]["var"] == dict(type="int", value=[0]) - def test_eom_mode(self, triangular_lattice): + @pytest.mark.parametrize("correct_phase_drift", (False, True)) + def test_eom_mode(self, triangular_lattice, correct_phase_drift): reg = triangular_lattice.hexagonal_register(7) seq = Sequence(reg, IroiseMVP) seq.declare_channel("ryd", "rydberg_global") det_off = seq.declare_variable("det_off", dtype=float) duration = seq.declare_variable("duration", dtype=int) seq.enable_eom_mode( - "ryd", amp_on=3.0, detuning_on=0.0, optimal_detuning_off=det_off + "ryd", + amp_on=3.0, + detuning_on=0.0, + optimal_detuning_off=det_off, + correct_phase_drift=correct_phase_drift, + ) + seq.add_eom_pulse( + "ryd", duration, 0.0, correct_phase_drift=correct_phase_drift ) - seq.add_eom_pulse("ryd", duration, 0.0) seq.delay(duration, "ryd") - seq.disable_eom_mode("ryd") + seq.disable_eom_mode("ryd", correct_phase_drift) abstract = json.loads(seq.to_abstract_repr()) validate_schema(abstract) + extra_kwargs = ( + dict(correct_phase_drift=correct_phase_drift) + if correct_phase_drift + else {} + ) + assert abstract["operations"][0] == { - "op": "enable_eom_mode", - "channel": "ryd", - "amp_on": 3.0, - "detuning_on": 0.0, - "optimal_detuning_off": { - "expression": "index", - "lhs": {"variable": "det_off"}, - "rhs": 0, + **{ + "op": "enable_eom_mode", + "channel": "ryd", + "amp_on": 3.0, + "detuning_on": 0.0, + "optimal_detuning_off": { + "expression": "index", + "lhs": {"variable": "det_off"}, + "rhs": 0, + }, }, + **extra_kwargs, } ser_duration = { @@ -766,17 +782,23 @@ def test_eom_mode(self, triangular_lattice): "rhs": 0, } assert abstract["operations"][1] == { - "op": "add_eom_pulse", - "channel": "ryd", - "duration": ser_duration, - "phase": 0.0, - "post_phase_shift": 0.0, - "protocol": "min-delay", + **{ + "op": "add_eom_pulse", + "channel": "ryd", + "duration": ser_duration, + "phase": 0.0, + "post_phase_shift": 0.0, + "protocol": "min-delay", + }, + **extra_kwargs, } assert abstract["operations"][3] == { - "op": "disable_eom_mode", - "channel": "ryd", + **{ + "op": "disable_eom_mode", + "channel": "ryd", + }, + **extra_kwargs, } @pytest.mark.parametrize("use_default", [True, False]) @@ -877,6 +899,10 @@ def _check_roundtrip(serialized_seq: dict[str, Any]): *(op[wf][qty] for qty in wf_args) ) op[wf] = reconstructed_wf._to_abstract_repr() + elif "eom" in op["op"] and not op.get("correct_phase_drift"): + # Remove correct_phase_drift when at default, since the + # roundtrip will delete it + op.pop("correct_phase_drift", None) seq = Sequence.from_abstract_repr(json.dumps(s)) defaults = { @@ -1425,7 +1451,8 @@ def test_deserialize_parametrized_pulse(self, op, pulse_cls): else: assert pulse.kwargs["detuning"] == 1 - def test_deserialize_eom_ops(self): + @pytest.mark.parametrize("correct_phase_drift", (False, True, None)) + def test_deserialize_eom_ops(self, correct_phase_drift): s = _get_serialized_seq( operations=[ { @@ -1434,6 +1461,7 @@ def test_deserialize_eom_ops(self): "amp_on": 3.0, "detuning_on": 0.0, "optimal_detuning_off": -1.0, + "correct_phase_drift": correct_phase_drift, }, { "op": "add_eom_pulse", @@ -1446,16 +1474,21 @@ def test_deserialize_eom_ops(self): "phase": 0.0, "post_phase_shift": 0.0, "protocol": "no-delay", + "correct_phase_drift": correct_phase_drift, }, { "op": "disable_eom_mode", "channel": "global", + "correct_phase_drift": correct_phase_drift, }, ], variables={"duration": {"type": "int", "value": [100]}}, device=json.loads(IroiseMVP.to_abstract_repr()), channels={"global": "rydberg_global"}, ) + if correct_phase_drift is None: + for op in s["operations"]: + del op["correct_phase_drift"] _check_roundtrip(s) seq = Sequence.from_abstract_repr(json.dumps(s)) # init + declare_channel + enable_eom_mode @@ -1470,11 +1503,15 @@ def test_deserialize_eom_ops(self): "amp_on": 3.0, "detuning_on": 0.0, "optimal_detuning_off": -1.0, + "correct_phase_drift": bool(correct_phase_drift), } disable_eom_call = seq._to_build_calls[-1] assert disable_eom_call.name == "disable_eom_mode" - assert disable_eom_call.kwargs == {"channel": "global"} + assert disable_eom_call.kwargs == { + "channel": "global", + "correct_phase_drift": bool(correct_phase_drift), + } eom_pulse_call = seq._to_build_calls[0] assert eom_pulse_call.name == "add_eom_pulse" @@ -1483,6 +1520,9 @@ def test_deserialize_eom_ops(self): assert eom_pulse_call.kwargs["phase"] == 0.0 assert eom_pulse_call.kwargs["post_phase_shift"] == 0.0 assert eom_pulse_call.kwargs["protocol"] == "no-delay" + assert eom_pulse_call.kwargs["correct_phase_drift"] == bool( + correct_phase_drift + ) @pytest.mark.parametrize( "wf_obj", diff --git a/tests/test_sequence.py b/tests/test_sequence.py index 79063b19..863a24e2 100644 --- a/tests/test_sequence.py +++ b/tests/test_sequence.py @@ -1402,8 +1402,11 @@ def test_multiple_index_targets(reg): assert built_seq._last("ch0").targets == {"q2", "q3"} +@pytest.mark.parametrize("correct_phase_drift", (True, False)) @pytest.mark.parametrize("custom_buffer_time", (None, 400)) -def test_eom_mode(reg, mod_device, custom_buffer_time, patch_plt_show): +def test_eom_mode( + reg, mod_device, custom_buffer_time, correct_phase_drift, patch_plt_show +): # Setting custom_buffer_time channels = mod_device.channels eom_config = dataclasses.replace( @@ -1449,22 +1452,39 @@ def test_eom_mode(reg, mod_device, custom_buffer_time, patch_plt_show): ] pulse_duration = 100 - seq.add_eom_pulse("ch0", pulse_duration, phase=0.0) + seq.add_eom_pulse( + "ch0", + pulse_duration, + phase=0.0, + correct_phase_drift=correct_phase_drift, + ) first_pulse_slot = seq._schedule["ch0"].last_pulse_slot() assert first_pulse_slot.ti == delay_slot.tf assert first_pulse_slot.tf == first_pulse_slot.ti + pulse_duration - eom_pulse = Pulse.ConstantPulse(pulse_duration, amp_on, detuning_on, 0.0) + phase = detuning_off * first_pulse_slot.ti * 1e-3 * correct_phase_drift + eom_pulse = Pulse.ConstantPulse(pulse_duration, amp_on, detuning_on, phase) assert first_pulse_slot.type == eom_pulse assert not seq._schedule["ch0"].is_detuned_delay(eom_pulse) # Check phase jump buffer - seq.add_eom_pulse("ch0", pulse_duration, phase=np.pi) + phase_ = np.pi + seq.add_eom_pulse( + "ch0", + pulse_duration, + phase=phase_, + correct_phase_drift=correct_phase_drift, + ) second_pulse_slot = seq._schedule["ch0"].last_pulse_slot() phase_buffer = ( eom_pulse.fall_time(ch0_obj, in_eom_mode=True) + seq.declared_channels["ch0"].phase_jump_time ) assert second_pulse_slot.ti == first_pulse_slot.tf + phase_buffer + # Corrects the phase acquired during the phase buffer + phase_ += detuning_off * phase_buffer * 1e-3 * correct_phase_drift + assert second_pulse_slot.type == Pulse.ConstantPulse( + pulse_duration, amp_on, detuning_on, phase_ + ) # Check phase jump buffer is not enforced with "no-delay" seq.add_eom_pulse("ch0", pulse_duration, phase=0.0, protocol="no-delay") @@ -1495,8 +1515,15 @@ def test_eom_mode(reg, mod_device, custom_buffer_time, patch_plt_show): ) assert buffer_delay.type == "delay" + assert seq.current_phase_ref("q0", basis="ground-rydberg") == 0 # Check buffer when EOM is not enabled at the start of the sequence - seq.enable_eom_mode("ch0", amp_on, detuning_on, optimal_detuning_off=-100) + seq.enable_eom_mode( + "ch0", + amp_on, + detuning_on, + optimal_detuning_off=-100, + correct_phase_drift=correct_phase_drift, + ) last_slot = seq._schedule["ch0"][-1] assert len(seq._schedule["ch0"].eom_blocks) == 2 new_eom_block = seq._schedule["ch0"].eom_blocks[1] @@ -1511,6 +1538,23 @@ def test_eom_mode(reg, mod_device, custom_buffer_time, patch_plt_show): assert last_slot.type == Pulse.ConstantPulse( duration, 0.0, new_eom_block.detuning_off, last_pulse_slot.type.phase ) + # Check the phase shift that corrects for the drift + phase_ref = ( + (new_eom_block.detuning_off * duration * 1e-3) + % (2 * np.pi) + * correct_phase_drift + ) + assert seq.current_phase_ref("q0", basis="ground-rydberg") == phase_ref + + # Add delay to test the phase drift correction in disable_eom_mode + last_delay_time = 400 + seq.delay(last_delay_time, "ch0") + + seq.disable_eom_mode("ch0", correct_phase_drift=True) + phase_ref += new_eom_block.detuning_off * last_delay_time * 1e-3 + assert seq.current_phase_ref("q0", basis="ground-rydberg") == phase_ref % ( + 2 * np.pi + ) # Test drawing in eom mode seq.draw() diff --git a/tutorials/advanced_features/Output Modulation and EOM Mode.ipynb b/tutorials/advanced_features/Output Modulation and EOM Mode.ipynb index 5451b11b..c96025b3 100644 --- a/tutorials/advanced_features/Output Modulation and EOM Mode.ipynb +++ b/tutorials/advanced_features/Output Modulation and EOM Mode.ipynb @@ -250,11 +250,11 @@ "source": [ "The modulation bandwidth of a channel can impose significant limitations on how a pulse sequence is programmed. Perhaps most importantly, it can force the user to program longer pulses than would otherwise be required, resulting in longer sequences and consequently noisier results.\n", "\n", - "To overcome these limitations, a channel can be equipped with an EOM that allows the execution of pulses with a higher modulation bandwidth. For now, EOM mode operation is reserved for `Rydberg` channels and works under very specific conditions:\n", + "To overcome these limitations, a channel can be equipped with an EOM that allows the execution of square pulses with a higher modulation bandwidth. For now, EOM mode operation is reserved for `Rydberg` channels and works under very specific conditions:\n", "\n", " 1. EOM mode must be explicitly enabled (`Sequence.enable_eom_mode()`) and disabled (`Sequence.disable_eom_mode()`).\n", " 2. A buffering time is automatically added before the EOM mode is enabled and after it is disabled, as it needs to be isolated from regular channel operation. During the starting buffer, the detuning goes to the value it will assume between EOM pulses (_i.e._ during delays).\n", - " 3. When enabling the EOM mode, one must choose the amplitude and detuning value that all square pulses will have. These values will also determine a set of options for the detuning during delays, out of which one chosen.\n", + " 3. When enabling the EOM mode, one must choose the amplitude and detuning value that all square pulses will have. These values will also determine a set of options for the detuning during delays, out of which the best one is chosen. When this detuning value is not zero, the phase of each qubit's state will drift during delays. If desired, this phase drift can be corrected through the `correct_phase_drift` option, which will adjust the phase of subsequent pulses accordingly. \n", " 4. While in EOM mode, one can only add delays or pulses of variable duration (through `Sequence.add_eom_pulse()`) – changing the phase between pulses is also allowed, but the necessary buffer time for a phase jump will still be enforced." ] }, @@ -280,12 +280,12 @@ "seq.add(Pulse.ConstantPulse(100, 1, 0, 0), \"rydberg\")\n", "seq.enable_eom_mode(\"rydberg\", amp_on=1.0, detuning_on=0.0)\n", "seq.add_eom_pulse(\"rydberg\", duration=100, phase=0.0)\n", - "seq.delay(200, \"rydberg\")\n", - "seq.add_eom_pulse(\"rydberg\", duration=60, phase=0.0)\n", + "seq.delay(300, \"rydberg\")\n", + "seq.add_eom_pulse(\"rydberg\", duration=60, phase=0.0, correct_phase_drift=True)\n", "seq.disable_eom_mode(\"rydberg\")\n", "seq.add(Pulse.ConstantPulse(100, 1, 0, 0), \"rydberg\")\n", "\n", - "seq.draw()" + "seq.draw(draw_phase_curve=True)" ] }, { @@ -302,7 +302,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As expected, inside the isolated EOM mode block in the middle we see that the pulses are much sharper, but we can only do square pulses with a fixed amplitude and there is some non-zero detuning in between them." + "As expected, inside the isolated EOM mode block in the middle we see that the pulses are much sharper, but we can only do square pulses with a fixed amplitude and there is some non-zero detuning in between them. \n", + "\n", + "We also observe how the phase of the second EOM pulse changes to correct for the phase drift during the detuned delay (because we set `correct_phase_drift=True`)." ] } ], From c4693ed2da88267e4961c11cb6f981ba82ebe607 Mon Sep 17 00:00:00 2001 From: Antoine Cornillot <61453516+a-corni@users.noreply.github.com> Date: Thu, 14 Sep 2023 18:16:54 +0200 Subject: [PATCH 07/18] Bug Fix: error message in switch_device (#580) * Fixing error message in switch_device * Modifying comments --- pulser-core/pulser/sequence/sequence.py | 8 +++++ tests/test_sequence.py | 41 ++++++++++++++++++++++--- 2 files changed, 45 insertions(+), 4 deletions(-) diff --git a/pulser-core/pulser/sequence/sequence.py b/pulser-core/pulser/sequence/sequence.py index 9d22a2be..ee86759e 100644 --- a/pulser-core/pulser/sequence/sequence.py +++ b/pulser-core/pulser/sequence/sequence.py @@ -553,6 +553,9 @@ def check_retarget(ch_obj: Channel) -> bool: continue if not strict: channel_match[old_ch_name] = new_ch_id + # Found a match, clear match error msg for this channel + if ch_match_err.startswith(base_msg): + ch_match_err = "" break params_to_check = [ @@ -574,6 +577,11 @@ def check_retarget(ch_obj: Channel) -> bool: else: # Only reached if all checks passed channel_match[old_ch_name] = new_ch_id + # Found a match, clear match error msgs for this channel + if ch_match_err.startswith(base_msg): + ch_match_err = "" + if strict_error_message.startswith(base_msg): + strict_error_message = "" break if None in channel_match.values(): diff --git a/tests/test_sequence.py b/tests/test_sequence.py index 863a24e2..8846bb52 100644 --- a/tests/test_sequence.py +++ b/tests/test_sequence.py @@ -336,22 +336,55 @@ def test_switch_device_down(reg, devices, pulses, mappable_reg, parametrized): # From sequence reusing channels to Device without reusable channels seq = init_seq( reg, - MockDevice, + dataclasses.replace(Chadoq2.to_virtual(), reusable_channels=True), "global", "rydberg_global", None, parametrized=parametrized, mappable_reg=mappable_reg, ) - seq.declare_channel("global2", "rydberg_global") + seq.declare_channel("raman", "raman_local", ["q0"]) + seq.declare_channel("raman_1", "raman_local", ["q0"]) + with pytest.raises( + TypeError, + match="No match for channel raman_1 with the" + " right type, basis and addressing.", + ): + # Can't find a match for the 2nd raman_local + seq.switch_device(Chadoq2) + with pytest.raises( TypeError, - match="No match for channel global2 with the" + match="No match for channel raman_1 with the" " right type, basis and addressing.", ): - # Can't find a match for the 2nd rydberg_global + # Can't find a match for the 2nd raman_local seq.switch_device(Chadoq2) + with pytest.raises( + ValueError, + match="No match for channel raman_1 with the" " same clock_period.", + ): + # Can't find a match for the 2nd rydberg_local + seq.switch_device( + dataclasses.replace( + Chadoq2, + channel_objects=( + Chadoq2.channels["rydberg_global"], + dataclasses.replace( + Chadoq2.channels["raman_local"], clock_period=10 + ), + Chadoq2.channels["raman_local"], + ), + channel_ids=( + "rydberg_global", + "rydberg_local", + "rydberg_local1", + ), + ), + strict=True, + ) + seq_ising = init_seq( reg, MockDevice, From 25b54eb34a8af03e2cd31fb60229f83002fa0b83 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Henrique=20Silv=C3=A9rio?= Date: Fri, 15 Sep 2023 10:50:27 +0200 Subject: [PATCH 08/18] Pin matplotlib < 3.8 (#582) --- pulser-core/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pulser-core/requirements.txt b/pulser-core/requirements.txt index 69fa4291..bcd036d5 100644 --- a/pulser-core/requirements.txt +++ b/pulser-core/requirements.txt @@ -1,5 +1,5 @@ jsonschema >= 4.18 -matplotlib +matplotlib < 3.8 # Numpy 1.20 introduces type hints, 1.24.0 breaks matplotlib < 3.6.1 numpy >= 1.20, != 1.24.0 scipy \ No newline at end of file From b5a75af027d4a7298a705cfb1a774144675d4c33 Mon Sep 17 00:00:00 2001 From: Antoine Cornillot <61453516+a-corni@users.noreply.github.com> Date: Fri, 15 Sep 2023 10:57:10 +0200 Subject: [PATCH 09/18] Fix switch device err message (#581) * Adding forgotten strict in test --- tests/test_sequence.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_sequence.py b/tests/test_sequence.py index 8846bb52..077c9cf3 100644 --- a/tests/test_sequence.py +++ b/tests/test_sequence.py @@ -359,7 +359,7 @@ def test_switch_device_down(reg, devices, pulses, mappable_reg, parametrized): " right type, basis and addressing.", ): # Can't find a match for the 2nd raman_local - seq.switch_device(Chadoq2) + seq.switch_device(Chadoq2, strict=True) with pytest.raises( ValueError, From d9e1fd2362e2ea03414f6a9b97c2626639606992 Mon Sep 17 00:00:00 2001 From: Louis Vignoli <97944962+lvignoli@users.noreply.github.com> Date: Fri, 15 Sep 2023 18:22:43 +0900 Subject: [PATCH 10/18] Change EmuTN default sampling rate (#578) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Change default sampling rate * Add hint to docstring * Fix test --------- Co-authored-by: Henrique Silvério --- pulser-pasqal/pulser_pasqal/backends.py | 7 +++++-- tests/test_pasqal.py | 2 +- 2 files changed, 6 insertions(+), 3 deletions(-) diff --git a/pulser-pasqal/pulser_pasqal/backends.py b/pulser-pasqal/pulser_pasqal/backends.py index 56dfb0b1..43d72333 100644 --- a/pulser-pasqal/pulser_pasqal/backends.py +++ b/pulser-pasqal/pulser_pasqal/backends.py @@ -24,7 +24,9 @@ from pulser.backend.remote import JobParams, RemoteBackend, RemoteResults from pulser_pasqal.pasqal_cloud import PasqalCloud -DEFAULT_CONFIG_EMU_TN = EmulatorConfig(evaluation_times="Final") +DEFAULT_CONFIG_EMU_TN = EmulatorConfig( + evaluation_times="Final", sampling_rate=0.1 +) DEFAULT_CONFIG_EMU_FREE = EmulatorConfig( evaluation_times="Final", sampling_rate=0.25 ) @@ -109,7 +111,8 @@ class EmuTNBackend(PasqalEmulator): """An emulator backend using tensor network simulation. Configurable fields in EmulatorConfig: - - sampling_rate + - sampling_rate: Defaults to 0.1. This value must remain low to use + this backend efficiently. - backend_options: - precision (str): The precision of the simulation. Can be "low", "normal" or "high". Defaults to "normal". diff --git a/tests/test_pasqal.py b/tests/test_pasqal.py index 5124c289..ca4b7279 100644 --- a/tests/test_pasqal.py +++ b/tests/test_pasqal.py @@ -321,7 +321,7 @@ def test_emulators_run(fixt, seq, emu_cls, parametrized: bool): sdk_config: EmuTNConfig | EmuFreeConfig if isinstance(emu, EmuTNBackend): emulator_type = EmulatorType.EMU_TN - sdk_config = EmuTNConfig(dt=1.0) + sdk_config = EmuTNConfig(dt=10) else: emulator_type = EmulatorType.EMU_FREE sdk_config = EmuFreeConfig() From 52709448e3e4d9a63109a7c218dba583cb0c002f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Henrique=20Silv=C3=A9rio?= Date: Fri, 15 Sep 2023 17:35:38 +0200 Subject: [PATCH 11/18] Clarify the Conventions in Pulser (#573) * Fix XY mode conventions * Adding the Conventions page * Change the order of the sections * Add Note and Warning text boxes * Better math highlights, bigger table * Fix typo in sum indices * Fix bug in math highlighting * Rephrasing to trigger RTD build * Cosmetic changes * Implement review suggestions * Adding energy level picture * Fix measurement value for XY in projectors * Add caption and change the warning position * Fix UTs * Fix random typos in tutorials * Edit SLM Mask tutorial and add link to conventions * Adapt XYZ Tutorial to new XY basis convention --- docs/source/conventions.rst | 246 ++++++++++++++++++ docs/source/files/two_level_ab.png | Bin 0 -> 59296 bytes docs/source/index.rst | 1 + docs/source/intro_rydberg_blockade.ipynb | 4 +- docs/source/review.rst | 4 +- .../pulser_simulation/qutip_result.py | 6 +- .../pulser_simulation/simresults.py | 18 +- .../pulser_simulation/simulation.py | 8 +- tests/test_simresults.py | 7 +- tests/test_simulation.py | 7 +- .../State Preparation with the SLM Mask.ipynb | 20 +- ...iltonians in arrays of Rydberg atoms.ipynb | 183 +++++-------- .../Spin chain of 3 atoms in XY mode.ipynb | 30 ++- 13 files changed, 384 insertions(+), 150 deletions(-) create mode 100644 docs/source/conventions.rst create mode 100644 docs/source/files/two_level_ab.png diff --git a/docs/source/conventions.rst b/docs/source/conventions.rst new file mode 100644 index 00000000..32e55afb --- /dev/null +++ b/docs/source/conventions.rst @@ -0,0 +1,246 @@ +**************************************** +Conventions +**************************************** + +States and Bases +#################################### + +Bases +******* +A basis refers to a set of two eigenstates. The transition between +these two states is said to be addressed by a channel that targets that basis. Namely: + +.. list-table:: + :align: center + :widths: 50 35 35 + :header-rows: 1 + + * - Basis + - Eigenstates + - ``Channel`` type + * - ``ground-rydberg`` + - :math:`|g\rangle,~|r\rangle` + - ``Rydberg`` + * - ``digital`` + - :math:`|g\rangle,~|h\rangle` + - ``Raman`` + * - ``XY`` + - :math:`|0\rangle,~|1\rangle` + - ``Microwave`` + + + +Qutrit state +****************** + +The qutrit state combines the basis states of the ``ground-rydberg`` and ``digital`` bases, +which share the same ground state, :math:`|g\rangle`. This qutrit state comes into play +in the digital approach, where the qubit state is encoded in :math:`|g\rangle` and +:math:`|h\rangle` but then the Rydberg state :math:`|r\rangle` is accessed in multi-qubit +gates. + +The qutrit state's basis vectors are defined as: + +.. math:: |r\rangle = (1, 0, 0)^T,~~|g\rangle = (0, 1, 0)^T, ~~|h\rangle = (0, 0, 1)^T. + +Qubit states +************** + +.. warning:: + There is no implicit relationship between a state's vector representation and its + associated measurement value. To see the measurement value of a state for each + measurement basis, see :ref:`SPAM` . + +When using only the ``ground-rydberg`` or ``digital`` basis, the qutrit state is not +needed and is thus reduced to a qubit state. This reduction is made simply by tracing-out +the extra basis state, so we obtain + +* ``ground-rydberg``: :math:`|r\rangle = (1, 0)^T,~~|g\rangle = (0, 1)^T` +* ``digital``: :math:`|g\rangle = (1, 0)^T,~~|h\rangle = (0, 1)^T` + +On the other hand, the ``XY`` basis uses an independent set of qubit states that are +labelled :math:`|0\rangle` and :math:`|1\rangle` and follow the standard convention: + +* ``XY``: :math:`|0\rangle = (1, 0)^T,~~|1\rangle = (0, 1)^T` + +Multi-partite states +************************* + +The combined quantum state of multiple atoms respects their order in the ``Register``. +For a register with ordered atoms ``(q0, q1, q2, ..., qn)``, the full quantum state will be + +.. math:: |q_0, q_1, q_2, ...\rangle = |q_0\rangle \otimes |q_1\rangle \otimes |q_2\rangle \otimes ... \otimes |q_n\rangle + +.. note:: + The atoms may be labelled arbitrarily without any inherent order, it's only the + order with which they are stored in the ``Register`` (as returned by + ``Register.qubit_ids``) that matters . + +.. _SPAM: + +State Preparation and Measurement +#################################### + +.. list-table:: Initial State and Measurement Conventions + :align: center + :widths: 60 40 75 + :header-rows: 1 + + * - Basis + - Initial state + - Measurement + * - ``ground-rydberg`` + - :math:`|g\rangle` + - | + | :math:`|r\rangle \rightarrow 1` + | :math:`|g\rangle,|h\rangle \rightarrow 0` + * - ``digital`` + - :math:`|g\rangle` + - | + | :math:`|h\rangle \rightarrow 1` + | :math:`|g\rangle,|r\rangle \rightarrow 0` + * - ``XY`` + - :math:`|0\rangle` + - | + | :math:`|1\rangle \rightarrow 1` + | :math:`|0\rangle \rightarrow 0` + +Measurement samples order +*************************** + +Measurement samples are returned as a sequence of 0s and 1s, in +the same order as the atoms in the ``Register`` and in the multi-partite state. + +For example, a four-qutrit state :math:`|q_0, q_1, q_2, q_3\rangle` that's +projected onto :math:`|g, r, h, r\rangle` when measured will record a count to +sample + +* ``0101``, if measured in the ``ground-rydberg`` basis +* ``0010``, if measured in the ``digital`` basis + +Hamiltonians +#################################### + +Independently of the mode of operation, the Hamiltonian describing the system +can be written as + +.. math:: H(t) = \sum_i \left (H^D_i(t) + \sum_{jeCysncikWNhildhnIxR|w7vJUpZ%P}%~OWjTQ}|8L`O%r zRafVjF&!P_ARXPty(}By9rw7Bx`Gyd68z6KM>Aa~0|UAP@S25g1N}BS zM&v8-4;}qZx((~E>F7?<@A~!Hn1261-(jGmi*TW1`sX_q@Dq7?68X=spNyIGzgx^? z`1x(d!A!=VuQ%>RevhkO)DM2Jdg_?_(9y}(A^+0vzhKcrN2f`rdra#LihjJ0wS2E* z;Qr5Hoz$}%wYYDeJ){OWemXe2I2#hwe9xe5>hrcDn7@?gN<*uk!I& z2{UNjxc$6we~ON<@Qe3bRKgFve&4&;z2atI~=#=b3Mw;qw+&_i%Z2 zLg~Z(|Irp-Qr&nqW?`kbdsE=+|M}r#TTNjbT%q89JE3W!Dcqm+Tcm;MaKNMFNfh>gH5~sJBCa&JqAT<4Ei6lU;yvNz1sNS z3HsArWS0KS?)t9yvl;$uhF?zO&t~|u8UAdBUo-IkYBONs?_0_v;J|M0hJ-`rvUi7M z_cJ`&EA85zcY0?`;d<1^6fiJM6{yOxatKR@U<@&3nhp#2zhWOr-Ns1;rfH8a-`$r7 zpK020L->D$Iumu14zokN?cnW;%^7!eL=7^JXIj?@48#vov#pa8oW{4UcmBa9mimZy 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zSpFPLwNn)d1VL=26?GZ^?qi>(ln(e#l3W*I4eEX!c_Kf7B~~5Q^uJ8PUfJQ1xtj=Gxr_hrisn-IK`V6-mE2 zS;;pj{%LRBhS7r*)?rGEY3HUFr<&eXAnii&?A`SsFY&+E8{oOUq22bEo@&;?eFFR+r zZG~T!6)4+qZZF@~9F-+vu;Qt%EUNj_xM#D6_xWW|$ArG#i_+65AFoU^PSYZ5H(wx} z{WvlL6!yzbBkqQ@{;aUMP-rb>W8a9>HaRe zW$cZAw*csG;Ewp;VzC(e1>Z5S9De@@{(yy?xP9Xs^y#0!k%8!Eq`vB&{#`fSqaPdn1^@f|i1y*6L#EgNKP#ToeE np.ndarray: # State vector ordered with r first for 'ground_rydberg' # e.g. n=2: [rr, rg, gr, gg] -> [11, 10, 01, 00] # Invert the order -> [00, 01, 10, 11] correspondence - # The same applies in XY mode, which is ordered with u first + # In the XY and digital bases, the order is canonical weights = ( - probs if self.meas_basis == "digital" else probs[::-1] + probs[::-1] + if self.meas_basis == "ground-rydberg" + else probs ) else: # Only 000...000 is measured diff --git a/pulser-simulation/pulser_simulation/simresults.py b/pulser-simulation/pulser_simulation/simresults.py index 8e954c54..9552414b 100644 --- a/pulser-simulation/pulser_simulation/simresults.py +++ b/pulser-simulation/pulser_simulation/simresults.py @@ -217,11 +217,11 @@ def _meas_projector(self, state_n: int) -> qutip.Qobj: Args: state_n: The measured state (0 or 1). """ - if self._basis_name == "digital": - return qutip.basis(2, state_n).proj() + if self._basis_name == "ground-rydberg": + # 0 = |g>; 1 = |r> + return qutip.basis(2, 1 - state_n).proj() - # 0 = |g or d> = |1>; 1 = |r or u> = |0> - return qutip.basis(2, 1 - state_n).proj() + return qutip.basis(2, state_n).proj() class NoisyResults(SimulationResults): @@ -495,9 +495,13 @@ def _meas_projector(self, state_n: int) -> qutip.Qobj: else self._meas_errors["epsilon_prime"] ) # 'good' is the position of the state that measures to state_n - # Matches for the digital basis, is inverted for ground-rydberg and - # for XY - good = state_n if self._basis_name == "digital" else 1 - state_n + # Matches for the digital basis and XY, is inverted for + # ground-rydberg + good = ( + 1 - state_n + if self._basis_name == "ground-rydberg" + else state_n + ) return ( qutip.basis(2, good).proj() * (1 - err_param) + qutip.basis(2, 1 - good).proj() * err_param diff --git a/pulser-simulation/pulser_simulation/simulation.py b/pulser-simulation/pulser_simulation/simulation.py index e2f36b1b..62433e18 100644 --- a/pulser-simulation/pulser_simulation/simulation.py +++ b/pulser-simulation/pulser_simulation/simulation.py @@ -402,7 +402,7 @@ def set_initial_state( if isinstance(state, str) and state == "all-ground": self._initial_state = qutip.tensor( [ - self.basis["d" if self._interaction == "XY" else "g"] + self.basis["u" if self._interaction == "XY" else "g"] for _ in range(self._size) ] ) @@ -683,7 +683,7 @@ def make_xy_term(q1: QubitId, q2: QubitId) -> qutip.Qobj: """Construct the XY interaction Term. For each pair of qubits, calculate the distance between them, - then assign the local operator "sigma_du * sigma_ud" at each pair. + then assign the local operator "sigma_ud * sigma_du" at each pair. The units are given so that the coefficient includes a 1/hbar factor. """ @@ -707,7 +707,7 @@ def make_xy_term(q1: QubitId, q2: QubitId) -> qutip.Qobj: / dist**3 ) return U * self.build_operator( - [("sigma_du", [q1]), ("sigma_ud", [q2])] + [("sigma_ud", [q1]), ("sigma_du", [q2])] ) def make_interaction_term(masked: bool = False) -> qutip.Qobj: @@ -752,7 +752,7 @@ def build_coeffs_ops(basis: str, addr: str) -> list[list]: elif basis == "digital": op_ids = ["sigma_hg", "sigma_gg"] elif basis == "XY": - op_ids = ["sigma_du", "sigma_dd"] + op_ids = ["sigma_du", "sigma_uu"] terms = [] if addr == "Global": diff --git a/tests/test_simresults.py b/tests/test_simresults.py index 767146dc..ec8258c1 100644 --- a/tests/test_simresults.py +++ b/tests/test_simresults.py @@ -360,8 +360,9 @@ def test_results_xy(reg, pi_pulse): assert results_._size == 2 assert results_._basis_name == "XY" assert results_._meas_basis == "XY" + # Checks the initial state assert results_.states[0] == qutip.tensor( - [qutip.basis(2, 1), qutip.basis(2, 1)] + [qutip.basis(2, 0), qutip.basis(2, 0)] ) with pytest.raises(TypeError, match="Can't reduce a system in"): @@ -382,5 +383,5 @@ def test_results_xy(reg, pi_pulse): ) # Check that measurement projectors are correct - assert results_._meas_projector(0) == qutip.basis(2, 1).proj() - assert results_._meas_projector(1) == qutip.basis(2, 0).proj() + assert results_._meas_projector(0) == qutip.basis(2, 0).proj() + assert results_._meas_projector(1) == qutip.basis(2, 1).proj() diff --git a/tests/test_simulation.py b/tests/test_simulation.py index 28cb3a97..54d0029a 100644 --- a/tests/test_simulation.py +++ b/tests/test_simulation.py @@ -914,7 +914,12 @@ def test_get_xy_hamiltonian(): < 1e-10 ) assert simple_ham[0, 1] == 0.5 * amp - assert simple_ham[3, 3] == -2 * detun + # |udd> 1 atom in |u> + assert simple_ham[3, 3] == -detun + # |udd> 3 atom in |u> + assert simple_ham[0, 0] == -3 * detun + # |ddd> no atom in |u> + assert simple_ham[7, 7] == 0 def test_run_xy(): diff --git a/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb b/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb index 7dc05244..a34ce30e 100644 --- a/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb +++ b/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb @@ -16,16 +16,18 @@ }, { "cell_type": "markdown", + "id": "467b6371", "metadata": {}, "source": [ "When performing quantum computations with global pulses, it might be hard to prepare the system in an arbitrary initial state. This is especially true in the XY mode, where only a global $\\sigma^x$ pulse can produce excitations whose number is otherwise conserved during free evolution. A partial solution to this problem is to utilize an SLM mask.
\n", - "Assume a system of three qubits in XY mode is initially in state $\\left| \\downarrow \\downarrow \\downarrow \\right\\rangle$, and that we are interested in preparing the state $\\left| \\uparrow \\downarrow \\downarrow \\right\\rangle$. Acting naively with a global $\\sigma^x$ pulse of area $\\pi$ would result in state $\\left| \\uparrow \\uparrow \\uparrow \\right\\rangle$. Using an SLM pattern, however, it is possible to detune the last two qubits away from resonance, and the same global $\\sigma^x$ pulse will produced instead the desired state $\\left| \\uparrow \\downarrow \\downarrow \\right\\rangle$.
\n", + "Assume a system of three qubits in XY mode is initially in state $\\left| 000 \\right\\rangle$, and that we are interested in preparing the state $\\left| 100 \\right\\rangle$. Acting naively with a global $\\sigma^x$ pulse of area $\\pi$ would result in state $\\left| 111\\right\\rangle$. Using an SLM pattern, however, it is possible to detune the last two qubits away from resonance, and the same global $\\sigma^x$ pulse will produced instead the desired state $\\left| 100\\right\\rangle$.
\n", "Let's see how it works in practice. First create the register:" ] }, { "cell_type": "code", "execution_count": null, + "id": "e5f9a381", "metadata": {}, "outputs": [], "source": [ @@ -43,6 +45,7 @@ }, { "cell_type": "markdown", + "id": "a0adcb3d", "metadata": {}, "source": [ "Now create the sequence and add a global $\\sigma^x$ pulse of area $\\pi$ in XY mode:" @@ -51,6 +54,7 @@ { "cell_type": "code", "execution_count": null, + "id": "7c2aecfb", "metadata": {}, "outputs": [], "source": [ @@ -65,6 +69,7 @@ }, { "cell_type": "markdown", + "id": "d1511bca", "metadata": {}, "source": [ "Drawing the sequence will show the following:" @@ -73,6 +78,7 @@ { "cell_type": "code", "execution_count": null, + "id": "4dce4509", "metadata": {}, "outputs": [], "source": [ @@ -81,6 +87,7 @@ }, { "cell_type": "markdown", + "id": "fa5c5fbb", "metadata": {}, "source": [ "To set up the SLM mask all we need to do is to create a list that contains the name of the qubits that we want to mask, and pass it to the $\\verb:Sequence.config_slm_mask:$ method:" @@ -89,6 +96,7 @@ { "cell_type": "code", "execution_count": null, + "id": "462c1a9c", "metadata": {}, "outputs": [], "source": [ @@ -99,6 +107,7 @@ }, { "cell_type": "markdown", + "id": "1aa757b8", "metadata": {}, "source": [ "At this point it is possible to visualize the mask by drawing the sequence. The masked pulse will appear with a shaded background, and the names of the masked qubits will be shown in the bottom left corner." @@ -107,6 +116,7 @@ { "cell_type": "code", "execution_count": null, + "id": "abd0dc82", "metadata": {}, "outputs": [], "source": [ @@ -115,6 +125,7 @@ }, { "cell_type": "markdown", + "id": "2e27a12b", "metadata": {}, "source": [ "The sequence drawing method also allows to visualize the register. If an SLM mask is defined, the masked qubits will appear with a shaded square halo around them:" @@ -123,6 +134,7 @@ { "cell_type": "code", "execution_count": null, + "id": "0fffe4c2", "metadata": {}, "outputs": [], "source": [ @@ -131,20 +143,22 @@ }, { "cell_type": "markdown", + "id": "21c01972", "metadata": {}, "source": [ - "Now let's see how the system evolves under this masked pulse. Since the pulse only acts on the first qubit, we expect the final state to be $\\left| \\uparrow \\downarrow \\downarrow \\right\\rangle$, or, according to Pulser's conventions for XY basis states, $(1,0)^T \\otimes (0,1)^T \\otimes (0,1)^T$ in the Hilbert space $C^8$:" + "Now let's see how the system evolves under this masked pulse. Since the pulse only acts on the first qubit, we expect the final state to be $\\left| 100 \\right\\rangle$, or, according to [Pulser's conventions for XY basis states](../conventions.rst#qubit-states), $(0,1)^T \\otimes (1,0)^T \\otimes (1,0)^T$ in the Hilbert space $C^8$:" ] }, { "cell_type": "code", "execution_count": null, + "id": "a9dead3e", "metadata": {}, "outputs": [], "source": [ "import qutip\n", "\n", - "qutip.tensor(qutip.basis(2, 0), qutip.basis(2, 1), qutip.basis(2, 1))" + "qutip.tensor(qutip.basis(2, 1), qutip.basis(2, 0), qutip.basis(2, 0))" ] }, { diff --git a/tutorials/quantum_simulation/Microwave-engineering of programmable XXZ Hamiltonians in arrays of Rydberg atoms.ipynb b/tutorials/quantum_simulation/Microwave-engineering of programmable XXZ Hamiltonians in arrays of Rydberg atoms.ipynb index fb35faf5..321afba7 100644 --- a/tutorials/quantum_simulation/Microwave-engineering of programmable XXZ Hamiltonians in arrays of Rydberg atoms.ipynb +++ b/tutorials/quantum_simulation/Microwave-engineering of programmable XXZ Hamiltonians in arrays of Rydberg atoms.ipynb @@ -140,9 +140,9 @@ "outputs": [ { "data": { - "image/png": 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", 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" + "
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", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -225,7 +223,7 @@ "source": [ "### Domain-wall dynamics\n", "\n", - "Now, we will look at the dynamics of the system under $H_{XX2Z}$ when starting in a Domain-Wall (DW) state $|\\psi_0\\rangle = |\\uparrow \\uparrow \\uparrow \\uparrow \\uparrow \\downarrow \\downarrow \\downarrow \\downarrow \\downarrow\\rangle$, for two distinct geometries : open boundary conditions (OBC) and periodic boundary conditions (PBC). In the case of $H_{XX2Z}$, only 2 pulses per Floquet cycle are required, as the $X$ and $-X$ pulses cancel out." + "Now, we will look at the dynamics of the system under $H_{XX2Z}$ when starting in a Domain-Wall (DW) state $|\\psi_0\\rangle = |\\uparrow \\uparrow \\uparrow \\uparrow \\uparrow \\downarrow \\downarrow \\downarrow \\downarrow \\downarrow\\rangle \\equiv |0000011111\\rangle$, for two distinct geometries : open boundary conditions (OBC) and periodic boundary conditions (PBC). In the case of $H_{XX2Z}$, only 2 pulses per Floquet cycle are required, as the $X$ and $-X$ pulses cancel out." ] }, { @@ -306,13 +304,13 @@ " for key, value in samples.items():\n", " for j in range(N_at):\n", " correl -= (\n", - " (2 * float(key[j]) - 1)\n", - " * (2 * float(key[(j + 1) % N_at]) - 1)\n", + " (1 - 2 * float(key[j]))\n", + " * (1 - 2 * float(key[(j + 1) % N_at]))\n", " * value\n", " / N_samples\n", " )\n", " magnetizations_obc[j][m] += (\n", - " (2 * float(key[j]) - 1) * value / N_samples\n", + " (1 - 2 * float(key[j])) * value / N_samples\n", " )\n", " correl_obc[m] = N_at / 2 + correl / 2" ] @@ -358,13 +356,13 @@ " for key, value in samples.items():\n", " for j in range(N_at):\n", " correl -= (\n", - " (2 * float(key[j]) - 1)\n", - " * (2 * float(key[(j + 1) % N_at]) - 1)\n", + " (1 - 2 * float(key[j]))\n", + " * (1 - 2 * float(key[(j + 1) % N_at]))\n", " * value\n", " / N_samples\n", " )\n", " magnetizations_pbc[j][m] += (\n", - " (2 * float(key[j]) - 1) * value / N_samples\n", + " (1 - 2 * float(key[j])) * value / N_samples\n", " )\n", " correl_pbc[m] = N_at / 2 + correl / 2" ] @@ -383,26 +381,22 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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", 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", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -422,7 +416,9 @@ "ax.set_xlabel(\"Cycle\", fontsize=16)\n", "ax.set_ylabel(\"Atom number\", fontsize=16)\n", "cbar = fig.colorbar(img, shrink=0.7)\n", - "cbar.set_label(r\"$\\langle \\sigma^z \\rangle$\", fontsize=16)" + "cbar.set_label(r\"$\\langle \\sigma^z \\rangle$\", fontsize=16)\n", + "\n", + "plt.show()" ] }, { @@ -439,24 +435,12 @@ "outputs": [ { "data": { + "image/png": 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", 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" ] }, - "execution_count": 15, "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, "output_type": "display_data" } ], @@ -469,7 +453,9 @@ "ax.set_xlabel(\"Cycle\", fontsize=16)\n", "ax.set_ylabel(r\"$\\langle N_{flip} \\rangle$\", fontsize=14)\n", "ax.plot(correl_pbc, \"--o\", color=\"blue\")\n", - "ax.plot(correl_obc, \"--o\", color=\"red\")" + "ax.plot(correl_obc, \"--o\", color=\"red\")\n", + "\n", + "plt.show()" ] }, { @@ -506,7 +492,7 @@ " for key, value in samples.items():\n", " for j in range(N_at):\n", " magnetizations_pbc[j][m] += (\n", - " (2 * float(key[j]) - 1) * value / N_samples\n", + " (1 - 2 * float(key[j])) * value / N_samples\n", " )" ] }, @@ -517,14 +503,12 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -534,7 +518,8 @@ "ax.set_xlabel(\"Cycle\", fontsize=16)\n", "ax.set_ylabel(\"Atom number\", fontsize=16)\n", "cbar = fig.colorbar(img)\n", - "cbar.set_label(r\"$\\langle \\sigma^z \\rangle$\", fontsize=16)" + "cbar.set_label(r\"$\\langle \\sigma^z \\rangle$\", fontsize=16)\n", + "plt.show()" ] }, { @@ -551,158 +536,132 @@ "outputs": [ { "data": { - "image/png": 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", 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kbTm6zKL858DlbCww3w68FrgSeFdEZGb+xYQ2fgb4FeDKiLi8Xfdm4Jci4kAgga8DrwbIzC9HxNnA1TQzML/GGZQlSZIkSaNEZpYFRtwKHJOZ50TEVsBtwNsz810R8RbgFzPz8auYa5F169bl+vXrp53G/IkYv63wGpEkSZKk1RYRl2bmulHbunwHdwfgO+3jJwA7AR9pn18I/OjmJihJkiRJ0kp1KXBvBR7TPn4O8K+ZuXQLn+1pPkIsSZIkSdJUdPkO7rnAOyPiccCRwP8a2PaTwA0V85IkSZIkqZMuBe7xwEOA59IUu28f2PYC4JMV85IkSZIkqZPiAjcz/x349THbfrpaRpIkSZIkbYYu98G9ISJGzpIcEY+LCD+iLEmSJEmami6TTO0NbDtm20OAR684G0mSJEmSNlOXAhdg3A1R1wF3riwVSZIkSZI237LfwY2I3wJ+q32awD9ExH8OhW0H7AycWT89SZIkSZLKTJpk6gbg0+3jI4D1wIahmLuBq4G/qpuaJEmSJEnlli1wM/Mc4ByAiAD4vcz8Wg95SZIkSZLUSZfbBB21molIkiRJkrQSxQUuQET8KPAyYC+amZMHZWYeXSsxSZIkSZK6KC5wI+KFwNk0My/fRvPd20HjZliWJEmSJGnVdXkH9/eBC4FXZObwRFOSJEmSJE1VlwL3R4E3WtxKkiRJkmbRVh1ivwLsslqJSJIkSZK0El0K3DcBb24nmpIkSZIkaaZ0+YjyW2newb0mIq4Dbh/anpn5c7USkyRJkiSpiy4F7r3AV1crEUmSJEmSVqK4wM3MQ1YxD0mSJEmSVqTLd3AlSZIkSZpZxe/gRsTTJsVk5j+tLB1JkiRJkjZPl+/gXgjkhJitl9sYEXsCHwTWtm2dmpnviYidgbOAvYGvAy/LzDsiIoD3AM8HfgAcmZmXdchZkiRJkrSF6FLgPn3Eul2AXwB+DnhtQRv3AG/MzMsi4mHApRHxSeBI4NOZeWJEHA8cDxwHHArs2y5PAU5p/5UkSZIkaRNdJpn63JhNfxsR7wL+C3D+hDa+CXyzffxvEXENsDtwGHBIG3YGzbvFx7XrP5iZCVwUETtGxG5tO5IkSZIk3a/WJFMfB17W5QURsTfwBOBiYO1A0fotmo8wQ1P83jTwspvbdcNtHRMR6yNi/YYNGzqmLkmSJElaBLUK3McC95UGR8T2wEeBYzPze4Pb2ndrJ33XdxOZeWpmrsvMdWvWrOnyUkmSJEnSgugyi/KrRqx+MPA44GjgbwvbeRBNcfuhzFx6za1LHz2OiN2A29r1twB7Drx8j3adJEmSJEmb6DLJ1AfGrL+bZgbk109qoJ0V+TTgmsz804FN5wJHACe2/54zsP61EXEmzeRS3/X7t5IkSZKkUboUuPuMWHdXZt7aoY2fAX4FuDIiLm/XvZmmsD07Io4GbmTj93nPo7lF0PU0twk6qsO+JEmSJElbkC6zKN+40p1l5ueBGLP5mSPiE3jNSvcrSZIkSVp8Xd7BBSAilu57uzNwO3BhZn68dmKSJEmSJHXRZZKphwEfA54K3AN8B9gFeENE/DPwC5n5/VXJUpIkSZKkCbrcJugdwBNpvkO7XWbuBmwHvKpd/4766UmSJEmSVKZLgfti4Hcy80OZeS9AZt6bmR8C/me7XZIkSZKkqehS4O4CXD1m29XtdkmSJEmSpqJLgfs14BfGbHt+u12SJEmSpKnoMovy/wL+JCK2Bz4EfBPYFTgc+DXgDfXTkyRJkiSpTJf74L4rItbQFLJHtqsD+E/gxMx8T/30JEmSJEkq0+k+uJn55oj4I+BgNt4H96LMvGM1kpMkSZIkqVSX++AeB+yRma8Dzh/a9l7gpsz8o8r5SZIkSZJUpMskU0cBV4zZ9qV2uyRJkiRJU9GlwN0LuG7Mtn8FHr3ydCRJkiRJ2jxdCtwfALuP2bYHcPfK05EkSZIkafN0KXD/GfgfEbHt4Mr2+Rvb7ZIkSZIkTUWXWZTfCnwBuDYi/hq4heYd3VcCu7Dx1kGSJEmSJPWuy31wvxQRTwf+GDiO5t3f+4DPAy/OzC+tToqSJEmSJE3W9T64XwSeFhHbATsBd2Tmf6xKZpIkSZIkddCpwF3SFrUWtpIkSZKkmdFlkilJkiRJkmaWBa4kSZIkaSFY4EqSJEmSFoIFriRJkiRpIVjgSpIkSZIWggWuJEmSJGkh9FrgRsT7I+K2iLhqYN1bI+KWiLi8XZ4/sO2EiLg+Ir4aEc/tM1dJkiRJ0nzp+x3cDwDPG7H+XZl5YLucBxARPw4cDvxE+5qTI2Lr3jKVJEmSJM2VXgvczPwn4PbC8MOAMzPz7sz8GnA9cNCqJSdJkiRJmmuz8h3c10bEFe1HmHdq1+0O3DQQc3O77gEi4piIWB8R6zds2LDauUqSJEmSZtAsFLinAD8GHAh8E/iTrg1k5qmZuS4z161Zs6ZyepIkSZKkeTD1Ajczb83MezPzPuAv2fgx5FuAPQdC92jXSZIkSZL0AFMvcCNit4GnLwKWZlg+Fzg8IraNiH2AfYEv9p2fJEmSJGk+bNPnziLib4BDgEdExM3AW4BDIuJAIIGvA68GyMwvR8TZwNXAPcBrMvPePvOVJEmSJM2PyMxp51DVunXrcv369dNOY/5EjN+2YNeIJEmSpPkVEZdm5rpR26b+EWVJkiRJkmqwwJUkSZIkLQQLXEmSJEnSQrDAlSRJkiQtBAtcSZIkSdJCsMCVJEmSJC0EC1xJkiRJ0kKwwJUkSZIkLQQLXEmSJEnSQrDAlSRJkiQtBAtcSZIkSdJCsMCVJEmSJC0EC1xJkiRJ0kKwwJUkSZIkLQQLXEmSJEnSQrDAlSRJkiQtBAtcSZIkSdJCsMCVJEmSJC0EC1xJkiRJ0kKwwJUkSZIkLQQLXEmSJEnSQrDAlSRJkiQtBAtcSZIkSdJC6LXAjYj3R8RtEXHVwLqdI+KTEXFd++9O7fqIiPdGxPURcUVEPLHPXCVJkiRJ86Xvd3A/ADxvaN3xwKczc1/g0+1zgEOBfdvlGOCUnnKUJEmSJM2hXgvczPwn4Pah1YcBZ7SPzwBeOLD+g9m4CNgxInbrJVFJkiRJ0tyZhe/grs3Mb7aPvwWsbR/vDtw0EHdzu+4BIuKYiFgfEes3bNiweplKkiRJkmbWLBS498vMBHIzXndqZq7LzHVr1qxZhcwkSZIkSbNuFgrcW5c+etz+e1u7/hZgz4G4Pdp1kiRJkiQ9wCwUuOcCR7SPjwDOGVj/qnY25YOB7w58lFmSJEmSpE1s0+fOIuJvgEOAR0TEzcBbgBOBsyPiaOBG4GVt+HnA84HrgR8AR/WZqyRJkiRpvvRa4GbmL43Z9MwRsQm8ZnUzkiRJkiQtiln4iLIkSZIkSStmgStJkiRJWggWuJIkSZKkhWCBK0mSJElaCBa4kiRJkqSFYIErSZIkSVoIFriSJEmSpIVggStJkiRJWggWuJIkSZKkhWCBK0mSJElaCBa4kiRJkqSFYIErSZIkSVoIFriSJEmSpIVggStJkiRJWggWuJIkSZKkhWCBK0mSJElaCBa4kiRJkqSFsM20E5AkaSFFjN+W2V8ekiRtQXwHV5IkSZK0ECxwJUmSJEkLwQJXkiRJkrQQLHAlSZIkSQvBAleSJEmStBAscCVJkiRJC2FmbhMUEV8H/g24F7gnM9dFxM7AWcDewNeBl2XmHdPKUZIkSZI0u2btHdynZ+aBmbmufX488OnM3Bf4dPtcmn8Ryy+SJEmSOpu1AnfYYcAZ7eMzgBdOLxVJkiRJ0iybpQI3gQsi4tKIOKZdtzYzv9k+/hawdtQLI+KYiFgfEes3bNjQR66SJEmSpBkzM9/BBX42M2+JiEcCn4yIrwxuzMyMiBz1wsw8FTgVYN26dSNjJEmSJEmLbWbewc3MW9p/bwP+DjgIuDUidgNo/71tehlKkiRJkmbZTBS4EfHQiHjY0mPgOcBVwLnAEW3YEcA508lQkiRJkjTrZuUjymuBv4tm9thtgA9n5ici4hLg7Ig4GrgReNkUc5QkSUBMmO09028LSZKmYyYK3My8AXj8iPXfAZ7Zf0aSJEmSpHkzEx9RliRJkiRppSxwJUmSJEkLwQJXkiRJkrQQZuI7uNqyODmJJEmSpNXgO7iSJEmSpIVggStJkiRJWggWuJIkSZKkhWCBK0mSJElaCBa4kiRJkqSF4CzKmmvLzcjsbMySJEnSlsUCV5JmmIM4kiRJ5SxwJUmdWHQvNs+vSnmtSJpFfgdXkiRJkrQQfAdX0lxb7h0E8F0ESerK36uS5pkFrrQF8GNkkiRJ2hL4EWVJkiRJ0kKwwJUkSZIkLQQLXEmSJEnSQrDAlSRJkiQtBCeZkiRpC+GEc5KkRWeBq4Xn7Q6k2eTPZpnSfrJ4lSTJAleSpKmxKJWkxefv+n5Z4EodLPIvqFl8N20Wc5KkeebvVZUq+Ztnkf8u0vyai0mmIuJ5EfHViLg+Io6fdj6StKgiYuwy7xb52CRJUmPm38GNiK2BvwCeDdwMXBIR52bm1dPNbPM52rXYPL+O+vqdSal/JT938/yzOYs5qR7Pbxn7SSVmvsAFDgKuz8wbACLiTOAwYG4L3BI1f4D7/GXgR5/65y/7fnmN929LHzBZdIt87op+X0z6BMEC90HJz+9SXM3fvX1fc4t8jZfw/80y8zwAN2vmocDdHbhp4PnNwFMGAyLiGOCY9un3I+KrPeVWwyOAby89WeaivT+uJGaF+9u0nZ73V5RTwf5K+2kF+1u9czeDOc1iP/V5PZXG1Mqp798FJTGz+PupVk5992XJ79W+fw7m9ffFCttalX6qmVPJ/wfz2k+z+Lt+0X+vriCmc049/L7YrP3NQMwmcbP4czAnHj12S2bO9AK8BPirgee/Avz5tPOqeHzra8X1GWNO5mRO5mROi5+3OZmTOZmTOS1+3l3i5mGZh0mmbgH2HHi+R7tOkiRJkqT7zUOBewmwb0TsExEPBg4Hzp1yTpIkSZKkGTPz38HNzHsi4rXAPwJbA+/PzC9POa2aTq0Y12dM3/szJ3PqO6bv/ZnTYuc0r3n3vT9zMqe+Y/renzktdk7zmneXuJkX7WeuJUmSJEmaa/PwEWVJkiRJkiaywJUkSZIkLQQLXEmSJEnSQrDAlSRJkiQthJmfRXlLERH7Z+ZXVhozHBcROwDPA3ZvN98C/GNm3lnQzlGZeXqXnGrtb7XzLo1brZiIeC7wQjY9vnMy8xMFefd5fofz7nV/hTlN7MtZyHtz2lrhdbIq565yTtXaqpV34fW02XlLkqTV5SzKMyIivpGZe600ZjAuIl4FvAW4gOYPMIA9gGcDb8vMD9bMqdb++si7NG41YiLi3cB+wAeBm9uQPYBXAddl5utL2prX81s5p3czoS9nJe+ubdW6TtrHtX42a+ZUra1aeRdeTyvKu93P1AbXarW12gNLq5jT3Ax0zPpg7UqPf8oDflXampWcSqzW74u++7LPfqp5jdf6nTIr/TTrLHB7FBHvHbcJOCIzH14S06GtrwJPGf5jIiJ2Ai7OzP0i4opl2tkvM7ftkFOt/VVpp31Nyf56i2lzujYz93tAUEQA12bmvj2f39K8e9tf5b7su59q9UHJsfV97mrmVKWtWnl3yKmoreWsxmDPSmK6tlU4ELCiQZVVymliTNtmtbaWyfvUzDxmpcdfGlc7ptJAz7QG/Kq0NWM5Vbmeul5zffdln/1U8xqv9Ttllvpp1vkR5X4dBbwRuHvEtl/qEFMaF8CoEYz72m0Aa4HnAncMxQTwhY451dpfrXZK4/qMAbgrIp6cmZcMxT0ZuKt93Of5Lc27z/3V7Mu++6lWWyXH1ve5q5lTrbZq5V0aV9TWhMJ7bd8xldt6/pgi/yzgWuD1wG8DTxo3qELzh1ffOZXEVGsrInZeJu/ndzi2Wbyeivqyz/2V9mXFtvrOqcr1VPOaK8y72vVUuL9aP3fVrvHCtnr9HVbST/PMArdflwBXZeYXhjdExFs7xJTGvR24LCIuAG5q1+1FM4L+++3zjwHbZ+blI9q5sGNOtfZXq53SuD5jAI4ETomIh7FxZG1P4LvtNuj3/Jbm3ef+avZl3/1Uq62SY+v73NXMqVZbtfIujSttaxYH1/ocMCgZVOk7p74HOjYAN7Lp8Wb7/JEdjq00rs+Y0r6cxQG/Wm31nVOt66nmNddnX5bG1eqnmtd4rd8pfffT/MpMl54WYGfgR1Ya0zFuJ+BwmncD39g+3ql23jX3V7OdWV6AXYEntcuu0zq/i3BeluvLWc67xrFN49zVyql2W7X2VRJXcM2dBvzsmNd+uO+Yyvt7Is27sFfTfAT5AuAa4CKad20BjgD+FTgFeHO7vK9dd+SUcpoYU7Mt4DpgrzF53zSlc9dbf0/h/Jb2ZZW2ppBTleup8jXXW19OoZ9qXuO1fqf02k/zvPgd3AWw9DGDzLx9zPa1DHzJPDNvLWx3+8z8/mbk0+v+NredkriuMRERwEFs+qX+L2bhD1qMmCl70vndXJt7/Kt5fle7LzdHretkOG4lx1dybJtz7mrl1Me567Mvh+NihZMnLYqI2JVNr6dvDW3fieadjeF+Gn6no7ecSmNqtBURrwE+n5lfGvG612XmnxUe1swq7ctZ3F+ttvrKaZavp777ss9+6vua6+t32CxfTzVY4M6IiDg/Mw8tjYmIvYA/BJ4J3EnzkYKHA58Bjs/Mr0fEgTQj5jvQfJQuaL5kfifwm5l52YT9lUxIMJhTH/u7MjN/cqXtdNhfl0kwngOcTDMqNjipymNojv+C0pxKzu+Edqr0U2w6CcaBrP75rd6XE2Kq91NJ3EqPbzXOXa2cejx3vfXl0P5qTJ5UfXBtJTHDcX0MGJToeUBo5gY65nWwtkNfVt9fzcG1vnOahetpOGYWzsvw9VSrnyrnNLGtkrxrxXSJW1R+B7dHEfHEcZuAA0tjWmcB7wZekZn3tq/dGngpcCZwMPAB4NWZefFQHgcDpwOPj4g3LLO/7TvmVGt/v7hMzK5tzMR2SuNqxQDvAZ41XHxGxD7AecAB7fPlZkjesX088fzW6qfSvqTe+e21L/vup1rHV3hs1c5drZxK2mmf1zq+WnmX/mwWTZ40wdU034GelZj745YbMIiIkgGKCybtr2Rgqe+cCmPujxsz0PF04B0RUXLrrWdn5icn7KvTuasV01N/V99fhXZqttWpnRm6nu6PmaHzcv/1VKufKuc0sa2SvGvF1OynCX0w0yxw+3UJ8DnY5AvdS3bsEAPwiMw8a3BjWwidGRFLk8Y8dPgP2jbuooh4aPv0HcAfAfeM2N9WHXOqtb+zgA8xeoKSh3RopzSuVsw2bJx0ZtAtwIMGnh/F5BmSS85vrX4q7cta57fvvuy7n2odX8mx1Tx3tXKqee767MvSuKLJk/ocXJvRwZeJA0tTyGmWBjpOo/njfy4Hazv0ZZ/7qznI3GtO9Hg9dRgY7a0PSq8nKvVT5ZxKznFJ3rVi6BA3zlI/zS0L3H5dQ/MuynXDGyLipg4xAJdGxMnAGWycFXVPmok9/qV9fn5EfJzmQh6MeRXwifb5ZcDfZ+alI/b3ax1zqrW/K4A/zsyrRsQ8q0M7pXG1Yt4PXBIRZ7Lp8R9O88tiySVMniG55PzW6qfSvqx1fvvuy777qdbxlRxbzXNXK6ea567PviyNK5mRGvodXJvFwZeSgaW+c+p1oCMizh2xfem1u7SP53WwtrQv+9xfzcG1vnPq83oqveb67IPS66lWP9XMqaStkoHRWjFFcYX9NLcscPv1Vjb95THodR1ioPnD9GjgbWz8fP3NwD/Q/lGXmf8tIg4FDmPTz+D/RWae1z4/CvjOmP2t65JTxf0dC3xvTMyLOrRTGlcaM26Sp3UAmfnOiPh7muP/qXbbLTQfM756IP4lbDqd+/0yc5/24cTzS71+KurLiue37748lh77iXrHV3Js1c5drZwqn7s++7IoLjPPaP8wGJw86ULghNx08qQ+B9dmcfClZGCp75z6Huh4KvBKYPh7j0HzfT2Y38Ha0r7sc381B9f6zqnP66n0muuzD0qvp1r9VDOnkrZK8q4VUxpX0k9zy0mmJEkaEiucvTwiHgt8JzO/PWLb2sy8tc+YgZxuz8wNE+IO4IGDIecuDRi0fXNXZv5gmeN/KnBjZn5jxLZ1mbl+IKeS3GvkNDGmY9xOLDNLdEScD/xhZn52xGv/KTOf1vHc1bpWerkGBvLuc3/LtlOzrQ7t/DjwguVyauN6uZ5Kz0nlPqjSThu74n5ahZxKrrtl864ZU7Of5lbOwL2KXBLgqBoxbdzvFsScWimmNKfi/dF8suDVNB+dvKJdzgf+K/CgGvvajJx2AE4EvkLzjtJ3aD66fSKwY0E75xfmNDGu8Pz2dg1sAX3ZqZ/6OL7CmFE5XTPlnDqdu777kmaE+0xgA82EIdcDt7Xr9i5o68qS43OZn4XmnuQ7TzsPl/lfvJbspyn05Vqae+I+EVg77Xz6XHwHd0bE6tyKZOdxIcCXMnOPkpjSnGrtLyL+hub2JWew8XsNe9B8/3TnzHx5ad4Vc/pHmlv0nJHtfcSiub/YEcAzM/M5sfxs0x/LzN3a1xXFjdPlWql5DSxyX1bupyrHVxiz0pyOBJ5ROadq567Pvmzb/r80s5d/JB84e/mxmTlp9vL3ZeaaMds3BkacmpnH9B0TzW0jTgBeCDyS5jtatwHnACfmhNtHRIfb2UXENjRfs3gR8Kh28y3tvk7LzB8u185w7jVyKo2JHm7TVqLk+EvjlmL6vAbax73ubyUxq7G/gWvpGcB36XgttW1VvZ5Wek7atlarnzbrZ65tq1Y/9X09ldyusFNMdLitY0SsZdN75d7KAvA7uD2KiCvGbaIZZSmKaePGfacwgO3axxuAG9t1S7J9/sjSmNKcau2PZua3/Yb2dTNwUURc26GdmjntnZknDSbU/sF9UkT8aruqdLbpiXEl57fPa6ByWzPXl4V5l/ZTreMriVlpTidGxFGVc6p27pbJezX6EurNXj5pQOj5fce0zqb5g/GQEQMGZwOTBgwObF8zMQb43zR/TL2VBw5U/jXw8tLca+VUmDdUuk3bcpb+GC09dxWvgz6vgV73V5pTz/ubeC216/q8niaek9Ljm+N+6vt6mph3rZjWB5h8W8cnAKfQFMH3394oIu5kqAieRxa4/VpL83n4O4bWB/CFDjHQ/OHw5FEjLbFxZuMbaN7lGPUdqC4xpTnV2t/tEfFS4KOZeV+7bSuaX3R3dGinZk43RsSbaN5JWvrO0Fqad8C6zoBdEncnk89vSUyt46/Z1iz2Zc1+qnV8JTGzmFPNc9dn3lBv9nKoN2gyr4MvJQOVpbn3PfhSZaCj8I/ReR1gLO3LPvdXc3CtVkzJtQT9Xk8l5wQWu5/6vp5KBkZrxUDZrQFPZ0IRPGIf8yNn4HPSW8pCM5vaz47Z9uHSmPbxHwAHjYk7qf33NcDjx8S8rkNMaU619rc3zQ/xBuDadrmtXbdPaTuVc9oJOImN3wW8neaP5pNovytCMwPrY8e088KBxxPjCs9vb9fAFtCXNfupyvEVxsxiTjXP3WDed7TLquTdPn4w8Bs03/+/sl3OB34T2LaNeSqw15i21g08vm6ZuJv6jmkfXwC8iYHvYtEMYB4HfKp9fhWw74T9lcRcRDMoudXAtq1o3rm9uGM/1cppYkz7+EzgZOApNB+vflT7+GTg7DbmUuBxE/b3Q5p3Uk4fsfxbx3NX61rp7RqYwjVXmlNv+yu5lvq+nkrOyRbQT31fTyV5V4lpH78X+DjN79ufbpeXt+v+fOlaGdVOu+36cdvmZZl6Ai4uyy009+LaZdp5uLi4uHRZqDcgNK+DL3szYaCyw/H1PfhSZaCj8A/WuRxg7NCX8zq4Vitm4rXU9/VUck62gH7q+3oqybtKzMDzQ2m+h/sP7fI+4PkD2ycWwfO8OMnUjIiI7TNz+F5UnWPauP0z8ysTYp6dmZ+sEFOaU639VYkZjouI/Rk9xfs1Be0clZmnrzSmQ1sl57e3a6BmWzPalzX7qcrxDcas5NpdrZxWEjMcFxHPpZkMZfD4zsnMTwzEV4mZkNPvZubvrTRmSxQRuwBk5rh7Ni+kKLxVklTC66mM/VQuIg5l9N8P500vq0qmXWG7NAvwjRoxNdvaUnKi+VjO5cDxNDe9fmX7+HKa2fu22H6a17y3lJxWeu3Oej/RTDpyHnA48LPtcni77j01Y3o+vmfXjgH2b6+H97bLccABJfm0r69yq7rCmInH1qEPesu7jatym7Zax1/zOphCX/Z5zXXOiWbukVOAc9vlFOB5Q/ETY1Z6nfR5Pc3oueu7nzrnvdrXwVIMK7yNZttG0e0f533xHdweRcQbxm0Cfjszdy6Jadt67zJxR2TmwyPi3GVinpGZDy2MKc2p1v6qxHTI6VrgJ3LothUR8WDgy5m5byw/k/R+mbltSUzbbklbJee3t2ugzbvWuZvFvqzZT1WOrzBm4rU7hZxqnrtr84ETFRERAVzb/mxWiWmfLzvjdmZuUxIzZvvgfqvcFi423ubqOOCXaL7HNjhj8eHAmZl5Yt85rTRmC8ip5BMBXW8NuKLrYI77cjVus/huYD/gg2zal6+i+e7i60tiauY0IabK9bQI525CTPV+6uM6GLguJ95Gs41fbjbtkluAFt2ibJY5i3K/3gH8EXDPiG1bdYgBOAp4I3D3iLhfav99Ks07OsMfIQ7goA4xpTnV2l+tmNK4+2gmNLhxKGa3dhvUnQG7JK7k/PZ5DdRsaxb7smY/1Tq+kpiSa7fvnGqeu7si4smZeclQzJOBuyrHQL3ZyycNCO1SM4bmfrOjBjr+FPgycGL7fLlBheJb1RXGlORd2ge95d3GLTuIURozwa8Bv1eznyi4DqbQl31ec9Vyovmu4qhBsbNovk/++pKY0uukz+tpRs9d3/1U7Xqi0nVQeGzVZqefUAQ/f8y2uWGB26/LgL/PzEuHN0TEr3WIgWZa8qsy8wsj4t7aPrwI+EFmfm5EzFc7xJTmVGt/tWJK444FPh0R17Hx1iB7AY8BXts+/xiwfWZePqKdCzvElMaVnN8+r4Gabc1iX9bsp1rHVxJzLJOv3b5zqnnujgROiYiHsXG0ek/gu+22mjHQjMA/Ghh1o/sPd4iBfgfzZnGgo+bAWd+DL3dSYaCj8A/WeR2srTmQNYs51Ro4u5OCAbGSuIrX0yyeuzvpt59qXk+1roOSmJLbaELZLQRLb1E2n3IGPie9pSzAY2nu9TVq29qBmDXLxbSPdwZ+pMe8J+Y0zwvNO9EHAy9ul4OBraeYz8Tz2+c1MM/LovfTrF27q3SMuwJPapddVzOmYs7nA08fs+2fKsc8D7i+jT21XT7RrnveQHyVW9UVxkzMu8Px9ZZ3+7jWbdq+Me7/SDbO5lqznyZeB1Poyz6vuZo5PRG4GLia5rY6F9DMNHwRzbtopTETr5O+r6cZPXd991PN66nKdVAYszf1ZqcvukXZvC5+B1dbhIhYy8AscTlihGzM66rMbl0S0yVumkr6ctr9PS5u6SM5mXl7ST5j2t2sYxuX0zRjVmt/EbH0bsHgzIxfzKH/cErjxuyv1mziE2Nqt7Ua2lH84b68JDPvnUY+goj4A5oZSb84YttJmXncKuzT66CiiNiVTX/ff2tzYirl0vv1NI+m1U99XQcD+1vR7PQR8Rrg85n5pRHbXpeZf7bCFKfKAndGRPuF7ojYATiB5nYWj6T5uMBtwDnAiZl5Z0Fb52fmoRNirszMnyyJqZRT8f5qxkTEE2hms9uB5j96aL6Qfyfwm5l52YS2ZnGShJLzW/UaaB9P7MtZ6e/BuIjYC/hD4JltHgE8HPgMzUzDX5/QztLPwYqOrTT3Gb3mukyC8RzgZJrR4cF+egxNP13QxhfF9ZX3cjG129ocqzloVBpXc2CllikMCE11oGPag4cOrs3m4NqI18zU74vV7u8ucQPxE3NaSd6lOQ3GtH9vP29of/9Y+Hd2tds6LgK/g9ujKPtC99k0f3gfsjT6044KHdFue0677onLtHVgG/OLy8TsWhrTIacq+6uYN8DpwKsz8+JNgiIObrc9PpafJXr7Nr5KTIe2Ss5vn9cAFPRlSUzffUnz0Z13A69YehcjIram+c7KmcDBhX1QcvzVrpUpXHO19vce4FnDAwcRsQ/NbXkOKI2L5WfA3rGNrxJTu63ldBxgHDmwEhF3UjawcjXN97InKYmrElNy/B3iesu7dUFB3MSYwj98Jw4wVr4O+u7LqvtbbtAsIooG1wbjllHlGiiMKYpbup5m8fdFT/1dFDfQTxNzqpB3ae4X0PTTq4C3tM+X9vd04B0R8bbM/OCEdk4r2FdR3CIUwRa4/Sr5QvfemXnS4IvaovKkiPjVgdWXAJ8bamvJju2/ZwEfavcx7CEdYkpzqrW/WjEADx0uSNr8L4qIh7ZPa81uXTrbdElcyfnt8xqAsr7ss79L4x6RmWcN5XMvcGZE/H67qqQPSo6tNKdZvOZqxWzDxomcBt0CPGjgeUncUdSZTbwkpmpbFQeXqgwata/pc/ClaOCssJ/6HhDqY6Bj6Y/auRysncVrjgUfXJtgqZCaud8XVOrv9jW1+qnkWim6nipeB79N853dO4f2txPNd3w/GHVnXV9OabE8syxw+1Uyq9mNEfEm4Iylj5RE81GTI9k4Syo0X2B/dWZet0xbVwB/nJlXjYh5VoeY0pxq7a9WDMD5EfFxmplPl3Ldk+b+ZJ9on9ea3bp0tumSuJLz2+c1AGV92Wd/l8ZdGhEn09w3bjCnI4B/aZ+X9EHJsdU8vr77qVbM+4FLIuJMNu2nw2n+06RDXK3ZxEtiardVa3Cp1qBRaVytmNKBs5K4vgeEqgx0FP5RO6+DtbN4zS304Frh9TSLvy9q9XdRXGE/leRUej3Vug6C0b8H7mPjGxnVZl2vUATPtpyBma62lIWyWc12Ak4CvgLc3i7XtOt2Hoh/CfDYMW29sP33qYyfIW1dh5jBnO5ol1E51dpflZiB54cC7wP+oV3eR3PfsqXtpbNbrzimQ1sl57e3a6C0L/vs7w5tPRj4DZoi9Mp2+QTwm8C2Xfqg8Ph7u54on3V9YlytmPbxAcDxwJ+1y/HAj494zbJxVJpNvCRmFdq6FHjcmG03dYh5L/Bx4OXAT7fLy9t1f97GfIF2ts5x7ZTGVYyZeGwd+qC3vNvHnwF+ekzc1zrE/BtwDM1g2vDy7Y79VOU6mEJf9pnTCTSDlscBv9wux7XrThiInxhX8RqYGFP5eprF3xdV+rtyP5XkVHo91bpWjgD+leYj5m9ul/e1645sY2rOun4H8PPAzw0thwC3jnrtPC1OMiVJUmUR8VTgxhz9iZ11mbm+JKZ9fChwGJtOPHJuZp7Xbn8s8J3M/PaIdtbmxk/eTIyrGFN6bCX9VDPv2zNzw4R+2hm4KzN/MBw3EF8S8xngd3L0u/1fy8x9Svupfb7i66DPmIGclu3zWjHt4wPG9NHVQ69ZNq7iNTAxpkNbE6+n9nHJdVLSl72dlyn1048DLxiXU4eYmtfBTjT33h2eZOqO5V63OSLifOAPM/OzI7b9U2Y+rfY+ezXtCntLW4D9aUaA3tsuxwEHFL72qFpxwO92iaH5gTsFOLddTmHg/oo190fzsZBX07zLdkW7nA/8V+BBpTEF+zt1lmKG40r6fCXnpUt/z1I/de3LgeM7f7Wup805vzViaCYSOZGNn/j4Ds2nK04EdhyInxhXK2ZC3ucX9tPEuD5jarflsmUsLPg9uF36XbyeVqef2vidVxpTuy2XlS2+g9ujiDiO5rP2Z7Lxc/170Hzn7MzMPHHC66d12493A/vRfPdwMO9XAddl5utr5hQRf0Nz65UzhvZ3BM0vhZeXxLRt7jxud8CXMnOPPmM65PRuJvT5Ss9Ll/7ukPcs9mWV66lyTrVi/pHmo09n5ANnOH9mZi7NcD4xrmLME5fJ+2OZuVv7uolxfcbUzGnM9o2BEb+bmb8XEdsARwMvAh7Vbr6F5hZsp2XmDye0c2pmHrPSmJptxcZb3hUdW599EP3dhm9izEDsio6/baPquasZU9LntWIm5FR0Tmqd35rXScfraamfDgPWsoK+nJXzskr9tHT7wGcA34UH3j6wJGaorbG3IiyJmZBvldtodombdxa4PYqIa4GfGP4PKyIeDHw5M/eNiCvGvRzYLzO3bV8zMS4ivrdMzHaZuU1hzLWZud+I4wng2szct32+qvtr93FtZu5XEtM+vpfxM1fvnpkP7jOmQ04T+7wwpkp/d8h7bvpy8PgKY2rmVCvmq5n52DF537+tJK5izL2Mn9374Mzcro2fGNdnTM2cRqzfRJfBpSkMCNWKKR04660POgwIrfpAx9If4x36aaYGGDtccw6uVcppzHba1y9dT+P66UjgGaV92a7r7bxMoZ/+L83tAz+SD7x94LGZeXBJTLuuSlux/Izq78vMNSUxbdtFccv009wXwc6i3K/7aEZobxxav1u7DZoRt+fSfPl7UNB8mZ8OcXcCT84RN/iOjbPslsTcFRFPzsxLhkKeDNw18LzW/m6PiJcCH83M+9ptW9H8IrijQwyUzVzdZ0xpXEmfl8TcSZ3+Ls17Fvuy1vVUM6daMTdG2QznJXG1Ykpm9y6N6zOmalsxYXCpffykEQMrNwMXRTMgCmW3lyuJqdlWSUzJsZXG1cpp76x3G76JMRP+GD+wfVzaT32eu5rXXEmf14opOW+lcX3GFMUVXk/j+unEiDhqQszwz0Gf56Xvfiq5fWBJTM22as28XxQ3oQjedcy2+ZEz8DnpLWUBngdcT/PdvlPb5RPtuue1MacBPzvm9R8eeDwxDvgD4KAxMSd1iHkizT24rqa5h9gFNH/kXcTA7HkV97c3zQ/nBuDadrmtXbdPaUwbVzJzdW8xHdqa2OeFMVX6e877cvj4rmsfL3c9jYqpmVOtmJ0om3V9YlzFmImze5fG9RmzCm19g4GZpYfilmYXvYhmEGWrgW1b0cx6enH7/DrGz/B9U2lMzbYKYyYeW999QPM78k1sOuP3Wpq5MD41sO4qYN8JbZXE3Evz7tZnRyz/0bGf+jx3Na+5iX1eMWbiOal8fqvEVL6eqvRl3+dlCv10JnAy8BSaN54e1T4+GTi7NKZmW1Saeb9DWz8EPkBzf+Th5d9GvXaelqknsKUtNP9xHQy8uF0OBraedl6Fue8KPKlddu1pn7sAu6w0Zl6Xkj6veV4WuS9Lj2/R+8Cln4V6g3l9DwjVihk+tgcMGpXGVcypdECo1sBKyR/jpf00UwOMHa45B9fq5VRyPQ320x2MuK1jSUzNtma0n0bdPvB8Nr194MSYmm1R8baOhW0VFcvzuvgd3J5FRNDcZHlwCvAv5sCJKInpEjcmj/0z8yulMdFMJPA8Hjh1+Z1Dr5kYV9rWmJyenZmfXGlMzbZWK6dafbna/V0aN+W+3J8H3qLgnMGfgRXEnJuZ1wzte2JcrZhljv+ozDy9RlyfMYue0zKv3QUgM7+zOa+fZaXHtmh9EBEvAa7MzK+O2PbCzPz7oXULdfyqq+v1tKWyn8pEh1uUzSML3B5FxHNoPo5wHc0fqtBMJvEY4Dcz84KSmNK2JuTSZVbjVwFvofkoyuC+ng28LTM/2MZPjCttq0bey8XUbGs1cqrVl330d2ncFPty4uzltWLa/fa6v1r9NCsxi5TTLAzmTXOQqmTQqDRu0QaEhuJX0k+rMnC22v3dvn5hB7L6zmko/rk0sxoPX0+f6BJTs62+c1qJaGe5X2lMzbb6zmkRWOD2KCKuAQ7NoenAI2If4LzMPKAkpkNb7x2XCnBEZj68MOarwFOG/yiL5obUF+fGWXYnxhXGnLtMTs/IzIeWxLTtVmlrCjnV6ssq/d0h71nsy5LZy6vEtM9721/UnXW9t5hFz6ltayYG86Y1qOCA0MSYozLz9Fnspz76u0M/zfXPQY85LV1P76bSLQZrtdV3Tm3cZhfBXk+LUQRb4PYoIq4DDsjMe4bWPxi4OjMfUxLToa1/A94I3D0inT/JzEcUxlxLMxPvd4f2tQOwfugP+2XjCmPuAF4JfH8onwDOysy1JTFtu1XamkJOtfqySn93yHsW+/IrwHMz88ahPng0cEE2t7apEtM+721/EXEry8ymnpmPal8zMa7PmEXPqW2rt8G8kph2330OUm3xA0Jjti/ltTQQMIv9VHPAb2EHsvrOacx22tfffz1lhVsMts9r3a6w75zezeSCetlZ7rPwtpbtvqu01XdOY7bTvr6oWJ5l3iaoX+8HLomIM9l4S409aUY8T+sQUxp3CXBVZg7eXgiAiHhrh5i3A5dFxAUD+9qL5p2IwanSS+JKYi4CfpCZnxuR01c7xNRsq++cavVlrf4ujZvFvjwW+HQ0g0KDffAY4LWVY/re38eA7TPz8hHHf+HA05K4PmMWPSdo/pAYNYJ8X7sNmolAxg3QHFQ5pu/9ldwWrzSuVkzN2/BNjJlQtKztkHdp3KzFQKW+rBgztzkVXk+1bjFYs62+c3r+mCL4LJqJ3F5Pvdtalsb1GVMUN6kIHrNtbljg9igz3xkR5wAvAH6qXX0L8IrMvLo0pkPcS9j0F8NgLvuUxmTmGe2I/XPZ+HGPC4ETMvOOgfiJcYUxh47Kp932tNKYmm1NIadafVmlvzvkPYt9+YmI2I8HTsh2SbY3XK8V0/f+MvPoZY7/lwceT4zrM2bRc2r1OZg3i4NUx+KAUElxU5J3adysxcBiD2T1nVPJ9XQkcEpEPIyN717uCXy33VYaU7OtvnMqKYI/CDwaeEABCHy4Q0zNtvrO6U7KiuW55EeUpyQidgbIzNtXElOzrdL9qT8RsZaB4mbML6LeYuY5pzGv2z4zh9+FWpWYvvdnTtPPKZqPIw8OLi1NMjX8B+pCioitmDAgVBpXK6ZPEXEacHpmfn7Etg8vDYjMYj/NY38vutLrqX2+K5v+n/itEa+ZGFOzrb5yiognAqcAo4rg12TmpaPa3NJExB/QTAr3xRHbTsrM46aQVjUWuD2KiL2APwSeQfODFsDDaW5IfXxmfr0kZjPaeibNSM1mxUw4pisz8ycLjn1iXJ8xs55TRBwIvA/YgeYXdNB8h+ROmlmyL6sY8wSa/wx2YNPJcO6PaXObGNdnTGlOE/p7Fid3MKcFymleB4Rq7m/E67aogY6CNpc+2j1YKG7WrQFnLcac6ua0EtHx9pB9tLWaOZUWy33mNO2YLnHzzo8o9+ss4N00HyO+FyAitgZeSjMT4cGFMTXbmhgTEb845ngC2PX+JwVxfcbMc07AB4BXZ+bFmwREHAycDjy+YszpBTEUxvUZU5RTRLyB0QLYvo2vElOzLXOa35zauAMZMbgUEXcyYSBnNWLanHrd3zKupvk46yQlcX3GVGtrqQiOZW75FxFFtwZcipu1mFnMe55zauNWUgRfwORrtySmZlurllNb0G5S1BYWd1tUP42yCEWwBW6/HpGZZw2uaIvKMyPi9zvE1GyrJOYs4EOMnjDlIQOPS+L6jJnnnB46XLQBZOZFEfHQKcTMc07vAP4IuGc4Dtiqckzf+zOn2cwJ6g0u9TogVCvGgY6Jlorg9wDPyjG3/AMOaFeVxM1azCzmPbc5FRbU72W0AHZs25wYUxrXZ0yXuGVcAOxlP01UWizPLAvcfl0aEScDZ7DpzMdHAP/SIaZmWyUxVwB/nJlXDR9QRDxr4GlJXJ8x85zT+RHxcZqJAgbPy6uAT0whZp5zugz4+xzxvZuI+LXKMX3vz5xmMyeY3wGhWjFb/EBHYRG8DRu/JzjoFuBBA89L4mYtxpzq5lRSLB/F+Fs//lL7b0lMaVyfMUVxhcWd/bTyInimWeD261XA0cDb2PTjJeey8dY+JTE12yqJORb43phjetHA45K4PmPmNqfM/G8RcShwGJuel7/IzPP6jpnnnGh+0X9nTH+vqxzT9/7MaTZzgvkdEKoV40BHWaH8furdGnDWYsypbk4lRfAl1Lk9ZM22+s6ppAi0n8qL5bnkJFOSJK2CMYMv5w4O0vQZ0+f+IuKxwO2ZuWFEv6zNdkKqkrg+Yyrn9AXgdWOK4Jsyc8/28QGM7surh14zMW7WYsypXk4RcQLwMpr5UYaL4LOzuX3kzsBdmfkDxiiJKY3rM6ZDW58BfmdMcfe1zNzHfirrp+X2MesscHsUEdvQvFv6Qjb9BXYOcFpm/rAkpmZbHWNeRHNj90k5jY3rM2aec2IZEXFqZh4zKzHmZE7m1K0tbRlKC2qpVGmxvCUrLQK3dIveTxa4PYqIv6G5fckZbPyYyR4033fdOTNfXhJTsy1zmtmcdma0AL6UmXv0GdPmbU7mZE7lbe0AnEDzx+hamknlbqMZyDoxM+/sM2aKOb0QeGRBTmPj+oypmRMrFBHnZ+ahNeJmLcac6uZUwn4qYz8tBr+D268nZeZ+Q+tuBi6KiGs7xNRsy5xmM6cNwI00fzQvyfb5I6cQY07mZE7d2jqb5n7iT8/2/ovR3JfxyHbbc3qOmVZOhwzFHDEmp+Xi+oypllNhofxERgvgwPufFMTNWow51c1pOUtFi/20PPupWz9NiptlFrj9uj0iXgp8NDPvA4iIrWjuOXtHh5iabZnTbOZ0A/DMzPwGQyLipinEmJM5mVO3tvbOzJMGt7eF0IkRcdQUYmYlp5Mi4lcLchqM6zOmZlslhfIlwOfYdMBkyY4Dj0viZi3GnCrmVFi02E/2U1HcSovgmZeZLj0twN4090C9Dbi2XW5r1+1TGlOzLXOa2ZxeAzx+zHX0ur5jzMmczKlzWxcAbwLWDqxbCxwHfKrvGHOaSk5fHXWdDG4DrgL2HRNz08DjiXGzFmNO1XO6l2bA5LMjlv+wn+yn2v00z4vfwe1ZjJ4g4JzMvKZLTM22zGlmc9p/RMy504oxJ3Myp04xOwHHt3FLH12+leYWbCdm5h19xpjTVHK6APgUcEZunKF5Lc1HuZ+dmc+KiJcAV2bmVxkSES/MzL9vH0+Mm7WYWcx7znO6CnhRZl43IuamzNzTfrKfavbT8Pp5stW0E9iSRMRxwIdpvodzcbsA/E1EHF8aU7Mtc5rZnN5EcyuAAL7YLjGtGHMyJ3Pq1lZm3pGZx2Xm/pm5c7sckJnH0Xwns9cYc+o/J+DlwC7A5yLi9oi4HbgQ2JnmKylk5kdG/RHa2mkgp4lxsxZjTnVzAt7K+L/bXzeNnOynxe6nuZYz8DbylrLQfBT1QSPWPxi4rjSmZlvmZE7zmrc5mdOs5jRpAb4xSzHmNJWcjprBnOa1L82p0vVkP9lPpf0064uTTPXrPpr7nt44tH63dltpTM22zMmc5jVvczKnWc2JiLiC0YLmu5q9xphT/zlN8Dbg9Hntp3nNe55zmqD4erKf7Kcx2wa9DTi9IG5mWeD261jg0xFxHbA02+ZewGOA13aIqdmWOZnTvOZtTuY0qzlB80fEc9l0BnVo/sD4whRizKnnnAr/yJzXfprXvOc2p4rXk/1kP9UogmeaBW6PMvMTEbEfcBCbTk5ySWbeWxpTsy1zMqd5zduczGlWc2p9DNg+My9nSERcOIUYc+o/p5I/Rue1n+Y173nOqdb1ZD/ZT1BeLM8lZ1GWJEmqLCJOA07PzM+P2PbhzPzlKaSlOeX1VMZ+KrPo/WSBK0mSJElaCN4mSJIkSZK0ECxwJUmSJEkLwQJXkqQOIuKtEZERMXaixog4pI05ZGDdsRHxi5uxvwPbfe7c4TUP2L8kSVsCC1xJkuq7DPip9t8lxwKdC1zgQOAtQHGBO2b/kiQtPG8TJElSZZn5PeCivvcbEVvTTCA5lf1LkjRtvoMrSdLmOSAiPhsRP4iIb0bE70XEVvDAjwhHxNeBRwOvaNdnRHyg3bZfRPxdRNwWEXdFxDci4v9ExDYRcSRweru/6wZeu3f72oyIt0fE8RHxNeA/gZ8c8xHpCyPi8xHxrIi4rM37qoh40fCBRcQvRcRX2ny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z84Lq9y2AG8bZMUmSJEmSlmM5E9xjgXdExLso197++6LYHwLntFUQETtHxAkRcXpEnBYRf1s9vnVEfD0i1lT/blU9HhHx3og4OyJOjYg9ltFfSZIkSdJGZDkT3NcAXwQeTZnsvm1R7InA14eo4wbglZl5H+BBwIsj4j5V3d/IzF2Bb1S/AzwW2LX6OQj4wDL6K0mSJEnaiGw67BMz8zfAX9XEHjJkHRcDF1f//1VEnAHsCOwD7FU97UjKNb2vrh4/KjMT+F5EbBkRO1T1SJIkSZJ0k+XcB/eciPjjmtgfRETrKcpLyuxCWazq+8CqRZPWS4BV1f93BC5YVOzC6rGldR0UESdHxMlr165dTjckSZIkSXNiOaco7wLcqiZ2a+Auw1YUEVsAnwZelpm/XByrvq3NZfSLzDwsM1dn5urttttuOUUlSZIkSXNiORNcqJ94rgauHqaCiLglZXL78cz8TPXwpRGxQxXfAbisevwiYOdFxXeqHpMkSZIkaT2NE9yIeHlE/CIifkGZ3H5h4fdFP2uBfwW+2tZYRARwOHBGZv7jotCxwAHV/w8APr/o8f2r1ZQfBFzj9beSJEmSpEHaFpk6h7KqMZSJ58nA0otcrwNOB/5tiPb+BHgO8JOIOKV67HXAIcAxEfE84Hzg6VXsy8DjgLOB3wLPHaINSZIkSdJGqHGCm5mfp/o2tXz5ypsz89xRG8vM7wBRE37kgOcn8OJR25MkSZIkbTyWc5sgvz2VJEmSJM2soSe4ABFxN8rpw3emrJy8WGbm88bVMUmSJEmSlmPoCW5E7AscQ1mY6jLKtbeLLevWPpIkSZIkjdNyvsF9C3Ai8KzMXLrQlCRJkiRJU7WcCe7dgFc6uZUkSZIkzaLG++Au8TNgm746IkmSJElSF8uZ4L4KeF210JQkSZIkSTNlOacoH0z5BveMiFgDXLkknpn5Z+PqmCRJkiRJy7GcCe6NwJl9dUSSJEmSpC6GnuBm5l499kOSJEmSpE6Wcw2uJEmSJEkza+hvcCPiYW3Pycxvd+uOJEmSJEmjWc41uCcC2fKcTUbviiRJkiRJo1vOBPfhAx7bBngC8GfAS8bSI0mSJEmSRrCcRaa+VRP6TES8B/gL4Ctj6ZUkSZIkScs0rkWmvgQ8fUx1SZIkSZK0bOOa4N4TWDemuiRJkiRJWrblrKK8/4CHNwP+AHge8JlxdUqSJEmSpOVaziJTH615/DrgU8Dfdu6NJEmSJEkjWs4E964DHrs2My8dV2ckSZIkSRrVclZRPr/PjkiSJEmS1MVyvsEFICIW7nu7NXAlcGJmfmncHZMkSZIkaTmWs8jU7YAvAg8FbgCuALYBXhER/wk8ITN/3UsvJUmSJElqsZzbBL0d2AN4DrB5Zu4AbA7sXz3+9vF3T5IkSZKk4SxngvsU4A2Z+fHMvBEgM2/MzI8D/7eKS5IkSZI0FcuZ4G4DnF4TO72KS5IkSZI0FcuZ4J4LPKEm9rgqLkmSJEnSVCxnFeUPAe+OiC2AjwMXA3cE9gOeD7xi/N2TJEmSJGk4y7kP7nsiYjvKRPbA6uEAfg8ckpn/PP7uSZIkSZI0nOWcokxmvg7YgXKq8v7A44EdMvP1w5SPiI9ExGUR8dNFjx0cERdFxCnVz+MWxV4bEWdHxJkR8ejl9FWSJEmStHFZzn1wXw3slJkvBb6yJPZe4ILM/IeWaj4KvA84asnj78nMdy2p8z6U05/vC9wJOD4idltYwVmSJEmSpMWW8w3uc4FTa2I/ruKNMvPbwJVDtrcPcHRmXpeZ5wJnA3sOWVaSJEmStJFZzgT3zsCamtjPgbt06MdLIuLU6hTmrarHdgQuWPScC6vHNhARB0XEyRFx8tq1azt0Q5IkSZK0Ui1ngvtbaiaYwE7AdSP24QPA3YHdKSszv3u5FWTmYZm5OjNXb7fddiN2Q5IkSZK0ki1ngvufwN9FxK0WP1j9/soqvmyZeWlm3piZ64APc/NpyBcBOy966k7VY5IkSZIkbWA598E9GPgucFZEfIwy2dwReDawDTffOmhZImKHzLy4+vVJwMIKy8cCn4iIf6QsMrUr8INR2pAkSZIkzb/l3Af3xxHxcOBdwKsp3/6uA74DPCUzf9xWR0R8EtgL2DYiLgT+HtgrInYHEjgPeEHV3mkRcQxwOnAD8GJXUJYkSZIk1YnMXH6hiM2BrYCrMvN3Y+9VB6tXr86TTz552t3QIBGDHx/hGJQkSZK0cYqIH2bm6kGx5ZyifJNqUjtTE1tJkiRJ0sZtOYtMSZIkSZI0s5zgSpIkSZLmghNcSZIkSdJccIIrSZIkSZoLTnAlSZIkSXPBCa4kSZIkaS44wZUkSZIkzQUnuJIkSZKkueAEV5IkSZI0F5zgSpIkSZLmghNcSZIkSdJccIIrSZIkSZoLTnAlSZIkSXPBCa4kSZIkaS5sOu0OSJJWgIjBj2dOth+SJEkN/AZXkiRJkjQXnOBKkiRJkuaCE1xJkiRJ0lxwgitJkiRJmgtOcCVJkiRJc8EJriRJkiRpLjjBlSRJkiTNBe+DK01T3b1FwfuLSpIkScvkN7iSJEmSpLngBFeSJEmSNBec4EqSJEmS5oITXEmSJEnSXHCCK0mSJEmaCxOd4EbERyLisoj46aLHto6Ir0fEmurfrarHIyLeGxFnR8SpEbHHJPsqSZIkSVpZJv0N7keBxyx57DXANzJzV+Ab1e8AjwV2rX4OAj4woT5KkiRJklagiU5wM/PbwJVLHt4HOLL6/5HAvosePyqL7wFbRsQOE+moJEmSJGnFmYVrcFdl5sXV/y8BVlX/3xG4YNHzLqwe20BEHBQRJ0fEyWvXru2vp5IkSZKkmTULE9ybZGYCOUK5wzJzdWau3m677XromSRJkiRp1s3CBPfShVOPq38vqx6/CNh50fN2qh6TJEmSJGkDszDBPRY4oPr/AcDnFz2+f7Wa8oOAaxadyixJkiRJ0no2nWRjEfFJYC9g24i4EPh74BDgmIh4HnA+8PTq6V8GHgecDfwWeO4k+ypJkiRJWlkmOsHNzGfUhB454LkJvLjfHkmSJEmS5sUsnKIsSZIkSVJnTnAlSZIkSXPBCa4kSZIkaS44wZUkSZIkzQUnuJIkSZKkueAEV5IkSZI0F5zgSpIkSZLmghNcSZIkSdJccIIrSZIkSZoLTnAlSZIkSXPBCa4kSZIkaS44wZUkSZIkzQUnuJIkSZKkueAEV5IkSZI0F5zgSpIkSZLmghNcSZIkSdJccIIrSZIkSZoLTnAlSZIkSXPBCa4kSZIkaS44wZUkSZIkzQUnuJIkSZKkueAEV5IkSZI0F5zgSpIkSZLmghNcSZIkSdJccIIrSZIkSZoLTnAlSZIkSXPBCa4kSZIkaS44wZUkSZIkzYVNp92BBRFxHvAr4EbghsxcHRFbA58CdgHOA56emVdNq4+SJEmSpNk1a9/gPjwzd8/M1dXvrwG+kZm7At+ofpckSZIkaQOzNsFdah/gyOr/RwL7Tq8rkiRJkqRZNksT3ASOi4gfRsRB1WOrMvPi6v+XAKsGFYyIgyLi5Ig4ee3atZPoqyRJkiRpxszMNbjAn2bmRRGxPfD1iPjZ4mBmZkTkoIKZeRhwGMDq1asHPkeSJEmSNN9m5hvczLyo+vcy4LPAnsClEbEDQPXvZdProSRJkiRpls3EBDcibhsRt1v4P/DnwE+BY4EDqqcdAHx+Oj2UJEmSJM26WTlFeRXw2YiA0qdPZOZXI+Ik4JiIeB5wPvD0KfZRkiRJkjTDZmKCm5nnAH884PErgEdOvkeSJEmSpJVmJk5RliRJkiSpKye4kiRJkqS54ARXkiRJkjQXnOBKkiRJkubCTCwyJXVVrcC9gcyccE8kSZIkTYvf4EqSJEmS5oLf4EqS5pZnd0iStHHxG1xJkiRJ0lxwgitJkiRJmgtOcCVJkiRJc8FrcCVppai5nhSvJ5UkSQL8BleSJEmSNCec4EqSJEmS5oITXEmSJEnSXHCCK0mSJEmaC05wJUmSJElzwQmuJEmSJGkuOMGVJEmSJM0FJ7iSJEmSpLngBFeSJEmSNBec4EqSJEmS5oITXEmSJEnSXNh02h2Q5l1EDHw8MyfcE0H9/gD3iSRJ0krnBFeSJKmruuSZiTNJmihPUZYkSZIkzQW/wZWkMfKU9A15WrhWill9/foa6onfumsGzOr7zkrmBFfqyDcmSdI0+XdIaufrZOPhBFfS3Fmpf8RWar+7muVxz3LfNF881qSVy9fvbHGCq7HxxT15bdvcfSJJs8H3442L+1szoeHyhnk+FX9FLDIVEY+JiDMj4uyIeM20+7OSRcTAH0mS5p1/AyVp/s38N7gRsQnwr8DewIXASRFxbGaePt2eSRrVSl4wxay8JmVej7U+zzyZ123Wldtl/Lpu06byXf9GTvXsrg4Ld3mcDuZ2Wb6Zn+ACewJnZ+Y5ABFxNLAPsGInuF3eePp+0+rSdhdtb+bT/EMyzTeWWd7m0/yQOo3tMolt3lf9kzjOp7lPpjkhWqnv1338HRq27S6mmRxbyYm5Nn3u72kea328Nwxbvk+z/Nlg1Pqn/tmgZWI+y8eSScENrYQJ7o7ABYt+vxB44OInRMRBwEHVr7+OiDMn1Ldx2Ba4HGoPsqZ4l7Iz03bNm8rcj3uE7TKv4755zLY9Ut1dXkMrue0ZO45t27YHxkZ4jYyt7Vl+35rltpv+/vbd9rxu85X6WW/OXr/rxUf4nDlr7lIbycyZ/gGeCvzbot+fA7xv2v0a4/hOHjXepaxt2/astD2v47Jt27Zt2563tud1XLZt27bdXnYl/ayERaYuAnZe9PtO1WOSJEmSJN1kJUxwTwJ2jYi7RsRmwH7AsVPukyRJkiRpxsz8NbiZeUNEvAT4GrAJ8JHMPG3K3RqnwzrEu5S1bduelbbndVy2bdu2bdvz1va8jsu2bdu228uuGFGdcy1JkiRJ0oq2Ek5RliRJkiSplRNcSZIkSdJccIIrSZIkSZoLTnAlSZIkSXNh5ldRnkcRsQrYsfr1osy8tOX598rMn3WJAxcDj1ncLvC1zLy6es4dmuJtbY9SPiKem5lH9FH3Qv3AZ5rKdqm7pe+18YVYRDwa2HdJ25/PzK927Rvwv33VvcLH3dj2KOMatu22uofYLiP1XZIkaWPiKsoTFBG7Ax8E7kD5cAqwE3A18KLM/FFNuV9k5p0b6m2LX1G1cdySdvcG3lT9/vd18cw8qqlt4A2jlB9mXKPWXZXvddyj7pNqXJ8BdgOOAi5c1Pb+wBrghx369kvgOz3VvZLHnU1tZ+bfdhh3Y9ttddO+Xbr0vXMCrKHswuR87AmTLsmUJX2rTQxMM9HT57gayrYdC2PpW5d+d0lC0VOCq03Tdu1zm7bFV0Lbfe7vhrK9vQ5mfNwz/5454vvaiqx7oTwd37dMjg/mBHeCIuIU4AWZ+f0ljz8I+ALwyUHFgAOAj9ZVO0T8RcA2S9+AImIr4PuUD88PbIjXvQgW2r64ofwlwJk1ZXcDPtSh7u8D1zaUvy+wdYdxN9W9G4PHtbjtnzaUPT8zd9sgGBHAWcC6Dn27b2ZucPnBmOpeyePOlrZ/11B367hb2m6ru227NPY9M3etqb9zAqyvBFdb38aQ2GtLHGwC3GPc/Z6BcdUmPMbRds8Jri6JnD4TXIdl5kGjjnua23yW22bE47gq3ymp6LhH6luv75ktbXd6X5vFuqvynd63OsbPB66hTH63r557GfB54JC2pMWsc4I7QRGxpu6DaESsA/4auG5A+N3ArYBXjhj/CGWid82SNu8AnEw5qB/QEL9jS9tXNpS/AlgNXLWkXADfBW7Xoe6TgdsDj66p/2zKxH7UcTfV/V3Km31d/OfA/RvKXg48LzNPWtL2nsDhlP05at/WAA/pqe6VPO5saXv7DuNua7ut7rbt0tb3ExhsHAmwtoTHeXRLQjUlRJqSCsPEmxIH1wHbTynR0+e4rqJ8mBlU9gDK/urSdp8Jri5JqK4Jrgc21P1jyofYuviLgNNqYuPY39M81vpsu+146LK/v9JQtuvrYJbH3SVRO833zLa2r60pP+t19/2+1SX+a+DNwJGZeUn1+B0pr49HZuaf1/R7RfAa3Mn6SkR8ifLh44LqsZ0pmZT/BX6amd9dWigiDgZO7RB/F/CjiDhuUbt3pmTd3kL58NwU37+l7bc1lP8usEVmnjKg7ImUyfOodb8FeGhD/Sd1HHdT3SdS3rTq4ue1lH0X8IGIuB03Z9V2pmTTDgT+oEPfjgfe11PdK3nc2dL2izqMu63ttrrbtktb30+kPlH0DOC5DXGq+pdaR/kDvIrmyXl0KP9zyvtLXd1tbbfFr42IByxNDAAPqPrcZdyzOq7bUT581x0LXdvuMu6mfl8LZEu8qe01HeteS/lGIxbFsvp9e5pfQ9Ey7mlu81luu+146LK/m/ZX19fBLI97pb5ntrV9C/rb5n3W3ff7Vpf4ppl56OIHq4nuoRHxl6xwTnAnKDP/JiIeC+zD+ufC/yvwPWqyX5l514jYukN8uyrD9uhF7Z4IvDYzrwKIiGPr4lWstu228oPKVWWf2TauIer+aEP9D+4y7pa6n1kXq+J3H6LsA6ts2eIFxy6p/v/DDn17LNyUiRt33St53G1tP2+Ivo/a9jB1N/WtMV4lc/pKgLUlPL7Wofx5LXU3JRWGiTclDt7ecdxdEj19jutHNB8L3+yxb+d16PeBdEtCdU1wHU351uIXA+q+gHKWRt12fV/LuLvu72kea3223XY8dNnf/0B/r4NZHneXRG1b3/p8z2xr+0srtO4D6fd9q0v8RxHxKso3uJdW/VlVlVvYvyuWpyhrWaoJKZl55YDYKpa3OvQWmfnrYeoesa/r1T9ObXVHxBbAb4A9WT+Z8YNsedHFogUwlrtN2/rWZ90LcXoed0TEcuuP7iuRb5GZv+7S9ihll5S/AzWLeywkijLztzV1tMWXJoIW6q5NUI2zfN8aEgMz3e82g8bVtq9nQUsipzXeR90R8WLgO5n54wF1vhT4ODO+XVeqPvb3PLwO+irbpf5JvGf2ObZZrbvre+Io8Wpfvobypdv2VexS4Fjg0HF9Fp8WJ7gTVH1AfS3lYFrFkBd0R8RXFr4hGnc8In6SmX/YUPYnwOOBdwKPpCxGE5RrIb9JeXFsyc2rQ19YxYdaHRr406a6M/O8pr619L1pIYjWcY9adxW/DPglJeu/eDGGe1C2yXFNdQNPZIRt2ta3Puuu4r2OG9gWeP9y6x+i38MsJPH8Udseteyi8iMv5DSgvoGJpK4Jjx6SMa3JlFGTDlX5hcRBL4meaY+rbQxd+jZKfIiyQyWhOiaZapNEdWW76nObLsQZPanY27E4xtdnbflh9+dyk+fjOM77ev0Om8Du0re27drlPbOP7TKucfXZ73Ecxw11t+2vib/vzQJPUZ6sYygTt4fn+hd0H0i5PvfFA8oEsHtE7FFT5zDxB0XEk2tid6yJ3RQHPgX8E/CszLyx6vcmwNMop3XdmobVoSPi3TV1b9FWd0S8s6lvEfGKhvhWXcbdUvcWLfFtgD2XTtAj4q7AlyPi6w1lt6Scilu3TY+IiCMbym8fEe/tqe6pjhvYDHhUTf0/jIiP1dVds00Wxxv3N/DPo7bdUnaY7fJ64P4DPrhtRVnco2n1yq8AL2BJIikiFhJJRwFvZElSISKupiXhAZweEQOTEsOWp5zittzYQtu1iYOIaEwcACdExPk99Lst3ve4jqurP1qSocP0rUO8rWxtvxfiHbbLcRExKEn0cODtEdG2AuzemVn3Gm3brn1uU4BzqEkqDnGs9Hksdj6OW8p/BngKNfuTcmlL3XteY/Kcjsd5X6/fIdpuLdvWN8pnvrrXyRHAExj9b0Vf26XruJpe/1M9jluS163va9Xvyx53tNweaSVwgjtZu+TgC7oPiYh3UM7jjwHltgROAr7VIf5EBi8OcGvKJPPjDfFtM/NTS/p9I2UC+pbq9+8vLZiZ34uIHYCtgBsG1H2LIepu69vbKdfaDKp/C7qNu6nuW7TE4ebrHRa7CLgl7Qtg3LZhm962pe1b0bzITJe6pz3ubKh/S5rH3dZ227g37dB2U9lhtkvQsLhHWwKM5kTSvwOPGDXhQbeEybY1iYVhkiltSYe2xMH2wL49JXqmOa6ta46HhWRol8Rd13G3JZka43RLMo2cJAIOj4h9G/r2J132d8/J1A93aZvmbf69iDh0xLLDJPaayv8MWNWwP19Ic/L8mKZxdznOW/rdOu6WthsT2F3fWyh/6+peJxcDf9bhb0Wn9+su27xlXGdGxLY99XvLlvKNx3FErG6pu+19LVvide97b6J8qbBiOcGdrPOj/oLu31A+JK5ZWijKAhfXdIj/HnhXZm6wrH1EPIpymnRT/IcR8X7gSNZf/fkA4H+AS6J+dehLgc9l5g8H1P38Ier+ZUvfLmio//Udx91U9/MpmdS6+MuBkyLi6CXj2o9yW5e9aV4Ao2nF7a8CezS0/doe6572uC9qqP/clrqbFlo6mLKkftO4P9Kh7aayw2yXttXE2xJcTYmkozomPLokTDanOQHWJenQljhoSsx1TfRMc1wvoTlZ2mVcXcfdlshpi3dJMrUliY4dEIObJ5FNr7Hb0W1/95lU7Np20zbfjuZxd03sNZVv3J+0J8/7PM67jrtLArvre8s66rfrLTq+Z3Z9X+uyzZvGtW3Huvs8jjslv6v/18XvEhGnDogF5TLKFc1rcCcomi/oPgP478zc4H5bVeZ4U+AnI8ZfC3w8B68OuZryZn1+Q/xUyiqwS1d/PhY4PDOvi8GrQx9LWU7/isy8fEDdqyjLpi+t+0LgC5QP/nu29O1XDfU/ETilw7ib6l5F+UB1ZWaurYlvzYBtkpmnxxALYNRt08z8ckTcs6Fv9wQu6KnuhXE3xXsbdxW/96A4cElT3W1tV+Ou3Z+ZeemobVd13IdyRsGo22Urahb3iIifAk9qSID9F+We0oMSSXtTJveDkgrnUhIeL62Z+F8AfBa4+4jlr6PcP7iu7gta2n4/8HTKpRJLEwfHVGN7Q03i4BrgOx3G3dS3aY7r95R7K9YdC21td4m3jXtNQ7/PpWz3pvhh1G+X2wPPaSh7MOVU/Lok0XuAZ1PuDbleccoZEGupf4113d9d4ldTtlvdsfIXHdtuOha3Bp7c03Hctr/PprxG6/bnY6h/z9uWcopoX8d513Ff3ND2tZQzbkYpO0zf/pf618k5wO8Z/T2zy3a5FviTnsa1DthvRo/j/VvqPrhhXG+hTG7r4tsCf0bN7Y8y805L21xJnOBK0gRFy4InbfGaMk+lOQH2ZZoTSY9gxIRHNfEfNWHyEOCsUZMpTUmHYRIHPSZ6hhnXSMmUtnENcSyc0WFcbX1vG/f1df2unjNMomdgoojhkkxNSaKvAO/MzBMGlPs28F7qt+uLgGM6btO+kqnDHMejJvZuHLXsMhJ7TYnBpv25GQ2JeWCXIbZL0+t7TV/j7pLAHjJRW7tNq+c1bdeR3zM7vq/1Ni7KF06zehx3Sn63jPtdwBGZ+Z0BdX4iW26POPMy058Z+AGeO0pscZxyAH+A8gZ+bPX/x7SUfWNbnPLt8AuAr1C+zT21+v9fA7dsKX/YKLFh+9ah7c51UxZaOIRyDcWVwBWUD4+HAFs2lP1KS91t8bbt1jTu3uoeQ9td+1Zbfpi2R92fw7RNyZgeTTktfg0la3tZ9dgui+JrB8Vb2v5JU9wff+bxhzKp23q5MX9W5o/71G06D+Pq0reOZVdRvineg3LN79S3Re/betod8KfaEfCLUWILccpiCl+mnPLwp9XPftVj/9yx7k9SJssPopzWs1P1/w9QTt3auuZnG0qmqC524ajbZFHfmtqurX8cdVMyYK8G7rio3B2rx/570ZvJ4p/7U04hGhRbHG9ruyl+aY91d22767ibyq/t2HbT/jyuY9v/DfwfYJNFdW9CeY1+b4j4k2t+ngKsbTmW2xJktckcekx4tMXHUPfICZW+x0VPyZSFOCMkO4cd16h9H8f+ojlR9BCmlCRqeo2N41jqsM1bk4Ydj8Wv93wcNyYGm/YnPSXmq/gRfY571L4xRKJ21G3a9joZw3HeNu7GY63juE6b4eO4U/Kbssjk96rxfB04vhrn94A9Gspu0VT3SvjxFOUJisEXc0M53/2+lIUDBsV2AzY4LWpJ/PzM3G1Am0G5cP43NWU3B+pOfViInzOo7qr+syjX351fPX9BVr/vQrk2Y1BsR+Dalrbb+hYtbf+qp7p3BM7NzHsOrCAigROWlF3wIMrtbuoWLFmIN7W9SUN8lyHaHrXucbTdddx15ffq2PYvGvbnmZR71o7a9oWZuWtN3WsAWuK7UL/i91Mz83aDylbl2+7xeyHwR4NCwI9rYuOKnwoMut/0sHU/sSH+Rco9vOviXwLu06HtLuM6jXK7kiNz/VvGHUC5rclrGupuG9e3KcfpUdy8sMlOlGu51lBWxxx1XG19fzTw1IayXfbXF4HzKMnc/8gNV8b9MOV+04NiL6PcMqau7g9m5nY1caL9vuh9v4aatvm+wItryn6R8tli1LrbjsXvUs7y6uM4btvfbwJeW1P2g5QP8ldTrsFd/Do4gJI0fWFD22375CLKrVf6GnfTPjsdGHRLqoWyp9K8P29H/TZ9Gc2vkw9RPm8OivX9ft12rHUZ1yeB/9tQ9zSP47M7jOuDlGO17i4HH8rMPx5YuOVzw0rgBHeCIuJSygeAq5aGKIsx3b8m9l3KB/u6st8FLgeel5knLWlzT8pCKjvngJtxVxfQJ/CAhvhFwLuBT2fmuurxW1BeYK+g/LF4ZA5erOl64O41sWHabotf29D2DcCOPdV9ASUjdjyDV8X+v8D9snnV66ZFgdrabopfD9ynp7q7tt113E3lu7bdtD/3pnybO2rbTYs8bUtZ5KIpfnfggBy84vcFbPi+cFOY8oFk4CrCVXwLmpNQXRIewyREurbdljBpSkr0Ne62cTUlx9qSKW3j+rPMvMWAeoOymNjdOoxrmMRe2zYddVxtiaLfZ+ZmNbHWJBHltTawOOWD4sUN8T+g39dQ12TqqHW3HYsDj7Uhy3bd30l5v6zbnxd3SMy3vr4zc1CfxzXupn22C837uy1Re4sOydQDmd77ddux1mVcB8zwcXxJl+R3S/nLKStfbxACXp+ZWw8qt1J4m6DJ+iLla/9TlgYi4ryG2InA71ri7wI+EBG34+Zs5c6UD/VHAXehnD661CcoC380xT8AHAq8PyIWPkhvSXmT3Q94HGWJ9Q0mJZQVVuti76RcF9Clb79oqP/4Hut+J/AxSmbvWxGxdFXsl1CWlx/kpZTXXlN8x5a21zXEj+qx7q5tdx33xQ3l/7Fj29/i5v25sET+JZT9+XTKQkyjtr2wyNObGLzIU7bE96TcMmuQJ1G+jWxKgN1AfTLnemCvnhIewyREurR9DaPfPq3PcbfVfX7U3zLuAsp708i3hYuIByxNdgIPqPp8TodxtfX9dy3j7rK/LqD5tnKXNMT+h/Zbzn2K5vuir6L+NXZ2y7i7voaatnnbLQa71N12LF7b43Hctr+vonl/XhkRT2NwYv4qur0O+h5323tLU9m2/Xl5h9fJs5ne+3XbNu8yrmfM8HHc9VaaTbde3JLm2yOtaH6DO2einFZx00ppC6dbjLH+bQAy84px1itpdBFxOA2rIVI+zB2bmT8YED8O+LvM/PGA2EspCY3v9BQ/Bnhbh7ovZvTbp30IeP+UxrWQHNuHDW8ZdyglmTLquF5BuZ57ULLzxZRvFLrsz6a+Xw4c19P+2pfm1cCPAp5TExvmlnMfovksieOof42dBDy/x9dQ0zY/g+ZbDO7Yoe62Y/FZlNNS+ziO96V5f/8MOLthf16+qA9LE/OvoSTmR90nr6KsC9HXuJv22eGU1b7ryi4kavfh5nuZLiRqD6XcBqtum7a9Tg4FPjGl9+vFx9q4x/Vwym2l6uqe5nF86oCyi1cDb3xfy8yTo/42nm+g4bZOmbnz0sdXEie4MyIitsjMpfffWy8WEUE5mBcfpD/Ilp0YEffKzJ81xSLiDpQX+OK6v5aZV7fUvXdmfn2U+BBla/s9ZLyp7b7H/dzMPGK5sSHjXbb5WOqOiHsxeMn8MxrK9j3uzts8Ih5NuaZt8bg+n5lfrZ5XG28r29D2GzPzzX3FtXHqO9k5byLiobR8UJxCtzQGJualDcUQt3WaQrfGxgnujIiGC7oj4heUxTPeT1kk5KIqtBPl2oAXZeZxHep+A2XBhOOW1L038KbMPGqUuodpe9Sy42ibjXTcXesG/hV4BmUVv8WLd+wHHJ2Zh/TVdp/jBj5DuV61bnGebIjvQMlODyybmX/bx7iGjC8kyJadzOmSTOka75JMqcqPnFAZx7gop4NNtN8LccqxPHLirss2p6wIPvK4+0gUjStJNEqSuc+kYVW+S2Jv5KThGNruGu+yv2c5kbvwOhi57T6TrcAxTf3q8/0a+N8ex/X9prq7JL9H7VvVr7dTvsHdoG7Wv7zpScCdlsYz8/qGtg/LzIOa+reSOcGdoCinjg0MAW+hTLgGxV5POf3lsZl53pI670o5/aHuzTqAgyinXw2KHUD5YP7ApR9+otwc+vuUUyjq6n4E8I2G+GOr/tWVPbyh7AHAR1viJzbEH0O5friubNdx/7whfl+6rYr9tZa2m7b541va7lL3Iyhvnvdd+sYZEZtRVq0eNLZxjbvPbd60EvlZQDbEr8sBC9wsKrtqaWxR28Os6N0Yz8za9RS6JHOmnZRgxGTKONruOK6rKIutTLTfVfwKyuqxIyXu6LbNO42bliTTqImiMWzTN1Juq7HsJHOfScO2+qf9+l3JbTPFRG6XtunpNVTFG1/flMlWX+/Xv6QsmNrHuBrrpjm53Rrv8r5FWaDyaupXA1/XEm9cLTwzd6ppe8VPfp3gTlBEXAv8A4Mv6D4YeGtN7OWUe2DdOzPXi1eTitMpH6BfyeDVUo+g3PttUOzdlNVbH5CZ1yyp+w7AyZRVXJ9NucZhvadQFubYrCH+TeAvGsrepqHf7wZu1RLfpKXtPscN/a2KvXlL203b/BstbXep+1NVvY/OzPPXC0bchTLu1Q1tdx03DeX7XIn8pkxpTfxbwMMayt6BbquFt8Xfs/TxRWN7PeX9oy6ZcwHltTKo7DAJjy7xtgRYUzLlNMqiRnV1tyU17kNZnGuUfg+TZLpVT/1ui98X2LpD4q7LNr8v3cbdlmRqShRtQYfbwg2RJPoN9UnmUynXdg6qu2vScJht3iWh2ZQ0HOZY65JUbIu3rf7etL8Hva8sxKedyG1NtnZou8trqO11sgWwWcNxmg397vq+d99sXh2+07hywKrYQya3h4l3ed9qu00nLfG21cLvWNN27eR3pXAV5cn6EfC5HHxB9+saYs8HPgKcFBFHs/5KaPtRPkDvDfw0M787oPwHG2IHA28DfhRlsZmFuu9c1fkWyoIlv83Mbw0ofyblD39d/OqWsje09O3UlvjPGur/Zc/jXkN/q2Jv1dJ20zZf22PdZ1JOmflGlCXqF2+3e1BWru5z3H1u86aVyA+k/FGoiz8feF9D2SfRbUXvtvjbqU+e3YLyB2tQNnMd5Y/ohxicVNgTeCj1SYeu8ce3tL2OctrV+UviO1SxppVtv9sSP6el7S7jemyP/W6Ln039vo4hxtVlm6/pUPa7wLXRvAL01dQnem4Adh01SVT9vRhk4YPmudz82l7sIkqitsux1GWb/5zyTVHdNm1ru8ux1tZ21+O8afX3tv3d9X2raZ9sQr/j7tJ2l9dQ2+vk+oZ+ravK9vW+t6bHcbWtPJ8d4019azuO21YDz5Z402rhSfkyZ9Dkd/ulz19pnOBO1nOBukUOHs6GbwoLVmfmpRHxOcq1DQ+uHr8IeFZmnh5lRdBra8rvWBfLzLsCRMSxlDeWhXP8TwRem5lXUX+aMJn5sLpYFd+6qWxEbN3Ut7Z4U9uU+z1Oa9x3b4g9s6VsW7yt7UEZuXHV/TCAiNiNDa9FOymrG5GP2HbXvo1jmz8wmhfnaYp/vCG2QeJqUduvbulbazzKAjlNCbKmZM5pdEt4dIlf3VK2KZnyEsof8VGTGpf0OK4zeux3W/wkuiXuumzz73Qcd1uSqSlR9IOG2DBJomfQ/AG5Kcl8Nv0lDdu223kNsRPpljQ8keZjra3tLsfxiZQP56Pu7z9idhO5bfGjOrTd5TXU9jr5bEO/XlL93tf73vH0m0RuqrspuT1MvMv7VtttOrMl3nQbz7XQeNunFc1TlLVRqCbKZOaVA2KrWH9Sculy4jXtta6KPUrZrvqsu63+5Yy7r20eMf6VyNviXcoOG6f8kbsyM9cOiK+qEmRbsX4yZ2HhoaXZ8plSZaOXlUyZBdPsd9d93aXv4xh3S5KpFxHxVupvpXVolUi6D/BENlxA5/QxtL8ij/N5NuXXcKe2+3oNtfWr723W53tDW91d42PoX+Nq4G3xAc9/MQ23dcrMf+nQ3alzgjsjouGC7qZYFf9KZj52lPgQZX+SmX/YR3yIsiOPq4r/DDgFeCTlFJEAbk+53vA1lCzXBynXR15YxXeqnvsiqqxcFV+8qMjVlEVFftTQdp8LYHTZ5r3V3Vb/MOOmnKHQyzanp5XIh2m74/7uFF8Jxp3QGEd8WMvte9/9XpTMmWjibiFO+WasNom0EpNMA55fmzBtKTfR47zPpOFCnI77u4/jYXFspSWwh0nGTuM1tBCnXCfb2/4eZWxjGtfFNKw8Hy13IegSbyvb0O9e73Kw0nmK8gQt/FEcFAIeXxMP4HERsUdD2d1b4qtr4gtln9xQ9o4d43euiS+U7TKutr7fnbJy7LMWZRc3oZwmczRwa+AFmfn99QpGPIiyMFc2xSPiyIa2t43Bq2YHsEVNbHG8yza/a0vbXfd3U987jZuy3XvZ5sA/A4/KmpXII6JpJfItI+K9DfFVNfFhyo4jfgfgtZRbCWxPOXYvo9wq4JCmP5Qdk1Bd42sol22sl9CIcupyY0KDsrhe08R+5Pgw46JcB7dBMmaIvvfW78qaiDifJYm7hX5Rk7gb0zY/B/glA5JIEfGi6veBSaaIaEwyUVaFbmq7Kd6l7MIH4N8C76QsQHRNeThuSpgufV9ZVLbLsQLdjofTI2Jg0nAW9ndbvMPxcFzbuOnvddD59R3lspK67fJvlGTtpF9DAN+mx/3dFm8YW9dxLaxUvHjl+YcDb4+IN1W//31P8eOBR9WVzYZV7ynr7zSNa+T4PEx+neBO1lrqVzO7E80Xe59EWal1cXzBli3xbSnXZdSV/RTwcQYvTHLrjvHbU07pqivbZVxtfd8kMz+1+IFqont0RLyl+v37Swtl5vci4rblv43xpoV9Nqdc91C36E/bokBdtvltW9ruur/7HPdte9zmm1K/SMwtKdfI163Y/YyW+Ispq4mOUnYc8WMoH7T3yuq0qCinSx0AHBNloblBhklC9ZkAuyvw7BETGsMkipriW3UZN83JmC9ExLt76ndbfDtg354Sd21tbwPsWZdEqn6dySRTTWzBwofPf2JwwvRrEfHamrrbjpWu27wtsddn2532d1u85Xho3N+0jJvpJrDbEr1NydifAffs6TXUFu91f7fEfxgRH+tpXFsCd1+aCI6bV55P4P49xS8Ftq8rGxFPbej3NlHWkRk5XhOD9snxzPMU5Qmqvq2oW83sesoLrO5i72uAJ2XmmhHi1wP3aSh7GXBAZm6w3P8Y4r8H9mgo22VcbW3/lrJQ1JGsvyjIAZRJ/yWUb3mPWhLfn7Ji5rqW+B7AS3Pwwj7XAQ+piV1Q1VdXtus2b2u76/5u6nvXcX+W/rb5+4GnU769X7pIzDGURXjekINX3T63ar8u/jvKa3uUsuOI/z4z77k0VsXPpCy4Vpe0OJDyGhkUeyolqVFXtmv8gBxw64eq32dTsvd1CY2XV3WPGj+YbuO+JDN3ren7OsrCXn30uy3+xszcpKZfZ1MSd3X97rrN30i5TVDd7eyS0W9313bbuCNovi1c2y3nPjHgcSgfBA8ALm3YbknzsdR0rHTd5gfTcovBGd7fXY6Htv19Vcu4u7wODqZ5m3d9fa+lfrv8GrhNT6+htvhH6Hd/N8Wvpdvru21cW2f9LSOT5ltKdomvBbZrKNvlNp1t8a9SkndLBfCIzLztgNiK4QR3gqL5gu5jgLfVxF5KuT7gJ5l55oD4vpRvp+rihwIfaSh7BeXeaYMm16sp34yNGn8+cFxD2V06jKut7w8C7ke5rnO9RUGAwzPzuoh47KB4Zn65qqM2HhH3BK7IzMsHtP0Q4Kya2CpKxrCu7Cpuvp/dKNv8KcC3eqp7NeWebb2MO8tiSG3bvG4xpYdQbqretNDSvWvqPj2qFbsz87dLy1d11Ma7lB1T/DjK6ppHZnUNWbW9D6RM3Ldi9CRUnwmwX1FOexsloTFMwqQp3nXcTcmYPYAn9NTvtnjbNu2SuGtr++qqjrokEsxukmlbmj8gH0+5d/qghOl+lPtgj3KsdN3mbYm9Ptu+mm77uy3edDy07e8vtIx7mgnstnhTMvZSyiS2j9dQW/xKylmIfe3vpvjtgef0NK61lFOv61aeT0oyp4/4NymXPTStev/OzDxhQL+/TbkGftT49ZTLmgZOjjOz7v69K4ITXEla4aKczvQayuR94Y/SJZRkzqHAfRk9CdUlwTVMfDtGSyINkyhqij8ROGXUfmfmyXXJGMr9Qfvq9zDxPQb1axmJu9oVuau2m+Jb19R9evWcWU0yfZPmD8j3BJ43qO+U00bPHuVYGcNx3phU7Jg07HV/t8W77O/qOV0T2CMlU2nfZo3xIZKxvbyGhow3riTeV5zy96zPcW1Fw8rzfcbbyvYlIr5Cw+Q4W27NOOuc4E5YlMUqBr0xndEUa6nzuZl5xCjxIcq+MTPf3Ed8IRYRj6ZkkRaP+/OZ+dXqeY3xhrYPpnzzvUFZyje41zeUbVu5euT4GOruss0Poyyw8TzKvdnuVIVu2i6UbGNtfNTtNsy4gb+jLJa0MFFLFi2WVP1et5jS+6uxDYq1LbTUdcXuLiuV9xqX1G6YCZOkIlpWEu8z3nfbmg9OcCcoIl5NWRDmaG5e7GYnyukXFwM71MSOzsxDGupdkbcwiXLrls9QTpk9ivXHvT9lJb1simfm3za0/Zuq3JFLyh5AyTq/sK4o8GPKjeJHjZ8KDFqFdai6M3Onmvgw2/zCmvoX2v5PyoqBddtlXUu8abt1GjdwGuWUnSNz/cWSDqScxpM18QMok+N/qIk9kvINZ13bXwQe3yH+VUoGto+6W+OZuUOHRFBrEqqpLGXhr7EnTPpMMlXxD1OucZq5RE/H+BGU0xjbkkSjJJFa43WJpGkmesaRJIqITSnHw75smDD9KOV9ZqzHStf4GJKGK3Z/Uz47DTPusSdTW8qOvE2HGXfP2/wEynvLI6hWEmf9Wy+uY8lK42OMvxf4G+pv+7hQdqR4NqyCnv3eSWCadzFojK90TnAnKCLOAu679I9d3LxwwG1rYqcBv6urljIB3OAa1UXx+1JWeK0rO+iao4X45pTbI4wa34JyzWZd2XMyc7cNghEBnEVZCKIpXneNQABbZGYMDJZ9cXfqV7XeEdikQ3wXyjUfo9Z9bcO4htnmTW2fN2ibwk3bhZZ403bbpaXttnGfm82LJdEQ/31mbtZQ9h7Ur8j9IMpiDKPG9wJO6KnuYeIfYvREUNd7Fy/cYmGUhMkdKZOGDaqme5KpLX5B1adZTPR0iV9EuSXFcpNEbfGFRFFTfF/KiuKD+tV3oqdTkikzd6iJL0yYrqb+eHgcZRXYUY6Vrvu77VjrkjRcyfv71Jp+H0j310FbMrXLNm1Lxk4zmfrfwHOA/8gNVxJ/WTWuf+op/mHK7ZH6qPtNlITDoDF/EHhBwzbpGv8I5S4J02j7g5m53cDgHEx+neBOUET8DHh0Zp6/5PG7UCZru9XEjqNcs/FoYOk5+QF8lzJxqIv/HLh/Q9kbKCu8XTqgzxdw8wpwo8RvAHZsKHsV8LzMPGlJbE8WfYvSEL9DQ9vXUVaP+3RmrqseuwXlDe0VlA8edataX0CZZI4ab1sVu63uLtu8re2LKIum1G2XbIk3bbeu4z6D5sWS1jXEX0W53rSu7B3ptmJ3U7xtpfIudQ8T/12XRBDNSai2BNfAJFXVflvCJOmWEOmUhGpJgE0z0dPXuNqSRF3jyfQSPXt1bPtPBjwON3/w/1XD8dCUXJt2MrVL0nAl7+9f9DjutmRq19dYUzJ2L6a3zf8s61e9XwOQ9StTd403bfOudSfTu5PAgVNsez/gWQMeb5z8rhTeB3eyXgZ8o3qxLV4t7R7AmxtiL6FMLrbIzFOWVhoRJ1K+4a2Ln9dS9hzgLpRTT5b6BHB9h/gPWsp+CvhARNyOmzPfO1M+0B9IeVE2xZ/UUP9HKC/w90fEwuR+S8ofh/0oWfetgA0mW5RTWdZ1iH+2Y92rGH2bn9BS9xcoE8GF7RKU7fJNynbJlnjTdus67o9Rstffiojtq8cvpSwy8fSqb3Xx1ZTbCNSVfQTlfriDvJTyfjhq/B97rHuY+Jsj4gFLE0HAAyhJhatpTkLt2iHBdWVEPI3BCZGrgGyIXwfs1VOSqS1+XYd+X0V532xK9ExrXNdGxKsYnOi5AFjXY/w3lHuLNiVq+opf37Huk2i+5/r5Tcdxh2NlHMnUpmPt/I10f/c57l/1/BprGlvX47xL/LcR8X4GryT+P9W4+opf0mPdVwHvysGroD+Kcvp4X/FnTbHtAykLeg2a/N56wGMrit/gTlj1R29P1r+G56TMvLEpNvmeTlaU03NuGndWp+0MGx+i/m0AMvOKrn2dJ23bxe22MkTEHsAHgEGJoBdTEkHHZuYPBpT9LvCymtihlA9bdWUPrdo9lJJAWJpIeg03J0wGxU+jXCf84wF1v5SSEKm7tVrX+N8D91nUr8WJnEH9Xhp/XEPdbbd963NcrwK2oVxbuDTRcyg3J4n6iJ8B/HeOftu3LvFDab4dXlvdb6X5LImHUn88/Asl0TTKsdJ1f7cdawtJw41tf3+L5pXls0P8g5Rkah91LxxjfR3nXeJPZcNV7y+kJM0Xr1vQR/woyunRfdT9MxpWQaffOwlM8y4GZwBPq5n8XpCZOy99fCVxgjthERFsOIn9QWZmU6ytbNe6G/p7r8z8WR/xhViUG1o/ZknfvpbVQgtd4zVt752ZX59GfNiyfY47Bq/Y/fmFfTVifKjVwNviDX3vc7Xw3uKTbLtrIqirlZowWan91vhUH95rP/hn5ucW/V57PHisSFoJIuKhtNwKbwrdGhsnuBMUEX9OWX1vDeVDPZSFKO4B/BvlAvpBsRdVv9eVbYs31p2ZxzX0ue9VlN9AWRDluCV925ty4T9d4pl51KTH1RYfpiwdt0vTuIF/pX4176Mpmc5R442rgbfVnXO6Wvgk2u6SEOkjmVKV6z0R1CVOOVVtJhM9fSSKNpZEz7jrXvS82uOhy7HSNT6NpGFbfBb2d3S8BWFTvM+6Z7ltakSPt5Rsi6/Uume57XngBHeCopwO8Nhcshx5RNyVcorEPWtiX65+rSvbFm+ru+5DYFCuT/hoh/hBlBVe68peDDxw6QflKDe+/j5lQjRq/ALKKWKD2n4E8I2GfneNP5ab98sodV9If+O+iPrVvE+r6h413rYaeFvdfa4W3lS2a3yabe8G/BWjJ0SOBx41YtnaZArMfGLgKsrCPTOX6Okar0sUbQyJnp7qfi7l9NxZ3N9TucVgW3za+5uOtyBsie9A2e591D3LbdeuyD/t/b0S657xtlf85NcJ7gRFWUDq3pl5w5LHFyYGt6mJnU5506kr2xZvq3sV8EoG3y7o3cCtOsSPoFyrUlf2SsoCNtcs6dsdKPeozA7xKykX0P96SbtBWdxqM8oqy33Evwn8RYe6r+lx3FdRv5r3cVXdo8bbVgNvq3tL+lstvKls1/g02/4uZRXkURMilwLbd0gy1V2iMIlEUJf444FbzWiip0v8VwxOiMx7oqdT25l5q5r4woTpWmZzf7e13SVpuJL39/nZ7RaETfHrcsCKvmOqe5bbvoGysNgGYbrfUrIt3nW1/2nVPcttb56ZAxcbbpscrwSuojxZHwFOioijWX8Vt/0oE6K62OHV76PG2+reG/hpZn53aYcj4mDK/eRGjX+wpezbgB9FxHGsv3r03sBbKH/YR42fBvw2M781oO0zKW/UfcWv7lj34T2O++00r9hNh3jbauBtdfe5WnhT2a7xabZ9ImUF6UHZynVw06qwdfGmWFvZoCy+U5es2bMl/njKGR6jlO0afyxwJ8q3uIvtUI0tO8S7lO0a34TybUtdMmQVzcmSLvGfr9S2I+JUBouq7LnM5v5uKzuz27zntq+N5pXls0P8xh7rnum26bbifpd419X+p1X3LLe9LiJ+ufRxbp4cr2hOcCcoM98REZ+nfLv24Orhi4BnZebpEXGfuhhAU9m2eFPdEfEhyhvboD7fNSK2HjVOuYajtmzV72Mpf8QWrvc4EXhtZl41jnhN2w+ri40pvnXXuvscd0TsRsOK3V3iEfGODnXXXuOTmc+si1Xxu3co2zU+zbafGREHMHpC5MgOZd8C/B+mlwjqEj+D2U30dIkfz8aZ6Ona9iNpnmy9jNnc321td0katsXP67Hurm2/i263IGyKPx94X091z3LbR9HfLSXb4m23nJzVume57V/TPLle0TxFeUqqSSGZeeVyYl3jfdbdtW1tKMq98RavinvpsPG2sjXtbZGZS7/tGku8z7ptO38d5ZThxQmPhYWgFhIitfEuZev6tRJEy63ZusT7rHuYuJYnIg4HjsjM7wyIfaJKJM3k/vZYqBcdb0HYFO+z7lluW/MhIt5Kwy0AM/PVU+jW2DjBnaCIuDPwTsq1YddQMsO3p5xC/F7gb2pir6GcalRXti0+bN2PBK4ec3yh7YFlc8nCV0u2108y8w/7iPdZ9zjaptzv7YPAHShZ1KAs9HA1ZdXsdQ3xfwb+tootXhToasqq2T9qaHteF0zYKNruMyHSZ3yabQ8yDwkP2x5f3Yuet3Dq++KJZO+3+bPtlXf7Q9uej7bndVzDxFc6T1GerE8B/0Q5NXghK7sJ5RSir1FOPRkUW1hFsa5sW7zPuju1HRHvrNlWAdwxIp7cIX7nmvg46u61bcrK1C/IzO+vF4x4EGXhrmyInwDsVVc2Io5saHuLiHhFh/i2NfFx1G3b9fHdGZDwiHIKcG1CpIr/E+X0y1HKvojqlDaWJFSGjA9Mxoyp7tZ4Q7LndMppnnW6xPus27Z7qDsitgAeQs2t+CKi9lZ8EdF4G78xxG17QNlsuP0hZUHDpuOhS7zPum17vuqe2bbnYfLrBHeyts3MTy1+oJr0HR0RRzXE3lL9Pmq8z7q7tv0p4OMMXsTm1h3jt6dcd9xH3X23fdulE1SAzPxeRNy2/Lc2vklL2bcD/0BZEXGpW3SMbw5s1VPdtl0f/yg9JURaynaNT7PtL0TEu9nQSk942PYIddfEFpxOuZ77UTn6bf7qynaN2/aAshHxdQYLYMuIeG+H+Kqa+Djqtu3Jtz2v42qN18SgfXI88zxFeYKirGJ8JWVRl8WrGR8APAH4Yk1sW8q3KHVl2+J91t217bsDB2TmBsv9R7nI/bIO8d8De/RUd99tf5aybY5i/e22P2U1z3UN8Z0o37TVld0DeGlm/rCm7Qs6xK8DHtJT3bZdH782M3ddGqviZ1MSInXx3+eA204MWbZrfJptr6Os4j4oafBySqKpLqnQFj8YeGtPddt2P22/ecDjUD4Ivh64gunc5q8tbtuDy07z9odd6rbtybc9r+Nqi38Q+PCAx4Py+fT2A2IrhhPcCareeJ8H7MP614wcS5mMPKcmdjjljb6ubFu8z7q7tr0n5X51vxiwvVZTvhkbNf584Lie6u617cw8OSIey4Dtlplfrp5XG2+J3RO4IjMvH9D2KkpWb9T4Q4Czeqrbtuvjr6e/hEhT2a7xaba9B/CEOUx42PZodW9H8wT4UODplMtyFh9L+1FWKF1VEzum+r2ubNe4bQ8uuzfwhhx8i8JzKe8Po8Z/Bzyyp7pte/Jtz+u42uLraJhcZ+a2Ax5fMZzgStIc6Csh0rXuWW2bch/NKzNz7YBtuZBUGDX+EGBNT3Xbdj9tf5aGCXBm7hwR92bwsXZ6U6yqo7e4bQ+MbU05s+W3DNAl3mfdtj35tud1XEO0/U0aJsdZ3cpzpXKCO0ERsSnlm859Wf8N+fOUa+gOqIkt/pZ0lHifdY+r7SdRblY/zvhC233U3WvbmXk9NSLisMw8aJR4l7K2vfLaljScKGe21E6Ac4jbrEnSStE2OV7pnOBOUER8knKrliO5+QbaO1EmQo+jLKowKLY15VS7urJt8T7rtu1+2n4hgwXwY+CPGuKnAn84YtmucduefNs/Bu4LvJbybcYqSgLlMkrC5JDq97r4+ykrDo9Stmt8FtreF9i+oewo8T7rtu0e2s7MqxlRRHwlMx+73Fjfcdu2bdue3bpnue154CrKk3X/zNxtyWMXAt+LstjK0knNQuwsgIaybfE+67btftpeC5xPmcAsyOr37VvidwJOHrFs17htT77t7SnXnH0TeHhmXgIQEXcEDqxi2RD/EeXaw1HKdo3PQtt7LYkdsKTsKPE+67btHtqOiKfRPLm+G4MFsDoi9qiJ7V4TG1fctm3btme37llue/ea2FxMfv0Gd4Ii4nuUVc0+nZnrqsduQbkn7L8Bf1kTewXlj21d2bZ4n3Xbdj9tb01ZeOAXLBHVqrkN8euBu49Ytmvctiff9gXAbzPznktjVfxMgIZ400rGbWW7xue17Xkd1zy3fR5lAnzkgAnwI6ufb8F6SaYFe1FueTUo9iBgs4ayXeO2bdu2Pbt1z3LbD6bc33upAL6YmTsMiK0cmenPhH6AXSj3P70MOKv6uax67E8bYndtKdsW77Nu2+6n7RcDf1xzHL20JX5Mh7Jd47Y9+bZfSrln3auAVYseXwW8Gji+JX5Fh7Jd4/Pa9ryOa57bPnPQ66t63pnAT4Fda+LXN8QuaCnbNW7btm3bs1v3LLe9cFbLCQN+fjeozEr68RTlCcrM8yLiYOB/WLLgUmaeERFX1MTOBWgo2xbvs27b7qftf42Ie0XEq9lwhch/qcrXxZ/eoWzXuG1Pvu1/iYiPAa8BvhUR21fxSymrBT+t+r0ufn/KNd+jlO0an9e253Vc89z2pyLiVZRvcC8FiLK68oGUD4ofBG7BYP/YEHsp5XKwvuK2bdu2Pbt1z3LbvwBekJlrlgainBm2onmK8gRVH073o9y37aLq4Z2qxy4G7lgTO5qSaakr2xbvs27b7qftdcAzq/9fuMz4/1KuCR2lrG2vvLaPzsxDqBERz83MI0aJdylr2xvXuFZ628DnKBPgfSjX4MLNE+BDMvOqvtreWLe5bdv2rLc9r+Oq4v8KvDczzxwQ2zczP1dXdkUY59fB/jT/UE5DveWAxzcDft8QW9NSti3eZ922bdu2Pd221yx9fMlzfjFqvEtZ2964xjXnbT93Ix23bdv2Rt32vI5riLYb3/NWwo+nKE/WOsq3POcveXwHyjd6dbF1HeN91m3btm3b0217XUScymABrGqJ71QTH6Zs1/i8tj2v45rbtmtiC94UES/vq+2NdZvbtm3PSNvzOq4u73tvAo5oiM88T1GeoIh4DPA+yjcyC+e33xm4B+VAem5N7CXV73Vl2+J91m3btm3b0237JZT7KT8auIr1BfBdYJOG+M8p1y+OUrZrfF7bntdxzXPblzNYALtR7ls+j+O2bdve2Nue13G1xdcAZ7ChAHbLzFsNiK0YfoM7QZn51YjYDdiT9ReKOSkzb4yId9TFAJrKtsX7rNu2bdu2p972F4EtMvMUloiIE4HfNcTP61C2a3xe257Xcc1z24+k+YPiV3pse2Pd5rZt27PQ9ryOqy1+A7A/9e95K5rf4EqSpI1aRBwOHJGZ3xkQ+0RmPnMK3ZKkXsz7e54TXEmSJEnSXKi7N5IkSZIkSSuKE1xJkiRJ0lxwgitJ0jJExMERkRFRu1BjROxVPWevRY+9LCKePEJ7u1dtbr2MMhu0L0nSxsAJriRJ4/cj4MHVvwteBix7ggvsDvw9MPQEt6Z9SZLmnrcJkiRpzDLzl8D3Jt1uRGxCWUByKu1LkjRtfoMrSdJo7h0RJ0TEbyPi4oh4c0TcAjY8Rbi63+FdgGdVj2dEfLSK7RYRn42IyyLi2oj4RUT8e0RsGhEHAkdU7a1ZVHaXqmxGxNsi4jURcS7we+APa06RPjEivhMRj4qIH1X9/mlEPGnpwCLiGRHxs6o/P4mIJ1blT1z0nC0i4l+q/l5X9f/4iLjXWLeyJEnL4De4kiSN5nPAR4B3AI8G/i+wDjh4wHOfBHwZ+PGi+Nrq3y8BVwEvBC4HdgQeR0lCfwl4K/AG4GnAhVWZixfVfSBwDvD/Ab8B/he4Q02f7w78c9Xny4FXAv8eEffKzLMBImJv4OPAscArgO2AfwJuDZy1qK73AE8EXgesAbYB/gTYsqZtSZJ65wRXkqTRfDgzD6n+f1xE3B54ZUT809InZub/RMR1wOWZedOpwxGxLXAPYJ/MPHZRkU9U/66NiJ9X/z9lYRK6RAB/npm/W1TvvWv6vC3wsMxcUz3vR5TJ8tOBt1fPeRNwOvCkzMzqeT8FTmb9Ce6DgY9n5uGLHvtsTbuSJE2EpyhLkjSaY5b8fjSwBfAHy6jjCsq3r4dExF9FxK4j9OOriye3LdYsTG4BMvMy4DLgznDTNbyrgU8vTG6r5/0QOHdJXScBB0bE6yJidVVWkqSpcoIrSdJoLq35fcdhK6gmkXtTvh19B3BWRJwTES9cRj8ubn/KTa4c8Nh1lNOPoXzDe0vKpHeppeN9KfAh4C8pk93LIuI9EXGbZfRHkqSxcoIrSdJoVtX8ftF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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], diff --git a/tutorials/quantum_simulation/Spin chain of 3 atoms in XY mode.ipynb b/tutorials/quantum_simulation/Spin chain of 3 atoms in XY mode.ipynb index 76df69e1..e87f3fb3 100644 --- a/tutorials/quantum_simulation/Spin chain of 3 atoms in XY mode.ipynb +++ b/tutorials/quantum_simulation/Spin chain of 3 atoms in XY mode.ipynb @@ -14,10 +14,10 @@ "We introduce here a new mode of interaction between the atoms driven by the dipole-dipole interaction. This mode is called the XY mode. The interaction hamiltonian of a system of $N$ qubits is now given by \n", "\n", "$$\n", - "H_{XY} = \\frac{1}{2}\\sum_{i<1| projector operator on site j.\"\"\"\n", " prod = [qutip.qeye(2) for _ in range(total_sites)]\n", - " prod[j] = (qutip.sigmaz() + qutip.qeye(2)) / 2\n", + " prod[j] = (qutip.qeye(2) - qutip.sigmaz()) / 2\n", " return qutip.tensor(prod)\n", "\n", "\n", - "magn = magnetization(0, 1)\n", + "excited = excitation(0, 1)\n", "plt.figure(figsize=[16, 6])\n", - "results.plot(magn)\n", + "results.plot(excited)\n", "plt.xlabel(\"Pulse duration (ns)\", fontsize=\"x-large\")\n", "plt.ylabel(\"Excitation of the atom\", fontsize=\"x-large\")\n", "plt.show()" @@ -174,9 +175,9 @@ "metadata": {}, "outputs": [], "source": [ - "magn_list = [magnetization(j, 3) for j in range(3)]\n", + "excited_list = [excitation(j, 3) for j in range(3)]\n", "\n", - "expectations = results.expect(magn_list)\n", + "expectations = results.expect(excited_list)\n", "\n", "plt.figure(figsize=[16, 18])\n", "plt.subplot(311)\n", @@ -214,7 +215,7 @@ "An external magnetic field can be added to the experiment, and will modify the hamiltonian. The XY Hamiltonian is then\n", "\n", "$$\n", - "H_{XY} = \\frac{1}{2}\\sum_{i Date: Fri, 22 Sep 2023 10:02:36 +0200 Subject: [PATCH 12/18] Use jobs order provided by the cloud (#583) --- pulser-core/pulser/backend/remote.py | 18 ++---------- pulser-pasqal/pulser_pasqal/pasqal_cloud.py | 31 +++------------------ pulser-pasqal/requirements.txt | 2 +- tests/test_backend.py | 4 +-- tests/test_pasqal.py | 12 +------- 5 files changed, 10 insertions(+), 57 deletions(-) diff --git a/pulser-core/pulser/backend/remote.py b/pulser-core/pulser/backend/remote.py index 39cbc504..f15af5d8 100644 --- a/pulser-core/pulser/backend/remote.py +++ b/pulser-core/pulser/backend/remote.py @@ -58,20 +58,12 @@ class RemoteResults(Results): the results. connection: The remote connection over which to get the submission's status and fetch the results. - jobs_order: An optional list of job IDs (as stored by the connection) - used to order the results. """ - def __init__( - self, - submission_id: str, - connection: RemoteConnection, - jobs_order: list[str] | None = None, - ): + def __init__(self, submission_id: str, connection: RemoteConnection): """Instantiates a new collection of remote results.""" self._submission_id = submission_id self._connection = connection - self._jobs_order = jobs_order @property def results(self) -> tuple[Result, ...]: @@ -87,9 +79,7 @@ def __getattr__(self, name: str) -> Any: status = self.get_status() if status == SubmissionStatus.DONE: self._results = tuple( - self._connection._fetch_result( - self._submission_id, self._jobs_order - ) + self._connection._fetch_result(self._submission_id) ) return self._results raise RemoteResultsError( @@ -112,9 +102,7 @@ def submit( pass @abstractmethod - def _fetch_result( - self, submission_id: str, jobs_order: list[str] | None - ) -> typing.Sequence[Result]: + def _fetch_result(self, submission_id: str) -> typing.Sequence[Result]: """Fetches the results of a completed submission.""" pass diff --git a/pulser-pasqal/pulser_pasqal/pasqal_cloud.py b/pulser-pasqal/pulser_pasqal/pasqal_cloud.py index 5d385f4e..b64592b8 100644 --- a/pulser-pasqal/pulser_pasqal/pasqal_cloud.py +++ b/pulser-pasqal/pulser_pasqal/pasqal_cloud.py @@ -143,23 +143,8 @@ def submit(self, sequence: Sequence, **kwargs: Any) -> RemoteResults: configuration=configuration, wait=False, ) - jobs_order = [] - if job_params: - for job_dict in job_params: - for job in batch.jobs.values(): - if ( - job.id not in jobs_order - and job_dict["runs"] == job.runs - and job_dict.get("variables", None) == job.variables - ): - jobs_order.append(job.id) - break - else: - raise RuntimeError( - f"Failed to find job ID for {job_dict}." - ) - - return RemoteResults(batch.id, self, jobs_order or None) + + return RemoteResults(batch.id, self) @backoff_decorator def fetch_available_devices(self) -> dict[str, Device]: @@ -170,9 +155,7 @@ def fetch_available_devices(self) -> dict[str, Device]: for name, dev_str in abstract_devices.items() } - def _fetch_result( - self, submission_id: str, jobs_order: list[str] | None - ) -> tuple[Result, ...]: + def _fetch_result(self, submission_id: str) -> tuple[Result, ...]: # For now, the results are always sampled results get_batch_fn = backoff_decorator(self._sdk_connection.get_batch) batch = get_batch_fn(id=submission_id) @@ -182,13 +165,7 @@ def _fetch_result( meas_basis = seq_builder.get_measurement_basis() results = [] - - jobs = ( - (batch.jobs[job_id] for job_id in jobs_order) - if jobs_order - else batch.jobs.values() - ) - for job in jobs: + for job in batch.ordered_jobs: vars = job.variables size: int | None = None if vars and "qubits" in vars: diff --git a/pulser-pasqal/requirements.txt b/pulser-pasqal/requirements.txt index 067102a0..495317ef 100644 --- a/pulser-pasqal/requirements.txt +++ b/pulser-pasqal/requirements.txt @@ -1,2 +1,2 @@ -pasqal-cloud ~= 0.3.3 +pasqal-cloud ~= 0.3.5 backoff ~= 2.2 \ No newline at end of file diff --git a/tests/test_backend.py b/tests/test_backend.py index 2e12cca7..b21cfd23 100644 --- a/tests/test_backend.py +++ b/tests/test_backend.py @@ -222,9 +222,7 @@ def __init__(self): def submit(self, sequence, **kwargs) -> RemoteResults: return RemoteResults("abcd", self) - def _fetch_result( - self, submission_id: str, jobs_order: list[str] | None - ) -> typing.Sequence[Result]: + def _fetch_result(self, submission_id: str) -> typing.Sequence[Result]: return ( SampledResult( ("q0", "q1"), diff --git a/tests/test_pasqal.py b/tests/test_pasqal.py index ca4b7279..84d57f5e 100644 --- a/tests/test_pasqal.py +++ b/tests/test_pasqal.py @@ -85,7 +85,7 @@ def mock_batch(mock_job, seq): class MockBatch: id = "abcd" status = "DONE" - jobs = {mock_job.id: mock_job} + ordered_jobs = [mock_job] sequence_builder = seq_.to_abstract_repr() return MockBatch() @@ -208,16 +208,6 @@ def test_submit(fixt, parametrized, emulator, seq, mock_job): ) ) - job_params[0]["runs"] = 1 - with pytest.raises(RuntimeError, match="Failed to find job ID"): - # Job runs don't match MockJob - fixt.pasqal_cloud.submit( - seq, - job_params=job_params, - emulator=emulator, - config=config, - ) - job_params[0]["runs"] = {10} with pytest.raises( TypeError, match="Object of type set is not JSON serializable" From c08dfa8c27959df01e6fcb828549173505f7795f Mon Sep 17 00:00:00 2001 From: Antoine Cornillot <61453516+a-corni@users.noreply.github.com> Date: Fri, 22 Sep 2023 11:50:01 +0200 Subject: [PATCH 13/18] Adding dmm config and modulation to sequence (#564) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Adding dmm config and modulation to sequence * Reverting changes for _SLMMask * Setting max_amp of dmm to zero * Fixing detection of virtual channels in Device * Reverting changes in serialization * Reverting SLM, modifying available_channels * deleting dmm of schedule if slm of xy, Fixing type * Add insert_slm_mask * fixing available_channels with slm * Special handling of samples from a DMM channel (#565) * Add `DetuningMap.get_qubit_weight_map()` * Define `_DMMSchedule.get_samples()` * Extract DMMSamples from a Sequence * Creating the `Traps` class * Eliminating the effects of the SLM mask * Use COORD_PRECISION in comparison * `Traps.coords` -> `Traps.sorted_coords` * Subclass `Traps` in `WeightMap` * Preserve effects of SLM mask in XY mode * Explicitly ask for labels in DetuningMap.draw() * Including slug in WeightMap * UTs for DetuningMap * Isort * Specialize pulse validation in DMM * Revamp test_dmm UTs * Formatting * Add support for legacy serializer * add in_ising * Add SLM pulse, ising, modif validate_channel * Add waiting_for_first_pulse, fixing mask time * Covering all code, modif after review * Add descr sequence, _config_detuning_map * Finishing UTs, fixing typos * Abstract representation support for new DMM features (#568) * Support for DMM channel serialization * WIP: Prepare for incoming updates to JSON schema * Add descr sequence, _config_detuning_map * Finishing UTs, fixing typos * de-/serializing det maps, adding schema, slug * Dev tests * Fixing doc --------- Co-authored-by: a_corni * Testing detuning of unmasked qubits, del print * Enabling use of add with slm * Replacing Modulate_det_map by add_dmm_detuning * Updating schema * finalizing replacing of modulate_detp_map * finalizing replacing of modulate_det_map * Rephrasing doc, add OpAddDmmDet * Handle parametrized sequence, switching device and DMM, and serialize config_det_map as an operation (#576) * Add slug description * Handle DMM & parametrized/switch_device/MapReg * Modifying schema, fixing type * Moving to a store decoration * Storing config_det_map * Taking into account review comments * Delete seq_tools * Testing MappableRegister, strict conversion * Replace modulate_det_map by add_dmm_detuning * Adding DMM notebook and Modifying SLM Mask (#569) * adding dmm, draw to DetuningMap * Testing avoiding circular import * Refactoring to avoid circular imports * Fix broken UTs * Import sorting * Fixing plot DetuningMap * Serialization/Deserialization of DMM in device * Fixing typos * Testing DMM and DetuningMap * Fixing typo * adding xfails, fixing type * Remove DMM from devices and finish UTs * Take into account review comments * Add annotations * Error in Global and Local * Defining _DMMSchedule * Fixing nits * Fixing typo * Creating DMM notebook, modif SLM notebook * Taking into account review comments * Fixing type * Fix labels in reg_drawer, draw det_maps in seq * Fixing doc build, add draw_detuning_maps to docs * Separating register/det_maps drawing from channels * introducing get_qubit_data * Add drawing of quantities per qubit * Fixing for local pulses * Adding bounds to label * Drawing legend for local targetting * FIX sampling rate, QutipEmulator * Updating figures * Updating SLM Mask & local addressability notebook * Adding explanation text * Fixing type * Replace modulate_det_map by add_dmm_detuning * Replace modulate_det_map for add_dmm_detuning * Fixing tests * Revert changes to Bayesian optimization notebook * Fixing docs * clearing outputs * Deleting scaling in favor extending to draw reg * Placing legend in lower part of drawing * Updating figures * Relaunching bayesian optimisation * Taking into account review comments * Printing sequence with DMM * Adding subscript and indent * Defining __str__ for DMM --------- Co-authored-by: HGSilveri --------- Co-authored-by: Henrique Silvério --- docs/source/index.rst | 1 + docs/source/tutorials/dmm.nblink | 3 + pulser-core/pulser/channels/base_channel.py | 3 +- pulser-core/pulser/channels/dmm.py | 67 +- pulser-core/pulser/devices/_device_datacls.py | 28 +- pulser-core/pulser/devices/_devices.py | 19 +- pulser-core/pulser/devices/_mock_device.py | 4 +- .../pulser/json/abstract_repr/deserializer.py | 41 +- .../abstract_repr/schemas/device-schema.json | 195 ++++++ .../schemas/sequence-schema.json | 133 ++++ .../pulser/json/abstract_repr/serializer.py | 29 +- pulser-core/pulser/json/supported.py | 3 +- pulser-core/pulser/register/_reg_drawer.py | 49 +- pulser-core/pulser/register/base_register.py | 6 +- pulser-core/pulser/register/mappable_reg.py | 7 +- .../pulser/register/register_layout.py | 145 +--- pulser-core/pulser/register/traps.py | 169 +++++ pulser-core/pulser/register/weight_maps.py | 112 ++- pulser-core/pulser/sampler/sampler.py | 14 +- pulser-core/pulser/sampler/samples.py | 34 +- pulser-core/pulser/sequence/_schedule.py | 39 +- pulser-core/pulser/sequence/_seq_drawer.py | 663 ++++++++++++++++-- pulser-core/pulser/sequence/_seq_str.py | 18 +- pulser-core/pulser/sequence/sequence.py | 443 ++++++++++-- .../pulser_simulation/simulation.py | 6 +- tests/conftest.py | 5 + tests/test_abstract_repr.py | 187 +++-- tests/test_channels.py | 2 +- tests/test_devices.py | 29 +- tests/test_dmm.py | 376 ++++++---- tests/test_json.py | 10 + tests/test_sequence.py | 576 ++++++++++++++- tests/test_sequence_sampler.py | 79 ++- tests/test_simulation.py | 284 +++++--- .../Local addressability with DMM.ipynb | 333 +++++++++ .../State Preparation with the SLM Mask.ipynb | 173 ++++- ... antiferromagnetic state preparation.ipynb | 56 +- .../Building 1D Rydberg Crystals.ipynb | 242 +++---- .../Shadow estimation for VQS.ipynb | 88 ++- 39 files changed, 3770 insertions(+), 901 deletions(-) create mode 100644 docs/source/tutorials/dmm.nblink create mode 100644 pulser-core/pulser/register/traps.py create mode 100644 tutorials/advanced_features/Local addressability with DMM.ipynb diff --git a/docs/source/index.rst b/docs/source/index.rst index e2bf8152..564f4ce8 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -87,6 +87,7 @@ computers and simulators, check the pages in :doc:`review`. tutorials/reg_layouts tutorials/interpolated_wfs tutorials/serialization + tutorials/dmm tutorials/slm_mask tutorials/output_mod_eom tutorials/virtual_devices diff --git a/docs/source/tutorials/dmm.nblink b/docs/source/tutorials/dmm.nblink new file mode 100644 index 00000000..61c75c01 --- /dev/null +++ b/docs/source/tutorials/dmm.nblink @@ -0,0 +1,3 @@ +{ + "path": "../../../tutorials/advanced_features/Local addressability with DMM.ipynb" +} diff --git a/pulser-core/pulser/channels/base_channel.py b/pulser-core/pulser/channels/base_channel.py index 2edd2b5f..6bd1dc33 100644 --- a/pulser-core/pulser/channels/base_channel.py +++ b/pulser-core/pulser/channels/base_channel.py @@ -117,6 +117,7 @@ def __post_init__(self) -> None: "min_avg_amp", ] non_negative = [ + "max_amp", "max_abs_detuning", "min_retarget_interval", "fixed_retarget_t", @@ -359,8 +360,6 @@ def validate_pulse(self, pulse: Pulse) -> None: Args: pulse: The pulse to validate. - channel_id: The channel ID used to index the chosen channel - on this device. """ if not isinstance(pulse, Pulse): raise TypeError( diff --git a/pulser-core/pulser/channels/dmm.py b/pulser-core/pulser/channels/dmm.py index 744fd2ee..8d88cf39 100644 --- a/pulser-core/pulser/channels/dmm.py +++ b/pulser-core/pulser/channels/dmm.py @@ -17,7 +17,10 @@ from dataclasses import dataclass, field from typing import Literal, Optional +import numpy as np + from pulser.channels.base_channel import Channel +from pulser.pulse import Pulse @dataclass(init=True, repr=False, frozen=True) @@ -50,11 +53,11 @@ class DMM(Channel): bottom_detuning: Optional[float] = field(default=None, init=True) addressing: Literal["Global"] = field(default="Global", init=False) - max_abs_detuning: Optional[float] = field(init=False, default=None) - max_amp: float = field(default=1e-16, init=False) # can't be 0 - min_retarget_interval: Optional[int] = field(init=False, default=None) - fixed_retarget_t: Optional[int] = field(init=False, default=None) - max_targets: Optional[int] = field(init=False, default=None) + max_abs_detuning: Optional[float] = field(default=None, init=False) + max_amp: float = field(default=0, init=False) + min_retarget_interval: Optional[int] = field(default=None, init=False) + fixed_retarget_t: Optional[int] = field(default=None, init=False) + max_targets: Optional[int] = field(default=None, init=False) def __post_init__(self) -> None: super().__post_init__() @@ -72,3 +75,57 @@ def _undefined_fields(self) -> list[str]: "max_duration", ] return [field for field in optional if getattr(self, field) is None] + + def validate_pulse(self, pulse: Pulse) -> None: + """Checks if a pulse can be executed in this DMM. + + Args: + pulse: The pulse to validate. + """ + super().validate_pulse(pulse) + round_detuning = np.round(pulse.detuning.samples, decimals=6) + if np.any(round_detuning > 0): + raise ValueError("The detuning in a DMM must not be positive.") + if self.bottom_detuning is not None and np.any( + round_detuning < self.bottom_detuning + ): + raise ValueError( + "The detuning goes below the bottom detuning " + f"of the DMM ({self.bottom_detuning} rad/µs)." + ) + + +def _dmm_id_from_name(dmm_name: str) -> str: + """Converts a dmm_name into a dmm_id. + + As a reminder the dmm_name is generated automatically from dmm_id + as dmm_id_{number of times dmm_id has been called}. + + Args: + dmm_name: The dmm_name to convert. + + Returns: + The associated dmm_id. + """ + return "_".join(dmm_name.split("_")[0:2]) + + +def _get_dmm_name(dmm_id: str, channels: list[str]) -> str: + """Get the dmm_name to add a dmm_id to a list of channels. + + Counts the number of channels starting by dmm_id, generates the + dmm_name as dmm_id_{number of times dmm_id has been called}. + + Args: + dmm_id: the id of the DMM to add to the list of channels. + channels: a list of channel names. + + Returns: + The associated dmm_name. + """ + dmm_count = len( + [key for key in channels if _dmm_id_from_name(key) == dmm_id] + ) + if dmm_count == 0: + return dmm_id + return dmm_id + f"_{dmm_count}" diff --git a/pulser-core/pulser/devices/_device_datacls.py b/pulser-core/pulser/devices/_device_datacls.py index 2dca543b..2cef6d0b 100644 --- a/pulser-core/pulser/devices/_device_datacls.py +++ b/pulser-core/pulser/devices/_device_datacls.py @@ -31,7 +31,8 @@ from pulser.json.utils import get_dataclass_defaults, obj_to_dict from pulser.register.base_register import BaseRegister, QubitId from pulser.register.mappable_reg import MappableRegister -from pulser.register.register_layout import COORD_PRECISION, RegisterLayout +from pulser.register.register_layout import RegisterLayout +from pulser.register.traps import COORD_PRECISION DIMENSIONS = Literal[2, 3] @@ -164,12 +165,10 @@ def type_check( for dmm_obj in self.dmm_objects: type_check("All DMM channels", DMM, value_override=dmm_obj) - # TODO: Check that device has dmm objects if it supports SLM mask - # once DMM is supported for serialization - # if self.supports_slm_mask and not self.dmm_objects: - # raise ValueError( - # "One DMM object should be defined to support SLM mask." - # ) + if self.supports_slm_mask and not self.dmm_objects: + raise ValueError( + "One DMM object should be defined to support SLM mask." + ) if self.channel_ids is not None: if not ( @@ -454,6 +453,9 @@ def _to_abstract_repr(self) -> dict[str, Any]: for p in ALWAYS_OPTIONAL_PARAMS: if params[p] == defaults[p]: params.pop(p, None) + # Delete parameters of PARAMS_WITH_ABSTR_REPR in params + for p in PARAMS_WITH_ABSTR_REPR: + params.pop(p, None) ch_list = [] for ch_name, ch_obj in self.channels.items(): ch_list.append(ch_obj._to_abstract_repr(ch_name)) @@ -462,12 +464,8 @@ def _to_abstract_repr(self) -> dict[str, Any]: dmm_list = [] for dmm_name, dmm_obj in self.dmm_channels.items(): dmm_list.append(dmm_obj._to_abstract_repr(dmm_name)) - # Add dmm channels if different than default - if "dmm_objects" in params: - params["dmm_channels"] = dmm_list - # Delete parameters of PARAMS_WITH_ABSTR_REPR in params - for p in PARAMS_WITH_ABSTR_REPR: - params.pop(p, None) + if dmm_list: + params["dmm_objects"] = dmm_list return params def to_abstract_repr(self) -> str: @@ -518,7 +516,7 @@ class Device(BaseDevice): def __post_init__(self) -> None: super().__post_init__() - for ch_id, ch_obj in self.channels.items(): + for ch_id, ch_obj in {**self.channels, **self.dmm_channels}.items(): if ch_obj.is_virtual(): _sep = "', '" raise ValueError( @@ -667,6 +665,8 @@ class VirtualDevice(BaseDevice): max_atom_num: int | None = None max_radial_distance: int | None = None supports_slm_mask: bool = True + # Needed to support SLM mask by default + dmm_objects: tuple[DMM, ...] = (DMM(),) reusable_channels: bool = True @property diff --git a/pulser-core/pulser/devices/_devices.py b/pulser-core/pulser/devices/_devices.py index bbfe8f6d..18a14e04 100644 --- a/pulser-core/pulser/devices/_devices.py +++ b/pulser-core/pulser/devices/_devices.py @@ -14,7 +14,7 @@ """Definitions of real devices.""" import numpy as np -from pulser.channels import Raman, Rydberg +from pulser.channels import DMM, Raman, Rydberg from pulser.channels.eom import RydbergBeam, RydbergEOM from pulser.devices._device_datacls import Device from pulser.register.special_layouts import TriangularLatticeLayout @@ -56,15 +56,14 @@ max_duration=2**26, ), ), - # TODO: Add DMM once it is supported for serialization - # dmm_objects=( - # DMM( - # clock_period=4, - # min_duration=16, - # max_duration=2**26, - # bottom_detuning=-20, - # ), - # ), + dmm_objects=( + DMM( + clock_period=4, + min_duration=16, + max_duration=2**26, + bottom_detuning=-20, + ), + ), ) IroiseMVP = Device( diff --git a/pulser-core/pulser/devices/_mock_device.py b/pulser-core/pulser/devices/_mock_device.py index 206d0455..f9092d7c 100644 --- a/pulser-core/pulser/devices/_mock_device.py +++ b/pulser-core/pulser/devices/_mock_device.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -from pulser.channels import Microwave, Raman, Rydberg +from pulser.channels import DMM, Microwave, Raman, Rydberg from pulser.devices._device_datacls import VirtualDevice MockDevice = VirtualDevice( @@ -31,5 +31,5 @@ Raman.Local(None, None, max_duration=None), Microwave.Global(None, None, max_duration=None), ), - # TODO: Add DMM once it is supported for serialization + dmm_objects=(DMM(),), ) diff --git a/pulser-core/pulser/json/abstract_repr/deserializer.py b/pulser-core/pulser/json/abstract_repr/deserializer.py index 9ce6f86b..e34111a5 100644 --- a/pulser-core/pulser/json/abstract_repr/deserializer.py +++ b/pulser-core/pulser/json/abstract_repr/deserializer.py @@ -23,7 +23,7 @@ import pulser import pulser.devices as devices -from pulser.channels import Microwave, Raman, Rydberg +from pulser.channels import DMM, Microwave, Raman, Rydberg from pulser.channels.base_channel import Channel from pulser.channels.eom import ( OPTIONAL_ABSTR_EOM_FIELDS, @@ -44,6 +44,7 @@ from pulser.register.mappable_reg import MappableRegister from pulser.register.register import Register from pulser.register.register_layout import RegisterLayout +from pulser.register.weight_maps import DetuningMap from pulser.waveforms import ( BlackmanWaveform, CompositeWaveform, @@ -281,14 +282,30 @@ def _deserialize_operation(seq: Sequence, op: dict, vars: dict) -> None: channel=op["channel"], correct_phase_drift=op.get("correct_phase_drift", False), ) + elif op["op"] == "add_dmm_detuning": + seq.add_dmm_detuning( + waveform=_deserialize_waveform(op["waveform"], vars), + dmm_name=op["dmm_name"], + protocol=op["protocol"], + ) + elif op["op"] == "config_slm_mask": + seq.config_slm_mask(qubits=op["qubits"], dmm_id=op["dmm_id"]) + elif op["op"] == "config_detuning_map": + seq.config_detuning_map( + detuning_map=_deserialize_det_map(op["detuning_map"]), + dmm_id=op["dmm_id"], + ) def _deserialize_channel(obj: dict[str, Any]) -> Channel: params: dict[str, Any] = {} channel_cls: Type[Channel] if obj["basis"] == "ground-rydberg": - channel_cls = Rydberg - params["eom_config"] = None + if "bottom_detuning" in obj: + channel_cls = DMM + else: + channel_cls = Rydberg + params["eom_config"] = None if obj["eom_config"] is not None: data = obj["eom_config"] try: @@ -352,9 +369,9 @@ def _deserialize_device_object(obj: dict[str, Any]) -> Device | VirtualDevice: params: dict[str, Any] = dict( channel_ids=tuple(ch_ids), channel_objects=tuple(ch_objs) ) - if "dmm_channels" in obj: + if "dmm_objects" in obj: params["dmm_objects"] = tuple( - _deserialize_channel(dmm_ch) for dmm_ch in obj["dmm_channels"] + _deserialize_channel(dmm_ch) for dmm_ch in obj["dmm_objects"] ) device_fields = dataclasses.fields(device_cls) device_defaults = get_dataclass_defaults(device_fields) @@ -379,6 +396,19 @@ def _deserialize_device_object(obj: dict[str, Any]) -> Device | VirtualDevice: raise AbstractReprError("Device deserialization failed.") from e +def _deserialize_det_map(ser_det_map: dict) -> DetuningMap: + trap_coords = [] + weights = [] + for trap in ser_det_map["traps"]: + trap_coords.append((trap["x"], trap["y"])) + weights.append(trap["weight"]) + return DetuningMap( + trap_coordinates=trap_coords, + weights=weights, + slug=ser_det_map.get("slug"), + ) + + def deserialize_abstract_sequence(obj_str: str) -> Sequence: """Deserialize a sequence from an abstract JSON object. @@ -433,6 +463,7 @@ def deserialize_abstract_sequence(obj_str: str) -> Sequence: # SLM Mask if "slm_mask_targets" in obj: + # This is kept for backwards compatibility seq.config_slm_mask(obj["slm_mask_targets"]) # Variables diff --git a/pulser-core/pulser/json/abstract_repr/schemas/device-schema.json b/pulser-core/pulser/json/abstract_repr/schemas/device-schema.json index f48833c5..80a63c3b 100644 --- a/pulser-core/pulser/json/abstract_repr/schemas/device-schema.json +++ b/pulser-core/pulser/json/abstract_repr/schemas/device-schema.json @@ -7,6 +7,100 @@ "description": "Hardware channel ID in the Device.", "type": "string" }, + "DMMChannel": { + "additionalProperties": false, + "description": "A DMM channel that can be physical or virtual.", + "properties": { + "addressing": { + "const": "Global", + "type": "string" + }, + "basis": { + "const": "ground-rydberg", + "description": "The addressed basis name.", + "type": "string" + }, + "bottom_detuning": { + "description": "Minimum possible detuning (in rad/µs), must be below zero.", + "type": [ + "number", + "null" + ] + }, + "clock_period": { + "description": "The duration of a clock cycle (in ns).", + "type": "number" + }, + "eom_config": { + "description": "Configuration of an associated EOM.", + "type": "null" + }, + "fixed_retarget_t": { + "description": "Time taken to change the target (in ns).", + "type": "null" + }, + "id": { + "$ref": "#/definitions/ChannelId", + "description": "The identifier of the channel within its device." + }, + "max_abs_detuning": { + "description": "Maximum possible detuning (in rad/µs), in absolute value.", + "type": "null" + }, + "max_amp": { + "const": 0, + "description": "Maximum pulse amplitude (in rad/µs).", + "type": "number" + }, + "max_duration": { + "description": "The longest duration an instruction can take.", + "type": [ + "number", + "null" + ] + }, + "max_targets": { + "description": "How many atoms can be locally addressed at once by the same beam.", + "type": "null" + }, + "min_avg_amp": { + "description": "The minimum average amplitude of a pulse (when not zero).", + "type": "number" + }, + "min_duration": { + "description": "The shortest duration an instruction can take.", + "type": "number" + }, + "min_retarget_interval": { + "description": "Minimum time required between the ends of two target instructions (in ns).", + "type": "null" + }, + "mod_bandwidth": { + "description": "The modulation bandwidth at -3dB (50% reduction), in MHz.", + "type": [ + "number", + "null" + ] + } + }, + "required": [ + "addressing", + "basis", + "bottom_detuning", + "clock_period", + "eom_config", + "fixed_retarget_t", + "id", + "max_abs_detuning", + "max_amp", + "max_duration", + "max_targets", + "min_duration", + "min_retarget_interval", + "mod_bandwidth" + ], + "type": "object" + }, "Device": { "anyOf": [ { @@ -30,6 +124,13 @@ ], "type": "number" }, + "dmm_objects": { + "description": "The DMM subclass instances specifying each channel in the device.", + "items": { + "$ref": "#/definitions/PhysicalDMMChannel" + }, + "type": "array" + }, "interaction_coeff_xy": { "description": "Coefficient setting the interaction stregth between atoms in different Rydberg states. Needed only if the device has a Microwave channel (otherwise can be null).", "type": [ @@ -134,6 +235,13 @@ ], "type": "number" }, + "dmm_objects": { + "description": "The DMM subclass instances specifying each channel in the device.", + "items": { + "$ref": "#/definitions/DMMChannel" + }, + "type": "array" + }, "interaction_coeff_xy": { "description": "Coefficient setting the interaction stregth between atoms in different Rydberg states. Needed only if the device has a Microwave channel (otherwise can be null).", "type": [ @@ -1314,6 +1422,93 @@ } ] }, + "PhysicalDMMChannel": { + "additionalProperties": false, + "properties": { + "addressing": { + "const": "Global", + "type": "string" + }, + "basis": { + "const": "ground-rydberg", + "description": "The addressed basis name.", + "type": "string" + }, + "bottom_detuning": { + "description": "Minimum possible detuning (in rad/µs), must be below zero.", + "type": "number" + }, + "clock_period": { + "description": "The duration of a clock cycle (in ns).", + "type": "number" + }, + "eom_config": { + "description": "Configuration of an associated EOM.", + "type": "null" + }, + "fixed_retarget_t": { + "description": "Time taken to change the target (in ns).", + "type": "null" + }, + "id": { + "$ref": "#/definitions/ChannelId", + "description": "The identifier of the channel within its device." + }, + "max_abs_detuning": { + "description": "Maximum possible detuning (in rad/µs), in absolute value.", + "type": "null" + }, + "max_amp": { + "const": 0, + "description": "Maximum pulse amplitude (in rad/µs).", + "type": "number" + }, + "max_duration": { + "description": "The longest duration an instruction can take.", + "type": "number" + }, + "max_targets": { + "description": "How many atoms can be locally addressed at once by the same beam.", + "type": "null" + }, + "min_avg_amp": { + "description": "The minimum average amplitude of a pulse (when not zero).", + "type": "number" + }, + "min_duration": { + "description": "The shortest duration an instruction can take.", + "type": "number" + }, + "min_retarget_interval": { + "description": "Minimum time required between the ends of two target instructions (in ns).", + "type": "null" + }, + "mod_bandwidth": { + "description": "The modulation bandwidth at -3dB (50% reduction), in MHz.", + "type": [ + "number", + "null" + ] + } + }, + "required": [ + "addressing", + "basis", + "bottom_detuning", + "clock_period", + "eom_config", + "fixed_retarget_t", + "id", + "max_abs_detuning", + "max_amp", + "max_duration", + "max_targets", + "min_duration", + "min_retarget_interval", + "mod_bandwidth" + ], + "type": "object" + }, "RydbergBeam": { "enum": [ "RED", diff --git a/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json b/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json index 21d0900c..96c42236 100644 --- a/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json +++ b/pulser-core/pulser/json/abstract_repr/schemas/sequence-schema.json @@ -397,6 +397,39 @@ ], "type": "object" }, + "OpAddDmmDet": { + "additionalProperties": false, + "properties": { + "dmm_name": { + "$ref": "#/definitions/ChannelName", + "description": "The name of the DMM." + }, + "op": { + "const": "add_dmm_detuning", + "type": "string" + }, + "protocol": { + "description": "Stipulates how to deal with eventual conflicts with other channels, specifically in terms of having multiple channels act on the same target simultaneously.\n\n- ``'min-delay'``: Before adding the pulse, introduces the smallest possible delay that avoids all exisiting conflicts.\n\n- ``'no-delay'``: Adds the pulse to the channel, regardless of existing conflicts.\n\n- ``'wait-for-all'``: Before adding the pulse, adds a delay that idles the channel until the end of the other channels' latest pulse.", + "enum": [ + "min-delay", + "no-delay", + "wait-for-all" + ], + "type": "string" + }, + "waveform": { + "$ref": "#/definitions/Waveform", + "description": "The waveform to add to the detuning of the DMM." + } + }, + "required": [ + "op", + "waveform", + "dmm_name", + "protocol" + ], + "type": "object" + }, "OpAlign": { "additionalProperties": false, "description": "Aligns multiple channels in time.\n\nIntroduces delays that align the provided channels with the one that finished the latest, such that the next action added to any of them will start right after the latest channel has finished.", @@ -418,6 +451,55 @@ ], "type": "object" }, + "OpConfigDetMap": { + "additionalProperties": false, + "properties": { + "detuning_map": { + "$ref": "#/definitions/WeightMap", + "description": "DetuningMap to associate with the DMM channel." + }, + "dmm_id": { + "$ref": "#/definitions/ChannelId", + "description": "ID of the DMM channel to configure." + }, + "op": { + "const": "config_detuning_map", + "type": "string" + } + }, + "required": [ + "op", + "detuning_map", + "dmm_id" + ], + "type": "object" + }, + "OpConfigSLM": { + "additionalProperties": false, + "properties": { + "dmm_id": { + "$ref": "#/definitions/ChannelId", + "description": "ID of the DMM channel to use for the SLM mask." + }, + "op": { + "const": "config_slm_mask", + "type": "string" + }, + "qubits": { + "description": "Qubit ID's to mask during the first global pulse of the sequence.", + "items": { + "$ref": "#/definitions/QubitId" + }, + "type": "array" + } + }, + "required": [ + "op", + "qubits", + "dmm_id" + ], + "type": "object" + }, "OpDelay": { "additionalProperties": false, "description": "Adds extra fixed delay before starting the pulse.", @@ -678,6 +760,15 @@ }, { "$ref": "#/definitions/OpEOMPulse" + }, + { + "$ref": "#/definitions/OpConfigSLM" + }, + { + "$ref": "#/definitions/OpConfigDetMap" + }, + { + "$ref": "#/definitions/OpAddDmmDet" } ], "description": "Sequence operation. All operations are performed in specified order." @@ -1017,6 +1108,48 @@ } ], "description": "Modulation waveform of any kind" + }, + "WeightMap": { + "additionalProperties": false, + "description": "Associates weights to trap coordinates. The sum of the provided weights must be equal to 1.", + "properties": { + "slug": { + "type": "string" + }, + "traps": { + "items": { + "$ref": "#/definitions/WeightedTrap" + }, + "type": "array" + } + }, + "required": [ + "traps" + ], + "type": "object" + }, + "WeightedTrap": { + "additionalProperties": false, + "properties": { + "weight": { + "description": "The weight on the site.", + "type": "number" + }, + "x": { + "description": "x-position in µm", + "type": "number" + }, + "y": { + "description": "y-position in µm", + "type": "number" + } + }, + "required": [ + "weight", + "x", + "y" + ], + "type": "object" } } } diff --git a/pulser-core/pulser/json/abstract_repr/serializer.py b/pulser-core/pulser/json/abstract_repr/serializer.py index ac5eb0ef..b5e2e07c 100644 --- a/pulser-core/pulser/json/abstract_repr/serializer.py +++ b/pulser-core/pulser/json/abstract_repr/serializer.py @@ -26,6 +26,7 @@ from pulser.json.abstract_repr.signatures import SIGNATURES from pulser.json.abstract_repr.validation import validate_abstract_repr from pulser.json.exceptions import AbstractReprError +from pulser.json.utils import stringify_qubit_ids if TYPE_CHECKING: from pulser.register.base_register import QubitId @@ -218,6 +219,15 @@ def remove_kwarg_if_default( "target": convert_targets(data["initial_target"]), } ) + elif call.name == "config_detuning_map": + data = get_all_args(("detuning_map", "dmm_id"), call) + operations.append( + { + "op": "config_detuning_map", + "detuning_map": data["detuning_map"], + "dmm_id": data["dmm_id"], + } + ) elif "target" in call.name: data = get_all_args(("qubits", "channel"), call) if call.name == "target": @@ -275,7 +285,21 @@ def remove_kwarg_if_default( elif call.name == "set_magnetic_field": res["magnetic_field"] = seq.magnetic_field.tolist() elif call.name == "config_slm_mask": - res["slm_mask_targets"] = tuple(seq._slm_mask_targets) + data = get_all_args(("qubits", "dmm_id"), call) + qubit_ids = stringify_qubit_ids(data["qubits"]) + if seq._in_xy and data["dmm_id"] == get_kwarg_default( + call.name, "dmm_id" + ): + # Use the old way in XY mode to preserve compatibility + res["slm_mask_targets"] = tuple(qubit_ids) + else: + operations.append( + { + "op": "config_slm_mask", + "qubits": qubit_ids, + "dmm_id": data["dmm_id"], + } + ) elif call.name == "enable_eom_mode": data = get_all_args( ( @@ -313,6 +337,9 @@ def remove_kwarg_if_default( data, call.name, "correct_phase_drift" ) operations.append({"op": "disable_eom_mode", **data}) + elif call.name == "add_dmm_detuning": + data = get_all_args(("waveform", "dmm_name", "protocol"), call) + operations.append({"op": "add_dmm_detuning", **data}) else: raise AbstractReprError(f"Unknown call '{call.name}'.") diff --git a/pulser-core/pulser/json/supported.py b/pulser-core/pulser/json/supported.py index 4824da63..9e7ad938 100644 --- a/pulser-core/pulser/json/supported.py +++ b/pulser-core/pulser/json/supported.py @@ -70,10 +70,11 @@ "TriangularLatticeLayout", ), "pulser.register.mappable_reg": ("MappableRegister",), + "pulser.register.weight_maps": ("DetuningMap",), "pulser.devices": tuple( [dev.name for dev in devices._valid_devices] + ["VirtualDevice"] ), - "pulser.channels": ("Rydberg", "Raman", "Microwave"), + "pulser.channels": ("Rydberg", "Raman", "Microwave", "DMM"), "pulser.channels.eom": ("BaseEOM", "RydbergEOM", "RydbergBeam"), "pulser.pulse": ("Pulse",), "pulser.waveforms": ( diff --git a/pulser-core/pulser/register/_reg_drawer.py b/pulser-core/pulser/register/_reg_drawer.py index 81a5cdea..638a1b3c 100644 --- a/pulser-core/pulser/register/_reg_drawer.py +++ b/pulser-core/pulser/register/_reg_drawer.py @@ -60,6 +60,7 @@ def _draw_2D( masked_qubits: set[QubitId] = set(), are_traps: bool = False, dmm_qubits: Mapping[QubitId, float] = {}, + label_name: str = "atoms", ) -> None: ordered_qubit_colors = RegDrawer._compute_ordered_qubit_colors( ids, qubit_colors @@ -68,9 +69,14 @@ def _draw_2D( ix, iy = plane if are_traps: - params = dict(s=50, edgecolors="black", facecolors="none") + params = dict( + s=50, + edgecolors="black", + facecolors="none", + label="traps", + ) else: - params = dict(s=30, c=ordered_qubit_colors) + params = dict(s=30, c=ordered_qubit_colors, label=label_name) ax.scatter(pos[:, ix], pos[:, iy], alpha=0.7, **params) @@ -93,15 +99,19 @@ def _draw_2D( if i in dmm_qubits.keys(): dmm_pos.append(c) dmm_arr = np.array(dmm_pos) + max_weight = max(dmm_qubits.values()) + alpha = ( + 0.2 * np.array(list(dmm_qubits.values())) / max_weight + if max_weight > 0 + else 0 + ) ax.scatter( dmm_arr[:, ix], dmm_arr[:, iy], marker="s", s=1200, - alpha=0.2 - * np.array(list(dmm_qubits.values())) - / max(dmm_qubits.values()), - c="black", + alpha=alpha, + c="black" if not qubit_colors else ordered_qubit_colors, ) axes = "xyz" @@ -115,6 +125,7 @@ def _draw_2D( # Determine which labels would overlap and merge those plot_pos = list(pos[:, (ix, iy)]) plot_ids: list[list[str]] = [[f"{i}"] for i in ids] + dmm_qubits = {str(q): w for q, w in dmm_qubits.items()} # Threshold distance between points epsilon = 1.0e-2 * np.diff(ax.get_xlim())[0] @@ -152,9 +163,7 @@ def _draw_2D( qubit_det = [] for q in plot_ids[i][j:]: extra_label = ( - f": {dmm_qubits[int(q)]:.2f}" - if not is_mask - else "" + f":{dmm_qubits[q]:.2f}" if not is_mask else "" ) qubit_det.append(q + extra_label) plot_ids[i][j:] = [", ".join(qubit_det)] @@ -215,6 +224,15 @@ def _draw_2D( # Only draw central axis lines when not drawing the graph ax.axvline(0, c="grey", alpha=0.5, linestyle=":") ax.axhline(0, c="grey", alpha=0.5, linestyle=":") + ax.legend( + loc="best", + bbox_to_anchor=(0.0, 0.0, 1.0, 0.3), + prop=dict(stretch="condensed", size=8), + handlelength=1.5, + handleheight=0.6, + handletextpad=0.1, + markerscale=0.8, + ) @staticmethod def _draw_3D( @@ -351,6 +369,7 @@ def _initialize_fig_axes( pos: np.ndarray, blockade_radius: Optional[float] = None, draw_half_radius: bool = False, + nregisters: int = 1, ) -> tuple[plt.figure.Figure, plt.axes.Axes]: """Creates the Figure and Axes for drawing the register.""" diffs = RegDrawer._register_dims( @@ -364,8 +383,12 @@ def _initialize_fig_axes( Ls = proportions * max( min(big_side / 4, 10), 4 ) # Figsize is, at most, (10,10), and, at least (4,*) or (*,4) - Ls[1] = max(Ls[1], 1.0) # Figsize height is at least 1 - fig, axes = plt.subplots(figsize=Ls, layout="constrained") + Ls[1] = max(Ls[1], 2.0 * nregisters) # Figsize height is at least 2 + fig, axes = plt.subplots( + nrows=nregisters, + figsize=Ls * nregisters, + layout="constrained", + ) return (fig, axes) @staticmethod @@ -373,6 +396,7 @@ def _initialize_fig_axes_projection( pos: np.ndarray, blockade_radius: Optional[float] = None, draw_half_radius: bool = False, + nregisters: int = 1, ) -> tuple[plt.figure.Figure, plt.axes.Axes]: """Creates the Figure and Axes for drawing the register projections.""" diffs = RegDrawer._register_dims( @@ -401,9 +425,10 @@ def _initialize_fig_axes_projection( fig_width = min(np.sum(widths), fig_height * 4) rescaling = 20 / max(max(fig_width, fig_height), 20) - figsize = (rescaling * fig_width, rescaling * fig_height) + figsize = (rescaling * fig_width, rescaling * fig_height * nregisters) fig, axes = plt.subplots( + nrows=nregisters, ncols=3, figsize=figsize, gridspec_kw=dict(width_ratios=widths), diff --git a/pulser-core/pulser/register/base_register.py b/pulser-core/pulser/register/base_register.py index 473b10a8..8552349e 100644 --- a/pulser-core/pulser/register/base_register.py +++ b/pulser-core/pulser/register/base_register.py @@ -206,7 +206,9 @@ def _validate_layout( ) def define_detuning_map( - self, detuning_weights: Mapping[QubitId, float] + self, + detuning_weights: Mapping[QubitId, float], + slug: str | None = None, ) -> DetuningMap: """Defines a DetuningMap for some qubits of the register. @@ -214,6 +216,7 @@ def define_detuning_map( detuning_weights: A mapping between the IDs of the targeted qubits and detuning weights (between 0 and 1, their sum must be equal to 1). + slug: An optional identifier for the detuning map. Returns: A DetuningMap associating detuning weights to the trap coordinates @@ -227,6 +230,7 @@ def define_detuning_map( return DetuningMap( [self.qubits[qubit_id] for qubit_id in detuning_weights], list(detuning_weights.values()), + slug, ) @abstractmethod diff --git a/pulser-core/pulser/register/mappable_reg.py b/pulser-core/pulser/register/mappable_reg.py index d11f5a06..4513493e 100644 --- a/pulser-core/pulser/register/mappable_reg.py +++ b/pulser-core/pulser/register/mappable_reg.py @@ -124,7 +124,9 @@ def find_indices(self, id_list: abcSequence[QubitId]) -> list[int]: return [self.qubit_ids.index(id) for id in id_list] def define_detuning_map( - self, detuning_weights: Mapping[int, float] + self, + detuning_weights: Mapping[int, float], + slug: str | None = None, ) -> DetuningMap: """Defines a DetuningMap for some trap ids of the register layout. @@ -132,12 +134,13 @@ def define_detuning_map( detuning_weights: A mapping between the IDs of the targeted traps and detuning weights (between 0 and 1, their sum must be equal to 1). + slug: An optional identifier for the detuning map. Returns: A DetuningMap associating detuning weights to the trap coordinates of the targeted traps. """ - return self._layout.define_detuning_map(detuning_weights) + return self._layout.define_detuning_map(detuning_weights, slug) def _to_dict(self) -> dict[str, Any]: return obj_to_dict(self, self._layout, *self._qubit_ids) diff --git a/pulser-core/pulser/register/register_layout.py b/pulser-core/pulser/register/register_layout.py index 22d0917b..5da293ae 100644 --- a/pulser-core/pulser/register/register_layout.py +++ b/pulser-core/pulser/register/register_layout.py @@ -15,17 +15,15 @@ from __future__ import annotations +import hashlib from collections.abc import Mapping from collections.abc import Sequence as abcSequence from dataclasses import dataclass -from functools import cached_property -from hashlib import sha256 from operator import itemgetter -from typing import Any, Optional, cast +from typing import Any, Optional import matplotlib.pyplot as plt import numpy as np -from numpy.typing import ArrayLike from pulser.json.utils import obj_to_dict from pulser.register._reg_drawer import RegDrawer @@ -33,13 +31,12 @@ from pulser.register.mappable_reg import MappableRegister from pulser.register.register import Register from pulser.register.register3d import Register3D +from pulser.register.traps import Traps from pulser.register.weight_maps import DetuningMap -COORD_PRECISION = 6 - @dataclass(init=False, repr=False, eq=False, frozen=True) -class RegisterLayout(RegDrawer): +class RegisterLayout(Traps, RegDrawer): """A layout of traps out of which registers can be defined. The traps are always sorted under the same convention: ascending order @@ -51,96 +48,10 @@ class RegisterLayout(RegDrawer): slug: An optional identifier for the layout. """ - _trap_coordinates: ArrayLike - slug: Optional[str] - - def __init__( - self, trap_coordinates: ArrayLike, slug: Optional[str] = None - ): - """Initializes a RegisterLayout.""" - array_type_error_msg = ValueError( - "'trap_coordinates' must be an array or list of coordinates." - ) - - try: - coords_arr = np.array(trap_coordinates, dtype=float) - except ValueError as e: - raise array_type_error_msg from e - - shape = coords_arr.shape - if len(shape) != 2: - raise array_type_error_msg - - if shape[1] not in (2, 3): - raise ValueError( - f"Each coordinate must be of size 2 or 3, not {shape[1]}." - ) - - if len(np.unique(trap_coordinates, axis=0)) != shape[0]: - raise ValueError( - "All trap coordinates of a register layout must be unique." - ) - - object.__setattr__(self, "_trap_coordinates", trap_coordinates) - object.__setattr__(self, "slug", slug) - - @property - def traps_dict(self) -> dict: - """Mapping between trap IDs and coordinates.""" - return dict(enumerate(self.coords)) - - @cached_property # Acts as an attribute in a frozen dataclass - def _coords(self) -> np.ndarray: - coords = np.array(self._trap_coordinates, dtype=float) - # Sorting the coordinates 1st left to right, 2nd bottom to top - rounded_coords = np.round(coords, decimals=COORD_PRECISION) - dims = rounded_coords.shape[1] - sorter = [rounded_coords[:, i] for i in range(dims - 1, -1, -1)] - sorting = np.lexsort(tuple(sorter)) - return cast(np.ndarray, rounded_coords[sorting]) - - @cached_property # Acts as an attribute in a frozen dataclass - def _coords_to_traps(self) -> dict[tuple[float, ...], int]: - return {tuple(coord): id for id, coord in self.traps_dict.items()} - @property def coords(self) -> np.ndarray: - """The sorted trap coordinates.""" - # Copies to prevent direct access to self._coords - return self._coords.copy() - - @property - def number_of_traps(self) -> int: - """The number of traps in the layout.""" - return len(self._coords) - - @property - def dimensionality(self) -> int: - """The dimensionality of the layout (2 or 3).""" - return self._coords.shape[1] - - def get_traps_from_coordinates(self, *coordinates: ArrayLike) -> list[int]: - """Finds the trap ID for a given set of trap coordinates. - - Args: - coordinates: The coordinates to return the trap IDs. - - Returns: - The list of trap IDs corresponding to the coordinates. - """ - traps = [] - rounded_coords = np.round( - np.array(coordinates), decimals=COORD_PRECISION - ) - for coord, rounded in zip(coordinates, rounded_coords): - key = tuple(rounded) - if key not in self._coords_to_traps: - raise ValueError( - f"The coordinate '{coord!s}' is not a part of the " - "RegisterLayout." - ) - traps.append(self._coords_to_traps[key]) - return traps + """A shorthand for 'sorted_coords'.""" + return self.sorted_coords def define_register( self, *trap_ids: int, qubit_ids: Optional[abcSequence[QubitId]] = None @@ -189,7 +100,9 @@ def define_register( return reg def define_detuning_map( - self, detuning_weights: Mapping[int, float] + self, + detuning_weights: Mapping[int, float], + slug: str | None = None, ) -> DetuningMap: """Defines a DetuningMap for some trap ids of the register layout. @@ -197,6 +110,7 @@ def define_detuning_map( detuning_weights: A mapping between the IDs of the targeted traps and detuning weights (between 0 and 1, their sum must be equal to 1). + slug: An optional identifier for the detuning map. Returns: A DetuningMap associating detuning weights to the trap coordinates @@ -205,11 +119,12 @@ def define_detuning_map( if not set(detuning_weights.keys()) <= set(self.traps_dict): raise ValueError( "The trap ids of detuning weights have to be integers" - f" between 0 and {self.number_of_traps}." + f" in [0, {self.number_of_traps-1}]." ) return DetuningMap( itemgetter(*detuning_weights.keys())(self.traps_dict), list(detuning_weights.values()), + slug, ) def draw( @@ -311,47 +226,25 @@ def make_mappable_register( qubit_ids = [f"{prefix}{i}" for i in range(n_qubits)] return MappableRegister(self, *qubit_ids) - def _safe_hash(self) -> bytes: - # Include dimensionality because the array is flattened with tobytes() - hash = sha256(bytes(self.dimensionality)) - hash.update(self.coords.tobytes()) - return hash.digest() - - def static_hash(self) -> str: - """Returns the layout's idempotent hash. - - Python's standard hash is not idempotent as it changes between - sessions. This hash can be used when an idempotent hash is - required. - - Returns: - str: An hexstring encoding the hash. - - Note: - This hash will be returned as an hexstring without - the '0x' prefix (unlike what is returned by 'hex()'). - """ - return self._safe_hash().hex() + @property + def _hash_object(self) -> hashlib._Hash: + return super()._hash_object def __eq__(self, other: Any) -> bool: - if not isinstance(other, RegisterLayout): - return False - return self._safe_hash() == other._safe_hash() - - def __hash__(self) -> int: - return hash(self._safe_hash()) + return super().__eq__(other) and isinstance(other, RegisterLayout) def __repr__(self) -> str: return f"RegisterLayout_{self._safe_hash().hex()}" - def __str__(self) -> str: - return self.slug or self.__repr__() + def __hash__(self) -> int: + return hash(self._safe_hash()) def _to_dict(self) -> dict[str, Any]: # Allows for serialization of subclasses without a special _to_dict() return obj_to_dict( self, self._trap_coordinates, + slug=self.slug, _module=__name__, _name="RegisterLayout", ) diff --git a/pulser-core/pulser/register/traps.py b/pulser-core/pulser/register/traps.py new file mode 100644 index 00000000..941e6db7 --- /dev/null +++ b/pulser-core/pulser/register/traps.py @@ -0,0 +1,169 @@ +# Copyright 2023 Pulser Development Team +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Defines a set of traps from their coordinates.""" +from __future__ import annotations + +import hashlib +from abc import ABC, abstractmethod +from dataclasses import dataclass +from functools import cached_property +from typing import Any, cast + +import numpy as np +from numpy.typing import ArrayLike + +COORD_PRECISION = 6 + + +@dataclass(init=False, eq=False, frozen=True) +class Traps(ABC): + """Defines a unique set of traps. + + The traps are always sorted under the same convention: ascending order + along x, then along y, then along z (if applicable). Respecting this order, + the traps are then numbered starting from 0. + + Args: + trap_coordinates: The coordinates of each trap. + """ + + _trap_coordinates: ArrayLike + slug: str | None + + def __init__(self, trap_coordinates: ArrayLike, slug: str | None = None): + """Initializes a RegisterLayout.""" + array_type_error_msg = ValueError( + "'trap_coordinates' must be an array or list of coordinates." + ) + + try: + coords_arr = np.array(trap_coordinates, dtype=float) + except ValueError as e: + raise array_type_error_msg from e + + shape = coords_arr.shape + if len(shape) != 2: + raise array_type_error_msg + + if shape[1] not in (2, 3): + raise ValueError( + f"Each coordinate must be of size 2 or 3, not {shape[1]}." + ) + + if len(np.unique(trap_coordinates, axis=0)) != shape[0]: + raise ValueError( + "All trap coordinates of a register layout must be unique." + ) + object.__setattr__(self, "_trap_coordinates", trap_coordinates) + object.__setattr__(self, "slug", slug) + + @property + def traps_dict(self) -> dict: + """Mapping between trap IDs and coordinates.""" + return dict(enumerate(self.sorted_coords)) + + def _calc_sorting_order(self) -> np.ndarray: + """Calculates the unique order that sorts the coordinates.""" + coords = np.array(self._trap_coordinates, dtype=float) + # Sorting the coordinates 1st left to right, 2nd bottom to top + rounded_coords = np.round(coords, decimals=COORD_PRECISION) + dims = rounded_coords.shape[1] + sorter = [rounded_coords[:, i] for i in range(dims - 1, -1, -1)] + sorting = np.lexsort(tuple(sorter)) + return cast(np.ndarray, sorting) + + @cached_property # Acts as an attribute in a frozen dataclass + def _coords(self) -> np.ndarray: + coords = np.array(self._trap_coordinates, dtype=float) + rounded_coords = np.round(coords, decimals=COORD_PRECISION) + sorting = self._calc_sorting_order() + return cast(np.ndarray, rounded_coords[sorting]) + + @cached_property # Acts as an attribute in a frozen dataclass + def _coords_to_traps(self) -> dict[tuple[float, ...], int]: + return {tuple(coord): id for id, coord in self.traps_dict.items()} + + @property + def sorted_coords(self) -> np.ndarray: + """The sorted trap coordinates.""" + # Copies to prevent direct access to self._coords + return self._coords.copy() + + @property + def number_of_traps(self) -> int: + """The number of traps in the layout.""" + return len(self._coords) + + @property + def dimensionality(self) -> int: + """The dimensionality of the layout (2 or 3).""" + return self._coords.shape[1] + + def get_traps_from_coordinates(self, *coordinates: ArrayLike) -> list[int]: + """Finds the trap ID for a given set of trap coordinates. + + Args: + coordinates: The coordinates to return the trap IDs. + + Returns: + The list of trap IDs corresponding to the coordinates. + """ + traps = [] + rounded_coords = np.round( + np.array(coordinates), decimals=COORD_PRECISION + ) + for coord, rounded in zip(coordinates, rounded_coords): + key = tuple(rounded) + if key not in self._coords_to_traps: + raise ValueError( + f"The coordinate '{coord!s}' is not a part of the " + "RegisterLayout." + ) + traps.append(self._coords_to_traps[key]) + return traps + + @property + @abstractmethod + def _hash_object(self) -> hashlib._Hash: + # Include dimensionality because the array is flattened with tobytes() + hash_ = hashlib.sha256(bytes(self.dimensionality)) + hash_.update(self.sorted_coords.tobytes()) + return hash_ + + def _safe_hash(self) -> bytes: + return self._hash_object.digest() + + def static_hash(self) -> str: + """Returns the idempotent hash. + + Python's standard hash is not idempotent as it changes between + sessions. This hash can be used when an idempotent hash is + required. + + Returns: + str: An hexstring encoding the hash. + + Note: + This hash will be returned as an hexstring without + the '0x' prefix (unlike what is returned by 'hex()'). + """ + return self._safe_hash().hex() + + def __eq__(self, other: Any) -> bool: + if not isinstance(other, Traps): + return False + return self._safe_hash() == other._safe_hash() + + def __str__(self) -> str: + return self.slug or self.__repr__() diff --git a/pulser-core/pulser/register/weight_maps.py b/pulser-core/pulser/register/weight_maps.py index 2e3e1fd2..5c93744d 100644 --- a/pulser-core/pulser/register/weight_maps.py +++ b/pulser-core/pulser/register/weight_maps.py @@ -15,19 +15,26 @@ from __future__ import annotations +import hashlib +import typing from dataclasses import dataclass -from typing import Optional, cast +from typing import TYPE_CHECKING, Any, Mapping, Optional, cast import matplotlib.pyplot as plt import numpy as np from matplotlib.axes import Axes from numpy.typing import ArrayLike +from pulser.json.utils import obj_to_dict from pulser.register._reg_drawer import RegDrawer +from pulser.register.traps import COORD_PRECISION, Traps +if TYPE_CHECKING: + from pulser.register.base_register import QubitId -@dataclass -class WeightMap(RegDrawer): + +@dataclass(init=False, repr=False, eq=False, frozen=True) +class WeightMap(Traps, RegDrawer): """Defines a generic map of weights on traps. The sum of the provided weights must be equal to 1. @@ -37,20 +44,54 @@ class WeightMap(RegDrawer): weights: A list weights to associate to the traps. """ - trap_coordinates: ArrayLike - weights: list[float] + weights: tuple[float, ...] - def __post_init__(self) -> None: - if len(cast(list, self.trap_coordinates)) != len(self.weights): + def __init__( + self, + trap_coordinates: ArrayLike, + weights: typing.Sequence[float], + slug: str | None = None, + ) -> None: + """Initializes a new weight map.""" + super().__init__(trap_coordinates, slug) + if len(cast(list, trap_coordinates)) != len(weights): raise ValueError("Number of traps and weights don't match.") - if not np.all(np.array(self.weights) >= 0): + if not np.all(np.array(weights) >= 0): raise ValueError("All weights must be non-negative.") - if not np.isclose(sum(self.weights), 1.0, atol=1e-16): + if not np.isclose(sum(weights), 1.0, atol=1e-16): raise ValueError("The sum of the weights should be 1.") + object.__setattr__(self, "weights", tuple(weights)) + + @property + def trap_coordinates(self) -> np.ndarray: + """The array of trap coordinates, in the order they were given.""" + return np.array(self._trap_coordinates) + + @property + def sorted_weights(self) -> np.ndarray: + """The weights sorted to match the sorted trap coordinates.""" + sorting = self._calc_sorting_order() + return cast(np.ndarray, np.array(self.weights)[sorting]) + + def get_qubit_weight_map( + self, qubits: Mapping[QubitId, np.ndarray] + ) -> dict[QubitId, float]: + """Creates a map between qubit IDs and the weight on their sites.""" + qubit_weight_map = {} + coords_arr = self.sorted_coords + weights_arr = self.sorted_weights + for qid, pos in qubits.items(): + dists = np.round( + np.linalg.norm(coords_arr - np.array(pos), axis=1), + decimals=COORD_PRECISION, + ) + matches = np.argwhere(dists == 0.0) + qubit_weight_map[qid] = float(np.sum(weights_arr[matches])) + return qubit_weight_map def draw( self, - with_labels: bool = True, + labels: typing.Sequence[QubitId] | None = None, fig_name: str | None = None, kwargs_savefig: dict = {}, custom_ax: Optional[Axes] = None, @@ -59,8 +100,8 @@ def draw( """Draws the detuning map. Args: - with_labels: If True, writes the qubit ID's - next to each qubit. + labels: If defined, writes the labels next to each site. Must have + the same length and order like the `trap_coordinates`. fig_name: The name on which to save the figure. If None the figure will not be saved. kwargs_savefig: Keywords arguments for @@ -74,16 +115,19 @@ def draw( combining this plot with other ones in a single figure, one may need to set this flag to False. """ - pos = np.array(self.trap_coordinates) + pos = self.trap_coordinates if custom_ax is None: _, custom_ax = self._initialize_fig_axes(pos) + labels_ = labels if labels is not None else list(range(len(pos))) + super()._draw_2D( custom_ax, pos, - [i for i, _ in enumerate(cast(list, self.trap_coordinates))], - with_labels=with_labels, - dmm_qubits=dict(enumerate(self.weights)), + labels_, + with_labels=labels is not None, + are_traps=True, + dmm_qubits=dict(zip(labels_, self.weights)), ) if fig_name is not None: @@ -92,8 +136,40 @@ def draw( if show: plt.show() + @property + def _hash_object(self) -> hashlib._Hash: + hash_ = super()._hash_object + # Include the weights and the type in the hash + hash_.update(self.sorted_weights.tobytes()) + hash_.update(type(self).__name__.encode()) + return hash_ + + def __repr__(self) -> str: + return f"{type(self).__name__}_{self._safe_hash().hex()}" + + def _to_dict(self) -> dict[str, Any]: + return obj_to_dict( + self, + trap_coordinates=self.trap_coordinates, + weights=self.weights, + slug=self.slug, + ) -@dataclass + def _to_abstract_repr(self) -> dict[str, Any]: + d: dict[str, Any] = dict( + traps=[ + {"weight": weight, "x": x, "y": y} + for weight, (x, y) in zip( + self.sorted_weights, self.sorted_coords + ) + ] + ) + if self.slug is not None: + d["slug"] = self.slug + return d + + +@dataclass(init=False, repr=False, eq=False, frozen=True) class DetuningMap(WeightMap): """Defines a DetuningMap. @@ -101,6 +177,6 @@ class DetuningMap(WeightMap): The sum of the provided weights must be equal to 1. Args: - trap_coordinates: an array containing the coordinates of the traps. + trap_coordinates: An array containing the coordinates of the traps. weights: A list of detuning weights to associate to the traps. """ diff --git a/pulser-core/pulser/sampler/sampler.py b/pulser-core/pulser/sampler/sampler.py index d528d6b1..6c5c6b2e 100644 --- a/pulser-core/pulser/sampler/sampler.py +++ b/pulser-core/pulser/sampler/sampler.py @@ -1,7 +1,7 @@ """The main function for sequence sampling.""" from __future__ import annotations -from typing import TYPE_CHECKING, Optional +from typing import TYPE_CHECKING, Any, Optional from pulser.sampler.samples import SequenceSamples, _SlmMask @@ -29,7 +29,17 @@ def sample( samples_list = [] for ch_schedule in seq._schedule.values(): - samples = ch_schedule.get_samples(IGNORE_DETUNED_DELAY_PHASE) + kwargs: dict[str, Any] = dict( + ignore_detuned_delay_phase=IGNORE_DETUNED_DELAY_PHASE + ) + if hasattr(ch_schedule, "detuning_map"): + if seq.is_register_mappable(): + raise NotImplementedError( + "Sequences with a DMM channel can't be sampled while " + "their register is mappable." + ) + kwargs["qubits"] = seq.register.qubits + samples = ch_schedule.get_samples(**kwargs) if extended_duration: samples = samples.extend_duration(extended_duration) if modulation: diff --git a/pulser-core/pulser/sampler/samples.py b/pulser-core/pulser/sampler/samples.py index 97f8abe1..ffca7d9c 100644 --- a/pulser-core/pulser/sampler/samples.py +++ b/pulser-core/pulser/sampler/samples.py @@ -11,6 +11,7 @@ from pulser.channels.base_channel import Channel from pulser.channels.eom import BaseEOM from pulser.register import QubitId +from pulser.register.weight_maps import DetuningMap from pulser.sequence._basis_ref import _QubitRef if TYPE_CHECKING: @@ -342,6 +343,17 @@ def masked(samples: np.ndarray, mask: np.ndarray) -> np.ndarray: return replace(self, **new_samples) +@dataclass +class DMMSamples(ChannelSamples): + """Gathers samples of a DMM channel.""" + + # TODO: Make these arguments KW_ONLY once python >= 3.10 + # Although these shouldn't have a default, in this way we can + # subclass ChannelSamples + detuning_map: DetuningMap | None = None + qubits: dict[QubitId, np.ndarray] = field(default_factory=dict) + + @dataclass class SequenceSamples: """Gather samples for each channel in a sequence.""" @@ -420,8 +432,18 @@ def to_nested_dict(self, all_local: bool = False) -> dict: ) addr = self._ch_objs[chname].addressing basis = self._ch_objs[chname].basis - if addr == _GLOBAL and not all_local: - start_t = self._slm_mask.end + is_dmm = isinstance(samples, DMMSamples) + in_xy = basis == "XY" + if is_dmm: + samples = cast(DMMSamples, samples) + det_map = cast(DetuningMap, samples.detuning_map) + det_weight_map = defaultdict( + int, det_map.get_qubit_weight_map(samples.qubits) + ) + else: + det_weight_map = defaultdict(lambda: 1.0) + if addr == _GLOBAL and not all_local and not is_dmm: + start_t = self._slm_mask.end if in_xy else 0 d[_GLOBAL][basis][_AMP][start_t:] += cs.amp[start_t:] d[_GLOBAL][basis][_DET][start_t:] += cs.det[start_t:] d[_GLOBAL][basis][_PHASE][start_t:] += cs.phase[start_t:] @@ -441,11 +463,13 @@ def to_nested_dict(self, all_local: bool = False) -> dict: for s in cs.slots: for t in s.targets: ti = s.ti - if t in self._slm_mask.targets: + if in_xy and t in self._slm_mask.targets: ti = max(ti, self._slm_mask.end) times = slice(ti, s.tf) d[_LOCAL][basis][t][_AMP][times] += cs.amp[times] - d[_LOCAL][basis][t][_DET][times] += cs.det[times] + d[_LOCAL][basis][t][_DET][times] += ( + cs.det[times] * det_weight_map[t] + ) d[_LOCAL][basis][t][_PHASE][times] += cs.phase[times] return _default_to_regular(d) @@ -459,5 +483,5 @@ def __repr__(self) -> str: # This is just to preserve backwards compatibility after the renaming of -# _TargetSlot to _PulseTarget slot +# _TargetSlot to _PulseTargetSlot _TargetSlot = _PulseTargetSlot diff --git a/pulser-core/pulser/sequence/_schedule.py b/pulser-core/pulser/sequence/_schedule.py index 5cfb8bc9..31edf0b1 100644 --- a/pulser-core/pulser/sequence/_schedule.py +++ b/pulser-core/pulser/sequence/_schedule.py @@ -16,16 +16,17 @@ import warnings from collections.abc import Iterator -from dataclasses import dataclass +from dataclasses import dataclass, fields from typing import Dict, NamedTuple, Optional, Union, cast, overload import numpy as np from pulser.channels.base_channel import Channel +from pulser.channels.dmm import DMM from pulser.pulse import Pulse from pulser.register.base_register import QubitId from pulser.register.weight_maps import DetuningMap -from pulser.sampler.samples import ChannelSamples, _PulseTargetSlot +from pulser.sampler.samples import ChannelSamples, DMMSamples, _PulseTargetSlot from pulser.waveforms import ConstantWaveform @@ -262,6 +263,32 @@ def __iter__(self) -> Iterator[_TimeSlot]: class _DMMSchedule(_ChannelSchedule): detuning_map: DetuningMap + def __post_init__(self) -> None: + super().__post_init__() + self._waiting_for_first_pulse: bool = False + + def get_samples( + self, + ignore_detuned_delay_phase: bool = True, + qubits: dict[QubitId, np.ndarray] | None = None, + ) -> DMMSamples: + ch_samples = super().get_samples( + ignore_detuned_delay_phase=ignore_detuned_delay_phase + ) + init_fields = { + f.name: getattr(ch_samples, f.name) + for f in fields(ch_samples) + if f.init + } + if qubits is None: + raise ValueError( + "'qubits' must be defined when extracting the samples of a" + " DMM channel." + ) + return DMMSamples( + **init_fields, detuning_map=self.detuning_map, qubits=qubits + ) + class _Schedule(Dict[str, _ChannelSchedule]): def __init__(self, max_duration: int | None = None): @@ -284,11 +311,15 @@ def find_slm_mask_times(self) -> list[int]: # Find tentative initial and final time of SLM mask if possible mask_time: list[int] = [] for ch_schedule in self.values(): - if ch_schedule.channel_obj.addressing != "Global": + if ch_schedule.channel_obj.addressing != "Global" or isinstance( + ch_schedule.channel_obj, DMM + ): continue # Cycle on slots in schedule until the first pulse is found for slot in ch_schedule: - if not isinstance(slot.type, Pulse): + if not isinstance( + slot.type, Pulse + ) or ch_schedule.is_detuned_delay(slot.type): continue ti = slot.ti tf = slot.tf diff --git a/pulser-core/pulser/sequence/_seq_drawer.py b/pulser-core/pulser/sequence/_seq_drawer.py index 536dc097..c123ce8e 100644 --- a/pulser-core/pulser/sequence/_seq_drawer.py +++ b/pulser-core/pulser/sequence/_seq_drawer.py @@ -14,6 +14,7 @@ from __future__ import annotations +import warnings from collections import defaultdict from dataclasses import dataclass, field from itertools import chain, combinations @@ -22,16 +23,19 @@ import matplotlib.pyplot as plt import numpy as np from matplotlib.axes import Axes +from matplotlib.colors import LinearSegmentedColormap from matplotlib.figure import Figure from scipy.interpolate import CubicSpline import pulser from pulser import Register, Register3D from pulser.channels.base_channel import Channel +from pulser.channels.dmm import DMM from pulser.pulse import Pulse from pulser.register.base_register import BaseRegister +from pulser.register.weight_maps import DetuningMap from pulser.sampler.sampler import sample -from pulser.sampler.samples import ChannelSamples, SequenceSamples +from pulser.sampler.samples import ChannelSamples, DMMSamples, SequenceSamples from pulser.waveforms import InterpolatedWaveform # Color scheme @@ -225,17 +229,254 @@ def gather_data( return data -def _draw_channel_content( +def gather_qubit_data( sampled_seq: SequenceSamples, + data: dict, register: Optional[BaseRegister] = None, + modulate: bool = False, +) -> list[dict[tuple, np.ndarray]]: + """Collects all the data per qubit for plotting. + + Args: + sampled_seq: The sampled sequence whose amplitude/detuning should + be displayed per qubit. + data: A dictionary associating ChannelDrawContents to channels. + register: The register associated with the sampled sequence. + modulate: Whether to gather the modulated amplitude/ + detuning using the modulation bandwidth of the channels. + + Returns: + A list of two dictionaries, associating an array of amplitude + (1st dict)/detuning (2nd dict) to tuple of qubits sharing same + amplitude/detuning. + """ + # Gathers all the targeted qubits + all_targets = ( + set().union( + *[ + set(target) + for ch, ch_data in data.items() + if ch not in ["measurement", "total_duration"] + for target in list(ch_data.target.values()) + ] + ) + if register is None + else set(register.qubit_ids) + ) + total_duration = data["total_duration"] + # Init: All the qubits are targeted by a pulse of zero amp/det + qubit_data: list[dict[tuple, np.ndarray]] = [ + { + tuple(all_targets): np.zeros(total_duration), + } + for _ in range(2) + ] + for ch, ch_data in data.items(): + # for each channel + if ch in ["measurement", "total_duration"]: + continue + # Associate a set of targets to a weight for each new target slot + for times, target in ch_data.target.items(): + y = ( + ch_data.get_input_curves() + if not modulate + else ch_data.get_output_curves(sampled_seq._ch_objs[ch]) + ) + weight_target_map: list[dict[float, set]] = [{} for _ in range(2)] + if isinstance(ch_data.samples, DMMSamples): + assert len(ch_data.target) == 1 + # DMM channel + # Defining targeted qubits + det_map = cast(DetuningMap, ch_data.samples.detuning_map) + det_weight_map = defaultdict( + int, + det_map.get_qubit_weight_map( + ch_data.samples.qubits + if not register + else register.qubits + ), + ) + # 0 amplitude on all qubits: + weight_target_map[0][0] = all_targets + # If zero detuning, equivalent to having zero weight + if np.all(0.0 == ch_data.samples.det): + weight_target_map[1][0] = all_targets + else: + # Regroup the qubits targeted by the same weight + for t, w in det_weight_map.items(): + if w not in weight_target_map[1]: + weight_target_map[1][w] = set() + weight_target_map[1][w].add(t) + else: + for i, samples in enumerate(y[:2]): + if np.all(samples == 0.0): + weight_target_map[i][0] = all_targets + continue + weight_target_map[i][1] = set(target) + weight_target_map[i][0] = all_targets - set(target) + + # Update qubit data + old_qubit_data = qubit_data.copy() + qubit_data = [{} for _ in range(2)] + for i, ch_samples in enumerate(y[:2]): # not interested in phase + for q, q_data in old_qubit_data[i].items(): + for w, set_t in weight_target_map[i].items(): + sub_target = set_t.intersection(set(q)) + if sub_target != set(): + pad_times = ( + 0 if times == "initial" else target[0], + 0 + if times == "initial" + else total_duration - target[1], + ) + qubit_data[i][tuple(sub_target)] = ( + w + * np.pad( + ch_samples[:total_duration], pad_times + ) + + q_data + ) + return qubit_data + + +def _draw_register_det_maps( + sampled_seq: SequenceSamples, + register: Optional[BaseRegister] = None, + draw_detuning_maps: bool = False, +) -> Figure | None: + fig_reg: Figure | None = None + det_maps = { + ch: cast(DetuningMap, cast(DMMSamples, ch_samples).detuning_map) + for (ch, ch_samples) in sampled_seq.channel_samples.items() + if isinstance(sampled_seq._ch_objs[ch], DMM) + } + n_det_maps = len(det_maps) + nregisters = ( + int(register is not None) + int(draw_detuning_maps) * n_det_maps + ) + # Draw masked register + if register: + pos = np.array(register._coords) + title = ( + "Register" + if sampled_seq._slm_mask.targets == set() + else "Masked register" + ) + if isinstance(register, Register3D): + labels = "xyz" + fig_reg, axes_reg = register._initialize_fig_axes_projection( + pos, + blockade_radius=35, + draw_half_radius=True, + nregisters=nregisters, + ) + + for ax_reg, (ix, iy) in zip( + axes_reg if nregisters == 1 else axes_reg[0], + combinations(np.arange(3), 2), + ): + register._draw_2D( + ax=ax_reg, + pos=pos, + ids=register._ids, + plane=(ix, iy), + masked_qubits=sampled_seq._slm_mask.targets, + ) + ax_reg.set_title( + title + + " projected onto\n the " + + labels[ix] + + labels[iy] + + "-plane" + ) + + elif isinstance(register, Register): + fig_reg, axes_reg = register._initialize_fig_axes( + pos, + blockade_radius=35, + draw_half_radius=True, + nregisters=nregisters, + ) + ax_reg = axes_reg if nregisters == 1 else axes_reg[0] + register._draw_2D( + ax=ax_reg, + pos=pos, + ids=register._ids, + masked_qubits=sampled_seq._slm_mask.targets, + ) + ax_reg.set_title(title, pad=10) + # Draw detuning maps + if draw_detuning_maps: + # Initialize figure for detuning maps if register was not shown + need_init = register is None + for i, (ch, det_map) in enumerate(det_maps.items()): + qubits = ( + register.qubits + if register + else cast(DMMSamples, sampled_seq.channel_samples[ch]).qubits + ) + reg_det_map = det_map.get_qubit_weight_map(qubits) + pos = np.array(list(qubits.values())) + if need_init: + if det_map.dimensionality == 3: + labels = "xyz" + ( + fig_reg, + axes_reg, + ) = det_map._initialize_fig_axes_projection( + pos, + nregisters=nregisters, + ) + else: + fig_reg, axes_reg = det_map._initialize_fig_axes( + pos, + nregisters=nregisters, + ) + need_init = False + ax_reg = ( + axes_reg + if nregisters == 1 + else axes_reg[i + int(register is not None)] + ) + if det_map.dimensionality == 3: + for sub_ax_reg, (ix, iy) in zip( + ax_reg, combinations(np.arange(3), 2) + ): + det_map._draw_2D( + ax=sub_ax_reg, + pos=pos, + ids=list(qubits.keys()), + plane=(ix, iy), + dmm_qubits=reg_det_map, + ) + sub_ax_reg.set_title( + f"{ch} projected onto\n the " + + labels[ix] + + labels[iy] + + "-plane" + ) + else: + det_map._draw_2D( + ax=ax_reg, + pos=pos, + ids=list(qubits.keys()), + dmm_qubits=reg_det_map, + ) + ax_reg.set_title(ch, pad=10) + return fig_reg + + +def _draw_channel_content( + sampled_seq: SequenceSamples, sampling_rate: Optional[float] = None, draw_phase_area: bool = False, draw_phase_shifts: bool = False, draw_input: bool = True, draw_modulation: bool = False, draw_phase_curve: bool = False, + draw_detuning_maps: bool = False, shown_duration: Optional[int] = None, -) -> tuple[Figure | None, Figure, Any, dict]: +) -> tuple[Figure, Any, dict]: """Draws samples of a sequence. Args: @@ -258,6 +499,9 @@ def _draw_channel_content( is skipped unless 'draw_input=False'. draw_phase_curve: Draws the changes in phase in its own curve (ignored if the phase doesn't change throughout the channel). + draw_detuning_maps: Draws the detuning maps applied on the qubits of + the register of the sequence. Shown before the pulse sequence, + defaults to False. shown_duration: Total duration to be shown in the X axis. """ @@ -271,11 +515,8 @@ def phase_str(phi: float) -> str: else: return rf"{value:.2g}$\pi$" - n_channels = len(sampled_seq.channels) - if not n_channels: - raise RuntimeError("Can't draw an empty sequence.") - data = gather_data(sampled_seq, shown_duration) + n_channels = len(sampled_seq.channels) total_duration = data["total_duration"] time_scale = 1e3 if total_duration > 1e4 else 1 for ch in sampled_seq.channels: @@ -291,49 +532,6 @@ def phase_str(phi: float) -> str: slm_box = dict(boxstyle="round", alpha=0.4, facecolor="grey", hatch="//") eom_box = dict(boxstyle="round", facecolor="lightsteelblue") - # Draw masked register - if register: - pos = np.array(register._coords) - if isinstance(register, Register3D): - labels = "xyz" - fig_reg, axes_reg = register._initialize_fig_axes_projection( - pos, - blockade_radius=35, - draw_half_radius=True, - ) - fig_reg.get_layout_engine().set(w_pad=6.5) - - for ax_reg, (ix, iy) in zip( - axes_reg, combinations(np.arange(3), 2) - ): - register._draw_2D( - ax=ax_reg, - pos=pos, - ids=register._ids, - plane=(ix, iy), - masked_qubits=sampled_seq._slm_mask.targets, - ) - ax_reg.set_title( - "Masked register projected onto\n the " - + labels[ix] - + labels[iy] - + "-plane" - ) - - elif isinstance(register, Register): - fig_reg, ax_reg = register._initialize_fig_axes( - pos, - blockade_radius=35, - draw_half_radius=True, - ) - register._draw_2D( - ax=ax_reg, - pos=pos, - ids=register._ids, - masked_qubits=sampled_seq._slm_mask.targets, - ) - ax_reg.set_title("Masked register", pad=10) - ratios = [ SIZE_PER_WIDTH[data[ch].n_axes_on] for ch in sampled_seq.channels ] @@ -513,7 +711,11 @@ def phase_str(phi: float) -> str: for coords in ch_data.target: targets = list(ch_data.target[coords]) tgt_strs = [str(q) for q in targets] - tgt_txt_y = max_amp * 1.1 - 0.25 * (len(targets) - 1) + if isinstance(ch_obj, DMM): + tgt_strs = ["⚄"] + elif ch_obj.addressing == "Global": + tgt_strs = ["GLOBAL"] + tgt_txt_y = max_amp * 1.1 - 0.25 * (len(tgt_strs) - 1) tgt_str = "\n".join(tgt_strs) if coords == "initial": x = t_min + final_t * 0.005 @@ -522,9 +724,9 @@ def phase_str(phi: float) -> str: axes[0].text( x, amp_top * 0.98, - "GLOBAL", - fontsize=13, - rotation=90, + tgt_strs[0], + fontsize=13 if tgt_strs == ["GLOBAL"] else 17, + rotation=90 if tgt_strs == ["GLOBAL"] else 0, ha="left", va="top", bbox=q_box, @@ -682,8 +884,276 @@ def phase_str(phi: float) -> str: ax.axhline(ax_lims[i][1], **hline_kwargs) if ax_lims[i][0] < 0: ax.axhline(0, **hline_kwargs) + return (fig, ch_axes, data) + + +def _draw_qubit_content( + sampled_seq: SequenceSamples, + data: dict, + register: Optional[BaseRegister] = None, + draw_input: bool = True, + draw_modulation: bool = False, + draw_qubit_amp: bool = False, + draw_qubit_det: bool = True, +) -> tuple[Figure | None, Figure | None]: + """Gets information to plot per qubits. - return (fig_reg if register else None, fig, ch_axes, data) + Draws the amplitude and detuning seen locally by each qubit. + + Args: + sampled_seq: The sampled sequence whose amplitude/detuning should + be displayed per qubit. + data: A dictionary associating ChannelDrawContents to channels. + register: The register associated with the sampled sequence. + draw_input: Whether to draw to input of the amplitude/detuning. + draw_qubit_modulation: Whether to draw the modulated amplitude/ + detuning using the modulation bandwidth of the channels. + draw_qubit_amp: Whether to draw the amplitude per qubit or not. + draw_qubit_det: Whether to draw the detuning per qubit or not. + + Returns: + A figure displaying the amplitude/detuning seen by the atoms locally. + The atoms having same amplitude/detuning are grouped together. If a + register is provided, these groups of atoms are displayed in space in + a second figure. + """ + # Show nothing if no drawing per qubit asked + if not draw_qubit_det and not draw_qubit_amp: + return (None, None) + # Or if a channel is not in the ground-rydberg basis + elif not np.all( + [ + ch_obj.basis == "ground-rydberg" + for ch, ch_obj in sampled_seq._ch_objs.items() + ] + ): + raise NotImplementedError( + "Can only draw qubit contents for channels in rydberg basis." + ) + # Gather data per targeted qubits + total_duration = data["total_duration"] + draw_data = {"input": draw_input, "modulated": draw_modulation} + n_data = sum(list(draw_data.values())) + qubit_data = [ + gather_qubit_data( + sampled_seq, data, register, (data_name == "modulated") + ) + if to_draw + else None + for data_name, to_draw in draw_data.items() + ] + # Figure composed of 2 subplots (input, modulated) each composed + # of 2 subplots (amplitude, detuning) + draw_quantities = [draw_qubit_amp, draw_qubit_det] + n_quantities = sum(draw_quantities) + ratios = [SIZE_PER_WIDTH[n_quantities]] * n_data + fig = plt.figure( + constrained_layout=False, + figsize=(20, sum(ratios)), + ) + gs = fig.add_gridspec(n_data, 1, hspace=0.075, height_ratios=ratios) + + fig.suptitle("Quantities per qubit over time", fontsize=16) + cmap = LinearSegmentedColormap.from_list("", COLORS) + hline_kwargs = dict(linestyle="-", linewidth=0.5, color="grey") + max_targets = 20 # maximum number of targets shown in legend + # If qubits can be defined, another figure is added to display legend + dmm_samples: list[DMMSamples] = [ + cast(DMMSamples, sampled_seq.channel_samples[ch]) + for ch in sampled_seq.channels + if isinstance(sampled_seq.channel_samples[ch], DMMSamples) + ] + qubits: None | dict = None + if register: + qubits = register.qubits + elif dmm_samples: + qubits = dmm_samples[0].qubits + else: + warnings.warn( + "Provide a register and select draw_register for a more" + "visible representation", + UserWarning, + ) + fig_legend: None | Figure = None + axes_legend: None | Axes = None + dimensionality_3d: bool | None = None + if register or dmm_samples: + dimensionality_3d = isinstance(register, Register3D) or ( + dmm_samples != [] + and cast(DetuningMap, dmm_samples[0].detuning_map).dimensionality + == 3 + ) + if dimensionality_3d: + labels = "xyz" + ( + fig_legend, + axes_legend, + ) = Register._initialize_fig_axes_projection( + np.array(list(cast(dict, qubits).values())), + nregisters=n_quantities, + ) + else: + (fig_legend, axes_legend) = Register._initialize_fig_axes( + np.array(list(cast(dict, qubits).values())), + nregisters=n_quantities, + ) + # The time axis of all channels is the same + time_scale = 1e3 if total_duration > 1e4 else 1 + time = np.arange(total_duration) / time_scale + final_t = time[-1] + t_min = -final_t * 0.03 + t_max = final_t * 1.05 + # Draw mode (input/modulated/both) + plot_index = 0 + for data_index, (data_name, to_draw) in enumerate(draw_data.items()): + if not to_draw: + continue + assert qubit_data[data_index] is not None + # Define plot + gs_ = gs[plot_index] + ax = fig.add_subplot(gs_) + for side in ("top", "bottom", "left", "right"): + ax.spines[side].set_color("none") + ax.tick_params( + labelcolor="w", top=False, bottom=False, left=False, right=False + ) + ax.set_ylabel(data_name, labelpad=40, fontsize=18) + subgs = gs_.subgridspec(n_quantities, 1, hspace=0.0) + axes = [fig.add_subplot(subgs[i, :]) for i in range(n_quantities)] + # Draw quantity (amplitude/detuning/both) + subplot_index = 0 + for i, draw_qty in enumerate(draw_quantities): + if not draw_qty: + continue + # Define subplot + sub_ax = axes[subplot_index] + sub_ax.axvline(0, linestyle="--", linewidth=0.5, color="grey") + if subplot_index > 0: + sub_ax.spines["top"].set_visible(False) + if subplot_index < n_quantities - 1: + sub_ax.spines["bottom"].set_visible(False) + if plot_index < n_data - 1 or subplot_index < n_quantities - 1: + sub_ax.tick_params( + axis="x", + which="both", + bottom=True, + top=False, + labelbottom=False, + direction="in", + ) + else: + unit = "ns" if time_scale == 1 else r"$\mu s$" + sub_ax.set_xlabel(f"t ({unit})", fontsize=12) + # Define the y axis + max_val = np.max( + [ + local_data + for local_data in list( + cast(list, qubit_data[data_index])[i].values() + ) + ] + ) + min_val = np.min( + [ + local_data + for local_data in list( + cast(list, qubit_data[data_index])[i].values() + ) + ] + ) + if i == 0: + max_val = 1 if max_val == 0 else max_val + max_val = max_val * 1.2 + min_val = min(min_val, 0.0) + elif i == 1: + # Makes sure that [-1, 1] range is always represented + max_val = max(max_val, 1) + min_val = min(min_val, -1) + range_val = max_val - min_val + max_val = max_val + range_val * 0.15 + min_val = min_val - range_val * 0.05 + sub_ax.set_xlim(t_min, t_max) + sub_ax.set_ylim(min_val, max_val) + # Plot one curve per target + nb_targets = len(cast(list, qubit_data[data_index])[i]) + for target_index, (target, q_data) in enumerate( + cast(list, qubit_data[data_index])[i].items() + ): + # label is simpler if qubits are defined + label: str = "" + if qubits: + label = f"targets_{target_index}" + else: + for label_index in range(0, len(target), max_targets): + sub_target = map( + str, + target[label_index : label_index + max_targets], + ) + label += ",".join(sub_target) + "\n" + # Add curve + color = cmap(target_index / nb_targets) + sub_ax.plot( + time, + q_data, + label=label, + color=color, + linewidth=0.8, + linestyle="--" if data_name == "modulated" else "-", + ) + # Add targets to legend if qubits are defined + if plot_index == 0 and qubits: + ax_leg = ( + axes_legend + if n_quantities == 1 + else cast(list, axes_legend)[subplot_index] + ) + targeted_atoms = {t: qubits[t] for t in target} + pos = np.array(list(targeted_atoms.values())) + if dimensionality_3d: + for sub_ax_leg, (ix, iy) in zip( + ax_leg, combinations(np.arange(3), 2) + ): + Register._draw_2D( + ax=sub_ax_leg, + pos=pos, + ids=list(targeted_atoms.keys()), + plane=(ix, iy), + qubit_colors={t: color for t in target}, + masked_qubits=set(target), + label_name=label, + ) + if target_index == 0: + sub_ax_leg.set_title( + f"{LABELS[i]} projected onto\n the " + + labels[ix] + + labels[iy] + + "-plane" + ) + else: + Register._draw_2D( + ax=ax_leg, + pos=pos, + ids=list(targeted_atoms.keys()), + qubit_colors={t: color for t in target}, + masked_qubits=set(target), + label_name=label, + ) + if target_index == 0: + ax_leg.set_title( + f"Targeted atoms for {LABELS[i][:8]}", pad=10 + ) + sub_ax.set_ylabel(LABELS[i], fontsize=14) + # Show legend only if qubits can't be defined + sub_ax.legend() + + if subplot_index > 0: + sub_ax.axhline(max_val, **hline_kwargs) + if min_val < 0: + sub_ax.axhline(0, **hline_kwargs) + subplot_index += 1 + plot_index += 1 + + return fig, fig_legend def draw_samples( @@ -693,7 +1163,10 @@ def draw_samples( draw_phase_area: bool = False, draw_phase_shifts: bool = False, draw_phase_curve: bool = False, -) -> tuple[Figure | None, Figure]: + draw_detuning_maps: bool = False, + draw_qubit_amp: bool = False, + draw_qubit_det: bool = False, +) -> tuple[Figure | None, Figure, Figure | None, Figure | None]: """Draws a SequenceSamples. Args: @@ -711,15 +1184,27 @@ def draw_samples( should be added to the plot, defaults to False. draw_phase_curve: Draws the changes in phase in its own curve (ignored if the phase doesn't change throughout the channel). + draw_detuning_maps: Whether to draw the detuning maps applied on the + qubits of the provided register. Shown before the samples, + defaults to False. + draw_qubit_amp: Draws the amplitude seen by the qubits locally after + the drawing of the sequence. + draw_qubit_det: Draws the detuning seen by the qubits locally after + the drawing of the sequence. """ + if not len(sampled_seq.channels): + raise RuntimeError("Can't draw an empty sequence.") slot_tfs = [ ch_samples.slots[-1].tf for ch_samples in sampled_seq.channel_samples.values() ] max_slot_tf = max(slot_tfs) if len(slot_tfs) > 0 else None - (fig_reg, fig, ch_axes, data) = _draw_channel_content( + # Draw register and detuning maps + fig_reg = _draw_register_det_maps( + sampled_seq, register, draw_detuning_maps + ) + (fig, ch_axes, data) = _draw_channel_content( sampled_seq, - register, sampling_rate, draw_phase_area, draw_phase_shifts, @@ -728,8 +1213,16 @@ def draw_samples( draw_phase_curve=draw_phase_curve, shown_duration=max_slot_tf, ) - - return (fig_reg, fig) + (fig_qubit, fig_legend) = _draw_qubit_content( + sampled_seq, + data, + register, + draw_input=True, + draw_modulation=False, + draw_qubit_amp=draw_qubit_amp, + draw_qubit_det=draw_qubit_det, + ) + return (fig_reg, fig, fig_qubit, fig_legend) def draw_sequence( @@ -742,7 +1235,10 @@ def draw_sequence( draw_input: bool = True, draw_modulation: bool = False, draw_phase_curve: bool = False, -) -> tuple[Figure | None, Figure]: + draw_detuning_maps: bool = False, + draw_qubit_amp: bool = False, + draw_qubit_det: bool = False, +) -> tuple[Figure | None, Figure, Figure | None, Figure | None]: """Draws the entire sequence. Args: @@ -768,23 +1264,60 @@ def draw_sequence( is skipped unless 'draw_input=False'. draw_phase_curve: Draws the changes in phase in its own curve (ignored if the phase doesn't change throughout the channel). + draw_detuning_maps: Whether to draw the detuning maps applied on the + qubits of the register of the sequence. Shown before the pulse + sequence, defaults to False. + draw_qubit_amp: Draws the amplitude seen by the qubits locally after + the drawing of the sequence. + draw_qubit_det: Draws the detuning seen by the qubits locally after + the drawing of the sequence. """ # Sample the sequence and get the data to plot shown_duration = seq.get_duration(include_fall_time=draw_modulation) sampled_seq = sample(seq) - - (fig_reg, fig, ch_axes, data) = _draw_channel_content( + if not len(sampled_seq.channels): + raise RuntimeError("Can't draw an empty sequence.") + # Draw register and detuning maps + fig_reg = _draw_register_det_maps( sampled_seq, seq.register if draw_register else None, + draw_detuning_maps, + ) + (fig, ch_axes, data) = _draw_channel_content( + sampled_seq, sampling_rate, draw_phase_area, draw_phase_shifts, draw_input, draw_modulation, draw_phase_curve, + draw_detuning_maps, shown_duration, ) - + draw_output = draw_modulation + for ch_obj in list(seq.declared_channels.values()): + draw_output = draw_output and ch_obj.mod_bandwidth is not None + if ( + not draw_output + and not draw_input + and (draw_qubit_det or draw_qubit_amp) + ): + warnings.warn( + "Can't display modulated quantities per qubit if a channel does " + "not have a modulation bandwidth, displays the input per qubit.", + UserWarning, + stacklevel=2, + ) + draw_input = True + (fig_qubit, fig_legend) = _draw_qubit_content( + sampled_seq, + data, + seq.register if draw_register else None, + draw_input=draw_input, + draw_modulation=draw_output, + draw_qubit_amp=draw_qubit_amp, + draw_qubit_det=draw_qubit_det, + ) # Gather additional data for sequence specific drawing for ch, sch in seq._schedule.items(): interp_pts: defaultdict[str, list[list[float]]] = defaultdict(list) @@ -814,4 +1347,4 @@ def draw_sequence( pts = np.array(ch_data.interp_pts[qty]) axes[ind].scatter(pts[:, 0], pts[:, 1], color=COLORS[ind]) - return (fig_reg, fig) + return (fig_reg, fig, fig_qubit, fig_legend) diff --git a/pulser-core/pulser/sequence/_seq_str.py b/pulser-core/pulser/sequence/_seq_str.py index b9413373..8cbd9539 100644 --- a/pulser-core/pulser/sequence/_seq_str.py +++ b/pulser-core/pulser/sequence/_seq_str.py @@ -15,8 +15,9 @@ from __future__ import annotations import warnings -from typing import TYPE_CHECKING +from typing import TYPE_CHECKING, cast +from pulser.channels import DMM from pulser.pulse import Pulse if TYPE_CHECKING: @@ -30,6 +31,8 @@ def seq_to_str(sequence: Sequence) -> str: target_line = "t: {}->{} | Target: {} | Phase Reference: {}\n" delay_line = "t: {}->{} | Delay \n" det_delay_line = "t: {}->{} | Detuned Delay | Detuning: {:.3g} rad/µs\n" + dmm_det_line = "t: {}->{} | Detuning: {} | Targets: {}\n" + for ch, seq in sequence._schedule.items(): if ( seq.channel_obj.addressing == "Global" @@ -56,7 +59,18 @@ def seq_to_str(sequence: Sequence) -> str: ) tgt_txt = ", ".join(map(str, tgts)) if isinstance(ts.type, Pulse): - if seq.is_detuned_delay(ts.type): + if isinstance(sequence.declared_channels[ch], DMM): + full += dmm_det_line.format( + ts.ti, + ts.tf, + ts.type.detuning + if not seq.is_detuned_delay(ts.type) + else "{:.3g} rad/µs".format( + cast(float, ts.type.detuning[0]) + ), + tgt_txt, + ) + elif seq.is_detuned_delay(ts.type): det = ts.type.detuning[0] full += det_delay_line.format(ts.ti, ts.tf, det) else: diff --git a/pulser-core/pulser/sequence/sequence.py b/pulser-core/pulser/sequence/sequence.py index ee86759e..39bf5533 100644 --- a/pulser-core/pulser/sequence/sequence.py +++ b/pulser-core/pulser/sequence/sequence.py @@ -40,6 +40,7 @@ import pulser import pulser.sequence._decorators as seq_decorators from pulser.channels.base_channel import Channel +from pulser.channels.dmm import DMM, _dmm_id_from_name, _get_dmm_name from pulser.channels.eom import RydbergEOM from pulser.devices._device_datacls import BaseDevice from pulser.json.abstract_repr.deserializer import ( @@ -53,16 +54,19 @@ from pulser.pulse import Pulse from pulser.register.base_register import BaseRegister, QubitId from pulser.register.mappable_reg import MappableRegister +from pulser.register.weight_maps import DetuningMap from pulser.sequence._basis_ref import _QubitRef from pulser.sequence._call import _Call from pulser.sequence._schedule import ( _ChannelSchedule, + _DMMSchedule, _PhaseDriftParams, _Schedule, _TimeSlot, ) from pulser.sequence._seq_drawer import Figure, draw_sequence from pulser.sequence._seq_str import seq_to_str +from pulser.waveforms import Waveform DeviceType = TypeVar("DeviceType", bound=BaseDevice) @@ -125,6 +129,7 @@ def __init__( self._register: Union[BaseRegister, MappableRegister] = register self._device = device self._in_xy: bool = False + self._in_ising_value: bool = False self._mag_field: Optional[tuple[float, float, float]] = None self._calls: list[_Call] = [ _Call("__init__", (), {"register": register, "device": device}) @@ -143,19 +148,49 @@ def __init__( self._empty_sequence: bool = True # SLM mask targets and on/off times self._slm_mask_targets: set[QubitId] = set() - + self._slm_mask_dmm: str | None = None # Initializes all parametrized Sequence related attributes self._reset_parametrized() @property def _slm_mask_time(self) -> list[int]: """The initial and final time when the SLM mask is on.""" + if ( + self._in_ising + and self._slm_mask_dmm + and not cast( + _DMMSchedule, self._schedule[self._slm_mask_dmm] + )._waiting_for_first_pulse + ): + slm_slot = self._schedule[self._slm_mask_dmm].slots[1] + return [slm_slot.ti, slm_slot.tf] return ( [] if not self._slm_mask_targets else self._schedule.find_slm_mask_times() ) + @property + def _in_ising(self) -> bool: + return self._in_ising_value + + @_in_ising.setter + def _in_ising(self, value: bool) -> None: + if not isinstance(value, bool): + raise TypeError("_in_ising must be a bool.") + if self._in_ising == value: + # If the value doesn't change, do nothing + return + if self._in_ising: # ie value = False + # Trying to switch off ising + raise ValueError("Cannot quit ising.") + # At this point, value = True + if self._in_xy: + raise ValueError("Cannot be in ising if in xy.") + self._in_ising_value = True + if self._slm_mask_dmm: + self._set_slm_mask_dmm(self._slm_mask_dmm, self._slm_mask_targets) + @property def qubit_info(self) -> dict[QubitId, np.ndarray]: """Dictionary with the qubit's IDs and positions.""" @@ -200,7 +235,29 @@ def get_register( @property def declared_channels(self) -> dict[str, Channel]: """Channels declared in this Sequence.""" - return {name: cs.channel_obj for name, cs in self._schedule.items()} + all_declared_channels = { + name: cs.channel_obj for name, cs in self._schedule.items() + } + # Add DMM and SLM whose configuration is stored + for call in self._to_build_calls: + if ( + call.name == "config_slm_mask" + or call.name == "config_detuning_map" + ): + dmm_id: str + if "dmm_id" in call.kwargs: + dmm_id = call.kwargs["dmm_id"] + elif len(call.args) > 1: + dmm_id = call.args[1] + else: + dmm_id = "dmm_0" + dmm_name = _get_dmm_name( + dmm_id, list(all_declared_channels.keys()) + ) + all_declared_channels[dmm_name] = self.device.dmm_channels[ + dmm_id + ] + return all_declared_channels @property def declared_variables(self) -> dict[str, Variable]: @@ -210,21 +267,45 @@ def declared_variables(self) -> dict[str, Variable]: @property def available_channels(self) -> dict[str, Channel]: """Channels still available for declaration.""" - # Show all channels if none are declared, otherwise filter depending - # on whether the sequence is working on XY mode - # If already in XY mode, filter right away - if not self._schedule and not self._in_xy: - return dict(self._device.channels) + all_channels = {**self._device.channels, **self._device.dmm_channels} + if not self._in_xy and not self._in_ising: + # If no channel has been declared nor any DMM configured, and if + # device is physical, don't show the DMM used for the SLM Mask + if ( + self._slm_mask_dmm is not None + and not self._device.reusable_channels + ): + return { + id: ch + for id, ch in all_channels.items() + if id != self._slm_mask_dmm + } + return all_channels else: - # MockDevice channels can be declared multiple times - occupied_ch_ids = [cs.channel_id for cs in self._schedule.values()] + occupied_ch_ids = [ + self._schedule[ch_name].channel_id + if ch_name in self._schedule + else _dmm_id_from_name(ch_name) + for ch_name in self.declared_channels.keys() + ] return { id: ch - for id, ch in self._device.channels.items() + for id, ch in all_channels.items() if ( - id not in occupied_ch_ids or self._device.reusable_channels + # MockDevice channels can be declared multiple times + ( + id not in occupied_ch_ids + or self._device.reusable_channels + ) + and ( + # If we are in XY mode, the dmm channels are available + # to configure a SLM mask if no slm mask was defined + ch.basis == "XY" + or (isinstance(ch, DMM) and self._slm_mask_dmm is None) + if self._in_xy + else ch.basis != "XY" + ) ) - and (ch.basis == "XY" if self._in_xy else ch.basis != "XY") } @property @@ -410,13 +491,59 @@ def set_magnetic_field( # No parametrization -> Always stored as a regular call self._calls.append(_Call("set_magnetic_field", mag_vector, {})) + def _set_slm_mask_dmm(self, dmm_id: str, targets: set[QubitId]) -> None: + ntargets = len(targets) + detuning_map = self.register.define_detuning_map( + { + qubit: (1 / ntargets if qubit in targets else 0) + for qubit in self.register.qubit_ids + } + ) + self._config_detuning_map(detuning_map, dmm_id) + # Find the name of the dmm in the declared channels. + for key in reversed(self.declared_channels.keys()): + if dmm_id == _dmm_id_from_name(key): + self._slm_mask_dmm = key + break + # Modulate the dmm if pulses have already been added to Global Channels + slm_mask_times = self._schedule.find_slm_mask_times() + if slm_mask_times: + max_amp = max( + [ + np.max(ch_schedule.get_samples().amp[: slm_mask_times[1]]) + for ch_schedule in self._schedule.values() + if not isinstance(ch_schedule, _DMMSchedule) + and ch_schedule.channel_obj.addressing == "Global" + ] + ) + self._modulate_slm_mask_dmm(slm_mask_times[1], max_amp) + else: + # Block the modulation of this dmm + cast( + _DMMSchedule, self._schedule[key] + )._waiting_for_first_pulse = True + @seq_decorators.store - def config_slm_mask(self, qubits: Iterable[QubitId]) -> None: + def config_slm_mask( + self, qubits: Iterable[QubitId], dmm_id: str = "dmm_0" + ) -> None: """Setup an SLM mask by specifying the qubits it targets. + If the sequence is in XY mode, masked qubits don't interact with + the incoming pulses until the end of the first pulse of the global + channel starting the earliest in the schedule. + + If the sequence is in Ising, the SLM Mask is a DetuningMap where + the detuning of each masked qubit is the same. DMM "dmm_id" is + configured using this Detuning Map, and modulated by a pulse having + a large negative detuning and either a duration defined from pulses + already present in the sequence (same as in XY mode) or by the first + pulse added after this operation. + Args: qubits: Iterable of qubit ID's to mask during the first global pulse of the sequence. + dmm_id: Id of the DMM channel to use in the device. """ if not self._device.supports_slm_mask: raise ValueError( @@ -436,15 +563,86 @@ def config_slm_mask(self, qubits: Iterable[QubitId]) -> None: if not targets.issubset(self._qids): raise ValueError("SLM mask targets must exist in the register.") + # If sequence is parametrized slm is configured at build if self.is_parametrized(): return if self._slm_mask_targets: raise ValueError("SLM mask can be configured only once.") - # If checks have passed, set the SLM mask targets + if self._in_xy or (not self._in_xy and not self._in_ising): + if dmm_id not in self._device.dmm_channels: + raise ValueError(f"No DMM {dmm_id} in the device.") + self._slm_mask_dmm = dmm_id + if not self._in_xy and self._in_ising: + self._set_slm_mask_dmm(dmm_id, targets) self._slm_mask_targets = targets + @seq_decorators.store + @seq_decorators.block_if_measured + def config_detuning_map( + self, + detuning_map: DetuningMap, + dmm_id: str, + ) -> None: + """Declares a new DMM channel to the Sequence. + + Associates a DetuningMap to a DMM channel of the Device. + + Note: + Regular devices only allow a DMM to be declared once, but + ``MockDevice`` DMM can be repeatedly declared if needed. + + Args: + detuning_map: A DetuningMap defining atoms to act on and bottom + detuning to modulate. + dmm_id: How the channel is identified in the device. + See in ``Sequence.available_channels`` which DMM IDs are still + available (start by "dmm" ) and the associated description. + """ + self._config_detuning_map(detuning_map, dmm_id) + + def _config_detuning_map( + self, + detuning_map: DetuningMap, + dmm_id: str, + ) -> None: + if dmm_id not in self._device.dmm_channels: + raise ValueError(f"No DMM {dmm_id} in the device.") + + dmm_ch = self._device.dmm_channels[dmm_id] + if self._in_xy: + raise ValueError( + f"DMM '{dmm_ch}' cannot work simultaneously " + "with the declared 'Microwave' channel." + ) + if dmm_id not in self.available_channels: + raise ValueError(f"DMM {dmm_id} is not available.") + + # Configures the DMM implementing an SLM mask if configured before + self._in_ising = True + + if self.is_parametrized(): + return + # Add a suffix to the DMM id if repetition in the declared channels + dmm_name = dmm_id + if dmm_id in self.declared_channels: + assert self._device.reusable_channels + dmm_name += ( + f"_{''.join(self.declared_channels.keys()).count(dmm_id)}" + ) + + self._schedule[dmm_name] = _DMMSchedule( + dmm_id, dmm_ch, detuning_map=detuning_map + ) + if "ground-rydberg" not in self._basis_ref: + self._basis_ref["ground-rydberg"] = { + q: _QubitRef() for q in self._qids + } + + # DMM has Global addressing + self._add_to_schedule(dmm_name, _TimeSlot("target", -1, 0, self._qids)) + def switch_device( self, new_device: DeviceType, strict: bool = False ) -> Sequence: @@ -506,10 +704,16 @@ def check_retarget(ch_obj: Channel) -> bool: for call in self._calls + self._to_build_calls if call.name == "enable_eom_mode" ] + all_channels_new_device = { + **new_device.channels, + **new_device.dmm_channels, + } + for old_ch_name, old_ch_obj in self.declared_channels.items(): channel_match[old_ch_name] = None + base_msg = f"No match for channel {old_ch_name}" # Find the corresponding channel on the new device - for new_ch_id, new_ch_obj in new_device.channels.items(): + for new_ch_id, new_ch_obj in all_channels_new_device.items(): if ( not new_device.reusable_channels and new_ch_id in channel_match.values() @@ -524,7 +728,6 @@ def check_retarget(ch_obj: Channel) -> bool: addressing_match = ( old_ch_obj.addressing == new_ch_obj.addressing ) - base_msg = f"No match for channel {old_ch_name}" if not (type_match and basis_match and addressing_match): # If there already is a message, keeps it ch_match_err = ch_match_err or ( @@ -563,14 +766,15 @@ def check_retarget(ch_obj: Channel) -> bool: "fixed_retarget_t", "clock_period", ] - + if isinstance(old_ch_obj, DMM): + params_to_check.append("bottom_detuning") if check_retarget(old_ch_obj) or check_retarget(new_ch_obj): params_to_check.append("min_retarget_interval") for param_ in params_to_check: if getattr(new_ch_obj, param_) != getattr( old_ch_obj, param_ ): - strict_error_message = strict_error_message or ( + strict_error_message = ( base_msg + f" with the same {param_}." ) break @@ -591,18 +795,20 @@ def check_retarget(ch_obj: Channel) -> bool: raise TypeError(ch_match_err) # Initialize the new sequence (works for Sequence subclasses too) new_seq = type(self)(register=self._register, device=new_device) - + dmm_calls: list[str] = [] # Copy the variables to the new sequence new_seq._variables = self.declared_variables - for call in self._calls[1:] + self._to_build_calls: - if not (call.name == "declare_channel"): - getattr(new_seq, call.name)(*call.args, **call.kwargs) - continue # Switch the old id with the correct id sw_channel_args = list(call.args) sw_channel_kw_args = call.kwargs.copy() - if "name" in sw_channel_kw_args: # pragma: no cover + if not ( + call.name == "declare_channel" + or call.name == "config_detuning_map" + or call.name == "config_slm_mask" + ): + pass + elif "name" in sw_channel_kw_args: # pragma: no cover sw_channel_kw_args["channel_id"] = channel_match[ sw_channel_kw_args["name"] ] @@ -610,10 +816,19 @@ def check_retarget(ch_obj: Channel) -> bool: sw_channel_kw_args["channel_id"] = channel_match[ sw_channel_args[0] ] - else: + elif "dmm_id" in sw_channel_kw_args: # pragma: no cover + sw_channel_kw_args["dmm_id"] = channel_match[ + _get_dmm_name(sw_channel_kw_args["dmm_id"], dmm_calls) + ] + dmm_calls.append(sw_channel_kw_args["dmm_id"]) + elif call.name == "declare_channel": sw_channel_args[1] = channel_match[sw_channel_args[0]] - - new_seq.declare_channel(*sw_channel_args, **sw_channel_kw_args) + else: + sw_channel_args[1] = channel_match[ + _get_dmm_name(sw_channel_args[1], dmm_calls) + ] + dmm_calls.append(sw_channel_args[1]) + getattr(new_seq, call.name)(*sw_channel_args, **sw_channel_kw_args) return new_seq @seq_decorators.block_if_measured @@ -647,11 +862,15 @@ def declare_channel( target will have to be set manually as the first addition to this channel. """ + if name.startswith("dmm_"): + raise ValueError( + "Name starting by 'dmm_' are reserved for DMM channels." + ) if name in self._schedule: raise ValueError("The given name is already in use.") if channel_id not in self._device.channels: - raise ValueError("No channel %s in the device." % channel_id) + raise ValueError(f"No channel {channel_id} in the device.") ch = self._device.channels[channel_id] if channel_id not in self.available_channels: @@ -679,10 +898,12 @@ def declare_channel( if cond: raise TypeError("The initial_target cannot be parametrized") - if ch.basis == "XY" and not self._in_xy: - self._in_xy = True - self.set_magnetic_field() - + if ch.basis == "XY": + if not self._in_xy: + self.set_magnetic_field() + self._in_xy = True + else: + self._in_ising = True self._schedule[name] = _ChannelSchedule(channel_id, ch) if ch.basis not in self._basis_ref: @@ -1020,9 +1241,47 @@ def add( `phase_jump_time` is respected. To override this behaviour, use the ``'no-delay'`` protocol. """ - self._validate_channel(channel, block_eom_mode=True) + self._validate_channel( + channel, + block_eom_mode=True, + block_if_slm=channel.startswith("dmm_"), + ) self._add(pulse, channel, protocol) + @seq_decorators.store + @seq_decorators.mark_non_empty + @seq_decorators.block_if_measured + def add_dmm_detuning( + self, + waveform: Union[Waveform, Parametrized], + dmm_name: str, + protocol: PROTOCOLS = "no-delay", + ) -> None: + """Add a waveform to the detuning of a dmm. + + Args: + waveform: The waveform to add to the detuning of the dmm. + dmm_name: The id of the dmm to modulate. + protocol: Stipulates how to deal with + eventual conflicts with other channels, specifically in terms + of having multiple channels act on the same target + simultaneously (defaults to "no-delay"). + + - ``'min-delay'``: Before adding the pulse, introduces the + smallest possible delay that avoids all exisiting conflicts. + - ``'no-delay'``: Adds the pulse to the channel, regardless of + existing conflicts. + - ``'wait-for-all'``: Before adding the pulse, adds a delay + that idles the channel until the end of the other channels' + latest pulse. + """ + self._validate_channel(dmm_name, block_if_slm=True) + self._add( + Pulse.ConstantAmplitude(0, waveform, 0), + dmm_name, + protocol, + ) + @seq_decorators.store def target( self, @@ -1397,6 +1656,9 @@ def draw( draw_phase_shifts: bool = False, draw_register: bool = False, draw_phase_curve: bool = False, + draw_detuning_maps: bool = False, + draw_qubit_amp: bool = False, + draw_qubit_det: bool = False, fig_name: str | None = None, kwargs_savefig: dict = {}, show: bool = True, @@ -1425,12 +1687,25 @@ def draw( True if the sequence is defined with a mappable register. draw_phase_curve: Draws the changes in phase in its own curve (ignored if the phase doesn't change throughout the channel). - fig_name: The name on which to save the - figure. If `draw_register` is True, both pulses and register - will be saved as figures, with a suffix ``_pulses`` and - ``_register`` in the file name. If `draw_register` is False, - only the pulses are saved, with no suffix. If `fig_name` is - None, no figure is saved. + draw_detuning_maps: Whether to draw the detuning maps applied on + the qubits of the register of the sequence. Shown before the + pulse sequence, defaults to False. + draw_qubit_amp: Draws the amplitude seen by the qubits locally + after the drawing of the sequence. + draw_qubit_det: Draws the detuning seen by the qubits locally after + the drawing of the sequence. + fig_name: The name on which to save the figures. Figures are saved + if `fig_name` is not None. If `draw_register`, `draw_qubit_amp` + and `draw_qubit_det` are False, only the pulses are saved, with + no suffix. If one of them is True, the pulses will be saved + with a suffix ``_pulses``. If draw_register is True, the + register is saved in another figure, with a suffix + ``_register`` in the file name. If `draw_qubit_amp` or + `draw_qubit_det` is True, the evolution of the quantities along + time for group of qubits is saved in another figure with the + prefix '_per_qubit', and the group of qubits having same + evolution of quantities along time are saved in a figure with + suffix '_per_qubit_legend'. kwargs_savefig: Keywords arguments for ``matplotlib.pyplot.savefig``. Not applicable if `fig_name` is ``None``. @@ -1467,7 +1742,7 @@ def draw( "Can't draw the register for a sequence without a defined " "register." ) - fig_reg, fig = self._plot( + fig_reg, fig, fig_qubit, fig_legend = self._plot( draw_phase_area=draw_phase_area, draw_interp_pts=draw_interp_pts, draw_phase_shifts=draw_phase_shifts, @@ -1475,20 +1750,55 @@ def draw( draw_input="input" in mode, draw_modulation="output" in mode, draw_phase_curve=draw_phase_curve, + draw_detuning_maps=draw_detuning_maps, + draw_qubit_amp=draw_qubit_amp, + draw_qubit_det=draw_qubit_det, ) - if fig_name is not None and fig_reg is not None: + if fig_name is not None: name, ext = os.path.splitext(fig_name) - fig.savefig(name + "_pulses" + ext, **kwargs_savefig) - fig_reg.savefig(name + "_register" + ext, **kwargs_savefig) - elif fig_name: - fig.savefig(fig_name, **kwargs_savefig) + suffix = ( + "_pulses" + if all(fig is None for fig in (fig_reg, fig_qubit, fig_legend)) + else "" + ) + fig.savefig(name + suffix + ext, **kwargs_savefig) + if fig_reg is not None: + fig_reg.savefig(name + "_register" + ext, **kwargs_savefig) + if fig_qubit is not None: + fig_qubit.savefig(name + "_per_qubit" + ext, **kwargs_savefig) + if fig_legend is not None: + fig_qubit.savefig( + name + "_per_qubit_legend" + ext, **kwargs_savefig + ) if show: plt.show() - def _plot(self, **draw_options: bool) -> tuple[Figure | None, Figure]: + def _plot( + self, **draw_options: bool + ) -> tuple[Figure | None, Figure, Figure | None, Figure | None]: return draw_sequence(self, **draw_options) + def _modulate_slm_mask_dmm(self, duration: int, max_amp: float) -> None: + if self._slm_mask_dmm is not None: + bottom_detuning = cast( + DMM, self.declared_channels[self._slm_mask_dmm] + ).bottom_detuning + min_det = -10 * max_amp + min_det = ( + bottom_detuning + if (bottom_detuning and min_det < bottom_detuning) + else min_det + ) + cast( + _DMMSchedule, self._schedule[self._slm_mask_dmm] + )._waiting_for_first_pulse = False + self._add( + Pulse.ConstantPulse(duration, 0, min_det, 0), + self._slm_mask_dmm, + "no-delay", + ) + def _add( self, pulse: Union[Pulse, Parametrized], @@ -1542,6 +1852,20 @@ def _add( self._phase_shift( pulse.post_phase_shift, *last.targets, basis=basis ) + if ( + self._in_ising + and self._slm_mask_dmm + and cast( + _DMMSchedule, self._schedule[self._slm_mask_dmm] + )._waiting_for_first_pulse + and channel_obj.addressing == "Global" + and not _ChannelSchedule.is_detuned_delay(pulse) + and not isinstance(channel_obj, DMM) + ): + self._modulate_slm_mask_dmm( + self._schedule[channel].get_duration(), + np.max(pulse.amplitude.samples), + ) @seq_decorators.block_if_measured def _target( @@ -1621,7 +1945,7 @@ def _check_qubits_give_ids( @seq_decorators.block_if_measured def _delay(self, duration: Union[int, Parametrized], channel: str) -> None: - self._validate_channel(channel) + self._validate_channel(channel, block_if_slm=True) if self.is_parametrized(): return self._schedule.add_delay(cast(int, duration), channel) @@ -1688,22 +2012,41 @@ def _last(self, channel: str) -> _TimeSlot: return self._schedule[channel][-1] def _validate_channel( - self, channel: str, block_eom_mode: bool = False + self, + channel: str, + block_eom_mode: bool = False, + block_if_slm: bool = False, ) -> None: if isinstance(channel, Parametrized): raise NotImplementedError( "Using parametrized objects or variables to refer to channels " "is not supported." ) - if channel not in self._schedule: + if channel not in self.declared_channels: raise ValueError("Use the name of a declared channel.") if block_eom_mode and self.is_in_eom_mode(channel): raise RuntimeError("The chosen channel is in EOM mode.") + if ( + block_if_slm + and channel == self._slm_mask_dmm + and cast( + _DMMSchedule, self._schedule[self._slm_mask_dmm] + )._waiting_for_first_pulse + ): + raise ValueError( + "You should add a Pulse to a Global Channel prior to" + " modulating the DMM used for the SLM Mask." + ) def _validate_and_adjust_pulse( self, pulse: Pulse, channel: str, phase_ref: Optional[float] = None ) -> Pulse: - channel_obj = self._schedule[channel].channel_obj + channel_obj: Channel + if channel in self._schedule: + channel_obj = self._schedule[channel].channel_obj + else: + # Sequence is parametrized and channel is a dmm_name + channel_obj = self.device.dmm_channels[_dmm_id_from_name(channel)] channel_obj.validate_pulse(pulse) _duration = channel_obj.validate_duration(pulse.duration) new_phase = pulse.phase + (phase_ref if phase_ref else 0) diff --git a/pulser-simulation/pulser_simulation/simulation.py b/pulser-simulation/pulser_simulation/simulation.py index 62433e18..1d6c91c7 100644 --- a/pulser-simulation/pulser_simulation/simulation.py +++ b/pulser-simulation/pulser_simulation/simulation.py @@ -728,6 +728,7 @@ def make_interaction_term(masked: bool = False) -> qutip.Qobj: or self._bad_atoms[q2] or ( masked + and self._interaction == "XY" and ( q1 in self.samples_obj._slm_mask.targets or q2 in self.samples_obj._slm_mask.targets @@ -804,7 +805,10 @@ def build_coeffs_ops(basis: str, addr: str) -> list[list]: if self.basis_name != "digital" and effective_size > 1: # Build time-dependent or time-independent interaction term based # on whether an SLM mask was defined or not - if self.samples_obj._slm_mask.end > 0: + if ( + self.samples_obj._slm_mask.end > 0 + and self._interaction == "XY" + ): # Build an array of binary coefficients for the interaction # term of unmasked qubits coeff = np.ones(self._tot_duration) diff --git a/tests/conftest.py b/tests/conftest.py index e206609b..556b9ca7 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -17,6 +17,7 @@ import pytest from pulser.channels import Raman, Rydberg +from pulser.channels.dmm import DMM from pulser.channels.eom import RydbergBeam, RydbergEOM from pulser.devices import Device @@ -72,6 +73,10 @@ def mod_device() -> Device: mod_bandwidth=4.0, ), ), + dmm_objects=( + DMM(bottom_detuning=-100), + DMM(clock_period=4, mod_bandwidth=4.0, bottom_detuning=-50), + ), ) diff --git a/tests/test_abstract_repr.py b/tests/test_abstract_repr.py index 3558c705..e7d8392c 100644 --- a/tests/test_abstract_repr.py +++ b/tests/test_abstract_repr.py @@ -27,7 +27,6 @@ from pulser import Pulse, Register, Register3D, Sequence, devices from pulser.channels import Rydberg -from pulser.channels.dmm import DMM from pulser.channels.eom import RydbergBeam, RydbergEOM from pulser.devices import AnalogDevice, Chadoq2, Device, IroiseMVP, MockDevice from pulser.json.abstract_repr.deserializer import ( @@ -236,46 +235,6 @@ def test_optional_channel_fields(self, ch_obj): dev_str = device.to_abstract_repr() assert device == deserialize_device(dev_str) - @pytest.fixture - def chadoq2_with_dmm(self): - # TODO: Delete once Chadoq2 actually has a DMM - dmm = DMM( - bottom_detuning=-1, - clock_period=1, - min_duration=1, - max_duration=1e6, - mod_bandwidth=20, - ) - return replace(Chadoq2, dmm_objects=(dmm,)) - - @pytest.mark.xfail( - raises=jsonschema.exceptions.ValidationError, strict=True - ) - def test_abstract_repr_dmm_serialize(self, chadoq2_with_dmm): - chadoq2_with_dmm.to_abstract_repr() - - @pytest.mark.xfail(raises=DeserializeDeviceError, strict=True) - @pytest.mark.parametrize( - "skip_validation", - [ - False, # Fails validation - True, # Fails because the DMM channel is deserialized as Rydberg - ], - ) - def test_abstract_repr_dmm_deserialize( - self, chadoq2_with_dmm, monkeypatch, skip_validation - ): - ser_device = json.dumps(chadoq2_with_dmm, cls=AbstractReprEncoder) - if skip_validation: - - def dummy(*args, **kwargs): - return True - - # Patches jsonschema.validate with a function that returns True - monkeypatch.setattr(jsonschema, "validate", dummy) - device = deserialize_device(ser_device) - assert device == chadoq2_with_dmm - def validate_schema(instance): with open( @@ -693,6 +652,8 @@ def test_mw_sequence(self, triangular_lattice): assert abstract["magnetic_field"] == mag_field assert abstract["slm_mask_targets"] == list(mask) assert abstract["measurement"] == "XY" + assert "dmm_channels" not in abstract + assert "config_slm_mask" not in abstract["operations"] def test_mappable_register(self, triangular_lattice): reg = triangular_lattice.make_mappable_register(2) @@ -858,6 +819,62 @@ def test_mappable_reg_with_local_ops( getattr(seq, op)(*args) seq.to_abstract_repr() + @pytest.mark.parametrize("is_empty", [True, False]) + def test_dmm_slm_mask(self, triangular_lattice, is_empty): + mask = {"q0", "q2", "q4", "q5"} + dmm = {"q0": 0.2, "q1": 0.3, "q2": 0.4, "q3": 0.1} + reg = triangular_lattice.rectangular_register(3, 4) + seq = Sequence(reg, MockDevice) + seq.config_slm_mask(mask, "dmm_0") + if not is_empty: + seq.config_detuning_map( + reg.define_detuning_map(dmm, "det_map"), "dmm_0" + ) + seq.add_dmm_detuning(ConstantWaveform(100, -10), "dmm_0_1") + seq.declare_channel("rydberg_global", "rydberg_global") + seq.add(Pulse.ConstantPulse(100, 10, 0, 0), "rydberg_global") + + abstract = json.loads(seq.to_abstract_repr()) + validate_schema(abstract) + assert abstract["register"] == [ + {"name": str(qid), "x": c[0], "y": c[1]} + for qid, c in reg.qubits.items() + ] + assert abstract["layout"] == { + "coordinates": triangular_lattice.coords.tolist(), + "slug": triangular_lattice.slug, + } + + assert "slm_mask_targets" not in abstract # only in xy + assert len(abstract["operations"]) == 1 if is_empty else 4 + + assert abstract["operations"][0]["op"] == "config_slm_mask" + assert abstract["operations"][0]["qubits"] == list(mask) + assert abstract["operations"][0]["dmm_id"] == "dmm_0" + + if not is_empty: + assert abstract["channels"] == {"rydberg_global": "rydberg_global"} + + assert abstract["operations"][1]["op"] == "config_detuning_map" + assert abstract["operations"][1]["dmm_id"] == "dmm_0" + assert abstract["operations"][1]["detuning_map"]["traps"] == [ + { + "weight": weight, + "x": reg._coords[i][0], + "y": reg._coords[i][1], + } + for i, weight in enumerate(list(dmm.values())) + ] + assert ( + abstract["operations"][1]["detuning_map"]["slug"] == "det_map" + ) + + assert abstract["operations"][2]["op"] == "add_dmm_detuning" + assert abstract["operations"][2]["dmm_name"] == "dmm_0_1" + + assert abstract["operations"][3]["op"] == "pulse" + assert abstract["operations"][3]["channel"] == "rydberg_global" + def _get_serialized_seq( operations: list[dict] = [], @@ -1013,10 +1030,96 @@ def test_deserialize_mappable_register(self): assert seq._register.layout == RegisterLayout(layout_coords) def test_deserialize_seq_with_slm_mask(self): - s = _get_serialized_seq(slm_mask_targets=["q0"]) + s = _get_serialized_seq( + [{"op": "config_slm_mask", "qubits": ["q0"], "dmm_id": "dmm_0"}], + **{ + "device": json.loads(MockDevice.to_abstract_repr()), + "channels": {}, + }, + ) + _check_roundtrip(s) + seq = Sequence.from_abstract_repr(json.dumps(s)) + assert seq._slm_mask_targets == {"q0"} + assert not seq._in_xy and not seq._in_ising + + def test_deserialize_seq_with_slm_mask_xy(self): + mag_field = [0.0, -10.0, 30.0] + s = _get_serialized_seq( + channels={}, + magnetic_field=mag_field, + slm_mask_targets=["q0"], + device=json.loads(MockDevice.to_abstract_repr()), + ) + _check_roundtrip(s) + seq = Sequence.from_abstract_repr(json.dumps(s)) + assert seq._slm_mask_targets == {"q0"} + assert seq._in_xy + + def test_deserialize_seq_with_slm_dmm(self): + traps = [ + {"weight": 0.5, "x": -2.0, "y": 9.0}, + {"weight": 0.5, "x": 0.0, "y": 2.0}, + {"weight": 0, "x": 12.0, "y": 0.0}, + ] + op = [ + { + "op": "config_detuning_map", + "detuning_map": {"traps": traps}, + "dmm_id": "dmm_0", + }, + { + "op": "config_slm_mask", + "qubits": [ + "q0", + ], + "dmm_id": "dmm_0", + }, + { + "op": "config_detuning_map", + "detuning_map": {"traps": traps, "slug": "det_map"}, + "dmm_id": "dmm_0", + }, + { + "op": "add_dmm_detuning", + "protocol": "no-delay", + "waveform": { + "kind": "constant", + "duration": 100, + "value": -10.0, + }, + "dmm_name": "dmm_0_2", + }, + { + "op": "pulse", + "channel": "global", + "protocol": "min-delay", + "amplitude": { + "kind": "constant", + "duration": 100, + "value": 10.0, + }, + "detuning": { + "kind": "constant", + "duration": 100, + "value": 0.0, + }, + "phase": 0.0, + "post_phase_shift": 0.0, + }, + ] + kwargs = {"device": json.loads(MockDevice.to_abstract_repr())} + s = _get_serialized_seq(op, **kwargs) _check_roundtrip(s) seq = Sequence.from_abstract_repr(json.dumps(s)) assert seq._slm_mask_targets == {"q0"} + assert seq.declared_channels.keys() == { + "digital", + "global", + "dmm_0", + "dmm_0_1", + "dmm_0_2", + } + assert not seq._in_xy and seq._in_ising def test_deserialize_seq_with_mag_field(self): mag_field = [10.0, -43.2, 0.0] diff --git a/tests/test_channels.py b/tests/test_channels.py index 5d948b94..0affe74d 100644 --- a/tests/test_channels.py +++ b/tests/test_channels.py @@ -27,7 +27,7 @@ @pytest.mark.parametrize( "bad_param,bad_value", [ - ("max_amp", 0), + ("max_amp", -0.00001), ("max_abs_detuning", -0.001), ("clock_period", 0), ("min_duration", 0), diff --git a/tests/test_devices.py b/tests/test_devices.py index 1214aa32..d3d0c742 100644 --- a/tests/test_devices.py +++ b/tests/test_devices.py @@ -136,14 +136,14 @@ def test_post_init_value_errors(test_params, param, value, msg): VirtualDevice(**test_params) -# TODO: Add test of comptability SLM-DMM once DMM is added for serialization -# def test_post_init_slm_dmm_compatibility(test_params): -# test_params["supports_slm_mask"] = True -# test_params["dmm_objects"] = () -# with pytest.raises(ValueError, -# match="One DMM object should be defined to support SLM mask." -# ): -# VirtualDevice(**test_params) +def test_post_init_slm_dmm_compatibility(test_params): + test_params["supports_slm_mask"] = True + test_params["dmm_objects"] = () + with pytest.raises( + ValueError, + match="One DMM object should be defined to support SLM mask.", + ): + VirtualDevice(**test_params) potential_params = ["max_atom_num", "max_radial_distance"] @@ -384,7 +384,10 @@ def test_convert_to_virtual(): assert Device( pre_calibrated_layouts=(TriangularLatticeLayout(40, 2),), **params ).to_virtual() == VirtualDevice( - supports_slm_mask=False, reusable_channels=False, **params + supports_slm_mask=False, + reusable_channels=False, + dmm_objects=(), + **params, ) @@ -403,6 +406,12 @@ def test_device_params(): def test_dmm_channels(): + with pytest.raises( + ValueError, + match="A 'Device' instance cannot contain virtual channels." + " For channel 'dmm_0', please define: 'bottom_detuning'", + ): + replace(Chadoq2, dmm_objects=(DMM(),)) dmm = DMM( bottom_detuning=-1, clock_period=1, @@ -426,5 +435,3 @@ def test_dmm_channels(): channel_objects=(Rydberg.Global(None, None),), channel_ids=("dmm_0",), ) - assert not dmm.is_virtual() - assert DMM().is_virtual() diff --git a/tests/test_dmm.py b/tests/test_dmm.py index 22055dd6..fe3673ba 100644 --- a/tests/test_dmm.py +++ b/tests/test_dmm.py @@ -13,6 +13,7 @@ # limitations under the License. from __future__ import annotations +import re from typing import cast from unittest.mock import patch @@ -20,174 +21,275 @@ import pytest from pulser.channels.dmm import DMM +from pulser.pulse import Pulse from pulser.register.base_register import BaseRegister from pulser.register.mappable_reg import MappableRegister from pulser.register.register_layout import RegisterLayout -from pulser.register.weight_maps import DetuningMap +from pulser.register.weight_maps import DetuningMap, WeightMap -@pytest.fixture -def layout() -> RegisterLayout: - return RegisterLayout([[0, 0], [1, 0], [0, 1], [1, 1]]) +class TestDetuningMap: + @pytest.fixture + def layout(self) -> RegisterLayout: + return RegisterLayout([[0, 0], [1, 0], [0, 1], [1, 1]]) + @pytest.fixture + def register(self, layout: RegisterLayout) -> BaseRegister: + return layout.define_register(0, 1, 2, 3, qubit_ids=(0, 1, 2, 3)) -@pytest.fixture -def register(layout: RegisterLayout) -> BaseRegister: - return layout.define_register(0, 1, 2, 3, qubit_ids=(0, 1, 2, 3)) + @pytest.fixture + def map_reg(self, layout: RegisterLayout) -> MappableRegister: + return layout.make_mappable_register(4) + @pytest.fixture + def det_dict(self) -> dict[int, float]: + return {0: 0.7, 1: 0.3, 2: 0} -@pytest.fixture -def map_reg(layout: RegisterLayout) -> MappableRegister: - return layout.make_mappable_register(4) + @pytest.fixture + def det_map( + self, layout: RegisterLayout, det_dict: dict[int, float] + ) -> DetuningMap: + return layout.define_detuning_map(det_dict) + @pytest.fixture + def slm_dict(self) -> dict[int, float]: + return {0: 1 / 3, 1: 1 / 3, 2: 1 / 3} -@pytest.fixture -def det_dict() -> dict[int, float]: - return {0: 0.7, 1: 0.3, 2: 0} + @pytest.fixture + def slm_map( + self, layout: RegisterLayout, slm_dict: dict[int, float] + ) -> DetuningMap: + return layout.define_detuning_map(slm_dict) + @pytest.mark.parametrize("bad_key", [{"1": 1.0}, {4: 1.0}]) + def test_define_detuning_map( + self, + layout: RegisterLayout, + register: BaseRegister, + map_reg: MappableRegister, + bad_key: dict, + ): + for reg in (layout, map_reg): + with pytest.raises( + ValueError, + match=re.escape( + "The trap ids of detuning weights have to be integers" + " in [0, 3]." + ), + ): + reg.define_detuning_map(bad_key) # type: ignore + with pytest.raises( + ValueError, + match=( + "The qubit ids linked to detuning weights have to be defined" + " in the register." + ), + ): + register.define_detuning_map(bad_key) -@pytest.fixture -def det_map(layout: RegisterLayout, det_dict: dict[int, float]) -> DetuningMap: - return layout.define_detuning_map(det_dict) + def test_qubit_weight_map(self, register): + # Purposefully unsorted + qid_weight_map = {1: 0.5, 0: 0.1, 3: 0.4} + sorted_qids = sorted(qid_weight_map) + det_map = register.define_detuning_map(qid_weight_map) + qubits = register.qubits + coords = [qubits[qid] for qid in sorted_qids] + weights = [qid_weight_map[qid] for qid in sorted_qids] + np.testing.assert_equal(det_map.sorted_coords, coords) + np.testing.assert_equal(det_map.sorted_weights, weights) + + # We recover the original qid_weight_map (and undefined qids show as 0) + assert det_map.get_qubit_weight_map(qubits) == { + **qid_weight_map, + 2: 0.0, + } + + def test_hash(self, det_map, det_dict, layout): + disordered_det_dict = { + i: det_dict[i] for i in sorted(det_dict, reverse=True) + } + assert disordered_det_dict == det_dict + assert list(disordered_det_dict) != list(det_dict) + + det_map2 = layout.define_detuning_map(disordered_det_dict) + + # The maps differ in the arguments order + assert np.any(det_map.trap_coordinates != det_map2.trap_coordinates) + assert det_map.weights != det_map2.weights + + # But are equal in sorted content + np.testing.assert_equal(det_map.sorted_coords, det_map2.sorted_coords) + np.testing.assert_equal( + det_map.sorted_weights, det_map2.sorted_weights + ) -@pytest.fixture -def slm_dict() -> dict[int, float]: - return {0: 1 / 3, 1: 1 / 3, 2: 1 / 3} + # And they have the same type, so they should be equal + assert type(det_map) is type(det_map2) + assert det_map == det_map2 + # This means their static hashes and reprs match + static_hash = det_map.static_hash() + assert static_hash == det_map2.static_hash() + assert repr(det_map) == repr(det_map2) == f"DetuningMap_{static_hash}" -@pytest.fixture -def slm_map(layout: RegisterLayout, slm_dict: dict[int, float]) -> DetuningMap: - return layout.define_detuning_map(slm_dict) + # However, if the types don't match, this should no longer hold + w_map = WeightMap(det_map.trap_coordinates, det_map.weights) + # Content is still the same + np.testing.assert_equal(det_map.sorted_coords, w_map.sorted_coords) + np.testing.assert_equal(det_map.sorted_weights, w_map.sorted_weights) -@pytest.mark.parametrize("bad_key", [{"1": 1.0}, {4: 1.0}]) -def test_define_detuning_att( - layout: RegisterLayout, - register: BaseRegister, - map_reg: MappableRegister, - bad_key: dict, -): - for reg in (layout, map_reg): + # But the rest isn't + assert static_hash != w_map.static_hash() + assert repr(w_map) != repr(det_map) + assert repr(w_map) == f"WeightMap_{w_map.static_hash()}" + assert w_map != det_map + + def test_detuning_map_bad_init( + self, + layout: RegisterLayout, + register: BaseRegister, + map_reg: MappableRegister, + ): with pytest.raises( - ValueError, - match=( - "The trap ids of detuning weights have to be integers" - " between 0 and 4" - ), + ValueError, match="Number of traps and weights don't match." ): - reg.define_detuning_map(bad_key) # type: ignore - with pytest.raises( - ValueError, - match=( - "The qubit ids linked to detuning weights have to be defined in" - " the register." - ), - ): - register.define_detuning_map(bad_key) + DetuningMap([(0, 0), (1, 0)], [0]) + bad_weights = {0: -1.0, 1: 1.0, 2: 1.0} + bad_sum = {0: 0.1, 2: 0.9, 3: 0.1} + for reg in (layout, map_reg, register): + with pytest.raises( + ValueError, match="All weights must be non-negative." + ): + reg.define_detuning_map(bad_weights) # type: ignore + with pytest.raises( + ValueError, match="The sum of the weights should be 1." + ): + reg.define_detuning_map(bad_sum) # type: ignore -def test_bad_init( - layout: RegisterLayout, - register: BaseRegister, - map_reg: MappableRegister, -): - with pytest.raises( - ValueError, match="Number of traps and weights don't match." + def test_init( + self, + layout: RegisterLayout, + register: BaseRegister, + map_reg: MappableRegister, + det_dict: dict[int, float], + slm_dict: dict[int, float], ): - DetuningMap([(0, 0), (1, 0)], [0]) + for reg in (layout, map_reg, register): + for detuning_map_dict in (det_dict, slm_dict): + detuning_map = cast( + DetuningMap, + reg.define_detuning_map(detuning_map_dict), # type: ignore + ) + assert np.all( + [ + detuning_map_dict[i] == detuning_map.weights[i] + for i in range(len(detuning_map_dict)) + ] + ) + assert np.all( + [ + layout.coords[i] + == np.array(detuning_map.trap_coordinates)[i] + for i in range(len(detuning_map_dict)) + ] + ) - bad_weights = {0: -1.0, 1: 1.0, 2: 1.0} - bad_sum = {0: 0.1, 2: 0.9, 3: 0.1} - for reg in (layout, map_reg, register): - with pytest.raises( - ValueError, match="All weights must be non-negative." - ): - reg.define_detuning_map(bad_weights) # type: ignore + @pytest.mark.parametrize("with_labels", [False, True]) + def test_draw(self, det_map, slm_map, patch_plt_show, with_labels): + for detuning_map in (det_map, slm_map): + labels = ( + list(range(detuning_map.number_of_traps)) + if with_labels + else None + ) + detuning_map.draw(labels=labels, show=True, custom_ax=None) + with patch("matplotlib.pyplot.savefig"): + detuning_map.draw(fig_name="det_map.pdf") with pytest.raises( - ValueError, match="The sum of the weights should be 1." + ValueError, match="masked qubits and dmm qubits must be the same." ): - reg.define_detuning_map(bad_sum) # type: ignore - - -def test_init( - layout: RegisterLayout, - register: BaseRegister, - map_reg: MappableRegister, - det_dict: dict[int, float], - slm_dict: dict[int, float], -): - for reg in (layout, map_reg, register): - for detuning_map_dict in (det_dict, slm_dict): - detuning_map = cast( - DetuningMap, - reg.define_detuning_map(detuning_map_dict), # type: ignore - ) - assert np.all( + slm_map._draw_2D( + slm_map._initialize_fig_axes( + np.array(slm_map.trap_coordinates) + )[1], + np.array(slm_map.trap_coordinates), [ - detuning_map_dict[i] == detuning_map.weights[i] - for i in range(len(detuning_map_dict)) - ] - ) - assert np.all( - [ - layout.coords[i] - == np.array(detuning_map.trap_coordinates)[i] - for i in range(len(detuning_map_dict)) - ] + i + for i, _ in enumerate(cast(list, slm_map.trap_coordinates)) + ], + with_labels=True, + dmm_qubits=dict(enumerate(slm_map.weights)), + masked_qubits={ + 1, + }, ) -def test_draw(det_map, slm_map, patch_plt_show): - for detuning_map in (det_map, slm_map): - detuning_map.draw(with_labels=True, show=True, custom_ax=None) - with patch("matplotlib.pyplot.savefig"): - detuning_map.draw(fig_name="det_map.pdf") - with pytest.raises( - ValueError, match="masked qubits and dmm qubits must be the same." - ): - slm_map._draw_2D( - slm_map._initialize_fig_axes(np.array(slm_map.trap_coordinates))[ - 1 - ], - np.array(slm_map.trap_coordinates), - [i for i, _ in enumerate(cast(list, slm_map.trap_coordinates))], - with_labels=True, - dmm_qubits=dict(enumerate(slm_map.weights)), - masked_qubits={ - 1, - }, +class TestDMM: + @pytest.fixture + def physical_dmm(self): + return DMM( + bottom_detuning=-1, + clock_period=1, + min_duration=1, + max_duration=1e6, + mod_bandwidth=20, ) + def test_init(self, physical_dmm): + assert DMM().is_virtual() -def test_DMM(): - dmm = DMM( - bottom_detuning=-1, - clock_period=1, - min_duration=1, - max_duration=1e6, - mod_bandwidth=20, - ) - assert dmm.basis == "ground-rydberg" - assert dmm.addressing == "Global" - assert dmm.bottom_detuning == -1 - assert dmm.max_amp == 1e-16 - for value in ( - dmm.max_abs_detuning, - dmm.min_retarget_interval, - dmm.fixed_retarget_t, - dmm.max_targets, - ): - assert value is None - with pytest.raises(ValueError, match="bottom_detuning must be negative."): - DMM(bottom_detuning=1) - with pytest.raises( - NotImplementedError, - match=f"{DMM} cannot be initialized from `Global` method.", - ): - DMM.Global(None, None, bottom_detuning=1) - with pytest.raises( - NotImplementedError, - match=f"{DMM} cannot be initialized from `Local` method.", - ): - DMM.Local(None, None, bottom_detuning=1) + dmm = physical_dmm + assert not dmm.is_virtual() + assert dmm.basis == "ground-rydberg" + assert dmm.addressing == "Global" + assert dmm.bottom_detuning == -1 + assert dmm.max_amp == 0 + for value in ( + dmm.max_abs_detuning, + dmm.min_retarget_interval, + dmm.fixed_retarget_t, + dmm.max_targets, + ): + assert value is None + with pytest.raises( + ValueError, match="bottom_detuning must be negative." + ): + DMM(bottom_detuning=1) + with pytest.raises( + NotImplementedError, + match=f"{DMM} cannot be initialized from `Global` method.", + ): + DMM.Global(None, None, bottom_detuning=1) + with pytest.raises( + NotImplementedError, + match=f"{DMM} cannot be initialized from `Local` method.", + ): + DMM.Local(None, None, bottom_detuning=1) + + def test_validate_pulse(self, physical_dmm): + pos_det_pulse = Pulse.ConstantPulse(100, 0, 1e-3, 0) + with pytest.raises( + ValueError, match="The detuning in a DMM must not be positive." + ): + physical_dmm.validate_pulse(pos_det_pulse) + + too_low_pulse = Pulse.ConstantPulse( + 100, 0, physical_dmm.bottom_detuning - 0.01, 0 + ) + with pytest.raises( + ValueError, + match=re.escape( + "The detuning goes below the bottom detuning " + f"of the DMM ({physical_dmm.bottom_detuning} rad/µs)" + ), + ): + physical_dmm.validate_pulse(too_low_pulse) + + # Should be valid in a virtual DMM + virtual_dmm = DMM() + assert virtual_dmm.is_virtual() + virtual_dmm.validate_pulse(too_low_pulse) diff --git a/tests/test_json.py b/tests/test_json.py index 35a94c95..c8a4f16e2 100644 --- a/tests/test_json.py +++ b/tests/test_json.py @@ -27,6 +27,7 @@ SquareLatticeLayout, TriangularLatticeLayout, ) +from pulser.register.weight_maps import DetuningMap from pulser.waveforms import BlackmanWaveform @@ -101,6 +102,15 @@ def test_register_from_layout(): assert new_reg._layout_info.trap_ids == (1, 0) +def test_detuning_map(): + custom_det_map = DetuningMap( + [[0, 0], [1, 1], [1, 0], [0, 1]], [0.1, 0.2, 0.3, 0.4] + ) + new_custom_det_map = encode_decode(custom_det_map) + assert new_custom_det_map == custom_det_map + assert type(new_custom_det_map) is DetuningMap + + @pytest.mark.parametrize( "reg", [ diff --git a/tests/test_sequence.py b/tests/test_sequence.py index 077c9cf3..3f560b49 100644 --- a/tests/test_sequence.py +++ b/tests/test_sequence.py @@ -25,6 +25,7 @@ import pulser from pulser import Pulse, Register, Register3D, Sequence from pulser.channels import Raman, Rydberg +from pulser.channels.dmm import DMM from pulser.devices import Chadoq2, IroiseMVP, MockDevice from pulser.devices._device_datacls import Device, VirtualDevice from pulser.register.base_register import BaseRegister @@ -36,6 +37,7 @@ from pulser.waveforms import ( BlackmanWaveform, CompositeWaveform, + ConstantWaveform, InterpolatedWaveform, RampWaveform, ) @@ -47,9 +49,19 @@ def reg(): return layout.rectangular_register(4, 7, prefix="q") +@pytest.fixture +def det_map(reg: Register): + return reg.define_detuning_map( + {"q" + str(i): (1 / 4 if i in [0, 1, 3, 4] else 0) for i in range(10)} + ) + + @pytest.fixture def device(): - return Chadoq2 + return dataclasses.replace( + Chadoq2, + dmm_objects=(DMM(bottom_detuning=-70), DMM(bottom_detuning=-100)), + ) def test_init(reg, device): @@ -59,14 +71,18 @@ def test_init(reg, device): seq = Sequence(reg, device) assert seq.qubit_info == reg.qubits assert seq.declared_channels == {} - assert seq.available_channels.keys() == device.channels.keys() + assert ( + seq.available_channels.keys() + == {**device.channels, **device.dmm_channels}.keys() + ) def test_channel_declaration(reg, device): seq = Sequence(reg, device) available_channels = set(seq.available_channels) assert seq.get_addressed_bases() == () - + with pytest.raises(ValueError, match="Name starting by 'dmm_'"): + seq.declare_channel("dmm_1_2", "raman") seq.declare_channel("ch0", "rydberg_global") assert seq.get_addressed_bases() == ("ground-rydberg",) seq.declare_channel("ch1", "raman_local") @@ -103,7 +119,7 @@ def test_channel_declaration(reg, device): seq2 = Sequence(reg, MockDevice) seq2.declare_channel("ch0", "mw_global") - assert set(seq2.available_channels) == {"mw_global"} + assert set(seq2.available_channels) == {"mw_global", "dmm_0"} with pytest.raises( ValueError, match="cannot work simultaneously with the declared 'Microwave'", @@ -111,6 +127,128 @@ def test_channel_declaration(reg, device): seq2.declare_channel("ch3", "rydberg_global") +def test_dmm_declaration(reg, device, det_map): + seq = Sequence(reg, device) + available_channels = set(seq.available_channels) + assert seq.get_addressed_bases() == () + seq.config_detuning_map(det_map, "dmm_0") + assert seq.get_addressed_bases() == ("ground-rydberg",) + seq.config_detuning_map(det_map, "dmm_1") + with pytest.raises(ValueError, match="No DMM dmm_2"): + seq.config_detuning_map(det_map, "dmm_2") + with pytest.raises(ValueError, match="DMM dmm_0 is not available"): + seq.config_detuning_map(det_map, "dmm_0") + + chs = {"dmm_0", "dmm_1"} + assert seq._schedule["dmm_0"][-1] == _TimeSlot( + "target", -1, 0, set(seq.qubit_info.keys()) + ) + assert set(seq.available_channels) == available_channels - chs + + seq2 = Sequence(reg, MockDevice) + available_channels = set(seq2.available_channels) + channel_map = { + "dmm_0": "dmm_0", + "dmm_0_1": "dmm_0", + } + seq2.config_detuning_map(det_map, "dmm_0") + # If a DMM was declared but not as an SLM Mask, + # MW channels are not available + assert set(seq2.available_channels) == (available_channels - {"mw_global"}) + seq2.config_detuning_map(det_map, "dmm_0") + assert set(seq2.available_channels) == (available_channels - {"mw_global"}) + assert channel_map.keys() == seq2.declared_channels.keys() + assert set( + seq2._schedule[channel].channel_id + for channel in seq2.declared_channels + ) == set(channel_map.values()) + with pytest.raises(ValueError, match="type 'Microwave' cannot work "): + seq2.declare_channel("mw_ch", "mw_global") + + seq2 = Sequence(reg, MockDevice) + seq2.declare_channel("ch0", "mw_global") + # DMM channels are still available, + # but can only be declared using an SLM Mask + assert set(seq2.available_channels) == {"mw_global", "dmm_0"} + with pytest.raises( + ValueError, + match="cannot work simultaneously with the declared 'Microwave'", + ): + seq2.config_detuning_map(det_map, "dmm_0") + + +def test_slm_declaration(reg, device, det_map): + # Definining an SLM on a Device + seq = Sequence(reg, device) + available_channels = set(seq.available_channels) + assert seq.get_addressed_bases() == () + with pytest.raises(ValueError, match="No DMM dmm_2 in the device"): + seq.config_slm_mask(["q0", "q1", "q3", "q4"], "dmm_2") + seq.config_slm_mask(["q0", "q1", "q3", "q4"]) + assert seq.get_addressed_bases() == tuple() + with pytest.raises( + ValueError, match="SLM mask can be configured only once." + ): + seq.config_slm_mask(["q0", "q1", "q3", "q4"], "dmm_1") + # no channel has been declared + assert len(seq._schedule) == 0 + # dmm_0 no longer appears in available channels + assert set(seq.available_channels) == available_channels - {"dmm_0"} + + # Configuring a DMM after having configured a SLM with the same DMM + seq2 = Sequence(reg, MockDevice) + available_channels = set(seq2.available_channels) + channel_map = { + "dmm_0": "dmm_0", + "dmm_0_1": "dmm_0", + } + seq2.config_slm_mask(["q0", "q1", "q3", "q4"]) + assert set(seq2.declared_channels.keys()) == set() + # If a DMM was declared as an SLM Mask, MW channels are still available + assert set(seq2.available_channels) == available_channels + # If other DMM are configured, the MW channel is no longer available + seq2.config_detuning_map(det_map, "dmm_0") + assert seq2._slm_mask_dmm == "dmm_0" + assert set(seq2.available_channels) == (available_channels - {"mw_global"}) + assert channel_map.keys() == seq2.declared_channels.keys() + assert set( + seq2._schedule[channel].channel_id + for channel in seq2.declared_channels + ) == set(channel_map.values()) + with pytest.raises(ValueError, match="type 'Microwave' cannot work "): + seq2.declare_channel("mw_ch", "mw_global") + + # Configuring an SLM after having configured a DMM with the same DMM + seq2 = Sequence(reg, MockDevice) + seq2.config_detuning_map(det_map, "dmm_0") + seq2.config_slm_mask(["q0", "q1", "q3", "q4"]) + # Name of DMM implementing SLM has a suffix + assert seq2._slm_mask_dmm == "dmm_0_1" + + # Configuring a SLM after having declared a microwave channel + seq2 = Sequence(reg, MockDevice) + seq2.declare_channel("ch0", "mw_global") + # DMM channels are still available, but can be configured using an SLM Mask + assert set(seq2.available_channels) == {"mw_global", "dmm_0"} + assert set(seq2.declared_channels.keys()) == {"ch0"} + seq2.config_slm_mask(["q0", "q1", "q3", "q4"], "dmm_0") + assert set(seq2.available_channels) == {"mw_global"} + assert set(seq2.declared_channels.keys()) == {"ch0"} + + # Declaring a microwave channel after having configured an SLM + seq2 = Sequence(reg, MockDevice) + available_channels = set(seq2.available_channels) + seq2.config_slm_mask(["q0", "q1", "q3", "q4"], "dmm_0") + # If a DMM was declared as an SLM Mask, all channels are still available + assert set(seq2.available_channels) == available_channels + assert set(seq2.declared_channels.keys()) == set() + # If MW channel is defined, only mw channels are available + seq2.declare_channel("ch0", "mw_global") + assert set(seq2.available_channels) == {"mw_global"} + # DMM is not shown as declared + assert set(seq2.declared_channels.keys()) == {"ch0"} + + def test_magnetic_field(reg): seq = Sequence(reg, MockDevice) with pytest.raises( @@ -131,14 +269,32 @@ def test_magnetic_field(reg): with pytest.raises(ValueError, match="can only be set on an empty seq"): seq.set_magnetic_field(1.0, 0.0, 0.0) + # Raises an error if a Global channel is declared (not in xy) seq2 = Sequence(reg, MockDevice) - seq2.declare_channel("ch0", "rydberg_global") # not in XY mode + seq2.declare_channel("ch0", "rydberg_global") with pytest.raises(ValueError, match="can only be set in 'XY Mode'."): seq2.set_magnetic_field(1.0, 0.0, 0.0) + # Same if a dmm channel was configured + seq2 = Sequence(reg, MockDevice) + seq2.config_detuning_map(det_map, "dmm_0") # not in XY mode + with pytest.raises(ValueError, match="can only be set in 'XY Mode'."): + seq2.set_magnetic_field(1.0, 0.0, 0.0) + + # Works if a slm mask was configured seq3 = Sequence(reg, MockDevice) + seq3.config_slm_mask(["q0", "q1"], "dmm_0") seq3.set_magnetic_field(1.0, 0.0, 0.0) # sets seq to XY mode + # dmm_0 doesn't appear because there can only be one in XY mode + # and the SLM is already configured assert set(seq3.available_channels) == {"mw_global"} + assert list(seq3.declared_channels.keys()) == [] + seq3.declare_channel("ch0", "mw_global") + assert list(seq3.declared_channels.keys()) == ["ch0"] + + seq3 = Sequence(reg, MockDevice) + seq3.set_magnetic_field(1.0, 0.0, 0.0) # sets seq to XY mode + assert set(seq3.available_channels) == {"mw_global", "dmm_0"} seq3.declare_channel("ch0", "mw_global") # Does not change to default assert np.all(seq3.magnetic_field == np.array((1.0, 0.0, 0.0))) @@ -165,6 +321,7 @@ def devices(): max_atom_num=100, max_radial_distance=60, min_atom_distance=5, + supports_slm_mask=True, channel_objects=( Raman.Global( 2 * np.pi * 20, @@ -186,6 +343,14 @@ def devices(): max_duration=2**26, ), ), + dmm_objects=( + DMM( + clock_period=4, + min_duration=16, + max_duration=2**26, + bottom_detuning=-20, + ), + ), ) device2 = Device( @@ -195,6 +360,7 @@ def devices(): max_atom_num=100, max_radial_distance=60, min_atom_distance=5, + supports_slm_mask=True, channel_ids=("rmn_local", "rydberg_global"), channel_objects=( Raman.Local( @@ -213,6 +379,14 @@ def devices(): max_duration=2**26, ), ), + dmm_objects=( + DMM( + clock_period=4, + min_duration=16, + max_duration=2**26, + bottom_detuning=-20, + ), + ), ) device3 = VirtualDevice( @@ -220,6 +394,7 @@ def devices(): dimensions=2, rydberg_level=70, min_atom_distance=5, + supports_slm_mask=True, channel_ids=( "rmn_local1", "rmn_local2", @@ -259,6 +434,14 @@ def devices(): max_duration=2**26, ), ), + dmm_objects=( + DMM( + clock_period=4, + min_duration=16, + max_duration=2**26, + bottom_detuning=-20, + ), + ), ) return [device1, device2, device3] @@ -293,6 +476,7 @@ def init_seq( initial_target=None, parametrized=False, mappable_reg=False, + config_det_map=False, ) -> Sequence: register = ( reg.layout.make_mappable_register(len(reg.qubits)) @@ -309,13 +493,45 @@ def init_seq( if parametrized: delay = seq.declare_variable("delay", dtype=int) seq.delay(delay, channel_name) - + if config_det_map: + det_map = reg.define_detuning_map( + { + "q" + str(i): (1 / 4 if i in [0, 1, 3, 4] else 0) + for i in range(10) + } + ) + if mappable_reg: + seq.config_detuning_map(det_map, "dmm_0") + else: + seq.config_slm_mask(["q0"], "dmm_0") return seq +def test_ising_mode( + reg, + device, +): + seq = Sequence(reg, device) + assert not seq._in_ising and not seq._in_xy + seq.declare_channel("ch0", "rydberg_global") + assert seq._in_ising and not seq._in_xy + with pytest.raises(TypeError, match="_in_ising must be a bool."): + seq._in_ising = 1 + with pytest.raises(ValueError, match="Cannot quit ising."): + seq._in_ising = False + + seq2 = Sequence(reg, MockDevice) + seq2.declare_channel("ch0", "mw_global") + assert seq2._in_xy and not seq2._in_ising + with pytest.raises(ValueError, match="Cannot be in ising if in xy."): + seq2._in_ising = True + + @pytest.mark.parametrize("mappable_reg", [False, True]) @pytest.mark.parametrize("parametrized", [False, True]) -def test_switch_device_down(reg, devices, pulses, mappable_reg, parametrized): +def test_switch_device_down( + reg, det_map, devices, pulses, mappable_reg, parametrized +): # Device checkout seq = init_seq( reg, @@ -385,6 +601,49 @@ def test_switch_device_down(reg, devices, pulses, mappable_reg, parametrized): strict=True, ) + # From sequence reusing DMMs to Device without reusable channels + seq = init_seq( + reg, + dataclasses.replace(Chadoq2.to_virtual(), reusable_channels=True), + "global", + "rydberg_global", + None, + parametrized=parametrized, + mappable_reg=mappable_reg, + config_det_map=True, + ) + seq.config_detuning_map(det_map, dmm_id="dmm_0") + assert list(seq.declared_channels.keys()) == [ + "global", + "dmm_0", + "dmm_0_1", + ] + + with pytest.raises( + TypeError, + match="No match for channel dmm_0_1 with the" + " right type, basis and addressing.", + ): + # Can't find a match for the 2nd dmm_0 + seq.switch_device(Chadoq2) + # Strict switch imposes to have same bottom detuning for DMMs + with pytest.raises( + ValueError, + match="No match for channel dmm_0_1 with the" " same bottom_detuning.", + ): + # Can't find a match for the 1st dmm_0 + seq.switch_device( + dataclasses.replace( + Chadoq2, + dmm_objects=( + Chadoq2.dmm_channels["dmm_0"], + dataclasses.replace( + Chadoq2.dmm_channels["dmm_0"], bottom_detuning=-10 + ), + ), + ), + strict=True, + ) seq_ising = init_seq( reg, MockDevice, @@ -503,10 +762,20 @@ def test_switch_device_down(reg, devices, pulses, mappable_reg, parametrized): @pytest.mark.parametrize("mappable_reg", [False, True]) +@pytest.mark.parametrize("trap_id", [20, 38, 50]) @pytest.mark.parametrize("parametrized", [False, True]) +@pytest.mark.parametrize("config_det_map", [False, True]) @pytest.mark.parametrize("device_ind, strict", [(1, False), (2, True)]) def test_switch_device_up( - reg, device_ind, devices, pulses, strict, mappable_reg, parametrized + reg, + device_ind, + devices, + pulses, + strict, + mappable_reg, + trap_id, + parametrized, + config_det_map, ): # Device checkout seq = init_seq( @@ -517,6 +786,7 @@ def test_switch_device_up( None, parametrized=parametrized, mappable_reg=mappable_reg, + config_det_map=config_det_map, ) with pytest.warns( UserWarning, @@ -524,12 +794,12 @@ def test_switch_device_up( "sequence unchanged", ): assert seq.switch_device(Chadoq2)._device == Chadoq2 - # Test non-strict mode assert "ising" in seq.switch_device(devices[0]).declared_channels # Strict: Jump_phase_time & CLock-period criteria - # Jump_phase_time check 1: phase not nill + # Jump_phase_time check 1: phase not null + mod_wvf = ConstantWaveform(100, -10) seq1 = init_seq( reg, devices[device_ind], @@ -538,7 +808,10 @@ def test_switch_device_up( l_pulses=pulses[:2], parametrized=parametrized, mappable_reg=mappable_reg, + config_det_map=config_det_map, ) + if config_det_map: + seq1.add_dmm_detuning(mod_wvf, "dmm_0") seq2 = init_seq( reg, devices[0], @@ -547,13 +820,16 @@ def test_switch_device_up( l_pulses=pulses[:2], parametrized=parametrized, mappable_reg=mappable_reg, + config_det_map=config_det_map, ) + if config_det_map: + seq2.add_dmm_detuning(mod_wvf, "dmm_0") new_seq = seq1.switch_device(devices[0], strict) build_kwargs = {} if parametrized: build_kwargs["delay"] = 120 if mappable_reg: - build_kwargs["qubits"] = {"q0": 50} + build_kwargs["qubits"] = {"q0": trap_id} if build_kwargs: seq1 = seq1.build(**build_kwargs) @@ -562,15 +838,43 @@ def test_switch_device_up( s1 = sample(new_seq) s2 = sample(seq1) s3 = sample(seq2) - nested_s1 = s1.to_nested_dict()["Global"]["ground-rydberg"] - nested_s2 = s2.to_nested_dict()["Global"]["ground-rydberg"] - nested_s3 = s3.to_nested_dict()["Global"]["ground-rydberg"] - + nested_s1_glob = s1.to_nested_dict()["Global"]["ground-rydberg"] + nested_s2_glob = s2.to_nested_dict()["Global"]["ground-rydberg"] + nested_s3_glob = s3.to_nested_dict()["Global"]["ground-rydberg"] + if config_det_map: + nested_s1_loc = s1.to_nested_dict()["Local"]["ground-rydberg"]["q0"] + nested_s2_loc = s2.to_nested_dict()["Local"]["ground-rydberg"]["q0"] + nested_s3_loc = s3.to_nested_dict()["Local"]["ground-rydberg"]["q0"] # Check if the samples are the same for key in ["amp", "det", "phase"]: - np.testing.assert_array_equal(nested_s1[key], nested_s3[key]) + np.testing.assert_array_equal(nested_s1_glob[key], nested_s3_glob[key]) if strict: - np.testing.assert_array_equal(nested_s1[key], nested_s2[key]) + np.testing.assert_array_equal( + nested_s1_glob[key], nested_s2_glob[key] + ) + if config_det_map: + for nested_s_loc in [ + nested_s1_loc[key], + nested_s2_loc[key], + nested_s3_loc[key], + ]: + if key != "det": + assert np.all(nested_s_loc == 0.0) + elif mappable_reg: + # modulates detuning map on trap ids 0, 1, 3, 4 + mod_trap_ids = [20, 32, 54, 66] + assert np.all( + nested_s_loc[:100] + == (-2.5 if trap_id in mod_trap_ids else 0) + ) + else: + # first pulse is covered by SLM Mask + np.all( + nested_s_loc[:252] + == -10 * np.max(pulses[0].amplitude.samples) + ) + # Modulated pulse added afterwards + assert np.all(nested_s_loc[252:352] == -10) # Channels with the same mod_bandwidth and fixed_retarget_t seq = init_seq( @@ -835,7 +1139,7 @@ def test_block_if_measured(reg, call, args): getattr(seq, call)(*args) -def test_str(reg, device, mod_device): +def test_str(reg, device, mod_device, det_map): seq = Sequence(reg, mod_device) seq.declare_channel("ch0", "raman_local", initial_target="q0") pulse = Pulse.ConstantPulse(500, 2, -10, 0, post_phase_shift=np.pi) @@ -848,6 +1152,10 @@ def test_str(reg, device, mod_device): seq.add_eom_pulse("ch1", duration=100, phase=0, protocol="no-delay") seq.delay(500, "ch1") + seq.config_detuning_map(det_map, "dmm_0") + seq.add_dmm_detuning(ConstantWaveform(100, -10), "dmm_0") + seq.add_dmm_detuning(RampWaveform(100, -10, 0), "dmm_0") + seq.measure("digital") msg_ch0 = ( "Channel: ch0\nt: 0 | Initial targets: q0 | Phase Reference: 0.0 " @@ -864,9 +1172,16 @@ def test_str(reg, device, mod_device): "\nt: 100->600 | Detuned Delay | Detuning: -1 rad/µs" ) + msg_det_map = ( + f"\n\nChannel: dmm_0\nt: 0 | Initial targets: {targets} " + "| Phase Reference: 0.0 " + f"\nt: 0->100 | Detuning: -10 rad/µs | Targets: {targets}" + f"\nt: 100->200 | Detuning: Ramp(-10->0 rad/µs) | Targets: {targets}" + ) + measure_msg = "\n\nMeasured in basis: digital" print(seq) - assert seq.__str__() == msg_ch0 + msg_ch1 + measure_msg + assert seq.__str__() == msg_ch0 + msg_ch1 + msg_det_map + measure_msg seq2 = Sequence(Register({"q0": (0, 0), 1: (5, 5)}), device) seq2.declare_channel("ch1", "rydberg_global") @@ -982,7 +1297,7 @@ def test_sequence(reg, device, patch_plt_show): @pytest.mark.parametrize("qubit_ids", [["q0", "q1", "q2"], [0, 1, 2]]) -def test_config_slm_mask(qubit_ids, device): +def test_config_slm_mask(qubit_ids, device, det_map): reg: Register | MappableRegister trap_ids = [(0, 0), (10, 10), (-10, -10)] reg = Register(dict(zip(qubit_ids, trap_ids))) @@ -1017,6 +1332,13 @@ def test_config_slm_mask(qubit_ids, device): assert seq._slm_mask_targets == {"q0", "q2"} else: assert seq._slm_mask_targets == {0, 2} + assert not seq._schedule + with pytest.raises(ValueError, match="DMM dmm_0 is not available."): + seq.config_detuning_map(det_map, "dmm_0") + seq.declare_channel("rydberg_global", "rydberg_global") + assert set(seq._schedule.keys()) == {"dmm_0", "rydberg_global"} + assert seq._schedule["dmm_0"].detuning_map.weights[0] == 0.5 + assert seq._schedule["dmm_0"].detuning_map.weights[2] == 0.5 with pytest.raises(ValueError, match="configured only once"): seq.config_slm_mask(targets) @@ -1031,7 +1353,7 @@ def test_config_slm_mask(qubit_ids, device): fail_seq.config_slm_mask({trap_ids[0], trap_ids[2]}) -def test_slm_mask(reg, patch_plt_show): +def test_slm_mask_in_xy(reg, patch_plt_show): reg = Register({"q0": (0, 0), "q1": (10, 10), "q2": (-10, -10)}) targets = ["q0", "q2"] pulse1 = Pulse.ConstantPulse(100, 10, 0, 0) @@ -1041,8 +1363,10 @@ def test_slm_mask(reg, patch_plt_show): seq_xy1 = Sequence(reg, MockDevice) seq_xy1.declare_channel("ch_xy", "mw_global") seq_xy1.add(pulse1, "ch_xy") + seq_xy1.add(pulse2, "ch_xy") seq_xy1.config_slm_mask(targets) assert seq_xy1._slm_mask_time == [0, 100] + assert "dmm_0" not in seq_xy1._schedule # Set mask and then add an XY pulse to the schedule seq_xy2 = Sequence(reg, MockDevice) @@ -1050,6 +1374,7 @@ def test_slm_mask(reg, patch_plt_show): seq_xy2.declare_channel("ch_xy", "mw_global") seq_xy2.add(pulse1, "ch_xy") assert seq_xy2._slm_mask_time == [0, 100] + assert "dmm_0" not in seq_xy2._schedule # Check that adding extra pulses does not change SLM mask time seq_xy2.add(pulse2, "ch_xy") @@ -1092,25 +1417,184 @@ def test_slm_mask(reg, patch_plt_show): seq_xy2.draw() -def test_draw_register(reg, patch_plt_show): - # Draw 2d register from sequence +@pytest.mark.parametrize("dims3D", [False, True]) +@pytest.mark.parametrize("draw_qubit_amp", [True, False]) +@pytest.mark.parametrize("draw_qubit_det", [True, False]) +@pytest.mark.parametrize("draw_register", [True, False]) +@pytest.mark.parametrize("mode", ["input", "input+output"]) +@pytest.mark.parametrize("mod_bandwidth", [0, 10]) +def test_slm_mask_in_ising( + reg, + patch_plt_show, + dims3D, + mode, + mod_bandwidth, + draw_qubit_amp, + draw_qubit_det, + draw_register, +): reg = Register({"q0": (0, 0), "q1": (10, 10), "q2": (-10, -10)}) + if dims3D: + reg = Register3D( + {"q0": (0, 0, 0), "q1": (10, 10, 0), "q2": (-10, -10, 0)} + ) + det_map = reg.define_detuning_map({"q0": 0.2, "q1": 0.8, "q2": 0.0}) + targets = ["q0", "q2"] + pulse1 = Pulse.ConstantPulse(100, 10, 0, 0) + pulse2 = Pulse.ConstantPulse(200, 10, 0, 0) + mymockdevice = ( + MockDevice + if mod_bandwidth == 0 + else dataclasses.replace( + MockDevice, + dmm_objects=(DMM(mod_bandwidth=mod_bandwidth),), + channel_objects=( + dataclasses.replace( + MockDevice.channels["rydberg_global"], + mod_bandwidth=mod_bandwidth, + ), + dataclasses.replace( + MockDevice.channels["rydberg_local"], + mod_bandwidth=mod_bandwidth, + ), + MockDevice.channels["raman_global"], + ), + channel_ids=("rydberg_global", "rydberg_local", "raman_global"), + ) + ) + # Set mask when ising pulses are already in the schedule + seq1 = Sequence(reg, mymockdevice) + seq1.declare_channel("ryd_glob", "rydberg_global") + if not draw_register: + with patch("matplotlib.figure.Figure.savefig"): + with pytest.warns( + UserWarning, + match="Provide a register and select draw_register", + ): + seq1.draw(draw_qubit_det=True, fig_name="empty_rydberg") + seq1.config_detuning_map(det_map, "dmm_0") + if mod_bandwidth == 0: + with pytest.warns() as record: + seq1.draw( + draw_qubit_det=True, draw_interp_pts=False, mode="output" + ) # Drawing Sequence with only a DMM + assert len(record) == 7 + assert np.all( + str(record[i].message).startswith( + "No modulation bandwidth defined" + ) + for i in range(6) + ) + assert str(record[6].message).startswith( + "Can't display modulated quantities per qubit" + ) + seq1.draw(mode, draw_qubit_det=draw_qubit_det, draw_interp_pts=False) + seq1.add_dmm_detuning(RampWaveform(300, -10, 0), "dmm_0") + # Same function with add is longer + seq1.add(Pulse.ConstantAmplitude(0, RampWaveform(300, -10, 0), 0), "dmm_0") + # pulse is added on rydberg global with a delay (protocol is "min-delay") + seq1.add(pulse1, "ryd_glob") # slm pulse between 0 and 400 + seq1.add(pulse2, "ryd_glob") + seq1.config_slm_mask(targets) + mask_time = 700 + 2 * mymockdevice.channels["rydberg_global"].rise_time + assert seq1._slm_mask_time == [0, mask_time] + assert seq1._schedule["dmm_0_1"].slots[1].type == Pulse.ConstantPulse( + mask_time, 0, -100, 0 + ) + # Possible to modulate dmm_0_1 after slm declaration + seq1.add_dmm_detuning(RampWaveform(300, 0, -10), "dmm_0_1") + assert seq1._slm_mask_time == [0, mask_time] + # Possible to add pulses afterwards, + seq1.declare_channel("ryd_loc", "rydberg_local", ["q0", "q1"]) + seq1.add(pulse2, "ryd_loc", protocol="no-delay") + assert seq1._slm_mask_time == [0, mask_time] + with patch("matplotlib.figure.Figure.savefig"): + seq1.draw( + mode, + draw_qubit_det=draw_qubit_det, + draw_qubit_amp=draw_qubit_amp, + draw_interp_pts=False, + draw_register=draw_register, + fig_name="local_quantities", + ) + seq1.declare_channel("raman_glob", "raman_global") + if draw_qubit_det or draw_qubit_amp: + with pytest.raises( + NotImplementedError, + match="Can only draw qubit contents for channels in rydberg basis", + ): + seq1.draw( + mode, + draw_qubit_det=draw_qubit_det, + draw_qubit_amp=draw_qubit_amp, + ) + # Set mask and then add ising pulses to the schedule + seq2 = Sequence(reg, MockDevice) + seq2.config_slm_mask(targets) + seq2.declare_channel("ryd_glob", "rydberg_global") + seq2.config_detuning_map(det_map, "dmm_0") # configured as dmm_0_1 + with pytest.raises( + ValueError, match="You should add a Pulse to a Global Channel" + ): + seq2.add_dmm_detuning(RampWaveform(300, -10, 0), "dmm_0") + with pytest.raises( + ValueError, match="You should add a Pulse to a Global Channel" + ): + seq2.add(Pulse.ConstantPulse(300, 0, -10, 0), "dmm_0") + seq2.add_dmm_detuning(RampWaveform(300, -10, 0), "dmm_0_1") # not slm + seq2.add(pulse2, "ryd_glob") # slm pulse between 0 and 500 + assert seq2._slm_mask_time == [0, 500] + assert seq2._schedule["dmm_0"].slots[1].type == Pulse.ConstantPulse( + 500, 0, -100, 0 + ) + + # Check that adding extra pulses does not change SLM mask time + seq2.add(pulse2, "ryd_glob") + assert seq2._slm_mask_time == [0, 500] + + seq5 = Sequence(reg, MockDevice) + seq5.declare_channel("ch", "rydberg_global") + var = seq5.declare_variable("var") + seq5.add(Pulse.ConstantPulse(200, var, 0, 0), "ch") + assert seq5.is_parametrized() + seq5.config_slm_mask(targets) + seq5_str = seq5.serialize() + seq5_ = Sequence.deserialize(seq5_str) + assert str(seq5) == str(seq5_) + + +@pytest.mark.parametrize("ch_name", ["rydberg_global", "mw_global"]) +def test_draw_register_det_maps(reg, ch_name, patch_plt_show): + # Draw 2d register from sequence + reg_layout = RegisterLayout( + [(0, 0), (10, 10), (-10, -10), (20, 20), (30, 30), (40, 40)] + ) + det_map = reg_layout.define_detuning_map( + {0: 0, 1: 0, 2: 0, 3: 0.5, 4: 0.5} + ) + reg = reg_layout.define_register(0, 1, 2, qubit_ids=["q0", "q1", "q2"]) targets = ["q0", "q2"] pulse = Pulse.ConstantPulse(100, 10, 0, 0) seq = Sequence(reg, MockDevice) - seq.declare_channel("ch_xy", "mw_global") - seq.add(pulse, "ch_xy") + seq.declare_channel(ch_name, ch_name) + seq.add(pulse, ch_name) + if ch_name == "rydberg_global": + seq.config_detuning_map(det_map, "dmm_0") seq.config_slm_mask(targets) seq.draw(draw_register=True) + seq.draw(draw_detuning_maps=True) + seq.draw(draw_register=True, draw_detuning_maps=True) # Draw 3d register from sequence reg3d = Register3D.cubic(3, 8) seq3d = Sequence(reg3d, MockDevice) - seq3d.declare_channel("ch_xy", "mw_global") - seq3d.add(pulse, "ch_xy") + seq3d.declare_channel(ch_name, ch_name) + seq3d.add(pulse, ch_name) seq3d.config_slm_mask([6, 15]) - seq3d.measure(basis="XY") + seq3d.measure(basis="XY" if ch_name == "mw_global" else "ground-rydberg") seq3d.draw(draw_register=True) + seq3d.draw(draw_detuning_maps=True) + seq3d.draw(draw_register=True, draw_detuning_maps=True) def test_hardware_constraints(reg, patch_plt_show): @@ -1216,7 +1700,8 @@ def test_hardware_constraints(reg, patch_plt_show): seq.draw(mode="input+output") -def test_mappable_register(patch_plt_show): +@pytest.mark.parametrize("with_dmm", [False, True]) +def test_mappable_register(det_map, patch_plt_show, with_dmm): layout = TriangularLatticeLayout(100, 5) mapp_reg = layout.make_mappable_register(10) seq = Sequence(mapp_reg, Chadoq2) @@ -1241,19 +1726,32 @@ def test_mappable_register(patch_plt_show): seq.__str__() # Warning if sequence has Global channels and a mappable register seq.declare_channel("ryd_glob", "rydberg_global") - warn_message_global = ( + global_channels = ["ryd_glob"] + if with_dmm: + seq.config_detuning_map(det_map, "dmm_0") + global_channels.append("dmm_0") + warn_message_rydberg = [ "Showing the register for a sequence with a mappable register." - + "Target qubits of channel ryd_glob will be defined in build." - ) - with pytest.warns(UserWarning, match=warn_message_global): + + f"Target qubits of channel {ch} will be defined in build." + for ch in global_channels + ] + with pytest.warns(UserWarning) as records: seq.__str__() + assert len(records) == len(global_channels) + assert [ + str(records[i].message) for i in range(len(global_channels)) + ] == warn_message_rydberg # Index of mappable register can be accessed seq.phase_shift_index(np.pi / 4, 0, basis="digital") # 0 -> q0 seq.target_index(2, "ryd_loc") # 2 -> q2 seq.add(Pulse.ConstantPulse(100, 1, 0, 0), "ryd_glob") + if with_dmm: + seq.add_dmm_detuning(RampWaveform(100, -10, 0), "dmm_0") seq.add(Pulse.ConstantPulse(200, 1, 0, 0), "ram") seq.add(Pulse.ConstantPulse(100, 1, 0, 0), "ryd_loc") assert seq._last("ryd_glob").targets == set(reserved_qids) + if with_dmm: + assert seq._last("dmm_0").targets == set(reserved_qids) assert seq._last("ram").targets == {"q0"} assert seq._last("ryd_loc").targets == {"q2"} @@ -1261,7 +1759,17 @@ def test_mappable_register(patch_plt_show): seq.draw(draw_register=True) # Can draw if 'draw_register=False' - seq.draw() + if with_dmm: + with pytest.raises( + NotImplementedError, + match=( + "Sequences with a DMM channel can't be sampled while " + "their register is mappable." + ), + ): + seq.draw() + else: + seq.draw() with pytest.raises(ValueError, match="'qubits' must be specified"): seq.build() diff --git a/tests/test_sequence_sampler.py b/tests/test_sequence_sampler.py index 511e3de2..2d8c4afb 100644 --- a/tests/test_sequence_sampler.py +++ b/tests/test_sequence_sampler.py @@ -14,14 +14,19 @@ from __future__ import annotations from copy import deepcopy +from dataclasses import replace +from typing import Literal import numpy as np import pytest import pulser import pulser_simulation +from pulser.channels.dmm import DMM from pulser.devices import Device, MockDevice from pulser.pulse import Pulse +from pulser.register.mappable_reg import MappableRegister +from pulser.register.register_layout import RegisterLayout from pulser.sampler import sample from pulser.sequence._seq_drawer import draw_samples from pulser.waveforms import BlackmanWaveform, RampWaveform @@ -277,17 +282,32 @@ def test_eom_modulation(mod_device, disable_eom): np.testing.assert_allclose(want, got, atol=1e-10) -@pytest.fixture -def seq_with_SLM() -> pulser.Sequence: +def test_seq_with_DMM_and_map_reg(): + reg = MappableRegister( + RegisterLayout([[-4, 0], [4, 0], [0, -4], [0, 4]]), *["q0", "q1"] + ) + seq = pulser.Sequence(reg, MockDevice) + seq.config_detuning_map( + reg.define_detuning_map({i: 0.25 for i in range(4)}), "dmm_0" + ) + with pytest.raises( + NotImplementedError, + match="DMM channel can't be sampled while their register is mappable.", + ): + sample(seq) + + +def seq_with_SLM( + ch_name: Literal["mw_global", "rydberg_global"] +) -> pulser.Sequence: q_dict = { "batman": np.array([-4.0, 0.0]), # sometimes masked "superman": np.array([4.0, 0.0]), # always unmasked } - reg = pulser.Register(q_dict) - seq = pulser.Sequence(reg, MockDevice) + seq = pulser.Sequence(reg, replace(MockDevice, dmm_objects=(DMM(),))) - seq.declare_channel("ch0", "rydberg_global") + seq.declare_channel("ch0", ch_name) seq.config_slm_mask(["batman"]) seq.add( @@ -298,34 +318,58 @@ def seq_with_SLM() -> pulser.Sequence: Pulse.ConstantDetuning(BlackmanWaveform(200, np.pi / 2), 0.0, 0.0), "ch0", ) - seq.measure() + seq.measure("ground-rydberg" if ch_name == "rydberg_global" else "XY") return seq -def test_SLM_samples(seq_with_SLM): +def test_SLM_samples(): + seq = seq_with_SLM("mw_global") pulse = Pulse.ConstantDetuning(BlackmanWaveform(200, np.pi / 2), 0.0, 0.0) a_samples = pulse.amplitude.samples def z() -> np.ndarray: - return np.zeros(seq_with_SLM.get_duration()) + return np.zeros(seq.get_duration()) + + want: dict = { + "Global": {"XY": {"amp": z(), "det": z(), "phase": z()}}, + "Local": { + "XY": { + "superman": {"amp": z(), "det": z(), "phase": z()}, + } + }, + } + want["Global"]["XY"]["amp"][200:400] = a_samples + want["Local"]["XY"]["superman"]["amp"][0:200] = a_samples + + got = sample(seq).to_nested_dict() + assert_nested_dict_equality(got, want) + + seq = seq_with_SLM("rydberg_global") + with pytest.raises(ValueError, match="'qubits' must be defined"): + seq._schedule["dmm_0"].get_samples() want: dict = { "Global": {"ground-rydberg": {"amp": z(), "det": z(), "phase": z()}}, "Local": { "ground-rydberg": { "superman": {"amp": z(), "det": z(), "phase": z()}, + "batman": {"amp": z(), "det": z(), "phase": z()}, } }, } + want["Global"]["ground-rydberg"]["amp"][0:200] = a_samples want["Global"]["ground-rydberg"]["amp"][200:400] = a_samples - want["Local"]["ground-rydberg"]["superman"]["amp"][0:200] = a_samples - got = sample(seq_with_SLM).to_nested_dict() + want["Local"]["ground-rydberg"]["batman"]["det"][0:200] = np.full_like( + a_samples, -10 * np.max(a_samples) + ) + + got = sample(seq).to_nested_dict() assert_nested_dict_equality(got, want) -def test_SLM_against_simulation(seq_with_SLM): - assert_same_samples_as_sim(seq_with_SLM) +def test_SLM_against_simulation(): + assert_same_samples_as_sim(seq_with_SLM("rydberg_global")) def test_samples_repr(seq_rydberg): @@ -408,8 +452,17 @@ def test_phase_sampling(mod_device): @pytest.mark.parametrize("draw_phase_shifts", [True, False]) @pytest.mark.parametrize("draw_phase_curve", [True, False]) def test_draw_samples( - mod_seq, modulation, draw_phase_area, draw_phase_curve, draw_phase_shifts + mod_device, + mod_seq, + modulation, + draw_phase_area, + draw_phase_curve, + draw_phase_shifts, ): + reg = pulser.Register.from_coordinates(np.array([[0.0, 0.0]]), prefix="q") + seq = pulser.Sequence(reg, mod_device) + with pytest.raises(RuntimeError, match="Can't draw an empty sequence."): + draw_samples(sample(seq, modulation=modulation)) sampled_seq = sample(mod_seq, modulation=modulation) draw_samples( sampled_seq, diff --git a/tests/test_simulation.py b/tests/test_simulation.py index 54d0029a..27c7c9e9 100644 --- a/tests/test_simulation.py +++ b/tests/test_simulation.py @@ -997,68 +997,54 @@ def test_mask_nopulses(): assert sim_empty.samples_obj._slm_mask.end == 0 -def test_mask_equals_remove(): - """Check that masking is equivalent to removing the masked qubits. +def test_mask_equals_remove_xy(): + """Check that masking is equivalent to removing the masked qubits in XY. - A global pulse acting on three qubits of which one is masked, should be + A global MW pulse acting on three qubits of which one is masked, should be equivalent to acting on a register with only the two unmasked qubits. """ reg_three = Register({"q0": (0, 0), "q1": (10, 10), "q2": (-10, -10)}) reg_two = Register({"q0": (0, 0), "q1": (10, 10)}) pulse = Pulse.ConstantPulse(100, 10, 0, 0) - local_pulse = Pulse.ConstantPulse(200, 10, 0, 0) - for channel_type in ["mw_global", "rydberg_global", "raman_global"]: - # Masked simulation - seq_masked = Sequence(reg_three, MockDevice) - if channel_type == "mw_global": - seq_masked.set_magnetic_field(0, 1.0, 0.0) - else: - # Add a local channel acting on a masked qubit (has no effect) - seq_masked.declare_channel( - "local", - channel_type[: -len("global")] + "local", - initial_target="q2", - ) - seq_masked.add(local_pulse, "local") - seq_masked.declare_channel("ch_masked", channel_type) - masked_qubits = ["q2"] - seq_masked.config_slm_mask(masked_qubits) - seq_masked.add(pulse, "ch_masked") - sim_masked = QutipEmulator.from_sequence(seq_masked) - # Simulation cannot be run on a device not having an SLM mask - with pytest.raises( - ValueError, - match="Samples use SLM mask but device does not have one.", - ): - QutipEmulator(sampler.sample(seq_masked), reg_three, IroiseMVP) - # Simulation cannot be run on a register not defining "q2" - with pytest.raises( - ValueError, - match="The ids of qubits targeted in SLM mask", - ): - QutipEmulator(sampler.sample(seq_masked), reg_two, MockDevice) - # Simulation on reduced register - seq_two = Sequence(reg_two, MockDevice) - if channel_type == "mw_global": - seq_two.set_magnetic_field(0, 1.0, 0.0) - seq_two.declare_channel("ch_two", channel_type) - if channel_type != "mw_global": - seq_two.delay(local_pulse.duration, "ch_two") - seq_two.add(pulse, "ch_two") - sim_two = QutipEmulator.from_sequence(seq_two) - - # Check equality - for t in sim_two.sampling_times: - ham_masked = sim_masked.get_hamiltonian(t) - ham_two = sim_two.get_hamiltonian(t) - assert ham_masked == qutip.tensor(ham_two, qutip.qeye(2)) - - -def test_mask_two_pulses(): + # Masked simulation + seq_masked = Sequence(reg_three, MockDevice) + seq_masked.set_magnetic_field(0, 1.0, 0.0) + seq_masked.declare_channel("ch_masked", "mw_global") + masked_qubits = ["q2"] + seq_masked.config_slm_mask(masked_qubits) + seq_masked.add(pulse, "ch_masked") + sim_masked = QutipEmulator.from_sequence(seq_masked) + # Simulation cannot be run on a device not having an SLM mask + with pytest.raises( + ValueError, + match="Samples use SLM mask but device does not have one.", + ): + QutipEmulator(sampler.sample(seq_masked), reg_three, IroiseMVP) + # Simulation cannot be run on a register not defining "q2" + with pytest.raises( + ValueError, + match="The ids of qubits targeted in SLM mask", + ): + QutipEmulator(sampler.sample(seq_masked), reg_two, MockDevice) + # Simulation on reduced register + seq_two = Sequence(reg_two, MockDevice) + seq_two.set_magnetic_field(0, 1.0, 0.0) + seq_two.declare_channel("ch_two", "mw_global") + seq_two.add(pulse, "ch_two") + sim_two = QutipEmulator.from_sequence(seq_two) + + # Check equality + for t in sim_two.sampling_times: + ham_masked = sim_masked.get_hamiltonian(t) + ham_two = sim_two.get_hamiltonian(t) + assert ham_masked == qutip.tensor(ham_two, qutip.qeye(2)) + + +def test_mask_two_pulses_xy(): """Similar to test_mask_equals_remove, but with more pulses afterwards. - Three global pulses act on a three qubit register, with one qubit masked + Three XY global pulses act on a three qubit register, with one qubit masked during the first pulse. """ reg_three = Register({"q0": (0, 0), "q1": (10, 10), "q2": (-10, -10)}) @@ -1066,47 +1052,49 @@ def test_mask_two_pulses(): pulse = Pulse.ConstantPulse(100, 10, 0, 0) no_pulse = Pulse.ConstantPulse(100, 0, 0, 0) - for channel_type in ["mw_global", "rydberg_global", "raman_global"]: - # Masked simulation - seq_masked = Sequence(reg_three, MockDevice) - seq_masked.declare_channel("ch_masked", channel_type) - masked_qubits = ["q2"] - seq_masked.config_slm_mask(masked_qubits) - seq_masked.add(pulse, "ch_masked") # First pulse: masked - seq_masked.add(pulse, "ch_masked") # Second pulse: unmasked - seq_masked.add(pulse, "ch_masked") # Third pulse: unmasked - sim_masked = QutipEmulator.from_sequence(seq_masked) - - # Unmasked simulation on full register - seq_three = Sequence(reg_three, MockDevice) - seq_three.declare_channel("ch_three", channel_type) - seq_three.add(no_pulse, "ch_three") - seq_three.add(pulse, "ch_three") - seq_three.add(pulse, "ch_three") - sim_three = QutipEmulator.from_sequence(seq_three) - - # Unmasked simulation on reduced register - seq_two = Sequence(reg_two, MockDevice) - seq_two.declare_channel("ch_two", channel_type) - seq_two.add(pulse, "ch_two") - seq_two.add(no_pulse, "ch_two") - seq_two.add(no_pulse, "ch_two") - sim_two = QutipEmulator.from_sequence(seq_two) - - ti = seq_masked._slm_mask_time[0] - tf = seq_masked._slm_mask_time[1] - for t in sim_masked.sampling_times: - ham_masked = sim_masked.get_hamiltonian(t) - ham_three = sim_three.get_hamiltonian(t) - ham_two = sim_two.get_hamiltonian(t) - if ti <= t <= tf: - assert ham_masked == qutip.tensor(ham_two, qutip.qeye(2)) - else: - assert ham_masked == ham_three + # Masked simulation + seq_masked = Sequence(reg_three, MockDevice) + seq_masked.declare_channel("ch_masked", "mw_global") + masked_qubits = ["q2"] + seq_masked.config_slm_mask(masked_qubits) + seq_masked.add(pulse, "ch_masked") # First pulse: masked + seq_masked.add(pulse, "ch_masked") # Second pulse: unmasked + seq_masked.add(pulse, "ch_masked") # Third pulse: unmasked + sim_masked = QutipEmulator.from_sequence(seq_masked) + + # Unmasked simulation on full register + seq_three = Sequence(reg_three, MockDevice) + seq_three.declare_channel("ch_three", "mw_global") + seq_three.add(no_pulse, "ch_three") + seq_three.add(pulse, "ch_three") + seq_three.add(pulse, "ch_three") + sim_three = QutipEmulator.from_sequence(seq_three) + + # Unmasked simulation on reduced register + seq_two = Sequence(reg_two, MockDevice) + seq_two.declare_channel("ch_two", "mw_global") + seq_two.add(pulse, "ch_two") + seq_two.add(no_pulse, "ch_two") + seq_two.add(no_pulse, "ch_two") + sim_two = QutipEmulator.from_sequence(seq_two) + + ti = seq_masked._slm_mask_time[0] + tf = seq_masked._slm_mask_time[1] + for t in sim_masked.sampling_times: + ham_masked = sim_masked.get_hamiltonian(t) + ham_three = sim_three.get_hamiltonian(t) + ham_two = sim_two.get_hamiltonian(t) + if ti <= t <= tf: + assert ham_masked == qutip.tensor(ham_two, qutip.qeye(2)) + else: + assert ham_masked == ham_three def test_mask_local_channel(): - seq_ = Sequence(Register.square(2, prefix="q"), MockDevice) + seq_ = Sequence( + Register.square(2, prefix="q"), + MockDevice, + ) seq_.declare_channel("rydberg_global", "rydberg_global") pulse = Pulse.ConstantPulse(1000, 10, 0, 0) seq_.config_slm_mask(["q0", "q3"]) @@ -1118,11 +1106,49 @@ def test_mask_local_channel(): assert seq_._slm_mask_time == [0, 1000] assert seq_._slm_mask_targets == {"q0", "q3"} - sim = QutipEmulator.from_sequence(seq_) - for qty in ("amp", "det", "phase"): - assert np.all(sim.samples["Local"]["digital"]["q0"][qty] == 0.0) - assert "q3" not in sim.samples["Local"]["digital"] + assert np.array_equal( + sim.samples["Global"]["ground-rydberg"]["amp"], + np.concatenate((pulse.amplitude.samples, [0])), + ) + assert np.array_equal( + sim.samples["Global"]["ground-rydberg"]["det"], + np.concatenate((pulse.detuning.samples, [0])), + ) + assert np.all(sim.samples["Global"]["ground-rydberg"]["phase"] == 0.0) + qubits = ["q0", "q1", "q2", "q3"] + masked_qubits = ["q0", "q3"] + for q in qubits: + if q in masked_qubits: + assert np.array_equal( + sim.samples["Local"]["ground-rydberg"][q]["det"], + np.concatenate( + (-10 / len(masked_qubits) * pulse.amplitude.samples, [0]) + ), + ) + else: + assert np.all( + sim.samples["Local"]["ground-rydberg"][q]["det"] == 0.0 + ) + assert np.all(sim.samples["Local"]["ground-rydberg"][q]["amp"] == 0.0) + assert np.all( + sim.samples["Local"]["ground-rydberg"][q]["phase"] == 0.0 + ) + + assert np.array_equal( + sim.samples["Local"]["digital"]["q0"]["amp"], + np.concatenate((pulse2.amplitude.samples, [0])), + ) + assert np.array_equal( + sim.samples["Local"]["digital"]["q0"]["det"], + np.concatenate((pulse2.detuning.samples, [0])), + ) + assert np.all( + np.isclose( + sim.samples["Local"]["digital"]["q0"]["phase"], + np.concatenate((np.pi * np.ones(1000), [0])), + ) + ) def test_effective_size_intersection(): @@ -1148,26 +1174,58 @@ def test_effective_size_intersection(): ) -def test_effective_size_disjoint(): +@pytest.mark.parametrize( + "channel_type", + [ + "mw_global", + "rydberg_global", + "raman_global", + ], +) +def test_effective_size_disjoint(channel_type): simple_reg = Register.square(2, prefix="atom") - rise = Pulse.ConstantPulse(1500, 0, 0, 0) - for channel_type in ["mw_global", "rydberg_global", "raman_global"]: - np.random.seed(15092021) - seq = Sequence(simple_reg, MockDevice) - seq.declare_channel("ch0", channel_type) - seq.add(rise, "ch0") - seq.config_slm_mask(["atom1"]) - sim = QutipEmulator.from_sequence(seq, sampling_rate=0.01) - sim.set_config(SimConfig("SPAM", eta=0.4)) - assert sim._bad_atoms == { - "atom0": True, - "atom1": False, - "atom2": True, - "atom3": False, - } - assert sim.get_hamiltonian(0) == 0 * sim.build_operator( - [("I", "global")] + amp = 1 + rise = Pulse.ConstantPulse(1500, amp, 0, 0) + np.random.seed(15092021) + seq = Sequence(simple_reg, MockDevice) + seq.declare_channel("ch0", channel_type) + seq.add(rise, "ch0") + seq.config_slm_mask(["atom1"]) + assert seq._slm_mask_time == [0, 1500] + sim = QutipEmulator.from_sequence(seq, sampling_rate=0.01) + sim.set_config(SimConfig("SPAM", eta=0.4)) + assert sim._bad_atoms == { + "atom0": True, + "atom1": False, + "atom2": True, + "atom3": False, + } + if channel_type == "mw_global": + assert sim.get_hamiltonian(0) == 0.5 * amp * sim.build_operator( + [(qutip.sigmax(), ["atom3"])] + ) + else: + basis = ( + "ground-rydberg" if channel_type == "rydberg_global" else "digital" + ) + assert np.array_equal( + sim.samples["Local"][basis]["atom1"]["amp"], + np.concatenate((rise.amplitude.samples, [0])), + ) + assert np.array_equal( + sim.samples["Local"][basis]["atom3"]["amp"], + np.concatenate((rise.amplitude.samples, [0])), + ) + # SLM + assert np.all( + sim.samples["Local"]["ground-rydberg"]["atom1"]["det"] + == -10 * np.concatenate((rise.amplitude.samples, [0])) ) + if channel_type == "raman_global": + assert np.all(sim.samples["Local"][basis]["atom1"]["det"] == 0.0) + assert np.all(sim.samples["Local"][basis]["atom3"]["det"] == 0.0) + for q in ["atom1", "atom3"]: + assert np.all(sim.samples["Local"][basis][q]["phase"] == 0.0) def test_simulation_with_modulation(mod_device, reg, patch_plt_show): diff --git a/tutorials/advanced_features/Local addressability with DMM.ipynb b/tutorials/advanced_features/Local addressability with DMM.ipynb new file mode 100644 index 00000000..daa16505 --- /dev/null +++ b/tutorials/advanced_features/Local addressability with DMM.ipynb @@ -0,0 +1,333 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Local Adressability with DMM" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from dataclasses import replace\n", + "from matplotlib import pyplot as plt\n", + "from pulser.channels.dmm import DMM\n", + "from pulser.devices import AnalogDevice\n", + "from pulser.register import Register\n", + "from pulser.register.register_layout import RegisterLayout\n", + "from pulser.register.mappable_reg import MappableRegister\n", + "from pulser.register.weight_maps import DetuningMap\n", + "from pulser.sampler import sampler\n", + "from pulser.sequence import Sequence\n", + "from pulser.pulse import Pulse\n", + "from pulser.waveforms import ConstantWaveform, RampWaveform" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Even when working with **global** addressing channels, the **detuning** of individual qubits can be addressed **locally** by using a specific channel named the **Detuning Map Modulator** or `DMM`.\n", + "\n", + "This `Channel` applies a `Global` pulse of **zero amplitude** and **negative detuning** on a `DetuningMap`. The `DetuningMap` consists of a set of weights on specific sites that dictate how the detuning applied by the `DMM` is distributed.\n", + "\n", + "This modulation of the `DetuningMap` by the `DMM` Channel is equivalent to adding a term $-\\frac{\\hbar}{2}\\sum_{i}\\epsilon_{i}\\Delta(t)\\sigma^{z}_{i}$ to the Ising Hamiltonian. Here, $\\Delta(t)$ is the detuning applied on the `DMM`, and $(\\epsilon_i)_{i}$ are the weights defined in the `DetuningMap` for each atom." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define a Detuning Map" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A `DetuningMap` associates a set of locations with a set of weights. The weights $(\\epsilon_i)_i$ have to be positive, between 0 and 1, and their sum has to be equal to 1. The locations are the trap coordinates to address." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "trap_coordinates = [(0.0, 0.0), (0.0, 5.0), (5.0, 0.0), (5.0, 5.0)]\n", + "weights_1 = [0.5, 0.25, 0.25, 0] # between 0 and 1, sum equal to 1\n", + "weights_2 = [1 / 3, 1 / 3, 1 / 3, 0] # between 0 and 1, sum equal to 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `DetuningMap` can be defined from a `RegisterLayout`, a `Register` or a `MappableRegister` by using the `define_detuning_map` method. All it takes is a mapping between trap/qubit IDs and weights." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "register_layout = RegisterLayout(trap_coordinates)\n", + "detuning_map = register_layout.define_detuning_map(\n", + " {i: weights_1[i] for i in range(4)} # mapping between trap ids and weights\n", + ")\n", + "\n", + "map_reg = MappableRegister(register_layout)\n", + "det_map_from_map_reg = map_reg.define_detuning_map(\n", + " {i: weights_1[i] for i in range(4)} # mapping between trap ids and weights\n", + ")\n", + "\n", + "register = Register.from_coordinates(\n", + " trap_coordinates, center=False, prefix=\"q\"\n", + ")\n", + "det_map_from_reg = register.define_detuning_map(\n", + " {\n", + " f\"q{i}\": weights_1[i] for i in range(4)\n", + " } # mapping between qubit ids and weights\n", + ")\n", + "\n", + "detuning_map.draw(labels=[0, 1, 2, 3])\n", + "assert detuning_map == det_map_from_map_reg\n", + "assert detuning_map == det_map_from_reg" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The traps are represented by a grey dot and highlighted by a grey square, whose shade is proportional to the value of the associated weight. It is possible to display the value of the weights by specifying a list of `labels`. If the weight is null then no `DMM` is applied: the atom is not highlighted by a grey square and the value of the weight is not shown when `labels` are specified." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "detuning_map_2 = register_layout.define_detuning_map(\n", + " {i: weights_2[i] for i in range(4)} # mapping between trap ids and weights\n", + ")\n", + "detuning_map_2.draw(labels=[0, 1, 2, 3])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DMM Channel and Device" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A `DMM` Channel is a `Channel` that accepts pulses of zero amplitude and detuning below 0 and above `bottom_detuning`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dmm = DMM(\n", + " clock_period=4,\n", + " min_duration=16,\n", + " max_duration=2**26,\n", + " mod_bandwidth=8,\n", + " bottom_detuning=-20, # detuning between 0 and -20 rad/µs\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `DMM` channels are defined separately from the other channels of the device. They are defined as a list in `dmm_objects`. They can be accessed via the property `dmm_channels` of the device, where an id is automatically associated to each `DMM` with the format `dmm_{index of appearance in dmm_objects}`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mock_device = replace(\n", + " AnalogDevice.to_virtual(),\n", + " dmm_objects=(dmm, DMM()),\n", + " reusable_channels=True,\n", + ")\n", + "print(mock_device.dmm_channels)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DMM in a Sequence" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In a `Sequence` defined with a `Device` having `dmm_objects`, the `DMM` channels can be configured using `config_detuning_map`. This configuration associates a `DMM` - referenced by `dmm_id` in the `Device`- with a `DetuningMap`, under a `dmm_name` in the `Sequence`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "seq = Sequence(register, mock_device)\n", + "seq.config_detuning_map(detuning_map, \"dmm_0\")\n", + "print(seq.declared_channels)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `dmm_name` is generated automatically. It is `dmm_id` if no detuning map has been associated to the `DMM` referenced by `dmm_id` in the device, otherwise it takes the suffix `_{number of times dmm_id has been declared so far}`. For instance, if we associate a new detuning map to `dmm_0` in the previous sequence, the name of this new declared channel will be `dmm_0_1`. To be noted that configuring a `dmm_id` multiple times is only possible in a `VirtualDevice` with `reusable_channels=True`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "seq.config_detuning_map(detuning_map_2, \"dmm_0\")\n", + "print(seq.declared_channels.keys())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's now apply a global detuning on the detuning maps. This is done by calling `add_dmm_detuning` and providing a waveform (the detuning $\\Delta(t)$ to modulate the `DetuningMap` with) and the `dmm_name` to use (provides the `DetuningMap` and checks that $\\Delta(t)$ is in agreement with the characteristics of the corresponding `DMM`)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "seq.add_dmm_detuning(ConstantWaveform(100, -10), \"dmm_0\")\n", + "seq.add_dmm_detuning(ConstantWaveform(100, -10), \"dmm_0_1\")\n", + "seq.draw(draw_detuning_maps=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Once a detuning map is configured, it is not possible to define a `Microwave` channel. However, it is possible to declare `Rydberg` and `Raman` channels. Let's declare a `Rydberg.Global` channel in our sequence." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "seq.declare_channel(\"ryd_glob\", \"rydberg_global\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Be careful with the protocols that are used to add the pulses to `Channels` and `DMM`:\n", + " \n", + " - The protocol to add a waveform to a `DMM` is by default `\"no-delay\"`, meaning that it will be added straight after the last pulse, without caring about the other channels. This is why the pulse on `dmm_0_1` is added at $t=0$. It can be changed to other values by defining the `protocol` argument.\n", + " - The protocol to add a pulse to a `Rydberg` or a `Raman` channel is `\"min-delay\"`, meaning that the pulse will by default be added after the end of the pulse of a `DMM`. It can be switched to `\"no-delay\"`.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "seq.add(\n", + " Pulse.ConstantPulse(100, 10, 4.5, 0), \"ryd_glob\", protocol=\"no-delay\"\n", + ") # added at the beginning with protocol \"no delay\"\n", + "seq.add_dmm_detuning(RampWaveform(200, -10, 0), \"dmm_0\") # added at t=100\n", + "seq.add(\n", + " Pulse.ConstantPulse(100, 5, 0, 0), \"ryd_glob\", protocol=\"no-delay\"\n", + ") # added at t=100\n", + "seq.draw()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It is possible to display the amplitude and detuning per qubits, by setting to `True` the arguments `draw_qubit_amp` and `draw_qubit_det`. This adds two plots after the drawing of the sequence. The first one shows the evolution of these quantities along time for groups of qubits experiencing the same amplitude or detuning. The second represents these group of qubits on a register. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "seq.draw(\n", + " mode=\"input+output\", # \"input\" only shows input signals, \"input+output\"\n", + " draw_qubit_det=True,\n", + " draw_qubit_amp=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see that by combining a global pulse with a positive detuning and pulses on the `DMM` channels, it is possible to have **positive local detuning** (see the detuning on `q3` from `t=0` to `t=100ns`).\n", + "\n", + "It can also be noted that from `t=100ns` to `t=300ns`, the local detuning is defined by the detuning ramp applied on `detuning_map`, hence it is locally a detuning ramp, going to 0 with a slope defined by the weight of `detuning_map` on each atom. This is why the detuning on `q3` during this duration is constant equal to 0 and that `q1` and `q2` have the same local detuning." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pulserenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb b/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb index a34ce30e..3683fdb0 100644 --- a/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb +++ b/tutorials/advanced_features/State Preparation with the SLM Mask.ipynb @@ -48,7 +48,15 @@ "id": "a0adcb3d", "metadata": {}, "source": [ - "Now create the sequence and add a global $\\sigma^x$ pulse of area $\\pi$ in XY mode:" + "## SLM Mask in XY mode" + ] + }, + { + "cell_type": "markdown", + "id": "c727c9f7", + "metadata": {}, + "source": [ + "Let's now create the sequence and add a global $\\sigma^x$ pulse of area $\\pi$ in XY mode:" ] }, { @@ -90,7 +98,7 @@ "id": "fa5c5fbb", "metadata": {}, "source": [ - "To set up the SLM mask all we need to do is to create a list that contains the name of the qubits that we want to mask, and pass it to the $\\verb:Sequence.config_slm_mask:$ method:" + "To set up the SLM mask all we need to do is to pass to the $\\verb:Sequence.config_slm_mask:$ method a list that contains the name of the qubits that we want to mask and the name of the `DMM` channel to use to configure the SLM Mask. The latter is taken as `dmm_0` by default. The device `MockDevice` contains one `DMM`, so `dmm_0` does indeed exist." ] }, { @@ -163,6 +171,7 @@ }, { "cell_type": "markdown", + "id": "268d32a2", "metadata": {}, "source": [ "Now run the simulation and print the final state as given by Pulser:" @@ -171,6 +180,7 @@ { "cell_type": "code", "execution_count": null, + "id": "1af830f5", "metadata": {}, "outputs": [], "source": [ @@ -182,6 +192,7 @@ }, { "cell_type": "markdown", + "id": "084d93b9", "metadata": {}, "source": [ "As expected, the two states agree up to numerical errors." @@ -189,13 +200,15 @@ }, { "cell_type": "markdown", + "id": "caf52b73", "metadata": {}, "source": [ - "## Notes" + "### Notes on XY mode" ] }, { "cell_type": "markdown", + "id": "40376d73", "metadata": {}, "source": [ "Since the SLM mask is mostly useful for state preparation, its use in Pulser is restricted to the first pulse in the sequence. This can be seen by adding an extra pulse in the previous example and drawing the sequence:" @@ -204,6 +217,7 @@ { "cell_type": "code", "execution_count": null, + "id": "e8c4fa49", "metadata": {}, "outputs": [], "source": [ @@ -213,6 +227,7 @@ { "cell_type": "code", "execution_count": null, + "id": "ecc4cef4", "metadata": {}, "outputs": [], "source": [ @@ -221,15 +236,17 @@ }, { "cell_type": "markdown", + "id": "f5260b2c", "metadata": {}, "source": [ - "This example also illustrates the fact that the SLM mask can be configured at any moment during the creation of a sequence (either before or after adding pulses) and it will automatically latch to the first pulse.
\n", + "This example also illustrates the fact that in XY mode, the SLM mask can be configured at any moment during the creation of a sequence (either before or after adding pulses) and it will automatically latch to the first pulse.
\n", "However, in order to reflect real hardware constraints, the mask can be configured only once. Trying to configure the mask a second time will raise an error:" ] }, { "cell_type": "code", "execution_count": null, + "id": "527ffd80", "metadata": {}, "outputs": [], "source": [ @@ -241,9 +258,153 @@ }, { "cell_type": "markdown", + "id": "662398b5", + "metadata": {}, + "source": [ + "## SLM Mask in Ising mode" + ] + }, + { + "cell_type": "markdown", + "id": "09b56b15", + "metadata": {}, + "source": [ + "In Ising mode, configuring an SLM Mask with a `DMM` labeled `dmm_id` in the device internally configures a detuning map using `config_detuning_map` (see notebook [\"Local Addressability with DMM\"](dmm.nblink) for an introduction) with `dmm_id` and a `DetuningMap` **distributing the applied detuning equally over all the masked qubits**.\n", + "\n", + "For instance in the last example qubits \"q1\" and \"q2\" are masked, so we expect a `DetuningMap` associating to the trap location of \"q0\" the weight 0, and to the trap locations of \"q1\" and \"q2\" the weight $1/2 = 0.5$:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2d6c9a1f", + "metadata": {}, + "outputs": [], + "source": [ + "# Create the sequence\n", + "seq = Sequence(reg, MockDevice)\n", + "\n", + "# Declare a global Rydberg channel and add the pi pulse\n", + "seq.declare_channel(\"ch\", \"rydberg_global\")\n", + "pulse = Pulse.ConstantDetuning(BlackmanWaveform(200, np.pi), 0, 0)\n", + "seq.add(pulse, \"ch\")\n", + "# Mask the last two qubits\n", + "masked_qubits = [\"q1\", \"q2\"]\n", + "seq.config_slm_mask(masked_qubits, \"dmm_0\")\n", + "seq._schedule[\"dmm_0\"].detuning_map.draw([0, 1, 2])" + ] + }, + { + "cell_type": "markdown", + "id": "4c2b1809", + "metadata": {}, + "source": [ + "We can see that the shade of the square covering qubit 1 and 2 are the same, and that no square covers qubit 0: the detuning map created is exactly the one wanted.\n", + "\n", + "Now what happens at the pulse level ?\n", + "\n", + "If the SLM Mask is configured while some pulses had already been added to the sequence- as it is the case in the previous example- a pulse of constant detuning is immediately applied on the detuning map configured for the SLM Mask. The value of this detuning is very large compared to the amplitude of the first pulse in the schedule (ideally, -10 times this amplitude, or `bottom_detuning` of the `DMM` if `bottom_detunig` is defined and its value is higher). " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aa4101a2", + "metadata": {}, + "outputs": [], + "source": [ + "seq.draw(draw_detuning_maps=True, draw_qubit_amp=True, draw_qubit_det=True)" + ] + }, + { + "cell_type": "markdown", + "id": "0d74c18c", + "metadata": {}, + "source": [ + "At the qubit level, you can see that all the qubits receive the $\\sigma^x$ pulse of area $\\pi$ in amplitude, but only qubit `q0` is on resonance (detuning is constant equal to 0) and will change state. Detuning on \"q1\" and \"q2\" being not of infinite values, they are not perfectly masked and therefore the state resulting from this sequence is not exactly the state $(0,1)^T \\otimes (1,0)^T \\otimes (1,0)^T$. However it is very close to this state and represents better the experiment." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5a0a77a3", + "metadata": {}, + "outputs": [], + "source": [ + "sim = QutipEmulator.from_sequence(seq)\n", + "results = sim.run()\n", + "\n", + "results.get_final_state()" + ] + }, + { + "cell_type": "markdown", + "id": "97d869c1", + "metadata": {}, + "source": [ + "Note: Of course, you can add pulses to channels or dmm after the SLM Mask:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5692c7e4", + "metadata": {}, + "outputs": [], + "source": [ + "seq.add(pulse, \"ch\")\n", + "seq.add_dmm_detuning(-BlackmanWaveform(200, np.pi), \"dmm_0\")\n", + "seq.draw()" + ] + }, + { + "cell_type": "markdown", + "id": "e689706c", + "metadata": {}, + "source": [ + "If the first operation performed in the sequence is the configuration of the SLM Mask, then the `DMM` used for the configuration of the SLM Mask cannot be used until a pulse is added on an Ising channel. The first pulse added will define the SLM Mask. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "331eb4e3", + "metadata": {}, + "outputs": [], + "source": [ + "# Create the sequence\n", + "seq = Sequence(reg, MockDevice)\n", + "# Mask the last two qubits\n", + "masked_qubits = [\"q1\", \"q2\"]\n", + "seq.config_slm_mask(masked_qubits, \"dmm_0\")\n", + "# Declare a global Rydberg channel and add the pi pulse\n", + "seq.declare_channel(\"ch\", \"rydberg_global\")\n", + "\n", + "try:\n", + " seq.add_dmm_detuning(-BlackmanWaveform(200, np.pi), \"dmm_0\")\n", + "except ValueError as err:\n", + " print(err)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7bd874cb", + "metadata": {}, + "outputs": [], + "source": [ + "# Masked pulse\n", + "seq.add(pulse, \"ch\")\n", + "seq.draw()" + ] + }, + { + "cell_type": "markdown", + "id": "00276258", "metadata": {}, "source": [ - "Although the example shown here makes use of the XY mode, everything translates directly to the Ising mode as well with the same syntax and restrictions." + "### Note:\n", + "As in XY mode, you cannot configure the SLM Mask twice. However, be careful that in Ising mode, the moment you configure the SLM Mask matters: once configured, the masked pulse is never changed." ] } ], @@ -263,7 +424,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.11.3" } }, "nbformat": 4, diff --git a/tutorials/quantum_simulation/Bayesian Optimisation for antiferromagnetic state preparation.ipynb b/tutorials/quantum_simulation/Bayesian Optimisation for antiferromagnetic state preparation.ipynb index f29133c5..a130f345 100644 --- a/tutorials/quantum_simulation/Bayesian Optimisation for antiferromagnetic state preparation.ipynb +++ b/tutorials/quantum_simulation/Bayesian Optimisation for antiferromagnetic state preparation.ipynb @@ -73,14 +73,12 @@ }, { "data": { - "image/png": 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\n", 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", 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d8KfPHfnYv1wI//vI4Mfo7u4e/EVEREREREaJ1p5Wbll+C3e9dBfTiqZxRuUZFGcVkxPIweP0ZLo8GaE8Tg8l4RJKwiUsnryY7mg3tW21bKnbwlfu/Qq1HbXMGzePD8z9AJfNuoyAJ5DpkkXGvJEYhk0F1g08/wDwsjHmMsuyzgVuY4SEYYkUeN+i7YDXCcnU4MeYO3fu4C8iIiIiIjLCbandws+f/jkrdq1g4fiFfHLRJw/2AtMsMBlKlmUR9ASZUjSFKUVTiCfjtPW2sa1+G7e9eBs33n8jRVlFvHfOe/ngvA9SmlOa6ZJFxqSRGIbZgdjA8/OBRwee7wIKMlLRcZhSBA+/Ah84483HHn4FJg/BXSXXrl3LkiVLBn8hEREREZERJpVK8cTmJ/jZ0z+jJ9rD/Mr5fGbxZ8jx52hmjpw0TruT/GA++cF8zpp4Ft393exp3sNLu1/i1hW3AnDZzMv42IKPMbNkpprwi5wkIzEM2wR8xrKsh0mHYQdmgpUAzRmr6hh94WL49K3QH0830XfYIZGEv66EL94JP7lq8GPk5uYO/iIiIiIiIiNILBHj7pfv5hfP/IJxOeNYOH4hxeFiIoEILocr0+XJGGazbIS8IWaXzWZ22Wx6Y73Ut9ezYf8GPnH7J+iKdnHpzEu5ZsE1zCmfo2BM5AQaiWHY14D7ga8AdxhjNg7svxJYlamijtU1i2BXA1x3C3ziFogEobkrfezfLoePnzP4MYLB4OAvIiIiIiIyAnT3d3PL8lv4wwt/YE7ZHD56+kfJDeSSG8hV83IZlnwuH+PzxzM+fzyXzbqM+o56NtRs4NN//DTtve1cPONirl54NadXnK5gTGSIjbgwzBiz3LKsPCBkjGk77NBvgd4MlXVcvvUB+MRieHIjNHVBXhAunAUVebBqF8yfMLjr7927l4qKiiGpVURERERkOGrpbuGXz/ySe9fey/zK+Vx/9vXk+HPI8ecoQJARw+1wMy53HONyx3HpzEtp6Ghg/b71fPEvX6S5u5lLZ17KpxZ9ilmlszJdqsioMOLCMABjTBJoe8PuJPDVgY8RY1wefOq81++LxmHhf0Hyj4O79rRp0wZ3ARERERGRYWpf6z5+/OSPeWbrM5w18Sw+fc6niQQihLyhTJcmMihOu5PSnFJKc0q5eObFNHQ0sG7fOj5+28eJxqO8f+77+eTZn6Q8tzzTpYqMWCMuDLMs68G3OFQKTGSEhWFvxQzBNfbu3UtBwYi5p4CIiIiIyDuqaqniu498l7V717Jo0iL++Zx/JjeYS8Ctpvgy+hwejF0y4xJqWmtYXbWaS39xKT6Xj6sWXMU1C68hx5+T6VJFRpQRF4YBLW/YtgPjgdnAdSe/nBNjKCZ09/X1DcFVREREREQy7/AQbPGUxXzy7E+SG8zF5/JlujSRk8LlcB3sMfbuOe9md+Nulm9fzs1Lb6Y8p5xPnv1J3j/3/bpRhMhRGHFhmDHmiIGXZVlfJB2G3XlyKxq+5s6dm+kSREREREQGpaqliu898j1W713NkslLuP7s68kL5uF1eTNdmkjGeJweppdMZ3rJdLr7u9lSt4XbXryNb973TS6YdgGfPfezzCmfk+kyRYatEReGvY0HgR9kuoijdcPv3/pYMjU0Y6xdu5YlS5YMzcVERERERE6i6pZqvvvId1m1ZxVLpizhU4s+RV4wD4/Tk+nSRIaVgCfA/Mr5zKuYR3N3M6v3rOa6268jmUry8TM/zvVnX0/YF850mSLDymgKw+YCawd5jUuAX5Beevl73hyulQN3AOGBc74OPHo8A8WTb3/8mkXHc9XXy8/PH/xFREREREROorr2Or7z8Hd4afdLLJmyhBsW3UAkGNFMMJF3YLNs5Afzedcp7+KiGRexu2k3L+58kf9b+n/MLJnJvyz5Fy6cfiE2my3TpYpk3IgLwyzL+uURdhcAlwOPHn7cGPOFY7i0HbgZuBCoAVaTnm225bBz/h24B/g1MJ10EFZxDGMcdNunj+ezjo3LpbXiIiIiIjIytPe288PHfsjDrz7MeVPP45Nnf5JIMKKeYCLHwWl3MqVwClMKp9DZ18mGfRv47iPf5fN//jwfmf8RPnfu58gL5WW6TJGMGXFhGDDrLfavAiIDH3DsN2ScD+wEdg9s/wV4N68Pwwxw4F7NWUDtMY5x0LItcN8a+MU16W3fdRCNHzq+9EY4Z9rxXj2tpqaGiRMnDu4iIiIiIiInUG+0l18++0vufOlOFk9azA3n3EBeMA+/25/p0kRGhZA3xKLJizhz4pnsb9vP8zufZ+EPFjKzeCb/euG/cs7kc7CsobiFm8jIMeLCMGPMuSfo0iXAvsO2a4Az3nDOfwNPAp8H/MAFxzvYzU/BR888tO1ywFNfTz9fuRN++cTgw7CZM2cO7gIiIiIiIidIPBHnDy/8gV8++0sWjF/ADYtuID+UT9ATzHRpIqOS3WanPLecq3Kv4srZV7Kuah3/9rd/ozvazfVnX88N59xAwBPIdJkiJ8WICcMsy/opcB/wojFmiFrMH7OPALcDPwEWAncBM4FjrmftHrj9sKWSFnDWlPTz0yrh/54ebKmwfft2IpHIO58oIiIiInKSpFIp/rr6r3z/se8zq2TWwbtDZvuyM12ayJgR9ARZPGUxZ008i70te3lu+3P86tlfsWjSIr580ZeZXTY70yWKnFAjJgwDvKSXLrosy3oEuB94whjTN0TX3w+UHbZdOrDvcNeTbrIP8BLgIb0ss/FYB2vuAv9hN8K58zOHnntd0Nh5rFd8s2TyHbr0i4iIiIicRE9veZpv3PcNKnIruOqMq8gP5ZPrz9USLZEMcdgdTMyfyMT8ibT3tLNy90quufUafC4fX734q7xnznvUcF9GpRHzf7Ux5jPGmBLgXaRDqu8CzZZlPWhZ1icsyxps97/VwCSgEnABHybdQP9w1cD5A8+nkQ7Dmo5nMK8LaloObV9x2qHnNS3p44M1a9ZbtVcTERERETl5Nu/fzKU/v5QfPf4j3j373Vw8/WKmFk0lEogoCBMZJsL+MJfMuoT/uPw/uGTGJfzi6V8w9T+m8qPHf0RPtCfT5YkMqREThh1gjFlljLnRGDMTmA08B1wL1FiW9YJlWV+xLKvkOC6dAD4HPAFsJX3XyM3At4ErB875MvApYAPw54Fxj7VRPwCLpqT7hh3JzU+ljw/W+vXrB38REREREZHjVN9Rzyfv+CTX3n4tp5afyvvnvp8ZxTMoyCrAZo24X0VExgS3w81p407jXy/8Vz533ud4addLzPivGfzLH/+Fvc17M12eyJAYScsk38QYs5N0/66fDMwMu4JDwdWPj+OSjw58YFnWraSXPzYaY/5zYF890AvkA3uB1cYcVxbGN94NZ38LWnvgwwugJAdqWuEvL8FdL8AL/3Vcl32doqKiwV9EREREROQY9UR7+PETP+betfdywdQLuG7hdRRkFeByDMHyBxE5Kew2O5WRSirPrqS1p5Xl25dz8c8vZkLeBL5x6TdYNHlRpksUOW7W8YY5o51lWecA3cCdA7PQsCzrR0CrMeYHlmV9Hcg2xnzt7a4zc+ZME+uoZvsPu9507KmN8C+3wa7GdAN9A4zPh5uvhYtPeetr3rEcnul8L3f+6R9v+xq2bdvGlClDMMVMREREROQoJFNJ7lhxBz958icsnLCQU0pOoSCrAJ/Ll+nSRGQI9MX6WLN3DUu3LcUYw9cv/Trvn/t+LXeWjLAsa60xZt7xfO6ImBk2MEvrqBhjPjEUYxpjlluWVfGG3e8Glgw8vwNYBrxtGOZwONjXFiUaB7fz9ccunAU7fgo76qGpEyJBmHwUk7mqWmwUlJe943l1dXUKw0RERETkpHhy85N8875vMjFvItedmZ4JFvaFM12WiAwhr8vLosmLWDBhAVtqt/DLZ3/JfzzwH/y/C/4f1599PQ77iIgYREbGzDDLsh56w65zgBSwcWB7Jun+Z8uNMVcyRAbCsIcPmxnWbowJDzy3gLYD229l3rx5xmOP89nTX+UjZw6+pv4YnPbffn59xyMsXrz4bc9tb28nHH7b8kREREREBmXz/s18+d4vg4GzJ51NcVYxkaAa44uMBclUkt1Nu3li8xPsbNzJJxd9ki+e/0V8bs0GlRNv1M8MM8ZcceC5ZVnfAPqA64wxPQP7/MAfOBSOnYyajGVZR0wSLcu6AbgBoLy8nLvvvpv3Xnkxe5v7edecFLkBONafDWIJ2FAFP33Sx6x557Jo0Tuvz964ceNRnSciIiIicqxae1r5z/v/k5V7VnLxjIspzyknP5ivmSEiY4jdZmdSwSQm5k+kpq2Gp7Y8xYz/msEH532Qr1/ydXICOZkuUeSIRsTMsMNZllUHnG+M2fKG/TOAZ4wxhUM4VgWvnxm2DVhijKmzLKsIWGaMedt1iPPmzTNr1qxhw4YN/Obmn7P02Sfp7Dr229I67HYmTqjkgx/5BJ+64QYcjnf+IWPFihWceeYQTEcTERERERmQSCb47fLfcvPSmzl/6vlMKZhCYVYhbqc706WJyDDQ2NnI01ufZuXulVw04yK+dcW3KAwP2a/pIgcNZmbYSAzDuoD3GmOefsP+C4B/GGNCQzhWBa8Pw/4XaDmsgX6OMebf3u4aB8KwTGhubiYSiWRkbBHJvLtX3s2N991IdWs15TnlfO+93+OqBVdluiwRERnBnt7yNF/7+9eYWjiVuRVzKQwVEvQEM12WiAxDHb0dPPPaMzy3/TnOm3oe37ryW5Rkl2S6LBlFxloYdjtwPvBVYOXA7gXAD4Glxphrh2icP5Nulh8BGoD/Au4H7gHKgSrgQ8aY1re7TibDsGXLlrFkyZKMjC0imXX3yru54a4b6I31Htznc/m45epbFIiJiMgx29m4k3/967/SF+/j3MnnUhQuIhJQXzAReWddfV08vfVplm1fxuLJi/nOe75DaXZppsuSUWCshWFe4CfAJwAnYAFx0j3DvmKM6X2bTz/pMhmG7dy5k4kTJ2ZkbBE5OsYYemO9dEe76e7vpjvaTV+sj1gyRjQRJZZ4/WM0EaU/3p9+Ho8SS8ZIpVIkTRJjDCmTwhjDb5f/lq7+rjeNF/KE+MpFX8HtdONxevA6vQQ9QbK8WWR5swj7wgcffS6ffskRERnjOvs6+e7D3+XJLU9yycxLqIxUUhAqwG6zZ7o0ERlhuqPdPL3laZZuW8qiSYv47nu+S1lOWabLkhFs1DfQP5wxpg/4F8uyvgpMGNi960AzfTkkFotlugSRUS2ZStLR10FbTxttvQMfPW209LTQ0t1CS08LrT2ttPe209XfdTDoMhiMMQcf3Q43bqcbt8ONy+HCaXNis9mwW3ZsNhs26/XPnXYnDpsDu82O3WbHZtmwsMACy7KwsI4YhAF09ndS3VpNMpUkkUoQT8aJJWOHwrZ4lL54H/3xfmKJGJZlYbfZyfXnUhAqoChcREm4JP2RXUJFbgWl2aVqliwiMsqkUinueOkOfvzEj1k0aRHXn309RVlF6gsmIsct4A7wnlPfwwXTL+DZrc+y5H+XcObEM/nue77LuNxxmS5PxpgRNzMMwLIsBzCf9HJF1+HHjDF3ZqSot6BlkiIjhzGG9t52GrsaaehsOPhY215LfUf9wX19sT5SJgWA1+XF5/LhcXrwODwHQy2vM73f7/Ljc6ePu+wunHbnwdlWB4KsA48Hwi6bZUuHUJYdy7IObh94fjSuv+N6mrqa3rQ/L5jHHz7+h9ftS5kUyVTy4AyzRDJxMCxLpBIkkgl6oj109XfR0d9BZ28nnf2ddEe76ejroL23HSwIe8NU5FYwIW8CkwomMa1oGlMKpxD2hQf19yIiIifXiztf5Mv3fJnynHLmV8ynKFxEyDtkbXlFRID0TLFntz7Ls689y+Ipi/n+e79PQVZBpsuSEWSsLZOcCjwEVJJeIpkkPcMtDkSHsoH+UMhkGNbV1UUwqIamIgCxRIza9lpq2mrY376ffa372Nuyl32t+9jfvp++WB+QDreC7iB+tx+vy4vH4SHoCRLyhgi6gwQ9QVyOdAZvt9lx2p3YbXYcdsfB2VoOmyPjywuXbVvGzUtvJpqIHtzndrj57LmfZcmUJYO+vjEmPassETu4pLOrv4u2njaau5tp7m6mrbeNpq4m+uP9ZPuzmVo4lRnFM5hVMouZJTMpzS7N+J+TiIgcsq91H1+996vUdtRywbQLKA4Xkx/M19dqETmhuqPdPLn5SZZuW8qVs6/kW1d+i2x/dqbLkhFgrIVhjwPtwPVAPTAHyAJ+Dfy7MeapjBV3BJoZJnJydPd3s6d5D3ua97CraRc7G3eyu3k3dR11xBNxLMsi25dNljcLn8tHwB0g7AuT7csm7AsfnLHltDtx2p24HC4cNsfrZnKNNMu2LeOulXfR3NVMJBjh6gVXD0kQdjSMMemQLJ7ucdbe205DV0N6dl1nI03dTXT2dRIJRDil7BROH3c68yrmMa1o2sGwUURETo7eaC8/euJH/H3d37lkxiVMyJtAfigfp92Z6dJEZAxp72vnsY2P8eLOF7l6wdV849Jv4Pf4M12WDGNjLQxrARYbYzZZltUBzDfGbLMsazHwK2PMKRku8XUyGYa9/PLLnHHGGRkZW2SoJVNJqlqq2Nm4kz3Ne9jZuJOdjTupaq0iGo/itDuJBCJk+bIIeoLk+HKI+COE/eH0UkS7HbfdjdPhxO1wD4vZW2NVMpWkL9ZHX7yP1u7W9Ey9tn3Ud9TT3N2M0+FkRvEMzhx/JosmL2Jm8UycDv1CJiIy1Iwx/G3t3/j2Q99mwfgFzCqZRUFWAT6XL9OlicgY1tzVzEMbHmJd9To+s+Qz/OuF/6o3S+WIxloY1grMM8bstixrJ3CDMeZZy7ImABuNMcPqu3cmw7CGhgYKCrTmWkYOYwyNXY1sr9/O9obtbK3bytb6rVS3VpNKpYgEIuQEcgi6g2T5ssgL5JHjzzk4g+vwJvRH21tLho9oIkpvtJeOvg5q22vZ27KXmrYaGjobCHlDnF5xOosmLeLMCWcyLnecwkwRkUHYWLORL/7li4S8IRaOX0hBqIDcQG6myxIROai2vZYHNzzIa3Wv8ZWLv8Knz/k0Npt+xpdDxloYthz4mTHmPsuy/gTkAv8DfAo4RTPDDtEySRmukqkkuxp3sbl2Mxv3b2Rz7WZ2Nu6kL9ZH0BMkL5hH2Bcmx59DQbCAbF82DrsDl8OF2+nG4/Do7oVjRCwRoyfaQ3N3M1UtVexp3kNtRy3tve1MLpjMkilLuGDaBcwum43dZs90uSIiw15rTyv/cf9/sHrvai6deSkl2SXkB/P1NVREhiVjDFUtVdy//n7qOur4/vu+z7vnvDvTZckwMdbCsIsBvzHmH5ZljQceAaYAzcCHjDHLMlnfG2UyDNu7dy8VFRUZGVsE0rdlr26tZtP+TWzav4n1+9bzWv1rxJIx8oP55AXzyPZlUxAqID+Qj9OR7tXlcXrwOD3qVSJvYoyhL95HV18XNe01B5fNNnQ2UJpdyjmTzuHC6Rcyv3I+bqc70+WKiAwbyVSSW5bfwk3P3sQF0y5gUsEkCkOF+lopIiNCyqTYUruFf6z7By6Hi198+BfMqziuDERGkTEVhh2JZVk5QJsZhi8mk2HYxo0bmTVrVkbGlrGns6+TDfs28Mq+V1hbtZbNtZvpjfaSG8glL5hHji+HwqxCCkIFOO1OPE5P+m6NTo+WNMqgxBIxuvq7qG2vPRiO7W/fTyQQ4YJpF3D57MuZO26uZj2IyJi1fPtyvnzPl5lcMJm55XPJz8ony5uV6bJERI5ZIpng5T0vc/8r9zOjeAY/+6efUZ5bnumyJEPGTBhmWZYTeAG4xhizLdP1HA0tk5TRqL6jnleqX2Fd1TpWV61mR8MOXA4XpeFScgO5FGUVUZRVdHBZo8/lU+glJ00imaCrv4u6jjq21W9je8N26jrqmJg/kYumX8Tlsy9ncsFk9RwTkVFvX+s+vnLvV2jsbOSCaRdQmFVIJBjR92MRGfGi8ShPb32aJzY/wbvnvJtvX/ltQr5QpsuSk2zMhGEAlmU1AmcbY7ZnupajkckwrKuri2AwmJGxZXQwxrC/bT+r9q5i1Z5VrNm7hpr2GsLeMEVZRUQCEUqzS8kL5OF0OPG5fHhdXi1vlGElnozT0dtBVUsV2xq2sbNxJ229bZxafirvOuVdXD7rciLBSKbLFBEZMv3xfv73if/lnjX3cNnMy6iIVBycmS0iMpp09nfy0PqHWLlnJZ8/7/N88fwvqrfwGDLWwrD/BTDGfDXTtRwNzQyTkaS9t501e9fw8u6XWbF7BbuadpHrz6Usu4zcQC5lOWWE3KH0bC+3D5/Lp3eXZcSJxqO09bSxs2knW+u3srNxJ26Hm4unX8z7Tnsf8yrm6U5FIjIiGWN4YP0D/OcD/8kZlWcws3gm+Vn5BNyBTJcmInJC1bbX8o91/6C6tZoff/DHvOuUd2W6JDkJxloY9n/AVcAeYC3Qc/hxY8wXMlHXW8lkGLZmzRrmzVNTQTmyaDzKqzWv8vKel1mxawWv1ryK0+5kXM448oJ5lOeUkxvIxe1w43f78bq8Cr5k1DHG0BPtob6jnk21m9hat5WGzgbmlM/hPXPew+WnXE62PzvTZYqIvKMttVv44l++iNfp5eyJZxMJRogEIloSLiJjhjGGLbVb+Ouav5Lrz+Xmq25mSuGUTJclJ9BYC8OWvs1hY4w576QVcxQyGYbV1tZSXFyckbFl+GnuambFrhU8v+N5Xtj5Al39XZTnlFMQLKA4XExxuBinw0nAHcDn8qnZuIxJ8WSc9t52ttVvY0vdFnY27sTv9nPJzEv4p3n/xMySmfrFUkSGlfbedv77wf/mhZ0vcNmsyyjJKqEgq0Dfx0VkzEokEyzfvpwHNjzAZTMv4/vv+z5Br9oHjUZjKgwbabRMUjLBGMPOxp28sPMFntv+HOuq1uGyu6iIVFCYVUhlbiV+tx+fy4ff7cflcGW6ZJFh58Cssf1t+9lUu4nNdZvp6OtgyeQlfPj0D3PO5HPUk0JEMiaZSnLbi7fx86d/znlTz2NywWTyg/l4Xd5MlyYiMix093dz//r7eXnPy3z9kq/z6cWf1puao8yoD8Msy6o0xuw5ynMtoNQYs+8El3VUMhmG7du3j7KysoyMLSdXIplg/b71LNu2jOe2P8eOxh0UhAooDZdSkl1CeXY5bqc7PevLrT5fIscjmojS1NXE5v2b2bh/I/va9nFq2al8cN4HuWL2Ffjd/kyXKCJjxIqdK/jSPV9ifGQ88yrmEQlGyPZpSbeIyJHsa93HX1f/lY6+Dm6+6mbOmnhWpkuSITIWwrB64BHg98aYl97inGzgw8AXgJuNMTedxBLfUibDsPXr1zNnzpyMjC0nVjKVZMO+DTz72rM8vfVpqluqGZc7jpJwCeW55eQF8nA73QQ9QTxOT6bLFRl1kqkkbb1tvFb3GhtqNrCraRcl4RLef9r7+eC8D1KYVZjpEkVkFKptr+Wrf/sqNa01XDj9QgpCBeSH8vUml4jIO0iZFOuq1nHPmnuYWTKTmz96M/mh/EyXJYM0FsKwMHAjcD2QIt04vxboB7KB6cA0YBXwbWPME5mp9M20TFKGQiqV4tWaVw+GX3ua91CeU05pdinjI+PJDeTicXoIeoJa8ihykqVMiu7+bnY37WbDvg281vAaboeb95/2fq464yrGRcZlukQRGeH64/387Kmf8aeX/8TFMy5mQv4E8oP5+p4vInKMovEoj216jKe3Ps0Xzv8C/3rBv+ou4iPYqA/DDrAsywu8CzgbGAd4gWbgFeAJY8ymDJZ3RJkMw7q6uggG1ShwJDLGsL1hO09ufpIntzzJzsadlOWUURoupTJSSSQQwevyEvKGcNqdmS5XRA7TE+2huqWa9fvWs3H/Ruw2O++Z8x6uXng1E/InZLo8ERlBjDH8fd3f+fZD32Z+xXxmlsykIFRAwBPIdGkiIiNafUc9f171Z5q7m7nl6ltYMGFBpkuS4zBmwrCRSDPD5Gi1dLfwzNZneHzz46zcvZKCYAGVkUrG5YwjPysfr9OrmV8iI0xfrI+athpeqX6FV/e/SiqV4so5V/KxMz7GtOJpmS5PRIaxtVVr+dJfv0RuIJcF4xeQF8wj15+r5s8iIkPkwNLJP6/6MwvGL+AXH/4F2X71XxxJFIYNY+oZJm8lloixcvdKHt/0OE9teYqUSTEpfxJlOWWMyxl3cOaXen6JjA7ReJT97fvTwVjNq/TH+7n8lMv52IKPMat0ln7BFREA6trr+OZ932R7w3Yumn4RhVmFFIQKsNvsmS5NRGRU6o/388D6B3hhxwvc+K4b+eSiT+rnshFCYdgwprtJyuF2Ne7i0Y2P8uimR9nbvJeJ+RMpzylnQt4EAu4AQW8Qv8uvL74io1w0EaW+vZ5X9qWDsa5oF5fOvJRrz7yWU0pP0dcAkTGoL9bHz576GX9e9WcunnkxlbmVFIQKcDvdmS5NRGRMqGmr4e6VdxNPxfn9Nb9nVumsTJck70Bh2DCmZZJjWywR44UdL/DQqw/x9NanCXvDTMqfdLDvl9/tJ+QN6d1ekTEslohR117HhpoNrN+3nu5oN1eccgXXnnUt04unZ7o8ETnBjDHcu+ZevvPwd1gwfgEzS2aSF8wj6FHfVxGRky1lUry06yXuXXMvV865kh+87wd6U2IYUxg2jGUyDKutraW4uDgjY49lDZ0NPLrxUR5Y/wDb6rcxKX8SFZEKJuRNwOfykeXNwuvyZrpMERmGDgRj66rXsX7femLJGO+Z8x6uO+s6Nd8XGYXW7F3Dl+75EpFAhAXjFxAJRIgEIpodKiKSYV39Xdyz+h621m3lpo/exIUzLsx0SXIECsMAy7JsQKkxpvokjLUX6AKSQOLt/vAzGYatWbOGefOO6/8LOQapVIq1VWt5+NWHeXTTo1hYTC6YzPi88RQGCwl4Apr9JSLHLJqIsr9tP2ur1rKhZgMYeN9p7+PaM69lXGRcpssTkUHY17qPb973TXY37eai6RdRFC4iP5ivnxVERIaZLfu3cMfKOzil9BR+fdWv1WB/mBkzYZhlWW7g68BHgHFAJ/AC8B2gDqg1xpzwnyIGwrB5xpjmdzpXyyRHp1gixrJty/j72r+zfMdyxuWOozJSyaT8SQQ8AbK8WfhcvkyXKSKjRDQepbq1+mAw5rK7+OC8D/LxhR+nOFszgEVGio7eDr7/2Pd5bONjXDj9QsbnjacgVKA7RYuIDGOxRIz719/P8zue57vv+S4fW/CxTJckA8ZEGGZZlgdYCkwB7gC2AznAFcBpwI3ADxSGHdLV1UUwqH4TQ6Wrv4vHNj7G39b+jY37NzKlcAoTIhMYnzcer8tL2BfGaXdmukwRGeX64/1UNVexpmoNG/dvxO/28+HTP8zHFnyM/FB+pssTkSOIJWL85rnf8Nvnfsu5U85lcsFk8kP5+N3+TJcmIiJHqbqlmttW3EaWN4vbrr2N8tzyTJc05o2VMOy/gY8BC40xTW84di3wG8B5ksKwPUAbYIDfGmNueatzNTNsZGvobODB9Q/yt7V/o66jjmlF05iQN4Gy7DI1vxeRjOuN9bKneQ9rq9aycf9Gcv25fPSMj/KR+R8hx5+T6fJExjxjDH9f93e+8/B3OLXsVGaXzSbXn6tlNiIiI1QyleTprU/z0IaH+Px5n+fLF31ZfR4zaKyEYduAG40xf3uL4/8K/MQYYzsJtZQYY/ZblpUPPAV83hiz/LDjNwA3AJSXl8+tqqo60SUd0caNG5k1S7eDPVZVLVXcu+Ze/rHuH8STcaYVT2NiZCL5oXyCniBBT1Bf8ERk2OmOdrO7cTdrqtawuXYzxVnFfGzhx/jQvA8R8oYyXZ7ImPPCjhf4+t+/Tn4onzMqzyAvkEckqOb4IiKjQXNXM3e+dCfd0W7++Mk/MqVwSqZLGpPGShjWD8wwxuzKdC2HG5ix1m2M+fGRjmdyZtjevXupqKjIyNgjTXVLNfesuYe/rf0bFhYzimcwuWAyIW+IsC+sZQwiMmIYY+iOdrOjYQdrq9aytX4rlbmVXL3wat532vv09UzkBNtWv41/+9u/0dXfxblTzqUgq0DN8UVERqGUSfHizhe5Z809fGrRp/jGpd/AZjvhc3PkMGMlDGsC3muMeeEtjs8BvmCM+cQJrsMP2IwxXQPPnwK+bYx5/Ejna5nk8FXdUs29a+/l3jX3AjCjeAZTC6eS5c0i7AvjdXkzXKGIyOAYY+js72Rb3TbWVa9jW8M2phZO5ZqF13DF7Cv0dU5kCNW01vDth7/NK9WvcOH0CynLLqMgq0D9REVERrm23jZuf/F2Ovs7+eP1f2Rq0dRMlzRmjJUw7B4gaYz5yBGOFQLLgEknumeYZVnjgfsGNh3An4wx33ur8zMZhjU0NFBQUJCRsYerfa37uHfNvdy79l4wMK1oGlOLphL2hcn2ZeNxejJdoojICZEyKdp72tnesJ211WvZ2biTU0pP4ZqF13DZrMt0NzuR49TU1cT/PPI/LN22lPOnnc/4yHjyQ/n6mUJEZAw5fJbYJ8/+JN+87JuaJXYSjJUwbCawErgf+CGwg0N3k/x3oIp0c/3BhGGXAL8A7MDvgR8c4ZwPAf9Nunn+BuCjb3fBTIZhL7/8MmeccUZGxh5OGjsb+evqv/LnVX8mZVLMLJ7J5MLJCsBEZMxKppK09bTxWv1rvFL9CruadnF65el8/MyPc+G0C3HYHZkuUWTY6+jt4MdP/pj7X7mf86edz8T8iUQCES1FFhEZw9p627jjxTto72vnj9f/kWnF0zJd0qg2JsIwAMuyzgZuBSYctjtBOsD6FVA1iAb6dmA7cCFQA6wGPgJsOeycScA9wHmk7yaZDzS+3UW1TDIzuvq7uP+V+7nzpTtp7WnllNJTmFqYngEW9oXxuXyZLlFEZFhIJBO09LSwpXYLG/ZtoKq1ijMnnMm1Z17L4imL1edI5A16o73ctPQm7lhxB0umLGFq4VRy/Dm6UYWIiADpNhUv7nyRv675K58865N8812aJXaijJkwDMCyLBtwOlAJdAEvGWNaB/p3fcUY863jvPRC0jO+Lh7Y/sbA4/cPO+dHpAOz3x/tRTMZhnV1dREMBjMydibEEjGe2PwEd750J1vrtjK7dDZTCqdQECwgy5eld2pFRN5BPBmnpauFzbWbWV+znpq2GpZMWcK1Z17LmRPO1A9yMqbFEjF+//zvuXnpzZw54Uxmlswk25dNtj8706WJiMgw1N7bzu0rbqejr4M/fepPTC6YnOmSRp0xFYadQB8gvUzykwPbVwNnAJ877Jz7SYdhZ5GeSfbfwBEb5x+gmWEnViqVXpt918q7eH7H80wrmsaUwimUhcvI8mUR9AR1C3MRkeMQS8Ro7G5ky/4trN+3nvrOei6cfiEfX/hx5lfO19dWGTOi8Si3vngrNy+9mdPKT2NO2Rxy/Dnk+HP070BERN5WyqR4YccL3LPmHr580Zf5/Hmf1/eOIaQwbGgcTRj2MBAn3TesFFgOzALa3+qimQzDtmzZwvTp0zMy9om2rX4bt794Ow9ueJCKSAVTC6ZSGakk5A2R5cvCZmn2gojIUIkmojR1NvHq/lfZsG8DLd0tXDrrUq4981pml83WD3UyKvXH+/n987/nN8t+w7yKecwqmUVOIIdcf67+nxcRkWPS2NXI75f/Hq/Ly92fvJuicFGmSxoVBhOGqUPuIfuBssO2Swf2Ha4GeJl0ILaH9CyxSaT7iw07LtfoujNYe28796y5h9tevA27zc7s0tl8evGnCbgDZPuy1fBZROQEcTvclOaUUppTyvlTz6ehs4ENNRv49F2fpqOvgytnX8m1Z13L9OLR+QaMjC19sT5uWX4Lv1v+O06vPJ3rzr6ObF82kUBEIZiIiByX/GA+X7v0azy+6XEWfH8BP3r/j/in+f+U6bLGNM0MO8RBOtw6n3QItpr0nSI3H3bOJaSb6n8ciACvAHOAlre6qJZJDk4yleTpLU/zhxf/wOb9m5k7bi7Ti6eT40svT3A73ZkuUURkzIrGo9S217J+33o21GygL9bHpbMu5eoFV2vGmIw4vdFefvPcb/j9C79n4fiFzCieQbY/WzPBRERkSFW3VPPb5b9lWtE0fv/x3xP0jJ0+30NNyySHzmXAz0n3A7sV+B7wbWAN8CBgAT8hHYolB47/5e0umMkwrLm5mUgkkpGxB+u1ute4fcXtPLD+ASYXTGZ60XTKsssI+8P6YiEiMgwdCMZe3f8qG/dvpK2njYtmXMRVZ1zFGZVnqPm+DFutPa3c9OxN/GXVX1gwYQGzimeR7c9WTzARETlh4ok4f1/3d1buXskt19zC+dPOz3RJI5LCsGEsk2HYihUrOPPMMzMy9vHo7Ovkz6v+zG0v3obD7mB26WwmF0wmy5tF2BfGbrNnukQRETkK0XiUhs4GNtVu4tWaV2nobGDJlCV89IyPsnjyYn09l2GhuqWanzz5E5597VnOmnQW0wqnke3LJuwLKwQTEZGTYkvtFn7/wu+5ZMYl/PRDP8XpcGa6pBFFYdgwlskw7Pnnn2fRokUZGftoGWN4effL/Hb5b1m1ZxXzxs1jWvG09DLIQA5uh5ZBioiMZLFEjMauRrbUbWHjvo3sa9vHgvEL+OgZH+XC6Rficoyu/pYy/G2s2cgPH/8hr9W9xqJJi5iQN4FsfzYhbyjTpYmIyBjUG+vlrpfuorq1mr/e8FemFU/LdEkjhsKwYSyTYVh7ezvhcDgjY7+T1p5W7nrpLm5fcTt5wTxml86mMreSLF8WQU9Q78iKiIxC8WSc1u5WttRtYUPNBvY072FO2Rw+MPcDXH7K5Qoj5IQxxvD01qf52VM/o7u/m4UTFjIuZxw5gRz8bn+myxMRkTHOGMOKXSv486o/841Lv8E/L/nnTJc0IigMG8bUQP8QYwzP73ie3zz3GzbWbGRexTymFU0jx5++TbnuBikiMnYkU0naetp4reE1NtVsYmfTTvICebzn1PfwgbkfoCJSkekSZRToifZw10t38dvlv6U8p5w5ZXMoDheT68/VTXhERGTYaepq4v+W/h/F4WLu/MSdhP3hTJc0rJ3UMMyyrGff4RQD9AHVwJPAA2YMJ26ZDMO2bdvGlClTMjL24Zq6mrh9xe38ceUfKQ2XMrN0JuNyxpHtzybgDmS6PBERybCUSdHV30V1SzWv7n+VbfXbiCfjXDzjYj4070OcXnG6GvDLMdnbvJebnr2JRzc9yoLKBUwtmkq2L5tIIKI330REZFhLJBPc98p9vLjzRW699lYWT1mc6ZKGrZMdhu0FvEDewK72gcfwwGMTYANySQdjLwKXGmN6jqfAkW6shmHGGF7c+SK/evZXbKvflp4FVjiNsC9MbiBXzZNFROQt9UR7aOhsYHPtZrbUbqG+s575lfP5wGkf4KIZFxHw6I0UebNUKsUzrz3DTc/eRF1HHQvHL2Ri/kRC3hDZvmy1YBARkRFlS+0Wbll+Cx+a9yG++57vYrfrd+g3OtlhWAWwFLgH+LExpmlgfx7wVeADwLlAF/AN4MvA/xpjvnY8BY50Y22ZZHd/N39c+Uduef4WCkIFzCmdQ1l2GdkBzQITEZFjF0vEaO1uZXvDdjbWbmRP8x5y/blcOutS3jPnPcwsmamQY4yra6/jthdv48+r/8yEyARmlsykJFxCTiAHn8uX6fJERESOW3e0mz88/we6+ru495/vpTy3PNMlDSsnOwy7D+gxxnzsLY7fDXiNMe8b2H4ImGaMmXg8BY50Y6WB/pbaLdy89GaWblvKvHHzmFk8M90LLKBeYCIiMjSSqSRd/V3sb9vPlrot7GjcQXN3M/PGzeOK2VdwycxLyPHnZLpMOQmSqSRPbH6C3z73W2rbazm94vSDs8DUh1REREYTYwzPvvYs971yH//7wf/lQ/M+lOmSho2THYZ1AP9mjPntWxz/Z+AHxpjwwPYXgR8aYzzHU+BIl8kw7Pnnn2fRokUn7PrxRJwHNjzAzc/eTDwVZ+64uUzKm6Tbk4uIyEnRH++ntaeVXU272Fq3ld1Nu/E4PVw0/SKumH0Fp1ecjtPhzHSZMoS21W/jjyv/yD/W/YMphVOYVTKLoqwiQt4QQU8w0+WJiIicMPta93HT0ps4e+LZ3PSRm3A5XZkuKeMGE4Yd79tmU9/h2OHrFVKkG+rLSXai1hTXttdyy/JbuGf1Pcwsmcl5U88jP5RPJBDB5dA/SBEROTk8Tg/F4WKKw8WcNfEsuvq7aOhoYEvdFr5x3zeoba+lJFzCBdMu4JKZl3Bq+anqWTkCNXQ28NfVf+VPL/8Jt8PNrJJZfOqcTxHyhMjx5+jvVERExoSynDK+deW3uHPFncz/n/n8/TN/Z0L+hEyXNWIdz8ywvwPvAq41xvzlDcc+AtwGPGyM+cDAvtuAOcaYU4em5JElkzPDmpubiUQiQ3a9VXtW8bOnfsbWuq0snLCQKQVTCPvCZPuzsVm6y5eIiAwf8WSczr5O9rfvZ3vDdnY37aauo47xkfFcMD0djs0snqm7VA5T7b3tPLThIf648o+0dLdw6rhTmZw/mZA3HYB5nGNywYGIiAjGGJZvX869a+/lh+//IR+e/+FMl5QxJ3uZ5DjgBaAYqAN2DhyaCBQN7DvLGFNlWZYHeBR4yBjzs+MpcKQb6Q30E8kE/1j3D37+zM/xOr2cXnE65Tnl5Phz8Lv9Q1OoiIjICRaNR+no66C2vZZtDdvY3bSbhs4GKiOVLJq0iPOmnsfplacrZMmgpq4mHlj/APesuYfGzkZmlsxkUsEk8oP5ZHmztAxSRETkMDWtNfzy2V+yaNKiMbts8qSGYQMD5gBfBy4HKgd27wUeIt0frOV4ihmNMhmG7dy5k4kTj+++Ba09rdyy/BbuXHEnM0pmMLt09sGlkE67+q+IiMjI1h/vp7Ovk7qOOnY17aKqpYra9lr8bj9nTjiTc6eey9kTzyY/lJ/pUke1XY27eHTjo/xt3d/o6e9hVuksxkfGEwlECHqDhDwh3S1URETkLfTH+7lzxZ3sa9s3JpdNnvQwTI5eJsOwLVu2MH369GP7nNot/Pzpn/PizhdZMGEBM4tnku3L1lJIEREZ1WKJGF39XbT2tLKneQ+7m3dT01ZDX6yPSfmTOGP8GSwcv5B5FfPI9mdnutwRqzfay7Lty3hs42Ms27aMHH8OE/MnMik/fQOegDtA0BNUACYiInKUjDE8t/057l1zLz/+4I/50Olj526TCsOGsZGwTDKVSvHE5if46VM/pTfWy/zK+UzMm0hOIIeAO3DiCxURERlmkqkkvbFeOvs7aexsZG/zXva376euo45YIsaUwimcUXkGp1eczqzSWRSEChTgHEEsEWPN3jU8t/05ntn6DPWd9UwtnEp5TjkVkQo8Dg9Zvix8Ll+mSxURERnRalpr+NWzv+Kcyedw00dvwmE/3vsljhyZWCZpARcAk4BcXn/3SABjjPnO8RQ02mQyDOvq6iIYfOv+GtF4lD+t+hO/fOaXlOeUc2r5qRRlFemukCIiIkcQT8bpifbQ3ddNfVc9e1v2Ut9RT1NXE93RbiKBCDNLZnJa+WnMLpvNzJKZY67PVVd/F6v3rOa57c+xdNtSWntaqYxUUhwupjynnFx/Lj6Xj6AnOCZ+SBcRETmZ+uP93PrirbR0t3Dfv9xHSXZJpks6oU52A/1JwP3AVN4cgh1gjDGj8j7XlmVdAvwCsAO/N8b84O3OH44zw9p72/n1sl9z10t3Mad8DrNLZ5MbyCUSiOj25CIiIscgkUzQG+ulN9ZLR18HdR117G/bT1N3Ew2dDcSTcXL9uUwqmMTUwqlML57OpPxJjM8bf1Ka9d+98m5uvO9GqlurKc8p53vv/R5XLbhqSK7d2dfJhn0bWFO1hlV7VrGpdhMOm4NxueMoziqmIlJByBPC4/QQ9AT1RpuIiMhJYIzhyS1P8vCGh/ndx3/HhdMvzHRJJ8zJDsMeB5YA/w48CxyxWb4xpup4ChrOLMuyA9uBC4EaYDXwEWPMlrf6nEyEYQd+8C3YV0BDWcPBH3yrWqr42VM/46ktT7Fg/AJmlcwi259Nti9bSztEDvP43x7nkg9ckukyREYc/dtJM8YQS8TojfemG/X3d9Lc1Ux9Zz2tPa2097bT3N2MMQa/209pdinjcsdRkVNBRaSCspwyynLKBv0m1d0r7+aGu26gN9Z7cJ/P5eOWq2856kAsGo9S01ZDVUsV2xq2sWn/JjbXbqapqwmv00txuJj8UD6FoUKKsopw2Bz43D4C7oBmfh0D/dsROT76tyPy1nY07OCmpTdx7ZnXMj4ynn+//9+pbq0muzqbX37rl0P25lgmnewwrAf4lTHm68cz4EgyEH6tAfYbYy63LOt9wK1AM7AW2AgkjTHff6trnOww7PAffPOfz6dxUSMeh4c55XOIJWIsnLCQqQVTyQnkjLmlGyJH60sf/RI//dNPM12GyIijfzvvLJFMEE1E6Y/3H3xs722ntaeVtt42Ovs76ervorOvk+5oNwA2y4bP7SMvkEckECE/mE+2P5uQJ0TQE8Tv9hNwBwi4A/jdfjxOD3abnfN+fB61HbVvqqEoVMQDn3uA/ng/vbFeWnpaaOluobGrMf3R2Zi+eUC8D7tlJ9ufTdgbJuwLk+vPpTCrkKAniM1mw+fy4XP5dKfpQdK/HZHjo387Im+vq6+L/3rov9jdtJuUSaV33g++Dx3bm2PD1WDCsON5yy4K7DmewUagLwJbgdDA9leAdcaY8yzL+g0wAejJVHFHcuN9Nx58B7hweiGNNNKf6Gdz7WZ+8N4fkBfKOynLMkREROTNHHYHDrsDv9t/xOOJZIJYMkY8GT/4kUqliCVj9PT30NmfDsn2Nu8lmogST8ZJpBIHz40lYiRSCYwxRwzCAOo66/jPB/8Th82B3WbH5/ThdrrxOX1kebMoCZdw3tTzcNqdWJaF2+HG5XDhcXoUeomIiIwgQW+Qjt6OQ0HYgN5YLzfed+OID8MG43hmhv0ZiBtjrjkxJQ0PlmWVAncA3wO+BFwBdAD3GmOutyxrIfBbYLkx5nNv+NwbgBsALr744rmPP/74Sa39gL1791JRUZGRsUVEREREREREThTLspqNMXnH87m24/icLwELLcv6smVZo7kT6s+BfwMORKi5QCdQOrBdA+QD+9/4icaYW4wx84wx85qbm09CqUcWjUYzNraIiIiIiIiIyAl03L3qjycMe5H0ssEfAT2WZVVZlrX7DR+7jreg4cCyrMuBRmPM2jcc6gcmWZZVCTiBLODBI3z+DZZlrbEsa01TU9OJL1hERERERERERI7K8fQMqwaObW3lyHMWcKVlWZcBHtLh3y+AMHAt8ATgA2qMMZvf+MnGmFuAWyDdQP/klPxmdXV1TJkyJVPDi4iIiIiIiIgMO8cchhljlpyAOoYVY8w3gG8AWJa1BPiKMeYqy7LuBQLGmMkDDfRfzVyV72zOnDmZLkFEREREREREZFg5nmWSY9nXgC9ZlrWTdA+xP2S4nre1cePGTJcgIiIiIiIiIjKsHM8yyTHFGLMMWDbwfDcwP5P1HAu73Z7pEkREREREREREhpV3DMMsy9pD+o6KU40xccuydh/FdY0xZsKgq5NBmTx5cqZLEBEREREREREZVo5mZlgV6Yb5BxrBj4UG+qPCpk2bWLJkSabLEBEREREREREZNt4xDHtjw/yx0EB/tCgtLc10CSIiIiIiIiIiw4oa6I9isVgs0yWIiIiIiIiIiAwrxxyGWZZltyzL94Z9YcuyvmxZ1vcsy5o1dOXJYDQ2Nma6BBERERERERGRYeV47ib5W2ABMBPAsiwn8AIwfeD4lyzLWmiMWT8kFcpxmzt3bqZLEBEREREREREZVo5nmeTZwIOHbX+AdBD2WeBMoAH4+uBLk8Fau3ZtpksQERERERERkQxaevdGrqv4JVfYvsN1Fb9k6d0bM11Sxh3PzLAiYM9h2+8CNhtjfg1gWdYtwKeHoDYZJK/Xm+kSRERERERERCRDlt69kZtueIRobxyApqoObrrhEQDOvWrsdrk6njDMAuyHbS8B/nHYdh2QP4iaZIhUVFRkugQRERERERGRUcsYQzKRIh5NEo8m0o/9iUPPB/YnE6mDH6lEikT8jdtJkvEDj4ZkIkkikSIZT5GMJw+en0qmMKn0uCZlMIaBx/RHKmnAHDr+4t9fOxiEHRDtjXPnjUsVhh2jPcDFwG8syzqL9EyxpYcdLwY6hqA2GaStW7dSUFCQ6TJERERERERETopkMkWsL0G0N37Ej/6eA48x+rsHHg/bF+1JEO2NEes/EG6lQ61UKh0yQTpoOhg4GbDZLewOGw6nDbvTjt1hw2a34XDYsDksbA4bls3CAmw2CywLmw2wrPR+m4UNsOwWNruFzW7DdmC/3YbNBja7HcsGlmVhc1gHn2MNvHDLwrLS+yzAsgFYbwrCDmiuHtuxzfGEYbcBP7UsaxNQAjQCTxx2/AzgtSGoTQZJM8NERERERERkuDLGEO2N09cVo7crSl9XjP7u2Ou2e9uj9Hb209M5sD3w2NcVo78nlg6pSM+OOhBWOdx2nC47Dqcd+4GAyjkQVg0EVXaHhcNlx+Gy43Q5cLodeEMunM70PpvTht1hx+6wsDvs6RCLgTFsVjp0skiHWdahcOp1z22HBVSHncvh+w7bPhGy8nx0NPW+aX+kPOuEjDdSHE8Y9gsgCLwHeAX4pjGmF8CyrFzSd5r88VAVKMevq6sr0yWIiIiIiIjIKJRMpOjp6Ke3I0pPRz897Yceu9v76W7to7utL73d1k9vZz+9nTGSydTBWVUYcLjsuDyOgwGW3XUgyLJhd9pwuu043U6cbjtZBX7yxmXhdDtwedLnWTYb6YQqPavKslnYbK9/fmif7WAoZbMfz/0ER55zrz6FR25eTTyaPLjP7XNyzffOzWBVmXfMYZgxxgDfGfh447EW1C9s2Ghpacl0CSIiIiIiIjIMpVKG3s4o3W19dLf209XaR1drH92tfXS1DYRZ7f10t/XT095Pb2eUWH8iHWSlDFjg9jpw+5w43ekwy+V2DARYDtw+By6vg7xxWZROzcXldeJ027DZ7YAZWCpoDczUOrQ08MBz60CgdYJmTI0Vs5aMA2DpXa/S0dRLbkmQa394/pjuFwZHEYZZlnXNwNO7jDHmsO23Y4wxdw2uNBmsuXPnZroEEREREREROYES8STdbf0Hg6wDzztb+uhs6qGzue9Q0NXWRyKWOjgry+1z4PI58XidOL2O9Awtpw2nJx1khSJe8spCuHxOXB47DqcDjEkHVQ4bdvtATyy7DfuBQMs+dmZdjRSzloxj1pJxtOzvZO4lEymoCGe6pIw7mplht5Oec/gXIHbY9tvFswYYiWHYJaSXgdqB3wM/eIvz3g/8DTgdWHNySjt2a9euZcmSJZkuQ0RERERERI5Cf2+czube1310NPXS3thDR2MvHU09dLX00dsRJTVwB0HLsvD4nbj9TlxuB06PI7200OPA43fiy3KTXRTA43fi8jpxOG2va/p+oH+W3WE7GHBZNs3GktHtaMKwcwGMMbHDt0chO3AzcCFQA6wGHgS2vOG8IPBF4OWTWt1xCAQCmS5BRERERERkTIrHknS1HAi1+l4XbLU39tDZ1EtHYw9dbf2kkilMyuB0O/AEXAPBVXqmltNtxxNwEczxklcewuN34fI40oGVBXb7QFP4gUDrwIdmZ4m8tXcMw4wxz73d9igyH9gJ7B7Y/gvwbt4chn0H+CHw1ZNX2vEpLi7OdAkiIiIiIiKjQrQvTkdjD+2NvbQ3dB96bOiho7GHjoHQKxFLYlIGywbegBtPwInb60wvPfQ4cPudeAMusmfm4Q6U4PY6sdnAsh2aofW6UMthU98skSF2PHeTHK1KgH2HbdcAZ7zhnNOAMuARRkAYtn37dgViIiIiIiIiR5BMpuhq6RtYgpierdVW30NbXTdt9d0H98ejSYwx2B02fCE33oALl8+B25Pus+ULuiicmE3lnALcPid2hw2wsDtfH2od2FawJZJ5CsOOng34KXBthus4ahMmTMh0CSIiIiIiIieFMYa+7tjB2VsHA66BcOtAwNXTHk3fDRHwBFx4g69flugNuskpCVI6NRdPwInT5cAAjsPDLaf94HMRGXkUhh2yn/SsrwNKB/YdEARmAssGtgtJ9xS7kmHaRL+lpYWysrJ3PlFERERERGQYMsbQ1xWjraGbtvoe2uu7aa3rpqW2i7a6Llrreuhs6iERP9Bzy443eGhposubXpboC7oZP6cAT9CNy2PHstJ3PHQ47didtoNBl5YkiowNCsMOWQ1MAipJh2AfBj562PEOIHLY9jLgKwzTIAygvb090yWIiIiIiIi8Saw/QftAwNVW301rXRettd201nbRWt9Ne30Psf4EqZTB5bHjC7rTjeUDLlyedOCVWxqkfHoenqALm80CyxoItezpR6cayYvIkSkMOyQBfA54gvSdJW8FNgPfJh14PZi50o7P3LlzM12CiIiIiIiMEclEKn2nxMNCrpb9XQOzuLppb+impyMKBmwH+285cftduAZ6bwUjPvIrw/iCLhwuB1jgcB4KtxwDyxMtm2ZvicjxG1FhmGVZbqAY8AJNxpimIR7i0YGPw/3nW5y7ZIjHHnJr165lyZIlmS5DREREREQyZOndG7nzxqU0V3cQKc/imu+dy7lXzTrqz0+lDF2tfW+YxdVNy/5OWmu7aa/vpqu1j1TKYFkW3qALb8CFJ+DE5XHgCbjwhTyMP7UAX6gcp9uOZbO9aQaXw2lXwCUiJ82wD8MsywoCHwM+AswHnIAFGMuy9pOeyXWLMWb1EI5ZBtwJFABm4Pq/sCwrB/grUAHsBT5kjGkbqnGHWjgcznQJIiIiIiKSIUvv3shNNzxCtDcOQFNVBzfd8AgAZ75varqpfF063DoQcLXs76KtPn0XxWQ8iTHgCTjxhdwDTeaduH1OfCEXpVNymTy/GLfXiWWRbip/oP/WwGwuLVEUkeFoWIdhlmV9CbgR2E16meL3gFqgD8gh3dB+EfCUZVkrgc8bY3YMwdAJ4MvGmHUDYdxay7KeIn0nyWeMMT+wLOvrwNeBrw3BeCdEbm5upksQEREREZGTKB5L0lLTSWN1B7f8vycOBmEHRHvj/Py6B/n7D1fgy3LjC7lw+1y4fQ68QRd5ZaGBPlxO7HY7lgUOl/3g7C2HU03mRWTkG9ZhGLAAWGyM2fQWx1cBt1qW9c/A9cBiYNBhmDGmDqgbeN5lWdZWoAR4N4eWR95Buon+sA3Ddu3apbtJioiIiIiMIol4koY97dTubKWpqoO63W007G6nsbqDWG8cy2YRyPbiD7vpau474jWS8RRXfGF+OuBy2Q/dSVGzuERkjBjWYZgx5kNHeV4U+L8TUYNlWRXAqcDLQMFAUAZQT3oZ5bA1efLkTJcgIiIiIiLHKJUyNFV3ULujlf3bW9i3tZn921pore0CyyIU8RHK9eDxu/BluRl3Sj4zFpfjdDmw2S0cLjtOl53XXtpPZ3Pvm66flecjXODPwCsTERkehnUYdjjLsqYDSWPMtoHtC4GPk77j44+MMckTMGYA+Dvw/4wxnYdPBTbGGMuyzFt83g3ADQDl5eVDXdZRq62tpbi4OGPji4iIiIjIWzPG0FLbRdWmJvZubGTvhgaqtzQR60sQzPUSzPXiz3ITyPEy54JKvCE3NpuF0+PA5XGkly863no213nXnMIjN68mHj30q5LTbefcq085GS9PRGTYGjFhGHAr8HNg20CD+wdIL1P8LBACvjGUg1mW5SQdhN1tjPnHwO4Gy7KKjDF1lmUVAY1H+lxjzC3ALQDz5s07YmB2MnR3d2dqaBEREREROUy0L87eVxvZta6OXa/Us+fVRno7+vGHPWQXBAhku4mUhZg4vxin04bTnQ68nB7H2wZeb2fWknEALL3rVTqae8mK+Dj36lMO7hcRGatGUhg2FVg38PwDwMvGmMssyzoXuI0hDMOs9BSwPwBbjTE/PezQg6Rno/1g4PGBoRrzRJg7d26mSxARERERGXN6u6LsXt/ArrV1bF9VS9XmRjCQWxpML1HM97Pow9Nxe5w4XHbcvnTwdSJ6ds1aMk7hl4jIG4ykMMwOxAaenw88OvB8F0Pfu+ss4Gpgo2VZ6wf2fZN0CHaPZVnXA1XAUfU0y5S1a9eyZMmSTJchIiIiIjJqxaMJdq9v4LWXati6Yh/VW5qxO2xEykJkRXwUVGYx9cxSHC4bbq8Tty8dgImISOaMpDBsE/AZy7IeJh2GHZgJVgI0D+VAxpgXgLe6V/D5QznWiZSbm5vpEkRERERERg1j0o3tX1u5n60v7uO1lTVEexPklYfILgxQMiWXmYvHYXfY8ARcuH3O417iKCIiJ85ICsO+BtwPfAW4wxizcWD/lcCqTBU1nAWDwUyXICIiIiIyYsWjCbavrmXLC/vY8uI+6na0Eox4iZSGCBf4WfyRmbi9Tlw+J56AE4dTM75EREaCEROGGWOWW5aVB4SMMW2HHfot8Ob7BQt79+6loqIi02WISIYsvXsjd964lObqDiLlWVzzvXM596pZmS5LRERk2OrtivLaSzVseq6Kjcuq6OmIUlAZJqcwwOTTi5h32QScbgcevwuX18Hhd5sXEZGRY8SEYQDGmCTQ9obdSeCrAx9ymGnTpmW6BBHJkKV3b+SmGx4h2hsHoKmqg5tueARAgZiIiMiAjuZetrxQzcbnqtjy/D4S8SSFlWGyiwMseO9UvIF0jy9vwIVds75EREaNEROGWZb14FscKgUmojDsTfbu3UtBwVDfW0BEhotUyhCPJohHk5iUIZUymIGP2772zMEg7IBob5zbv/4Mp182EYfLjt1px+G06V1tEREZMzpbetm4rIr1T+/mtRU12J329Myv4gBLrp6F2+PAE3Dh8TtPyJ0dRURkeBgxYRjQ8oZtOzAemA1cd/LLGf76+voyXYKIHCaVMvR29NPR1Etncy/d7f30dkbp64zR1dZHT1s/PR1Rejr66e2I0tsZpb8nTjKeBMAM/MekDMYYABwuOza7DZuNdKg1EGy17u86Yg0tNV3ceMEfScZTpFKGZCKVvluIBZbNwrIsLJuF1+/EE3ThDbrxBV34szxk5fvIyvcTzvcTivgIRbyEIj78YQ92/cIgIiLDUF93jM3PV7P+6d1sXFaFZVkUTsgmryzERdfPwelx4Am68ficWDa9OSQiMlaMmDDMGHPEwMuyrC+SDsPuPLkVDX9z587NdAkio14ymaK9oYfW2i5aa7toqe2meV8HbQ096dCrqYfezhiQDrHcAw12PX4nTrcDu9OG3WHH5bHj8jrwBJyEIl5cXidOjwOn2zYQNFlgDBwIrCyw2S3AwhoIwqyBVMuy4Hf/+iRdLW8OxIO5Xq784nyMSd8Ry6QOPKZnlpEypAwDM87Ss85i/QnifQnq97Szd2Mj0d448WiSaG+caG+c/p74QD02QhEvucVBcktD5JWHyCvLIlIaIqc4QLgggE2/aIiIyAkUjybY9vJ+XnlqN+uf3kO0N07RhGxyS0Ocd/UsXD4nXoVfIiJj3ogJw97Gg8APMl3EcLR27VqWLFmS6TJERixjDO2NPTTsaadhb3v6cU87zTWdtNV1E4+mZ2z5stz4Qm48ASdunwtf0Eko10d+RRbegAun246Fhc1hS4dfdht2hy29bU/vH+qliud/fDaP3Lz6YI0ATred8z8+m0C2d1DXTiVTpJLpWWWJeJJkIkUyniIZT9LfHaO7I0pPez+vvVTDuid2Ee2J09sZo68rOhCY+SioDFM0IZviyTkUTcihoCKLUMSnJZsiInJMUinD3lcbWPv4Ll55ajdt9d0Ujs8mUhrkrPdPwxtwpWc6B1wKv0RE5KDREIbNBdZmuojhKD8/P9MliAx7/b1x6na2sn97C3W72qjb0Ur9nnba67tJpQy+kJtgjhdflhtPwEUox0t+ZRhf0JUOtOw2HE47Dpct3YdrYF+mzVoyDoCld71KR3MvWREf5159ysH9g2Gz27DZ00s03Tjf9txUMkUiniIRS5KIJYlFE/R1Rulq7aexqoNdr9TT2xGlu72PaE8ch8tOfkWY0qkRxs3Io3xGHqVTcvGF3IOuW0RERof2xh5eeWo3ax7dwa519UTKQuSPy2L2+RUEc7zpN6ZCrmHx/VhERIanEROGWZb1yyPsLgAuBx49/Lgx5gsnrbBhzOVyZboEkWEhEU/SsLed2u2t1GxrYd+WJmq2tdDV0ofdaSOc7yeQ48EXchPI8XDa5Anpd5DtFk63HafLjmPgYyTNXJq1ZNyQhF+DYbPbcNltuDyHfbspOfTUGEMynkovxYyml2N2tvTRVt/Fyw9u4+nbN9DZ3EsynsQf9lAyJZfyGXlMOLWQiln5ZBcGRtTfiYiIHLtEPMnWFTWsfWwnrzy1G8uC4km55FdkMf2sMpweJ/4sNw6X7vYoIiJHZ8SEYcCst9i/CogMfMBAj2mBmpoaJk6cmOkyRE6aZDJF/e42qjc3sffVRnZvaKBuRyuplCErz0cw14sv6CKU52PBe6YcvFOUy+NI9+dy2bWE4iSzLOtg0Ajp2V+R8iygECA9m6w/QawvQW9nP+2Nvezb0sTGpXtpb+ylrztKMMdHxcw8KucUMnFuEeNm5uELaiaZiMhIVr+7jXVP7GLVIzuo39VG0YRs8sqzWHLVTLwBF96QG7fPqTdERETkuFgH7kgmJ8a8efPMmjVrMjJ2c3MzkUjknU8UGWGMMbTWdbN7fT3Vm5rYtb6efVuaScSShPJ86eArx0tOcZCsPC92hx2n24HL68DptmvZxCiQSqaI9iWI9cXpbuunta6blppO2ht6aG/sIRlPkVceYsJpRUxZUMKkecXklYX0S5OIyDDV1x3j1aV7WfvYTjYtryYQ9lA4IZvC8WGy8nx4Ai58Ibe+h4uIDELL/k7mXjKRgopwpksZEpZlrTXGzDuezx32M8Msy/opcB/wojEmlel6RpLt27crDJMRzxiT7i21ro4da+rYsbqW5ppOAmEPOcVB/NkeCsdnM3VhCQ6nHZfXidvrwOl2aJbXKGaz29IzAwIusvL8lEzOBSAZTxLtS9DfE6OzqZfmmk6eunU993zvBXo7omQXBZhwWhHTFpYweX4JBZVhBWQiIhlSu7OV1Y/s4OUHt9PR2EPJlFzyykJccsOpuLxO/GHP65fZi4iIDJGR8N3FC/wFcFmW9QhwP/CEMaYvo1WNAMlk8p1PEhlGjDHU7mxl59o6dqyuY8eaWjoaewhFfGQXBsjK8zL7/Eq8IRdOtwO3Lx186V1iOcDutONz2vGF3OQUBak4pQCTMsT6E/T3xOlo6qZ5XxfL/rSJ+366ku62frLyfAMBWSnTziojf1yWAjIRkRMgHkuy5YVqXn5oOxue3oM/y0Px5Bxmn19JMMeDx5+e/aU3s0RE5EQbMcskLcuaD7x74KMSeIZ0MPaQMaYpg6W9rUwuk2xvbyccDmdkbJGj0d3ez47VtWxdsY8tL+6jeV8n4YIAucVBQnleIqVBvEEPTrcdt8+Jy+tQSCFDwhhDrC9BtDdOZ0svzfs6adzbQUttFz3t/eSPy2LqglJmLh7HlDNKdDdLEZHj1FbfzZrHdrLygW3s39ZC8aQc8iuyKJ6Qg8un2V8iIieTlkke9rkjJQw7nGVZEzkUjJ0BrCYdjP3ZGLM/g6W9SSbDsGXLlrFkyZKMjC3yRslkiurNTWxbuZ/NL1Sze30DdoeN/PIQ4cIA+eOy8Ic9ON0OPH4FX3LyHQjI+rqjtNV107C3g8a9HbTWdmGMoXJ2AdPPLmfGojLGzcjH7tCMRBGRN0qlDDvX1rHqoe2sfWwnAMVTciiakE24IIA34MYXcmlWt4hIBigMO2REvg1jjNkJ/AT4iWVZecAVwJUDh3+cscKGmaKiokyXIGNYrD/B9lX72fhcFRuXVtFW301uaZCcogC5JUEmn5Hu8eUNOHH7nPqhWDLOsqz00lufk3B+gMrZhaSSKfp74vR0RGmq7mDLC9Us//Mm2ht7COZ6mXZmGaecW8GMReUEwp5MvwQRkYzo7YzyylO7efnB7Wx7eT/55VkUjA9zzodn4A268GV5cPucmS5TRETkoBE5M2wkyeTMsG3btjFlypSMjC1jT29nlK0r9rFxWRUbn6uirytG4fgw2UUBCivC6VlfXgfeQLrfl8hIFY8m6O+O09HcS8PuVup2tdNc04mFxYS5hZxybgWzz6sgr1y9x0RkdDLGsH97C6sf3sHLD22nu62fkim5FFRkkT8ujNvvxJ/l0QxaEZFhRjPDDhnWv5FalnXr0Z5rjPnEiaxlJKqrq1MYJidMT0c/G5dVseHZPWx+fh8mZQ6GX2e9fyregBu334kn4NIPwzKqON3pu5UGc72UTsk9NHusvY+GPR28/MA2Hr5pNT0dUcqnRZhxTjmzz6+kcnYBds2AFJERKh5NsPG5KlY9tINXl+4lFPFSND6buZdMxB924wu58QRcehNARERGhGEdhgF5b9g+B0gBGwe2ZwI2YPnJLGqkmDNnTqZLkFEk1p9g64p9vPLUbjY8s5dELEnxpGxyi4Ocf82s9PIyvwtvwKW7QMmYYrPb8IXSvwjmlYeZcU458f4EvZ3ppZW71zew8v5ttDf2EC7wM3NRObMvGM+0M0txe7VsSESGr9a6LtY8upOV92+jbncbJZNzya8IcekNp+L0OglkezTbW0RERqRh/d3LGHPFgeeWZX0D6AOuM8b0DOzzA3/gUDgmh9m4cSOLFi3KdBkyQiWTKXatq2f907tZ98RuOpp6KJqQTaQ0xDkfno7H78ITUPgl8kaWZeHyOnF5nYQLAkw6vYRELElfV4y2hi7qdrZxz/+8QEtNJ96QmxmLyjntovHMWFSOx+/KdPkiMoalUoZd69LN71c/uhObzaJsWoQJc4uYd9lE3H4nvpBbfT5FRGTEG9Zh2Bt8ATj/QBAGYIzpsSzrO8AzwPcyVtkwZbfbM12CjDDNNZ2sfXwXqx7azv5tLeRXZJFXFuK0S8YTyPbi8TnxBnUHKJFj5XDZCeZ6CeZ6KZ+eTzKRor87RntjN3U72/nHT1Zyy/97ArfPxfSzyjj1ovHMWjwOX8id6dJFZJTr7Yqy/uk96eb3K2soqAinm99/ZAZevwtfKN32QMsfRURkNBlJYVgAKAa2vGF/EeA7+eUMf5MnT850CTLMxWNJtr64j9WP7GD903twehyUTM6mck4Bp10yHpc3/Q6ww6lgVWQo2R02/GEP/rCHksmRg33HOpp6qN3RxsO/Ws1t//Y0DqedaWeWcupF4znl3AoC2d5Mly4io0DdrlZWP5Je/tjZ0kvZtDzyx4V41+dOx+VxEAh7cLj0vV9EREavkRSG/R24zbKsrwIrB/YtAH4I/CNjVQ1jmzZtYsmSJZkuQ4aZxuoO1j62k5cf2k79rjaKJ+WQNy7E+deegufAO8C6/bnISXV437GiCTmYi8bT1x2js7mXul2tPP67V7jr35dh2SymLihJh2PnVZIV0XtBIvLOEvEkW1fUsOqh7bzy1G78WW5KpuQy+4IKgjk+PH7N/BYRkbHFMsZkuoajYlmWF/gJ8AnACVhAnHTPsK8YY3ozWN5bmjdvnlmzZk1Gxt65cycTJ07MyNgyfCSTKba/vJ+X7t/GK0/swh1wUTwph4KKMOEC/0AAph+ARYYzkzL098TobO2jfmcbtTtaaazqwBjDlDNKOPXC8cw+v5Jwvj/TpYrIMNHR3Mu6x3ey8oHtVG1uomRyDgUVWRRWZuP0OvBnefTml4jIGNOyv5O5l0ykoCKc6VKGhGVZa40x847rc0dKGHbAQNP8CQObuw7vIXaSxr8E+AVgB35vjPnB252fyTBsy5YtTJ8+PSNjS2b198R45andvHTfNrav2k/h+GwKKsMUT87F7bHj0w/AIiPagXCsq7WP+t3tB8OxVCLF5PnFB8Ox7MJApksVkZPEGEPVpkZWPbSDVQ/vIBFLUjY9Qv64LLKLAri9TvxZbuxqfSAiMmYpDDvsc0dSGGZZlgOYD5QDr7vlljHmzpMwvh3YDlwI1ACrgY8YY97Yx+ygTIZhy5Yt0zLJMaS1rotVD+9gxT9eo6Wmk9KpEQoqsyioCOPyOfFnebA7NPtLZDQ6EI51t70+HEvEkkyeX8ycC9LhWG5xMNOlisgQ6u+J8erSvax6eAebl1eTWxKkcGI2RRNy8AaceINu3fVZREQOUhh22OeOlDDMsqypwENAJeklkknSPc/iQNQYEzoJNSwE/tsYc/HA9jcAjDHff6vPyWQY1tXVRTCoX3xGs/3bW3jxb1tZ+cA2AEqnRiicECac79cPwCJj2KFwrJ+GvelwrKmqg1h/golzizj1ognMPq+CSOkJ/9YpIkPIGEPNthbWPraT1Q/voKOpl5IpueSVh8ivDOP2OPGH3TjdI6ktsIiInCwKww4ZSd8pfw6sBeYA9QOPWcCvgX8/STWUAPsO264BzjhJYx+TbS/v59lHXuCjX7gi06XIEDLGsH9bC6se2s6aR3fi9jkZNzOP0981CbfPiS/r9c3v+7pjGaxWRDLNH/Ywfk4hlacU0Ncdo7cjSlN1Jyv+sZX7fvwS0d44FbMLOGXJOKYvKlc4JjIM9ffE2fJCNeuf2s1rK/cTivgonpTN9EVluL1O3AEXvqAbmz395lc8miQeTWa4ahERGY4SMX1/OGAkhWGnA4uNMT2WZaUAhzFmnWVZ/wb8Cjgls+UdYlnWDcANAGVlZXR3d9PX10dPT7q9WW5uLtFolO7ubgCys7NJJpN0dnYCEA6HAWhvbwcgFApht9tpa2sDIBAI4Ha7aWlpAcDv9+P1emlubgbA6/VSu7eRmp1NPHb38zjsTlw2D/3JHoxJYbc5cNm8RJO9pEwSm2XHbfcRS/WRTCWwLBseu59Yqp9kKo5lWXjsAeKpKIlUOlzxOoIkTIx4MgqAxxEgaRLEk/0AuB1+jEkRS/alt+3pO55Fk+n7HLjsXizLRjSR/jNx2j3YLQf9ie6BbTcOy0VfogsAh82F0+amP9mNMQa7bey8pv5kD22N3ex/rY2a9e2Eil2Mm5PLJV+ahtvuJ2WPYTkNFga/10U03kc8kX5NAW+IWDxGLJF+DX5PkEQyQTSefg0+d4CUSdEfS78GrzvdfLsvmn4NHpcPm2WjN5p+DW6nF4fdQU9/+jW4HB5cThfdfen/d50OF26nl56+TgwGh92Jx+Wlp78bY1I47A48Lh+90R5SqSQ2mx2f209/rJdEMv335PcE6I/1kUjGsbDwe0N6TXpNek1D8Jqcbovi0ixyJ7uIRgP0d+fhdQRobWxn4/rXePofK+nYFyenxEfBlCB5ZSFycnP0tVyvSa/pJL+m/kQPXS19NO7oZt/mVnDHyCvPYtzUIv7pWwvp7GrH7rTwB/y4XemvEQli+rqn16TXpNek16TX9I6vyVMIKVuM5ubmE5pHBAIBmpubMcbg8XgIBAK0tbWRTCZxuVyEQiHa29tJJBI4HA7C4TCdnZ3EYjHsdjvZ2dl0d3fT39+PZVlEIpGDuQpAJBI5+Px4jaRlkq3APGPMbsuydgI3GGOetSxrArDRGHPC7y8/kpZJvvj3rTx11xouumaeGqWOQMYYane0svXFfexYU0e4wM+EUws5/V2TqDgln5yiIC7PSMqyRWQ4SyZTdLf101rXzcZn97DphWr2v9ZCd1s/BRVhKucUUDm7gHCBH8vS0muRoRbri7NnQyM71tSyb2szoYiX8ul5TDurlMnzS4mUBAlFfOr9KSIicpixskxyEzAb2A2sAr5mWVYS+BSw8yTVsBqYZFlWJbAf+DDw0ZM09jHrjXdlugQ5BsYYGva0s+m5KnasqSOnOMDE04r4zP9dSuWsfLILA+oBIiInhN1uIyviIyvio3JWPpd/fj7dbX3pcGzpXjY9X83DN62ms6WP/PIsxs8poGJ2ATlFAYVjIschlUxRu6OV3evr2fVKA/H+BMWTc6icnc97vnQGxRNzCBcE8AZc73wxEREROWYj6Tfr7wH+gef/DjwCLAWagQ8N0RiXAL8A7MDvgR8cftAY84W//e1vjq985SuvxePxpN1uv7m6unrzEI095DyOEz5ZToZAS20Xm56r4rUVNQRzvEyaX8Rnbr6UylMUgIlIZthsFqFcH6FcHxUz83nXZ0+nu62PtvpuNj1XzablVTz267V0NPeSVxZi/Ox0OJZbElQ4JnIExhja6rrZvb6BXevqaK3tIlKeRdnUXN7/1YVMPK2InOIAgRwvdrtmf4mIiJxoI2aZ5JFYlpUDtJmheRF2YDtwIenG+KuBjwBbDjvnXOBloBf4DLAE+Ke3u2gml0k+eseLvOvas7RMchjqbOll8/PVbF5ejdPtYNK8IuZfMZnxpxYQKQkpABORYS2VMvS099Pe2MOm5VVsXFZFzdZm2ht7iZQGqZxdQOWcQiKlCsdk7OrtjLL31UZ2vVLH/m0tBMIeSqdFmHhaIVPPLCN/XBZZeX61PRARETlOo36ZpGVZTuAF4BpjzLYD+40xrUM4zHzSyy13D2z/BXg3rw/Dlh72fCXwsSEcf8jFk7qT4HDS2xll64p9bFpWRTJhmDC3gA//xyKmLiwlUhrC7XW+80VERIYBm80imOMlmOOlbGqESz51Gj0dUTqaetj8QjUbn63iqT+8Qlt9N9mFAcpn5FF5SgGF48N6g0ZGrVh/gpqtzex5tYE9GxoAKJ2SDr/e86UFFE3IJpzvxxdyKyQWERHJsBERhhlj4gN9uk7kNLYSYN9h2zXAGW9z/vXAYyewnkELuMKZLmHMS8ST7Fhdx/qnd9PV0sf4Uwt512fnMXPxOPLKs/AF3ZkuUURk0CzLIhD2EAh7KJmUy4XXzqGvO0ZXSy9bX9rPpmV7WXHfa7Ts68TpcVA6LULlrHzKpkfw6uugjFDxaIJ9W5vZu7GRqo2NxPoTFI7PpnRKLtd871zKZ+QRLggQzPFisyn8EhERGU5GRBg24A7SzfK/mulCSM8ImwcsznQhb6c71p7pEsYkYwz7t7Ww4Zm9VG1qpHx6HgvfO4W5l0ykoCJMMMeb6RJFRE4oy7LwBd34gm4KKrJZ8pGZRPvidLX2sX9bC+uf2cOONbU8f8+WdIBQGWbcrHzGzcwnp1hN+WV4ikcT1LzWwt5XG9i7sZFYX4LC8WFKpkT44DfOZvzsAsKFfoI5XhyaASkiIjKsjaQwzA9cZVnWhcBaoOfwg8aYLwzy+vuBssO2Swf2vdEFwI2kg7DoIMc8oey2kfTXO/J1NPXw6rN72fLCPsL5fqaeVcIHvr6Qsml5ZOX59a6wiIxpbq8Td4mTSEmI2edVkogn6Wnvp6W2m43L9rJ1RQ2P37KW9sZesvJ8lE+LUDYjj+KJObh9WkYuJ19/d4yabS1Ub2mi6tX0zK+C8dmUTM7mA18/i8pT8skpChLI8eJ0KfwSEREZSUZSWjINWDfwfPwbjg3F8snVwCSgknQI9mHgo28451Tgt6TvOtk4BGOeUG67J9MljHrR3jivvVTD+qf3kEykmDy/mE/8+AImn15MTnFQ7wyLiLwFh9NOVp6frDw/42cXcOUX5tPXFaOzpZeda+vY+FwVG57ew1O3rieVSJFfEaZsWoTSqRHyx2Vhd+iOezJ0jDG0N/Swb2sz1ZubqN3egs1uo6AyTNHEbD5049lUnlJAuMCv8EtERGQUGDFhmDHm3BM8RAL4HPAE6TtL3gpsBr4NrAEeBP4XCAD3DnxONXDlCa7ruPXGuzNdwqhkjGHflmbWPbGL+l1tVM4p4JJPn8bs8yooqAjj8bsyXaKIyIhjWRa+kBtfyE1hZTZnf2A68ViS7rY+2uq62fJCNdtW1fL8XzfTur8Lh8tO8aQcyqZHKJkSIbvQr+WVctSS8SQNe9vZt6WZqs1NNNd0Esj2UjQhfLC/Z/HEHLLyfASyvQpfRURERplhHYZZllVpjNlzlOdaQKkxZt87nvzWHh34ONx/Hvb8gkFc+6TzOvyZLmFU6W7rY8Oze9m0rIrsogAzF4/j6u8uoWRyLqGIT7+EiYgMMafLTnZBgOyCAOPnFPIuY+jvidPT3k/drjY2P1/FznX1bHhmL53NvekgbWI2JZNyKJqYQ25xEEtL1Mc8kzI07++idkcL+7e1ULuzjUQ0QW5JiMLxYc5831Qmn1FCXmmIQI4XX8it1gYiIiKj3LAOw4CXLMt6BPi9MealI51gWVY26SWNXwBuBm46ifUNa/FULNMljHipZIpd6+pZ+/guulr6mHJGMdf+8HymnFFMbklIyyBFRE4iy7LwBlx4Ay4ipSFmLR5HKmXo64rS095P9ZYmtq6ooWpzExuXVdHR2IPT7SC/MkzJpByKJ+WQNy5LX7tHMWMMnc291O5oZf+2Fmq2tdDXGSMr30dBZZhxM/O46Po5FE9Kv5EVyPbg9qonnYiIyFgz3MOwqaSb1T9iWVaKdOP8WqAfyAamk+4ltgr4f8aYJzJV6HCUSMUzXcKI1VbfzStP7ea1l2oonpjDGVdOYv7lkykcn40v5M50eSIiMsBms/BnefBnecgfF2bepZMOBWQdURr3trN1RQ17NtTzwr1baK3txhhDpDREfkWYwvFh8sqzCOf7NYtshEnGkzTVdNKwu5363W3U726jpyNKIOwhvyKLgsow86+cwrgZEcIFAQJhD56AS7O+REREZHiHYcaYduCrlmX9J/Au4GxgHOAFmoE7gCeMMZsyVuQwFnCFM13CiJKIJ3ltRQ3rnthFMmmYtrCEz/7mMsbPKSSnKKgfnkVERojXBWTlWcw8ZxxmYIllb2eU9sYedqyuZc/6enasqWPVQ9vpaunD7rQTKQ0OhGTZ5JWHtAx+GDDG0NXSR/O+Thqq2qnf1UZTdSeplCGnMEBuaZCiiTmc/aHplE7JJZzvx5fl0XJHEREReUvDOgw7wBjTB/xt4EOOUnesPdMljAht9d2se3wX21btp3xGPhdcN5tTL5xA4Xg1wxcRGS0OX2KZWxxkwpxCIP1GSF9XjL6uKC21XexaV8/eTY28trKGl/7RTXdbHzaHjXC+n9ySIHnlWeSWBMkpDuINuhSUDaFkIkVbfTfNNZ007+uksaqDlv1dJGJJ/FlusgsD5BQHOPWi8YyfU0ikLERwoMeXN6C/CxERETl6IyIMk+PjsKkHxltJJVPsWFPHmkd3EOtNMP3sMj7/u8sZP7uAcEFA7ySLiIwRDqedYI6XYI6X/HFhpi0sAw4LybpjdDT3ULWxkeotzTTuaWfXK/V0NPbQ3xPH7rCRXegnuzBAdmGAcGGArDwfWXk+nG79mPVG8WiCtvpu2up7aK/vprWum9a6Lrpa+sCyCEW8B/8s514ygfIZeeQNhF7eoBtv0KWebyIiIjJo+iltFHPaNKvpjbpa+3jlyd1sfr6aoonZnPPhGcy7dJJmgYmIyOu8LiQrz2LSacUApFKGWF+c/p44/T0x2hu62belmf07Wmmq7qBuVxtdrX10t/aTiCex220EI16y8nyE8/0EIz6C2R782V4C2R48fucJndH0/9u78yirqjvR499fzRRDMTkwQwQFlBiV4BQV2iFxSDDv+dLmmWirK768bs3wkvY5xLY7tu+1nU7sdjl0UPOMLjqaOEEa08Y4pFeMIjgrKKAIghgGmWuu2u+Pc4ECC6wqqurW8P2sdVedu8+uc34H7l777l/ts8/rz6zg6fteY/P6SiqGljPj659myvQxHXKu+roGtm6oYuuGKrZsqGLrhkq2rKtk8/pKtqyvpL6mgcLiAgYMLc+9+jDuyAM54byJDB8/mAFD+1I+oISyvtkMvsKigg6JU5IkyWRYD1ZVvz3fIXQJKSXee20tC+ctZdPa7Uw8YST/45bPM+Gzw10LTJLUKgUFQVnfktwfUPpy8LhBTDxu1M79tdX1WbKsso7aqnq2bKhkzbKNfPjORtav2sKflm9i+as1VG6poWpLDTXbs4fdFBQV0Lcim/lU1q+U8gEllPcvpax/CX36Z8mhsn4llJQVUVxaSHFpEYXFBftMpL3+zArm3baAupoGADavq2TebQsA9pkQa6hroKaqPruW6npqK+t2rrdWuSV7cmfllhoqN2fvayrrSAkKCwvoO7CUvgPLsldFKaMmD+WoURUc/KmBDDq4H30rSiktL975cpaXJEnKB5NhPVh5cb98h5BX1dtqefXJ5bzy5HIGD+/PZ04fx3HnTmT4hMGU9/eJkJKk9ldSVkRJWRH9BvUBYPj4wUw8duTO/Y2NidrqeuprskRTXU0DtdX1bNtYxYZVW9i0rpKt6yvZ+lE12zZWsXVlFTXb66iprKOmqo66mgbqa7NXQ10jAAnYLScWQQSsX7WFxvq0W3x1NQ3M/Zf5PPvQYnb8SgJIiZQgyBJzJWWFFJUWUVyaJd/KyospyyXkho7sT/8hBzHwwL4MPLAvAw4sp3xAKWXlxRTnrr+krIjisiIKC53dJUmSuh6TYT1YTUN1vkPIi3UrN/PCvy/l/UXrOHTaCL52w3QmnziKA0ZVeMuFJCmvCgqCsvJiKG/Zup4NDY001DVSX5clvxrqs1djw46fKbedaKhroLGhkfr6RuprG7jq5HubPWZjQ+L7s8+lqKiAgsICCgqDgqICiooLKSzK3hcWFez+Ki6kqDj76YxqSZLU3XX5ZFhE/A3wXErpiYgYBHwfGA68CdyfUlqV1wC7sIbG+nyH0GlSY2Lpi2uYP+dtGhsSU2aM4byrTmDsEQcyYEh5vsOTJKlNCgsLKCwsoKSs9V/ZDhhTwboVm5stP/zE0e0RniRJUrfU5ZNhwDeBR3LbvwIOAjYB5wL/JyKuTCn9c14i6+L6lQzMdwgdrnp7La/8bjmvPLGcg8ZVMP2CI/js2RMYdsjgNg0cJEnqKS68cQa3XjaPmsq6nWWl5cVceOOMPEYlSZKUf90hWzAYWB8Rh5DNELsOICKKgIuBmyPivZTSo3mMsUvaVrsp3yF0mPWrtvDCr5ew4o11HHbsCC76hz/j8M+NYsiIAd6+IUkSMOOCKQDce+3TrF+5maGjK7jwxhk7yyVJknqr7pAM+4gsIXYi8K87ClNK9cCdEVEIXAk8mpfourDiwpJ8h9CuUmNi2UtrmD93CfW1DdmtkFd/jrGHH0D/wX3yHZ4kSV3OjAummPySJEnaQ3dIhv0OuBkYAywEVu+x/0ngps4OqjsojO7w3/vJ6mrqefXJ93jxN8s4YEwFJ31lEtPOOYxh4wdR2qdlCxBLkiRJkiRB90iGfQ+4A3gbOCEiDgUeSintWABjJrAuX8F1ZdX1lfkOYb9s21jNgnlLWfzH9xl/9MH89789hSnTRzN0VIWPapckSZIkSW3S5ZNhKaV1wHkAEVEA/ASYFRFLgb7ABODq/EXYdZUX9893CG2ybuVmnnvkbda88xGHnzyay396FuOPGc7AA/sS4XpgkiRJkiSp7bp8MqyplFIj8J2IuBv4MjAE+LuU0i/a6xwR8SPgi0At8A5wcUppU27f1cClQAPwrZTS4+113o7QnWaGpZR477W1PPfwW9TV1POZ08fxtRtOYczhB1I+oDTf4UmSJEmSpB6iWyXDdkgpvQ683kGHfwK4OqVUHxE3kc06+98RMRk4HzgcGA78LiIOTSk1dFAc+62x64a2U0NdA2/+4X1e+PUSKoaWc/x/PYzjZ05k2PjBlJR1y4+nJEmSJEnqwsw27CGl9Nsmb58nd4sm2dpk96eUaoDlEbEMmAY818khtli/koH5DmGvqrfX8uJ/vMNrT73H6MMP4MvfP56jThvHgWMGUljkemCSJEmSJKljmAzbt0uAB3LbI8iSYzusypV1WdtqN+U7hI/ZtrGK+XOWsGTBB0w6fiSX/vh0Jp84isHD+rkemCRJkiRJ6nC9MhkWEb8DDm5m17UppTm5OtcC9cDsNhz/MuAygNGjR+9HpPunpLDrrLX10Zpt/PHhxax+ewNTZozhirvOYfzRw6gYWp7v0CRJkiRJUi/SK5NhKaXT9rU/Iv4COAc4NaWUcsWrgVFNqo3MlTV3/FnALICpU6em5up0huzhm/n14bsb+cOvFrN57XY+c8Y4vnrdSYydcpCL4kuSJEmSpLzolcmwfYmILwBXAqeklJo+jnEu8G8R8ROyBfQnAC/kIcQWq6mvyst5U0qsfHMdf/jVIhrqGpl61gRO+vPJjJw4lLLy4rzEJEmSJEmSBCbDmnMrUAo8kVvD6vmU0jdTSm9GxC+BRWS3T/5VV36SJEDfkgGder7UmFjywgf88aHFlA8o5YQvT+T4/zKR4eMHU1zqR02SJEmSJOWfGYo9pJTG72PfjcCNnRjOfqmq29Yp52mob+SN369g/twlHDB6AGd+82imnj2Bg8cN8smQkiRJkiSpSzEZ1oMlOna5svq6Bl55YjkLH1vKqMlDOe+qEzj6jE9xwOiBFBT4ZEhJkiRJktT1mAzrwfoWV3TIcetq6nnp8Xd46fF3+dSRB/H1v5/Op2eMY8iI/uRuLZUkSZIkSeqSTIb1YNtqN7Xr8Wqr6lj42DJefXI5h0wdzsX/eBpTThnNoIP7mQSTJEmSJEndgsmwHqy0sKxdjlO9vZYF/76U13+/gsOOHcFlt3yeSSeMYtBB/drl+JIkSZIkSZ3FZJj2qmprDfPnLmHxs+8z8YRR/OUdZzHxuJFUDC3Pd2iSJEmSJEltYjKsB6tpqG7T723fXM3zj77Nkhc+4PCTRnH5nedw6GeHM2CISTBJkiRJktS9mQzrwfqVDGxV/W0bq3nu4cW88/KfmDJ9DFfcdQ6HTh1O/8F9OiZASZIkSZKkTmYyrAfbXre5ZfU2V/PcQ2+x7KUPOfLUsXzrrrOZMHU4/QaZBJMkSZIkST2LybAeLNj3Ex4rt9Tw3CNvsXTBB3x6xli+ffc5jJ86nH4D22fhfUmSJEmSpK7GZFgP1qe4+ac9Vm2r5flH3uKt51czZcYYvnX3F7OZYCbBJEmSJElSD2cyrAfbXrtlt/fV22uZP2cJi559nyNOHs0Vd57DYdO8HVKSJEmSJPUeJsN6oKdnv86d3/ktNY3bufWFxzjpzyezbVM1b/5+JZM/N4rLZ53NYdNGuDC+JEmSJEnqdUyG9TBPz36dWy+bR01lHWVDYMv6SubdvpDDpg3nL+84k4nHj2TAkPJ8hylJkiRJkpQXJsN6mHuvfZqayjoAarfmChNsWL2Vaeccmr/AJEmSJEmSuoCCfAeg9rV+5ead2wUlu8o3rN7aTG1JkiRJkqTexWTY7r4AvA0sA65qZn8p8EBu/3xgbKdF1kJDR1fs3D5wamq2XJIkSZIkqbcyGbZLIXAbcCYwGfhq7mdTlwIbgfHAzcBNnRlgS1x44wxKy4sBqK8MAErLi7nwxhn5DEuSJEmSJKlLMBm2yzSyGV/vArXA/cDMPerMBH6e234QOBWIzgqwJWZcMIXLZ53NAWMq2LYCDhhTweWzzmbGBVPyHZokSZIkSVLeuYD+LiOA95u8XwUcu4869cBmYAiwvsOja4UZF0xhxgVTeOaZZ5g+fXq+w5EkSZIkSeoyTIZ1sBdffHF9RKzI0+mH0sUSdVI3YduR2sa2I7WNbUdqG9uO1Ho9qd2MaesvmgzbZTUwqsn7kbmy5uqsIvu3qwA27OugKaUD2jHGVomIhSmlqfk6v9Rd2XaktrHtSG1j25HaxrYjtZ7tJuOaYbssACYA44AS4Hxg7h515gIX5bbPA54CEpIkSZIkSeoWnBm2Sz1wOfA42ZMlfwa8CfwQWEiWCLsbuI9sof2PyBJmkiRJkiRJ6iZMhu3usdyrqb9psl0N/LfOC2e/zcp3AFI3ZduR2sa2I7WNbUdqG9uO1Hq2GyBS8i4/SZIkSZIk9Q6uGSZJkiRJkqRew2RY+/kC8DbZemJXNbO/FHggt38+MLYjg4mIL0TE2xGxLCKai0fqKT6p7f0vYBHwGvDkddddd1xEPB0RiyLizYj4NkBEDI6IJyJiae7noFx5RMQtubb0WkQc3UnXJXVJEVEYES+PHDlyPvD2kiVL3hs1atTKXBt5ICJKcvVKI+KB/v37rzn22GPT7bff/sU8hy7lTUQMjIgHI+KtiFgcEcfvR7/zSf0ewFfI+r43gX/rqOuSOlpEfDf3fe2NiPhFRJRFxLiImL+3fidXPj8ixnZASJ/U/kYDTwMvk333PKsDYpA+JiJ+FhFrI+KNJmWt7mci4qJc/aURcVFz58qDnwFrgTf2sj+AW8ja5WtAi8ZrJsPaRyFwG3AmMBn4au5nU5cCG4HxwM3ATR0VTER8LJ6I2DMeqSdoSdt7GZgKfBp48KKLLroa+F5KaTJwHPBXufZxFfBkSmkC8CS7vuCcSfak2QnAZcAdHXpFUtf37Yh4a9KkSUcAZ06aNGnh9ddfn1JKXyLr5y7N1bu0rKxs29atW5decskly2644YYr8heylHf/AvxHSmkicCSwmLb1Oy3p9yYAVwMnAocD32n/y5E6XkSMAL4FTE0pHUH2+T+fbBx1c0ppPHv0O8DGXHlHjLda0v5+APwSOCoX6+3tHIO0N/eQJWubalU/ExGDgeuBY4FpwPU7Emh5dg8fv7am2jReMxnWPqaRZSHfBWqB+4GZe9SZCfw8t/0gcCpZBrPD4kkpvZtS2ls8Uk/Qkrb3NFCZ235+/PjxQ1NKLwGklLaSDUhGsHsb/Tlwbm57JnBvyjwPDIyIYR1zOVLXFhEjgbMvueSSZ6uqqrZHxPLGxsbpF1xwwSx2taFzc9Vn3nPPPX2Bmy6++OIP1q9fPy0iOqrfk7qsiKgATiZ7KjkppdqU0iba1u+0pN/7BtmAfWPu/dp2viSpMxUBfSKiCCgH1gB/Rjaego+3nd3GW+3c77Sk/SVgQG67AvigHc8v7VVK6T+Bj/Yobm0/83ngiZTSRymljcAT7DsJ1Vmau7amZgL3krW/54GBwCeO10yGtY8RwPtN3q/Kle2tTj2wGRiSx3iknqC1n/VLgd/seJObPn8U2a3LB6WU1uR2fQgc1MZzSD3ZPwNXjhgxYkhNTU01WT+2qU+fPivJ2sXO9tGnT59DjjzyyAHAvJKSklRYWLiNjuv3pK5sHLAO+H8R8XJE3BURfWlbv9OSPunQ3OtZskFBVxjISK2WUloN/BOwkiwJthl4EdiUUqrPVWu2feT2t/d4qyXt72+Br+X2PQY4K1r51Np+pruOe9oUt8kwSb3F18hul/wRQET0Ax4CvpNS2tK0Ysoes+ujdqUmIuIcYG1K6cUWVC8YNmzYsAceeOCHHR2X1A0Uka1fckdK6ShgO3usNdTO/U4R2a0i08lu47qT7K/kUreSuz1rJllCeTjQl66f3P0q2S1dI8nWC7sPx9zqAhzffFxRvgPoIVYDo5q8H5kra67OKrJ/9wpgQx7jkXqCln7WTwOuBU4BaiKimCwRNjul9HCuzp8iYlhKaU1umvCO20psT1LmROBLEXFWcXFx/4KCgoFk6yANrKqqGt2nT5/V7Gof/ceOHVs8ffr0R4Caurq6g/v27Vu8devWscD6fF2AlCergFUppfm59w+SJcPa0u+0pE9aRTbjuQ5YDiwhS44taJ/LkTrNacDylNI6gIh4mKwvGhgRRbnZX821j1W52yrbe7zVkvZ3KbsSds8BZcBQvF1Z+dHafmY12R9SmpY/0wlx7q82jdfMUrePBWRfMsYBJWSLJc7do85cYMfTGM4DnqLjMrMLgAm5J63sLR6pJ2hJ2zsK+CnwJWBtbu2Iu4HFKaWfNKnXtI1eBMxpUn5h7qkrxwGbm0w3lnqNlNLVKaWRKaWxJSUlXznppJOqU0o/KCgoeGb27NmXsasNzQE2P/XUU9+dPn36HGDsXXfd9W5xcfFTxcXFC/N6EVIepJQ+BN6PiMNyRaeSPemxLf1OS/q9R9k1mBlKdsvku+14SVJnWQkcFxHlue9vO9rO02TjKfh429ltvJWbDdNeWtL+VubiBJhElgxb144xSK3R2n7mceCMiBiUm5l5Rq6sq5sLXEi2JvtxZLdIf+J4zZlh7aMeuJzsg1JI9ujPN4EfAgvJ/nPuJpsmu4xs8bfzOyqYlFJ9ROwWT0rpzY46n5RHLWl7PwL6Ab8CmDNnzraZM2eeCLweEa/kjnMN8A/ALyPiUmAF2WPpIVvv4SyytlsJXNzhVyV1cdu3b29YvHjxG8DjixYtKj399NMLvvGNb8w55phjah977LHf5qrdDdwXEcsmT5584DXXXHN1HkOW8u0KYHbuj5TvkvUlBbS+32lJv/c42QBmEdAA/DUddzeC1GFSSvMj4kHgJbLP/svALGAecH9E/H2u7O7cr+zsd+iY8VZL2t/3yG5N/i7ZxIe/wFvT1Aki4hdkfwgZGhGryJ4K2arxTUrpo4i4gV0ziX+YUtrXwvWdZee1kc1+vh4ozu37V9o4Xov2TZZLkiRJkiRJXZe3SUqSJEmSJKnXMBkmSZIkSZKkXsNkmCRJkiRJknoNk2GSJEmSJEnqNUyGSZIkSZIkqdcwGSZJktTLRERpRCyKiGH7eZwfR8T/bK+4JEmSOoPJMEmSpB4kIt6LiNM+odplwH+mlNbs5+n+CbgmIkr28ziSJEmdxmSYJElS7/NN4L79PUgumfYW8KX9jkiSJKmTmAyTJEnqISLiPmA08OuI2BYRVzZTZzTwKWB+k7J7IuK2iJgXEVsjYn5EHJLbFxFxc0SsjYgtEfF6RBzR5JDPAGd36IVJkiS1I5NhkiRJPURK6evASuCLKaV+KaV/bKbaFODdlFL9HuXnA38HDAKWATfmys8ATgYOBSqArwAbmvzeYuDIdrsISZKkDmYyTJIkqXcZCGxtpvyRlNILuSTZbOAzufI6oD8wEYiU0uI91hrbmjumJElSt2AyTJIkqXfZSJbc2tOHTbYrgX4AKaWngFuB24C1ETErIgY0qdsf2NQxoUqSJLU/k2GSJEk9S/qE/a8B4yKiqMUHTOmWlNIxwGSy2yX/usnuScCrrY5SkiQpT0yGSZIk9Sx/Ilsgv1kppVVka4JNa8nBIuKzEXFsRBQD24FqoLFJlVOA37Q9XEmSpM5lMkySJKln+b/ADyJiU0R8fy91fgp8vYXHGwDcSXZ75QqyxfN/BBARw8hmiz26PwFLkiR1pkjpk2bSS5IkqSeJiFLgZeDUPRbDb+1xfgy8k1K6vd2CkyRJ6mAmwyRJkiRJktRreJukJEmSJEmSeg2TYZIkSZIkSeo1TIZJkiRJkiSp1zAZJkmSJEmSpF7DZJgkSZIkSZJ6DZNhkiRJkiRJ6jVMhkmSJEmSJKnXMBkmSZIkSZKkXuP/A6nyq3ViaeqdAAAAAElFTkSuQmCC\n", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -361,7 +359,7 @@ "output_type": "stream", "text": [ "S_Neel(AF state) = 13.0\n", - "computed in 0.27140900000000023 sec\n" + "computed in 0.046875 sec\n" ] } ], @@ -427,7 +425,7 @@ { "data": { "text/plain": [ - "0.8377870256410256" + "0.9060304615384616" ] }, "execution_count": 12, @@ -535,14 +533,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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\n", 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" + "
" ] }, "metadata": {}, @@ -619,14 +615,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -660,8 +654,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "final = {'010101010101': '46.7%', '101010101010': '48.2%'}\n", - "S_Neel (final_sampled) = 12.774\n" + "final = {'010101010101': '51.1%', '101010101010': '44.7%'}\n", + "S_Neel (final_sampled) = 12.688\n" ] } ], @@ -708,14 +702,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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\n", 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", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], diff --git a/tutorials/quantum_simulation/Building 1D Rydberg Crystals.ipynb b/tutorials/quantum_simulation/Building 1D Rydberg Crystals.ipynb index 1aab5f2c..b9b72b6e 100644 --- a/tutorials/quantum_simulation/Building 1D Rydberg Crystals.ipynb +++ b/tutorials/quantum_simulation/Building 1D Rydberg Crystals.ipynb @@ -102,7 +102,7 @@ " seq.declare_channel(\"ising\", \"rydberg_global\")\n", " seq.add(resonant_pulse, \"ising\")\n", "\n", - " simul = Simulation(seq, sampling_rate=0.2)\n", + " simul = QutipEmulator.from_sequence(seq, sampling_rate=0.2)\n", "\n", " obs = [\n", " sum(occupation(reg, j) for j in range(i, i + N))\n", @@ -127,14 +127,12 @@ "outputs": [ { "data": { - "image/png": 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", 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5uRlvvPEGdu3ahWQyierqasycOROnnHIKNE0bihgJmVmLO+Id8Cpedq8/AkmUoEgKOhOd8Kt+SKKU65CIiAaN62ZuTgRByKvu9fmQxB/M5/GhK9WFkDcEVSnN1V6IqHhFkhGkrTQq/BW5DiVvBdQAoqkoyoyyom8E7fPdwNNPP40f/vCHWL16NWpra1FfXw+v14vOzk5s374dmqbh8ssvxx133IExY8YMZcwlKZLiidsXPo8P3aluxNNxhH2cIJCIikdcj2eWH8qjdYRFUcTxJxyf/TkfaIqGzkQnupPdqA3X5jocIqJBo5s6ulJd8Hl8uQ4lr0miBFmS0RHvgN/jz5vyaSj0KZmfOXMmPB4PrrnmGjz//PNoaGjo9Xdd17F8+XI8++yzmD17Nh577DFccsklQxJwKTIsA11Jnrh9IYoiVFlFe7wdAS3A1nkiKgqO46Az0QlZkvPquiYIAjRv/vXKC6gBdKe6EfaFszMcExEVukgqAsMyEPAHch1K3vN7/Nnht/lUCT7YBLcPa7i8/PLLmDdvXp922NHRgZ07d2LWrFnHHNxgi0ajCIfDiEQiCIUK50PtSnRhT/cetsr3keu66Ep2YXTF6KI+eYmodCT0BHZ27ERIC+VVMp/POhOdqAvVoSpYletQiIiOmWmZ2NmxE5IosZKyj2LpGLyKFw0VDUU7TLlPfQ76msgDQGVlZV4m8oXKcRx0p7qL6qRd9eYqXHT+RRhXPw5Nk5rwzTu+iUR88GacFAQBsigjkoxwvWEiKgrRVBQChLxL5B3HQWtLK1pbWvs10dCSV5fg9i/djo+f8nE0VDZg7oy5gx6b1+NFd7K7pNYbJqLilTAS0C29KHKCVDKFX/y/X+Cyz1yGmZNnYmLDRJx35nn45X//clDnYfEqXiSMBFJGatD2mW8GPINOa2srWlsPLbxnzJhxzEHRAQkjgaSeRNhbHOO/1723Dp+96LMYP3E87vn2Pdi3dx+efPRJNG9vxq9+86tBO47P40PCSCBtpuH1cP1NIipcuqkjpsfy8lrmui5279wNAKisruzz8373m9/hj7/7I6bNmIbauqEZ167JGrqSXUjoCc6hQkQFzXEcdCe7ocrFMannrp278I07voHTP3Y6Pv/FzyMQDGDJq0vwn//xn3hr9Vv44eM/HJTjyJIMx3EQS8fgU4tzuHKfutkfbM2aNbj66quxcePGbKunIAhwXReCIOTdrLYHK8Ru9vu692XG/RVJMn/lJVdi/br1WPLmEgRDmdkln/mfZ/DVr3wVzzz/DD728Y8N2rHYxZKIikF3shsfdH2Ql0OtHMdB87ZmAEDj+MY+TzLUsq8FlVWVUBQFV116FTZv3Iw3331z0OPr6WI5unL0oO+biGi49Ay1CmvhopjMrbOjE22tbZg0ZVKvx2+7+TYsenoRlq5ZisbjGgflWGkzDcdxMLZqbF6tBDNY+v1tuPbaazFx4kQsW7YMO3bsQHNzc6//0+CxbAsJPVEwtXArl6/EJz/+SRxXdxxOnXkqnvr5U/jBAz/AyPKRAIBYNIbXX3sdn7nkM9lEHgD+5bP/An/Ajz++8MdBjUdTNMT0GLvaE1FBi6ViUCQl12EcliiKGDdxHMZNHJe9wfyosgAA6kbUQVGG/jVpioaUmYJhGUN+LCKioZIyUoCbP6uGfJSPKgcqKisOSeQB4Pz55wMAtm7eOmixqLIK3dKRNtODts980u/qiR07duD555/H+PHjhyIeOkjaTEO3dJT5ynIdykfauH4jLrv4MlRWVuK2O26DZVv4wQM/QFX1gVbxTRs2wbIszJjZeyiGx+PB8dOOx7p31w1qTKqsIq7H2dWeiAqWYRlIWamCqdTtS1kwnBRJQSwdQ9pMwyN7chIDEdGxcF0XMT0GVSn+cqCttQ1AJtkfLIIgAAKQNJIIaMW3CkC/k/lzzjkH77zzDpP5YZA0khAEoSBmX/z+gu8DLvC7F3+HkQ2ZWrf5F87HOaedk91m//79AIDa2kPHR9bU1WDl8pWDGpMkSrAdm8k8ERWstJnOLEOkFsYNSF/KguEmiRISeoKrmxBRQdItHbqpF8wS1QMtBwzDwE+f+ClGjxmNphObBjUmTdYQS8dQFagqmN4NfdXvZP6nP/0prr76aqxbtw7Tpk07pJvcP/3TPw1acKXMdV3E9XhBtMbYto3XXn0N8z45L3vSAsCESRPwsY9/DK8ufhUAkE5lurd41ENbR1RVzf59MCmSgoSeQLm/fND3TUQ01FJGKu9msD+YYztY906mV9WUaVP6VBYMN1VWkdATsB07r99LIqLD0U0dlmMVxHjvvuYEh/ONr30DWzZtwf8s+h/I8uC+VlVWEU1HoVt60TXw9fudWr58Of7+97/jz3/+8yF/y/cJ8AqJaZswbbMglp/oaO9AOpVG47hDJ6oYN2Fc9sTVvJnXYuiHjl3UdT3798GkSAp0U+dNHBEVHNd1kTASeTteHgBcuDANEwDQ3t7ep7JguCmSgrgVh2mbLAeIqODolg5RKIzW5L7mBB/2+COP4+lfPo2vfv2rOOe8we/JJYoiHNeBaZvworiS+X5/M770pS/hiiuuwL59++A4Tq9/TOQHj2mbsGwLspj/tXB91dO9vqe7/cFaW1qHZHkiRVJgOpmKESKiQmLZVqY1Jo/LAVEUMWX6FEyZPiVvuy5KogTHdTgJHhEVHNd1kTSSRT3nx6JnFuH+e+/HlZ+7Erf8xy1DdhxBEIqyHOh3ydvR0YFbb731sOOeafAYlgEXbkGMl6+sqoTm1dC8vfmQv23fuj3786QpkyDLMt59+91e2xiGgfXr1uP46ccPemySKMFyLCbzRFRwDNuAaZt53TIvCAJ8fh98fh+qqqv6VBbkSjHexBFRcbPszD1sPlfqHqyvOUGPl198GV/98ldxwYUX4Dvf/86QxuaRPEgYiSE9Ri70O5n/zGc+g7/97W9DEQsdRLf0gukOKEkSzvr4WXj5xZexZ/ee7ONbN2/FkleXZH8PhUM442Nn4LfP/RbxWDz7+POLnkcinsCnPv2pIYlPgADLtoZk30REQ8WyLbhuYVTqAn0vC3JBEZWiXZaIiIpXT4NUPlfqHqw/5cCKv6/AF6/7IuaeOheP/uTRIe/dJYkSTMuE7RRXT3LB7eci3Pfffz8WLlyI+fPnY/r06YdMgPflL395UAMcTNFoFOFwGJFIBKFQfs9qu7tjN1JmqmCWUNiwbgMu/MSFqKyqxNXXXQ3LsvDz//dzVFVXYeP6jdjTlTmh33vnPXx63qcxYdIEXH715di3dx9+8uOfYO6pc/HM888MSWyRVASV/krUhGqGZP9EREOhM9GJfd378noCT8dx0NXRBQAoryzHpg2b+lQWbFi3AX956S8AgN/++rdob23H52/+PABg6vFTcd4F5w1qnEkjCVEQcVz1cYO6XyKioRRPx7GzYycq/IO3VNtQ60tO8MH7H+ATZ3wChmngm/d9E8FgsNc+phw/BVOnTR3UuEzbhG7pGFs5tqiGLfQ7mW9sPHRCg+zOBAE7duw45qCGSiEl8zvadsB13byccTGlp/DyhpexeMNidMQ7MLJ8JM47/jwEOgP49t3fxqYNmzCifgS+8OUvoHV/Kx767kPZGzgAWLl8Je6/936se3cd/AE/LrzoQtx1910IBIem4iKWjiGgBjCyfORHb0xElCdao63oSHQg7A3nOpRDuK6L17e8jpfeewloATRFw+SZk3HB9Auw4a0N+K9v/NdRy4JFzyzCbTfddth9X3LZJVj42MJBjTdtpuE6LhqrG/N2bD8R0YdFU1Hs7tydt5W66/asw/+9+39Yu3stPJIHp004DfNnzMfu9buPWg4sW7oMl1x4yRH3e9sdt+H2O28f1Fgdx0FMj6GxqrEgJhjvq34PwGhuPnQMxHD68Y9/jAcffBAtLS044YQT8KMf/Qhz5szJaUyDzXZsuI4LQcy/rpVJPYn7/nQflm9fDlEUocka9kX34a3338IF0y7AH//6x15LZ/zggR8cso85p8zB71/+/bDFLIkSx8wTUcExLCMvZzB2XRdPLHkCz695HqZtYpJnEizDwquvvYql25bivovuw5//1nvFmw+XBZf+26W49N8uHbaYJVGC7mRWNmEyT0SFIp+7hC9evxgL/7oQsXQMXo8XLlw8tfwpvLrpVXzr0986ajlw6umn9mroGw6iKMJ27Lx+Twdi0Eq0ffv24Xvf+95g7e6wFi1ahNtuuw333HMP3nrrLZxwwgmYN28eWltbh/S4w81xHNiw8/Im7g/v/gHLti9DbagWoytGoyZUg7GVY1HuK8ef1/0ZS7bkdlzk4QiCkKkg6V8nFCKinLIcKy/nTlmzaw1++/Zv4VN9GFs1FnpIh11mY0TZCKzdvRaLVi3KdYiHEAUxs/KO6+Q6FCKiPrMdOy/nTemMd+KxJY8hbaUxtmos6sJ1GBEegTGVY7Cnaw8effXRvLzvFgSh6MqBfrfMX3vttYd9fNeuXVi5ciW+9rWvHXNQR/LQQw/h+uuvx+c+9zkAwBNPPIH/+7//w89+9jPceeedfd6Pbdu9JhVyHCf7+8E19j1L7YmiOOTbuq4Lx+n95RIEAY7twIV72G0FCBClA/sdsm3/8ToA4KX3XoJH9sCreCG4/3ie4CKoBdGR6MDi9Ytx1sSzjviaJUk6ZL8Hb3vw+9CfbY/2vgsQ4DgOLMuCKIrD8nkOx/fk4PcnH7YdzM8zF9+To73mfNiWn/3Qfvb5+D3pueE40ra5Kh9e2/wadFNHfbj+QDkAF6qswq/68df1f8UVJ10Bn+rrtd+e15eL74kAAS7cTKvMUWLIl8+e1wheI/g9KczvyZFe80C3dVwn+3h/9jvU5cMbW99AR7wDoytGQ4CQLQskUUJNqAYbWzZi496NmFQ3qdd+e17HkXKNw73v/dn2oz7Pnu0Gkpfk8hpxNP1O5ru6unr9bts2duzYgY0bN+Kxxx7r7+76zDAMrFmzBnfddVf2MVEUce6552L58uWHfY6u69B1Pft7NBoFACxbtgyf+MQn4PFkJj/YvXs3mpubMWLECEyaNCm7/d///nc4joOTTz4ZmpYZW7F3715s27YNNTU1mDr1wMQMK1asgGmaOOmkk+D3+wEALS0t2LJlC6qqqjBt2rTstqtWrUI6ncaJJ56YHbvf2tqKjRs3ory8HFOOn5L5ICFg47qNSKfSmDh1IoKhzOQQka4Itm/ZDn/Aj8nTJmf3u3nDZiQTSYybNA5l5WUAgFgkhq2btsLr82LqjAPxbtu8DbFoDI0TGlFRmZlUIxFLYPOGzVA1FdOaDsS7Y8sORLojqBtdh85kJ3yKD4qrYIQ5ArZgY48n001GkzUY7QbWrlqLhrENqKk7MOHc2lVrIUkSmk5qyj72fvP76GjrwMjRI1FXXwcAMA0T7739HgRBwIlzT8xu+8GuD9C2vw0jRo1A/ah6AJnv3jur3wEAzJwzM3si7N29F/v37UftiFqMGjMKQOYEW7p0KQRBwOmnnw5Zznz133//fezcuRP19fWYOHFi9nhLly6F67o45ZRToKpqJoYPPsCOHTtQV1eHyZMPvO/Lly+HZVmYM2cOfD4fgExPla1bt6K6uhrHH39gyb0333wThmFg9uzZCAQC2c9+06ZNqKiowIwZM7Lbrl69GqlUCjNnzkQ4nBkz29bWhg0bNqCsrAxNTQfey7fffhvxeBwzZsxARUXm8+zs7MR7772HYDCIWbNmZbd95513EI1GMW3aNFRVVQEAIpEI1q5dC5/P12vYyrp169DV1YUpU6Zkl6OMxWJ46623oGkaTj755Oy2GzZsQHt7OyZOnIj6+sxnlEwmsWrVKiiKgtNOOy277aZNm9Da2orx48dj1KjMZ6TrOlasWAFRFHHmmWdmt926dSv27duHxsZGjBkzJvM9MU0sW7YMAHDWWWdlt92xYwc++OADjB49Gscdl5noynEcvPHGGwCAM844I3vh3rlzJ95//32MGjUK48ePz+6jZ9tTTz01b68RJ5xwQnbbNWvWIJlMoqmpCWVlZQAyS4iuW7cOoVAIJ5544Dxau3YtYrEYpk+fjsrKSgCZa/q7776LQCCA2bNnZ7d977330N3djalTp6KmJnMuR6NRvP322/B6vZg7d25223Xr1qGzsxOTJ09GXV3mXE4kEli9ejU8Hg9OPfXU7LYbN25EW1sbJkyYgJEjM/NYpFIprFy5ErIs4/TTT89uu2XLFrS0tOC4447D6NGjAWTKguXLl0MQBHzsYx/Lbrtt2zbs3bsXY8eOxdixYwFkrhFLly4FAJx55pnZa0RzczN2796NhoYGjBs3DkDmGtHz2efLNQLIrMbR1dGFndt3IlwWxvjJB76rG97bAD2tY9LUSQiEMteTrs4uNG9tRjAUxMSpB+LdtH4TUskUJkyegFBZ5jsV6Y5g++bt8Pl9mDJ9yoH3feMWJOIJjJs4DmUVZQCAeCyOLRu2QPNq2Ne9LzuzcrVVDc3R0C63Iykl4fP4YBs21qxcg4pwBabPnI6DrV21FqMbR6O6thoAkE6lseHdDZBlGSfMPvC93rV9Fzo7OjFqzCjUjqjNfvbr3l4HURQxc87M7La7d+5Ge2s76hvqMWLkCACAZVl4d01mGdRZJx+4/u1s3onWllZeI3iNAFD41wjeRxT/fUTVqKoD7+Xb62BZFqbOmAqvLzOnVkdbB95vfh9l5WUYN2lcdtv1766HoRuYPG0y/IHM9aSzvRM7t+9EMBzExCkHvqsDyTU64h0QIEASJWiOhhqzBoZgoMXTAp/Hh7ZYG3Zs2YHU7lSvXAPIlANHyjXGjhuLyurMtSeVTGHjexuheBTMOPHA97p5WzO6O7t75Rp6Wsf6d9Z/ZK4hQIBhGHhj5RsFdY04mn734/7d737X698f/vAHrFu3Dvfddx9eeOGF/u6uz9rb22Hb9iHr29fW1qKlpeWwz1mwYAHC4XD2X0NDw5DFN5gECBCETCtCPvFIHoS1MFJm6rB/T1tphH29J2q6/c7bsX1v7tcXJiIqRPlWDgBAdaj6wDwkLhCwA6g2qyG4AlJGCpqiQZXVXs+5/c7b8fqK13MQLRERDbaQFsr2dvqwlJGCqmR6ah3s9jtvx+Zdm4crxMPKxzL1WPV7Nvsj2bFjB44//nikUodP9I7V3r17MXLkSCxbtgynnHJK9vGvfe1rWLJkCd58881DnnO4lvmGhgZ0dnairKwsb7s9Oa6D5o5mqLIKCVLedLMXBAHPrHwGP3n9J6gP1WdngnQFFwk9gY5EB+6Ydwc+MfUTedXtKWWm4DouxlSMYTf7IdyW3eP42RfyZ5+P35NdHbtgORY0WcurbvYrd63EN373DQS0AMrVcowyMq1i26Xt2N29G5fOuhRfOPsLg9o18li3tR0bCT2BMRVj4JE9ef/Z8xrBawS/J4X5PTnSax7otp2JTrTGWlHmK8urbvYdiQ5c/z/XI2WmMCI0AgL+MRQANnZ17MK0kdPwyL8+AkEU+p1rDGU3+65kFxrKG+D3+Af9sy+YbvZH8s4772DmzJkfveEAVVVVQZIk7N+/v9fj+/fvz3bZ+jBVVbPdFg4mSVL2TQNwxDfr4A94qLcVBOHA4w4gIjPjoqIoR9/24ONJhx5vULY96HV8uunTWLNrDdbsWgOP7IEma0gYCbiui7MnnY2PT/n4Ifvoy36HclvXdSFL8mHfy3z47Af8PcmzbYfr8xzKbQF+9gPZNl8/z0L/nsiinJnR/gjbDtk1/yO2nTN2Di6YfgH+9O6f0J3sRtwTh+EY6DQ6MWXEFHx27mdz/hl9eFvHdSCKImRJPqYyCuA1YiDb5uu5XOjXiIFsy+/J0G4LDO7nKYkSetpd+7PfoS4fakI1+Pcz/h0//tuP0dzejKAWhO1mKk1rw7X44llfhKwcmmbm/DNyM+9poX1Pjqbfyfxtt912yGP79+/H73//e8yfP7/X3x966KF+B3QkHo8Hs2bNwiuvvIKLLroIQKb24pVXXsHNN988aMfJB5IoQRTF7MmbT4JaEN+66Fv44zt/xF82/AWd8U5Mqp2E86edjwumXQCP7Ml1iIewHRuaXDzrSRJRafDIHsT0WK7DOIQoivjKOV/B8fXH48X3XsSujl0I+UO4eOrF+NQJn0KFvyLXIR7CdmxIkAZ0o0RElCv5uLJVjwtPuBB1oTr86b0/4d0P3oUsyrhg2gX4p6Z/QmNVY67DO4TjZCp183GVmGPR7272Z599dt92LAh49dVXBxTUkSxatAhXX301nnzyScyZMwcLFy7Er3/9a2zatOmQsfSHE41GEQ6HEYlEshPG5KvdHbuRMlMIaIFch3JUPSdGPoukIqj0V6ImVPPRGxMR5YnORCf2de9Dub8816EcVSGUAykjBUEQcFz1cbkOhYioz+LpOHZ17Mr7cqAnnTy453O+MW0TaTONxqrGvGx8HKh+t8z/7W9/G4o4+uTSSy9FW1sb7r77brS0tKCpqQkvvfRSnxL5QqPICuJGPNdhfKR8v4EDMjeasjRoI0qIiIaFJEhA/t4XAcjcwHV3dQMAyivK8/ZGznZs+Dy+XIdBRNQvkpgZGtwzjjpf5XNsPRzXgSRIRdcyX3AZzs0331x03eoPR5XV7BrDdGxcuNlllIiICoUsyZn10fP4Js5xHDRvbQYAhE8KH3YMYD4wHTM7aSsRUaGQRRmyJMO0zaJqTc4Fy7bgkT1Fl8z3qVn1/PPPx4oVKz5yu1gshu9+97v48Y9/fMyBlTpFUlCEqycMO9uxIYkSk3kiKjiKpECWZFiOletQjkiAgGAoiGAomJ3NOF/xRpiICo0syfBInrwuBwqFaZvwKcXXQ6tPLfOXXHIJLr74YoTDYVx44YWYPXs26uvroWkaurq6sGHDBixduhQvvvgi5s+fjwcffHCo4y56HtmTrYljIjpwpm3CI3r4HhJRwVEkBbIow7KtvL2GiZKIiVMn5jqMo3IcB6Ig5u17SER0JIIgwKt40ZnszHUoBc9xnaKs1O1TMn/dddfhiiuuwHPPPYdFixbhJz/5CSKRCIDMl2zq1KmYN28eVq1ahSlTpgxpwKWiEG7iCoFlW/Aq3qLrUkNExU8QBPg8PnQlu+CFN9fhFCzDNqCISlHexBFR8VMVFbZj5zqMgtZTqVuM5UCfx8yrqoorrrgCV1xxBQAgEokglUqhsrLysOt307ERBAFBLYj2eDu8Ht7EDZRhG6gOVuc6DCKiAfEqXrQ77bkOo6AZloGgFmSlLhEVJFVWIYlSdugo9Z9u61AltSiT+QFPRR4Oh1FXV8dEfgh5PV44rpOX680Xgp6LHic9IqJCpSkaFEmBaZu5DuWwHNvBhnc3YMO7G+DY+Tlpq+VYCKj5vcwrEdGRqLIKTdGgW3quQylYuqkjoAWKsjIk/9cVK2GarEGVVRi2ketQCpJu6VBlFaqs5joUIqIB8cgeeBUvdDM/b+JcuEglU0glU3DzcNbWnnlnWKlLRIVKFEUE1WDelgP5znVdOK4Dn1p8k98BBbg0XSlRZAU+jw/RdJQJ6QDopo7aUC1EkXVWRFSYeoZcRVPRXIdyWKIoYsLkCdmf841u6tAUrSi7VhJR6fB6vBAEITP2Ow+vtfnMsI1M7wa5OCt1+W3IcyFvCLZjs6t9P1m2BVEU4fMUZy0cEZUOn8cHRVZgWPnXS0sQBITKQgiVhSAI+bU0neu6MGwDZd6yvIuNiKg/vIoXXo8XKTOV61AKTspIIaSFoMjFOTScyXye83l88Co8efsrZaYQ8AQ4eSARFTxVURHSQkgayVyHUlB0S4cma6zUJaKCJ4oiyrxlHDffTz2rAAS04p03pd/J/NVXX43XX399KGKhw5BECWW+MqTNdK5DKRiu68K0TYR9YbbGEFFRCGpBAJnldfKJ67ro7upGd1d33vUgSxkphLzF2xpDRKXFr/qhyioT+n5IGSn4VX9RV+r2O5mPRCI499xzMWHCBHznO9/Bnj17hiIuOkhADcAje5jQ91HKTMGreIv6xCWi0uLz+ODz+PKudd5xHGzfvB3bN2/Pq4oG0zYhiVK2EoSIqNB5ZE+ml5aeX+VAviqVoVb9TuZfeOEF7NmzB1/4whewaNEijB07FhdccAF+85vfwDTzc+mcQqcqKsq95Xl3E5ePXNdF2kijMlAJWeL8jkRUHERRRIW/AqZt5lXSLECAz++Dz++DgPy5WYqn4wh7wxxqRURFJewLQ5Zkts73QUJPIKAGirqLPTDAMfPV1dW47bbb8M477+DNN9/E+PHjceWVV6K+vh633nortm7dOthxlrywLwxN1jh2/iMk9AT8mp+tMURUdAJqAEEtiLgez3UoWaIkYsr0KZgyfQpEKT+m4dEtHbIko9xfnutQiIgGlaZoKPeVI6Ench1KXnMcB4ZtoMJfUZRryx/smEreffv2YfHixVi8eDEkScInP/lJvPfee5g6dSoefvjhwYqRkOlaU+4vR8pI5d24xHyRPXF9xX/iElHp6Wmdd1wHlm3lOpy8ldATKPeVc215IipKZb4yqLLKBr6jiOtxhLQQAmpxt8oDA0jmTdPE888/j0996lMYM2YMnnvuOdxyyy3Yu3cvfvnLX+Kvf/0rfv3rX+O+++4binhLWtgbhl/151WrTD6JpqMIa2G2yhNR0fKrfpT5yhBLx3IdSl5KGklosoYyX1muQyEiGhIe2YMKfwVSeiqvhl3lC8My4MJFhb8CopgfPcaGUr8HFY8YMQKO4+Cyyy7DypUr0dTUdMg2Z599NsrKygYhPDqYLMmoClRhd+dumLYJReIMvT3SZjrz/gSrSuLEJaLSJAgCKv2VSOpJJI1kzif6dGwHWzZuAQBMnDIxp13tLduCbuoYVT4KHtmTsziIiIZama8MCT2BaDrKysuDuK6LuB5HTbCm6MfK9+h3Mv/www/jkksugaYduftaWVkZmpubjykwOryAGkClvxJtsTaU+8uLenbGvnIcB0kjiRHhEZzsiIiKnqqoqA5W44OuD6DKak6HFblwkYgnsj/nUjQdRYW/AiFvKKdxEBENNUmUUBWoQspMIW2mOazoH+J6HH7Vjwp/Ra5DGTaCW0IDsKPRKMLhMCKRCEKhwi3sTcvEB90fQDd13rQA6Ep0IaSFMLJ8JFvliagkuK6LfZF96Ep25XTZHdd1EemKAADC5eGcxRFPxyEJEhoqG9gqT0QloyPegX2RfQh7wyU/X5Ru6UibaTSUN5RMqzxwjBPgUW4osoLaYC1EUSz55epi6Rg0RUNNqIaJPBGVDEEQUB2oht/jRzQdzWkcZRVlKKvIXYVC2kzDcR3UhGuYyBNRSSn3laPCX4FIKlLSE2RbtoWEniip7vU9mP0UKJ/qQ22wFoZlwLCMXIeTEz2zeNaGaqEqao6jISIaXoqsoDZUC1mUS3aZItM2kTJSqA3VcvJTIio5oiiiOlCNoBZEJBXJdTg54TgOoukoqvxVJdW9vgeT+QIW8oZQE6xBXI+X3DJFuqVDN3XUhmpLrgaOiKiH1+NFbagWlmMhbaaH/fiu6yIWjSEWjQ17q5Dt2IilY6gKVHECKCIqWT0Vu6qkltxKJ67rIpKKIKyFURWsKsm5xJjMFzBBEFDhr0B1oBrRVLRkEnrDMpDUk6gJ1iDsDec6HCKinAp5Q6gL1SFtpoc9oXccB1s2bMGWDVuGdYkk27ERSUVQ4a8o2Rs4IqIemqKhrqwOoiAini6NJaxd10V3sht+1Y/acC1kqd/zuhcFJvMFThRFVAerURWoKomEXrd0xPU4akO1qAxU8gaOiAiZZYpqQ7XDntALEKB5NWheDQKG53rck8iX+8pRG6ot+UmfiIgAwK/6MSI8AhBQ9An9wYn8iPCIkp4vhbPZFwnHcdAWa0NbvA1+1Q9VLr4x5CkzhbSRZiJPRHQYPTc3+yL74JE9OV+DfiiYtolYOoYKfwUTeSKiw4in49gX2QfLsRDSQkV3v+w4DrpT3QioAYwIjyj5ebPYMl8kelro60J1SBmpopvlPpaOwbIt1JfVM5EnIjoMQRBQ7i/HyLKRcFwH0VS0qGY3TpkpxNNxVAeqmcgTER1BQAtgZNlIaIqGrmTXsA6BGmqmbaI71Y1yXznqy+pLPpEHmMwXFVEUURWsKqobOcdx0J3shizIGFk2EuX+cibyRERHEfaFMapsFFRFLZobuVg6BtMyUV9Wj5pQDRN5IqKj8Kk+jCwbiTJvGbpT3TBtM9chHbODK3TrwnUl3bX+YKU5U0CRC/vCUCQF+2P70ZXsQkANFOQXPm2mkTSSCGkh1IRqoClarkMiIioIPtWHkdJItEZb0Z3qhtfjhVfxDvpxHNvBti3bAADjJ46HKA1uG4FlW4imo/AqXq5eQkTUDx7ZgxFlI6BICjoSHZBFGX7VX3CNYj1Lz8mSjPqyepT5ygruNQwlJvNFyqf60CA3oCPegc5kJ3RLR0ANFMSX33EcxPQYREFEXagO5f5ytsIQEfWTR/agvqweftWPtngbupPdCGkhiOLgJdwuXMQisezPgymhJ2DaJir9lagMVBZkpTQRUS5JooSaUA18qg+t0VZ0JbsQ1IJQJCXXofVJykwhZaSyS895PYNfKV3oOAFeCYin42iLtyGhJ+BVvHl7Iriui6SRhG7pCGpBVAeq4VOLbwInIqLhljbTaIu2IZKOwCN5Bq11xnVddLZ3AgAqqioGZZ89vbK8ihfVwWoEtWBBVEQTEeUz0zLRmehER6IDgiAgoAbytrHMtE3E03EosoJKfyXKfeWDWhFdTJjMlwjLthBJRdCV6ELaTMOn+vKq23rKSCFlpuBVvKgMVCKoBfP2AkNEVIgcx0Fcj6Mj0YGEnoCmaPAq3rxJlHVLR9JIwiN5UO4rR9gbhiIXRusREVEh6Gk464x3Zruu+z3+vEmULdtCQk9AEASUectQ5i/Lq3wlHzGZLzGGZSCaiqIr2QXd0qHKKryKNycnse3YSBkpGLYBTdZQ7s/cvMkSR38QEQ0V27ERS8fQEe9AykxBkRT4PL6cVKC6rptZdtRMwyN7UOYtQ9gb5gzFRERDyHVdxPU4OhOdiKfjEEURXsWbs+FMaTONlJGCKIoIaSGU+8rZO7ePmMyXKMMykNAT6E51I6knIYoiVFmFKqtD2krjOA50W0faTAMA/B4/ynxl8Hv8bIEhIhpGPS0gkVQEcT0O13WhKRpUWe1zBa/rukgmMkuh+vy+PpUfruvCsA3opg7LseBVvCjzlSGgBpjEExENI8dxkDSSiKajmVVDbDObDwx145phGdAtPXvMsDeMgBqA15M/PcYKAZP5Euc4DhJGAvF0HAk9Ad3SIQgCPLIHiqRAFuVjOqFc14VpmzBtE4ZlAAKgSRoCWgABLZCzXgFERJThui5SRgpxPY5YOgbd0uHChUfyQJZkKKJyxOu0bdtYu2otAKDppCZI0qGt+67rwnIsWLYF3dLhuA5UWYXP40NQC8Kv+jmsiogox9JmGgk9gVg6hrSZhuVYUCQl++9Yr9OWbcF0MvmA7djwyB5osoaQN8RGvWPA/swlThRFBLUggloQlm1lu7nE9MwNXdyOZ7YTRIiCCEmUIAgCJKH3Ce3CheM6cF0XtmPDdmw4rpOpGJAyFQPlvnJ4PV5oisYbNyKiPCEIAnyqDz7Vh6pAVaYcMDPJvWEZSBkpuK6bufaLUqY8EDNlgmu7kJTM9dy0TJiOCcd14DgObDdTFggQMpUCkoKqQGY2Yk3WeONGRJRHNEWDpmio8FdAtzK9aGOpf+QDVhyO6wAAJEHqVRYI6N3od3A+4LgObMeGCxeymCkHyrxl8Kt+aIrGVUoGAVvm6bAOblHvaVXv+dm2bTjInNAu3OxJ3JPs9yTvPa37iqRAlo6thZ+IiIafZVu9rv+GZcCwM60qruui579sOQARkiRBFmV4ZE+vckCRFJYDREQFxnbsA9f/g8oDy7HgOE62HAAA4R//iaIIRVSgyJl8oCc3UKQj9/SigWHLPB1WT1f7w9WYOY6TrZ3raa0BkK2hIyKi4iBL8mHHTfa0uvT8zHKAiKg4SWKmJf7Ds8q77oFeuT1tw4IgZHtx0fBgMk/9JooiRPBmjYioVAmCwJVHiIhK2OGG3dLwK5iMbOzYsdnanp5/DzzwQK7DIiIiKlmO42DdunVYt24dHMfJdThEREQlpaCq1e+77z5cf/312d+DwWAOoyEiIiptruuivb09+zMRERENn4JK5oPBIOrq6nIdBhERESHTzXLixInZn4mIiGj4FMxs9mPHjkU6nYZpmhg9ejT+7d/+Dbfeeitk+cj1EbquQ9f17O/RaBQNDQ2czZ6IiIiIiIgKWsG0zH/5y1/GiSeeiIqKCixbtgx33XUX9u3bh4ceeuiIz1mwYAH+67/+q0/7dxwHhmEMVrh5TVEUSBInrCAiIiIiIipUOW2Zv/POO/Hd7373qNts3LgRkydPPuTxn/3sZ7jhhhsQj8ehquphn9vXlnnDMNDc3FxSk/eUlZWhrq6O3SKJiGjAXNdFMpkEAPh8PpYpREREwyinyXxbWxs6OjqOus1xxx0Hj+fQtc7Xr1+PadOmYdOmTZg0aVKfjheNRhEOh3sl867r4v3334dpmqivry/69XF7brxaW1tRVlaGESNG5DokIiIqULZt44033gAAnHHGGez1RURENIxy2s2+uroa1dXVA3ru2rVrIYoiampqjikGy7KQTCZRX18Pn893TPsqFF6vFwDQ2tqKmpoa3nwREdGAKYqS6xCIiIhKUkGMmV++fDnefPNNnH322QgGg1i+fDluvfVWXHHFFSgvLz+mfdu2DQCHbf0vZj0VF6ZpMpknIqIBkSQJp512Wq7DICIiKkkFkcyrqopnn30W9957L3RdR2NjI2699Vbcdtttg3aMUhvnV2qvl4iIiIiIqJgURDJ/4oknYsWKFbkOY1B1d3fjiSeewJ133pnrUIiIiIiIiKjAFPdsb4PMcRys2L4CC/+6ED/86w+xsnklBjp/YHd3Nx544IFBjpCIiGj4OI6DDRs2YMOGDSW1IgwREVE+YDLfR7Zj4zsvfgc3/upGPPHaE3j8tcdxw1M34Lt//u5H3sBcfvnlmD17NmbMmIH58+ejpaUFN954I2KxGJqamjB79mwAwLZt23DuuedixowZaGpqwgsvvJDdhyAIuP/++zF37lyMHTsWL7zwAhYsWIDZs2djwoQJeO211wBkVgg477zzMH36dMyYMQOf+9znhuotISKiEue6LlpbW9Ha2jrgym0iIiIamILoZp8Plmxegl+v/jVCWggNFQ0AgI5EB55d9SxOn3A6Tp9w+hGfu3Dhwuys/Q888ADuvfdePPHEE2hqasLatWuz211++eW49tprccMNN2Dr1q04+eSTMXPmTIwZMwYAEAgE8Oabb+KVV17Bpz/9aTz66KNYvXo1nnvuOXz1q1/FqlWr8Ktf/QqNjY34y1/+AgDo7OwconeEiIhKnSAIGD9+fPZnIiIiGj5M5vvo9a2vw7AMlPsPzJ5f6a9ER7wDS7ctPWoy/8wzz+Cpp55COp1GOp1GVVXVIdvEYjG89dZb+Pvf/w4AmDBhAk4//XS88cYb2WT+0ksvBQDMnj0biUQCn/3sZwEAc+bMwdatWwEAJ598Mh5++GHcfvvtOPPMM3H++ecPzhtARET0IaIoYtSoUbkOg4iIqCSxm30f2Y59xL+ZtnnEvy1duhSPPPIIXnzxRaxbtw4PPfQQ0ul0n4754VYOTdMAILuU3MG/W5YFADjllFOwdu1azJ07F7/97W9x0kknZZffIyIiIiIiouLAZL6P5jTOgSRKSOiJ7GPxdByyKOOksScd8XldXV0IBoOorKyEYRh48sknAQChUAipVAqGYQAAgsEgTjzxRPz85z8HkBk/v3TpUpx55pn9irO5uRmBQAD/+q//ih/96EfYsmUL4vF4f18uERHRR3JdN9vrjGPmiYiIhhe72ffRJ6Z+Ai+vfxmvbnoVQOYGRhREfGLqJ/DxyR8/4vPOP/98/OpXv8KkSZNQWVmJc889F3v27EFFRQWuuuoqzJgxA4FAAKtXr8bTTz+NG2+8EY8++igEQcBPf/pTjB49ul9xvvbaa3jooYeyrfUPPvggwuHwMb12IiKiw3EcJ7t07BlnnJHtOUZERERDT3BLqCo9Go0iHA4jEokgFAoBANLpNJqbm9HY2Jjttn4kaTONP737J7yx9Q2IgogzJ5yJC6ZfAE05+vPyUX9eNxER0eHYtp2d6+W0005jMk9ERDSM2DLfD5qi4V9m/Qv+Zda/5DoUIiKinJMkqd/DwYiIiGhwcMw8ERERERERUYFhMk9ERERERERUYNjN/h9KaOoAAJlJi4iIiI6F4zjYunUrAGDChAkQRbYREBERDZeST+YVRYEgCGhra0N1dfUha7sXG9d1YRgG2traIIoiPB5PrkMiIqIC5bou9u3bBwAYP358jqMhIiIqLSWfzEuShFGjRuGDDz7Azp07cx3OsPH5fBg9ejRbUYiIaMAEQUBjY2P2ZyIiIho+Jb80XQ/btmGaZo4iG16SJEGWZd54ERERERERFaiSb5nvIUkS18clIiIiIiKigsBknoiIiAbEdd1sr7aeOWiIiIhoeHDANBEREQ2I4zhYtmwZli1bxlVSiIiIhllJtcz3TA8QjUZzHAkREVHhs20biUQCQKZs5XA1IiKiwRMMBo/a662kkvlYLAYAaGhoyHEkREREREREREd2uInbD1ZSs9k7joO9e/d+ZA0H9U00GkVDQwN279591C8ZUTHjeUCljucAlTqeA1TqeA4MHbbMH0QURYwaNSrXYRSdUCjEE5dKHs8DKnU8B6jU8RygUsdzYPhxAjwiIiIiIiKiAsNknoiIiIiIiKjAMJmnAVNVFffccw9UVc11KEQ5w/OASh3PASp1PAeo1PEcyJ2SmgCPiIiIiIiIqBiwZZ6IiIiIiIiowDCZJyIiIiIiIiowTOaJiIiIiIiICgyTeSIiIiIiIqICw2Sejomu62hqaoIgCFi7dm2vv7377rs444wzoGkaGhoa8L3vfS83QRINsp07d+K6665DY2MjvF4vxo0bh3vuuQeGYfTajucAFbsf//jHGDt2LDRNw9y5c7Fy5cpch0Q0JBYsWICTTjoJwWAQNTU1uOiii7B58+Ze26TTadx0002orKxEIBDAxRdfjP379+coYqKh9cADD0AQBNxyyy3Zx3gODD8m83RMvva1r6G+vv6Qx6PRKM477zyMGTMGa9aswYMPPoh7770XP/nJT3IQJdHg2rRpExzHwZNPPon169fj4YcfxhNPPIH//M//zG7Dc4CK3aJFi3DbbbfhnnvuwVtvvYUTTjgB8+bNQ2tra65DIxp0S5YswU033YQVK1Zg8eLFME0T5513HhKJRHabW2+9FX/84x/x3HPPYcmSJdi7dy8+85nP5DBqoqGxatUqPPnkk5gxY0avx3kO5IBLNEAvvviiO3nyZHf9+vUuAPftt9/O/u2xxx5zy8vLXV3Xs4/dcccd7qRJk3IQKdHQ+973vuc2NjZmf+c5QMVuzpw57k033ZT93bZtt76+3l2wYEEOoyIaHq2trS4Ad8mSJa7rum53d7erKIr73HPPZbfZuHGjC8Bdvnx5rsIkGnSxWMydMGGCu3jxYvdjH/uY+5WvfMV1XZ4DucKWeRqQ/fv34/rrr8dTTz0Fn893yN+XL1+OM888Ex6PJ/vYvHnzsHnzZnR1dQ1nqETDIhKJoKKiIvs7zwEqZoZhYM2aNTj33HOzj4miiHPPPRfLly/PYWREwyMSiQBA9rq/Zs0amKbZ65yYPHkyRo8ezXOCispNN92E+fPn9/quAzwHcoXJPPWb67q45pprcOONN2L27NmH3aalpQW1tbW9Huv5vaWlZchjJBpO27Ztw49+9CPccMMN2cd4DlAxa29vh23bh/2O8/tNxc5xHNxyyy047bTTMG3aNACZ67rH40FZWVmvbXlOUDF59tln8dZbb2HBggWH/I3nQG4wmaesO++8E4IgHPXfpk2b8KMf/QixWAx33XVXrkMmGlR9PQcOtmfPHpx//vm45JJLcP311+cociIiGi433XQT1q1bh2effTbXoRANm927d+MrX/kKnn76aWialutw6B/kXAdA+eP222/HNddcc9RtjjvuOLz66qtYvnw5VFXt9bfZs2fj8ssvxy9/+UvU1dUdMntlz+91dXWDGjfRYOnrOdBj7969OPvss3HqqaceMrEdzwEqZlVVVZAk6bDfcX6/qZjdfPPN+NOf/oTXX38do0aNyj5eV1cHwzDQ3d3dq2WS5wQVizVr1qC1tRUnnnhi9jHbtvH666/j0Ucfxcsvv8xzIAeYzFNWdXU1qqurP3K7Rx55BN/+9rezv+/duxfz5s3DokWLMHfuXADAKaecgq9//eswTROKogAAFi9ejEmTJqG8vHxoXgDRMerrOQBkWuTPPvtszJo1Cz//+c8hir07OvEcoGLm8Xgwa9YsvPLKK7jooosAZLoev/LKK7j55ptzGxzREHBdF1/60pfwu9/9Dq+99hoaGxt7/X3WrFlQFAWvvPIKLr74YgDA5s2b8f777+OUU07JRchEg+qcc87Be++91+uxz33uc5g8eTLuuOMONDQ08BzIAcF1XTfXQVBh27lzJxobG/H222+jqakJQGZimEmTJuG8887DHXfcgXXr1uHaa6/Fww8/jM9//vO5DZjoGO3ZswdnnXUWxowZg1/+8peQJCn7t57aZ54DVOwWLVqEq6++Gk8++STmzJmDhQsX4te//jU2bdp0yFh6okL3xS9+Ec888wx+//vfY9KkSdnHw+EwvF4vAOALX/gCXnzxRfziF79AKBTCl770JQDAsmXLchIz0VA766yz0NTUhIULFwLgOZALbJmnIREOh/GXv/wFN910E2bNmoWqqircfffdTGKoKCxevBjbtm3Dtm3benWzBDKtNwDPASp+l156Kdra2nD33XejpaUFTU1NeOmll5jIU1F6/PHHAWSSl4P9/Oc/zw7PevjhhyGKIi6++GLouo558+bhscceG+ZIiXKH58DwY8s8ERERERERUYHhbPZEREREREREBYbJPBEREREREVGBYTJPREREREREVGCYzBMREREREREVGCbzRERERERERAWGyTwRERERERFRgWEyT0RERERERFRgmMwTERERERERFRgm80RERHRU//3f/43zzjtvyI/z0ksvoampCY7jDPmxiIiICh2TeSIiIjqidDqNb37zm7jnnnuG/Fjnn38+FEXB008/PeTHIiIiKnRM5omIiOiIfvOb3yAUCuG0004bluNdc801eOSRR4blWERERIWMyTwREVEJaGtrQ11dHb7zne9kH1u2bBk8Hg9eeeWVIz7v2WefxYUXXtjrsbPOOgu33HJLr8cuuugiXHPNNdnfx44di29/+9u46qqrEAgEMGbMGPzhD39AW1sbPv3pTyMQCGDGjBlYvXp1r/1ceOGFWL16NbZv3z7wF0tERFQCmMwTERGVgOrqavzsZz/Dvffei9WrVyMWi+HKK6/EzTffjHPOOeeIz1u6dClmz549oGM+/PDDOO200/D2229j/vz5uPLKK3HVVVfhiiuuwFtvvYVx48bhqquuguu62eeMHj0atbW1eOONNwZ0TCIiolLBZJ6IiKhEfPKTn8T111+Pyy+/HDfeeCP8fj8WLFhwxO27u7sRiURQX18/4OPdcMMNmDBhAu6++25Eo1GcdNJJuOSSSzBx4kTccccd2LhxI/bv39/refX19di1a9eAjklERFQqmMwTERGVkO9///uwLAvPPfccnn76aaiqesRtU6kUAEDTtAEda8aMGdmfa2trAQDTp08/5LHW1tZez/N6vUgmkwM6JhERUalgMk9ERFRCtm/fjr1798JxHOzcufOo21ZWVkIQBHR1dX3kfm3bPuQxRVGyPwuCcMTHPrwUXWdnJ6qrqz/ymERERKWMyTwREVGJMAwDV1xxBS699FJ861vfwr//+78f0ip+MI/Hg6lTp2LDhg2H/O3DXeN37NgxKDGm02ls374dM2fOHJT9ERERFSsm80RERCXi61//OiKRCB555BHccccdmDhxIq699tqjPmfevHlYunTpIY///ve/x29/+1ts374d999/PzZs2IBdu3Zhz549xxTjihUroKoqTjnllGPaDxERUbFjMk9ERFQCXnvtNSxcuBBPPfUUQqEQRFHEU089hTfeeAOPP/74EZ933XXX4cUXX0QkEun1+Pz58/G9730PU6dOxeuvv47HHnsMK1euxFNPPXVMcf7v//4vLr/8cvh8vmPaDxERUbET3IPXgyEiIiL6kEsuuQQnnngi7rrrLgCZdeabmpqwcOHCQT1Oe3s7Jk2ahNWrV6OxsXFQ901ERFRs2DJPRERER/Xggw8iEAgM+XF27tyJxx57jIk8ERFRH7BlnoiIiPplqFrmiYiIqO+YzBMREREREREVGHazJyIiIiIiIiowTOaJiIiIiIiICgyTeSIiIiIiIqICw2SeiIiIiIiIqMAwmSciIiIiIiIqMEzmiYiIiIiIiAoMk3kiIiIiIiKiAsNknoiIiIiIiKjA/H/w5c3K5WGuEwAAAABJRU5ErkJggg==", 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Est. time left: 00:00:00:00\n", + "Total run time: 0.03s\n" ] }, { "data": { - "image/png": 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", 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", 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Est. time left: 00:00:00:00\n", + "80.0%. Run time: 0.14s. Est. time left: 00:00:00:00\n", + "90.0%. Run time: 0.16s. Est. time left: 00:00:00:00\n", + "Total run time: 0.18s\n" ] }, { "data": { - "image/png": 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", + "image/png": 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", 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Est. time left: 00:00:00:02\n", + "60.0%. Run time: 2.83s. Est. time left: 00:00:00:01\n", + "70.0%. Run time: 3.31s. Est. time left: 00:00:00:01\n", + "80.0%. Run time: 3.77s. Est. time left: 00:00:00:00\n", + "90.0%. Run time: 4.25s. Est. time left: 00:00:00:00\n", + "Total run time: 4.68s\n" ] } ], @@ -228,14 +222,12 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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", 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", 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"text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -422,14 +412,12 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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Run time: 1.15s. Est. time left: 00:00:00:01\n", + "60.0%. Run time: 1.34s. Est. time left: 00:00:00:00\n", + "70.0%. Run time: 1.53s. Est. time left: 00:00:00:00\n", + "80.0%. Run time: 1.75s. Est. time left: 00:00:00:00\n", + "90.0%. Run time: 2.00s. Est. time left: 00:00:00:00\n", + "Total run time: 2.28s\n" ] } ], @@ -512,14 +500,12 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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", 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", 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", 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", 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", 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Est. time left: 00:00:00:04\n", + "60.0%. Run time: 4.99s. Est. time left: 00:00:00:03\n", + "70.0%. Run time: 5.83s. Est. time left: 00:00:00:02\n", + "80.0%. Run time: 6.68s. Est. time left: 00:00:00:01\n", + "90.0%. Run time: 7.53s. Est. time left: 00:00:00:00\n", + "Total run time: 8.35s\n" ] }, { "data": { - "image/png": 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", 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", 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", 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bV4qFrQZgh19UjEISJGTVLJF+MSmGpngTMceFj+3YyGgZxMQYWpOtxPlVAhrsjMJ4CnZMy8S27Db0Kr3eRGGEdVuZtomubBfSWhoxMUacn2EZ2Ni9EYZjYGrdVCQiibCVCjBsAxu7NsJ0TUxJTkEyStb+aNgGPur+CLqlY0rdFKSiqbCVCiDdz7ItfNT7EVRdxaT6SaiP1oetVIBlW9jUuwmKrpDtZyhoS7WhIdYQtlIBfreRwAloTjYjLpFVJ+Nn3HmWR2uyFckIWeeXciGnA5FSFpqpYXPfZvSpfUhFUsQFEpqpoT3djrSa9ma8JczPsAx057uDhUR7lV7k9FzYWgGGZaA7t92PFdGrkuVn2mbgJ/FSMNkiKZi2iZ6cV4QsCZLXfoT5deW6YDs2JFFCWt0xDxEJmLaJ7ny3t0yLIBXMk0QCvp/t2JB4qWCeJFJgGAbJSBIuXGzt2+oV7RPml4p4NwCbejd5xzNBfuXy8RhzNsFRDRVb+rZAt3TUReqIqs8BvEBnW2YbNEsbVARMArqloyvXBd3UAz+/uBYuQh+pYFgGunJdUA018NNMDV1Z8vyScjLw68x1woU3n1OY+IFEXs8H9SUk+imGUui3vaYt7DtsP5DN6TkkItv9rB1+Ydc8FfjJO/y6cl1wXIe4c05UjEK3dK/94KI+Wk+UX0yKBTenruuiMd5IlF+p0GBnnFMQ6ETrwtYZhGqq6Mh0wDCN0E+KQ+GfdAzLKCikjYgRL6DIdQEIL6DoH4j1bz9ZkIm4YPcPdIby89uPBD8/EAv8rPADiv6B2EA/MEBXrguu64bW5TZUoAh4628xYEIPKPxAJ28M7edPyUBawCPxEhiGQWemE3CB+hhZAY+/gLE/yGUiBDw02BnH+IGOYRtEBjqaqQWBTth3p0PhBxIDAx2fgRfsWgc8/oVaN/VR/RgwoflppjZkIOsHFGEFPP6FemAgFvjx3txKXbkuMAwTmp+iKwWBTn8/Bgy6891BF0gYfgMDMR9/KHdPvgcsw4bi52d0hvNjGHIDHpETAQnozHYCDIjL8Ei8BAYTJ+Chwc44RTM1bE1vJTajo1s6tmW2wbRMIgMdvwZmuEDCJwgo8l0Ag5oVFfoXmjH75Wrv153vHjaQCPx4GZpb+4BstECnvx+AUPz8GaWHulD7SLwEF27NAzLfTzGGDsT6+wEIAtpaHeuWYxV0XQ3nJ3IiXNcNLSAbDT/g6cp67UdaUbXIi3DhoiPTAYZh0BhvDFupZGiB8jjEtEx0ZDqgmRqRgY5lW+jMdEKzNOJGHADeibIn3+PNYDuGOWBkQQYLFj25HmiGVnU/f/qAYvw4lkN3rrumfn7Xxlj8eJYPgqNa+PlLe4zJj/f8uvJe3Uy1cVwnWFphpECiv5/AC0HwUQu/3nxvMMPuaH4SL0HgBfTkveU2auHXk+spqNEZzU/kRXTnu4kq6vcRORGSIKEr20VU0bePxEuISlF0ZDqQVtJh65QMDXbGGY7joDPXiayWDSrnScJxnOCkkpDIq9EpOJHLY5/sLiJGYLs2upVumLZZNT/XdYORYMX4yYIM13XRle+qul+f4o20KqYGK/Db3m1YC79iJjP0lwvpznWT6cd7NRTd2W7oll5Vv7SSRkbLFDUZn+/Xk+2piZ8/J9FY/SReAsdw6M31QjOrf0NQLH7A2JntrMkNQbH4AWNHtgOKXv2AuxrQYGcc4adje/I9xPU/+/irgpNYjAzAG5Ja5IncJybGggUPbdeuil9aTaNP6SvJLypGoZs6unPdVfPLqBn0Kr0lrYEUk2IwLKOq7ZfVsuhT+hAVoyVtX9P21pKzner45fQcevO9iIiRoqfmj4pRmE4N/JReRMVoyX7dOW+IejX9/GxmMUTESNB+1fIrh4gQge3YwczUpBEVo3AcBx3ZDiL9RmPcBDtLly7FgQceiEQigZaWFpxwwgl47733RnzP/fffD4ZhCh6yPPSCj+OBjJrBtuw2xKU4kWuYZLUsunJdiAjFn8hrQU7PoSffA5kv/kQJIKiZyGpZ9OX7Kj4HRV7Po1fpLbn9GMarOcnpuar59Sg9iAiRkldK9v16c5WfY0QxFHTnuyEJUsl+MSkWBCSO61TUTzXUwK/UeabiUtzbT6rk15PvgcAJZfkphoJepQp+5g6/UtcJ8/168j0V96sEcSkORffW5KtWQFsOCTmBvJ7Htsw2Iv1GYtwEO8uXL8f555+Pl19+Gc888wxM08TRRx+NfH7kPuJkMomtW7cGjw8//LBGxpVF0RV0ZDuCdCJpqKaKzmxnWSeiaqKZGnpyPeBZviw/lmERk2LoU/oq2r+uWzp6cj3gGK5sv7gUR6/Si4yaqbgfy7AV8etT+5BWK9f/7xecswxb1oKP/f0q2X7+yDW4KMvPD2gr7ecXdLuuG3TpleOXVtMV9/NXVq+EX0bLEFl/4o+6S6tp4iYdBDy/ukgd+tQ+dGW7iPMbiXEzGuupp54q+Pn+++9HS0sLVq9ejU9+8pPDvo9hGLS1tY35e3Rdh67v6HPOZCp3wJaKn9q0HRvxCHkFv7ZjoyfnpYZJG+0AeHU6fUofLMeqyGgWnuUhCt4sy5Iglb2asl9HZDpmRfw4loMkeLMYS4JU1sXB9+tT+irqJwsy+tQ+yIJcEb9epReGVZkpDgr8eBmyWJ6fX6dTMT+GQ0SMoE/pg8RLZa9j5Pvpll6ROkCO8db06lV6K+qnmRoSUgX2v+1+/vFByvpjPv4NVU++B7IoEzfIg2VZJOQEuvJdiErR0CflHCvjJrMzkHTai8obGkYeqpfL5TB9+nRMnToVn/3sZ/HWW2+N+PqlS5cilUoFj6lTp1bMuVR6873IalkkZfICCQBIK+mgoJZEMmoGOT1X0UUBZV6G7djoU/rKTofntBzyep5ov5yWq+hFQeIlOI4XRJVbv5PX88Ein5VC4iWvWFztLdsvp+cq7idyXnatTy2//XJ6Dhk1U9GLqsAJYMCgV+ktu7sjb2zfvmKsYnWAAieAYSrjVw0ETgDLsujJ98C0qjfgoFQEToDACsH0IuOBcRnsOI6Diy66CIceeij22muvYV83e/Zs3HvvvfjTn/6EBx98EI7j4JBDDsGmTZuGfc+ll16KdDodPD766KNq/AljJq/n0ZXrQkyq3IFeSVRDRY/S4w3PLrIgtBZopoa0mkZEiFTcLypFkdWyZa2xpJlakCGqtJ9ff1JOd4Ju6ehT+iDyYsXrsHy/rFp6d6BhGejNexmESvtFxagXSJXp15evTvtVws+0TfQpfRA4oSp+iqGUtf+ZtonefC94lq+8nxCFaqgV7U6tJDExBkVX0KdUvv6uEsSkWFBHRaLfQMZNN1Z/zj//fLz55pt46aWXRnzdggULsGDBguDnQw45BLvvvjvuuusuXH311UO+R5IkSFJ53RKVwnZsrx99++KKpOHPZ+K6ZPr53S+2Y1clVc0x27uLlL6SurOq7ccyrLdoo5ouqbuo0t1/Q/mV053ld1+ZdnUmrmQZ1usuKrE7K+i+sqszgzjDMGV1Z1W6+2ooP7+7SBbkkv0M26hKVtv3848P0rqz/PqiXqUXESlCXHeWP2BjvHRnkXcrPgoXXHAB/vrXv+K5557DTjvtVNR7BUHAvvvui7Vr11bJrrIQ332lpivePVRJqtF9NRCZl2E5VkndRdXovhpIOd1ZeT1f8e6rgfTvzirFr9LdQwPxZ+AtpTurGt1XA/G7s3qV4v3yRr7i3VcDKejOKsHP776qFqR3Z/EsH3RnkThcfjx1Z42bYMd1XVxwwQX44x//iH/84x+YOXNm0Z9h2zbeeOMNTJo0qQqGlUU3dfQoPYiKUSK7r/zuDYmvfPdLJTBtExk1U5PutagURU7LFTW7rWmbSCtpiLxYdT+/u6hYv2p1Xw0kJsWQ1/NFTVbm+1Wj+2ogfndRMX5+AFyN7qGB+N1FpPvltbHPrmw7NtJqGhzLVd9ve3cWibMXAzu6szJa+INlhsLvziK1O9CHvKvUMJx//vl48MEH8fDDDyORSKC9vR3t7e1Q1R2zTZ5xxhm49NJLg5+vuuoqPP300/jggw/w2muvYfHixfjwww/xla98JYw/oSj80RvljlSpFhklA9M2ifXLaTkYtlGT7jWO4cBzPDJqZsx3rzktB93Wa9J+LMNC4ASk1XRxflZt/frUvjHfXef1PHRLr8n2ZRkWIicGXY5jIaflanb8MgwDiZfQlx+7n6Ir0M3abF/fL62kx5ydUAwFqqEiIpQ3kmss+H5ZNVvV2cdLhWEYyKIcXBNIw+8O7FV6oZvVmz27XMZNsHPHHXcgnU7j8MMPx6RJk4LHo48+Grxm48aN2Lp1a/Bzb28vzjnnHOy+++449thjkclksGLFCuyxxx5h/AljRjVU9Cq9xPXR+qimirSWrsmJqBR0S0dGy9TUTxbkMd9dG5ZRc7+IEIFqqGP2y2rZmrefZmrI66Pf/ffP2tUq6ykLMnRLH1MxummbyKpZiLxYMz+Jl6Db+piyE6ZtIq2ma+onCzJ0Wx/T2lR+1slftbwW+H5j2f/CQOZl77gsoxi9msiCDMM20Kf0ha0yLIw7HsqoQySTySCVSiGdTiOZrH7tjOu62Jreij6lj8hFPgGgI9OBPqWPyLW5AG8F5rSSrvmcP6qhgmEYTK6bPGLqvTvXjV6lt+btp5ka4AKT60f268n3oFfprXmtmO83qW7SiDMg9+Z70Z3vDq39iPWzNMAB2uraRpwBOSw/3dLhOA7aUm0jTkzZp3gT1iUjoy+SWmk/27ExKTWJyIlRDduAaZuYUjeFyIy6bukwLAPTG6cT6TduMjsfFxRDQVpNk5vVMVRk1AxxIxd8VNPrey93IrNSGMvdv2ZqyOrZUNpvLHf/flZM5mt/shrL3X8YWTufsfiFkbXzkfntfiPsf37WLoyLkcRLMGxjxPbzs2KyWLusnY/ES973E1q7I3IiLMtCRiGzdkfiJVi2hd58b9gqQ0KDHcLw51QodW2fapNW03Bdt+S1c6pNTsuF5uf3/WfUzLC1E3k9D9u2w/MTvNqE4fxyWg62bYd2Z+v7DVfbkdfzMG0zND9ZkJFRM8PWduT1PCzHCtdPG9mvVrVsQxERI8hq2WFrT/J6Hrpdm1qsoYiKUWT1bFVXbi+HqBRFRs8QuXI7gGCpEBJXbqfBDkFoplb1oarloFveXW0YWZOxYFgGFEMJNYXqZ09Uc/DBbtomcnouXD9uu98QJyPTNpHX86H6+dmJ4dovr+VDrRXzsxNDXWwsx0JOy4U655SfnRhq+1qOFfr+J3IiTNsccmSg7djIatlQ20/gBFi2ReTFGvD8bMcuauRdLRE4AZZjEVn7RIMdgshpOdhuOHf9YyGv52HZFrF+iqHAtM1Q/RiGAc/xQYapP6qhhpqVADw/gROQ1bOD/DRTg2EZodcrCJyArJYdNO+OZmow7PD9RE5ERssM8lMN1fPjwvWTeAlZfZj2swjx07KDRgaqphpq1slnOD9S8LPHJM67AyCY6JI0PxrsEIJlW0gr6VBqJcaC7djIaBlIAnkzJQNk3BX6+COz+g/DdFwHWT0b+oUG8LqKVEMtyE44roOMlgk9kAC2+5nq4PbTskR070qCBN3UC9rPdV3k9Bx4jg99XiyRF6EZWkF2zHVd5LQcOJYL3U/iJejWEO2n5cAxZPgZlkFsdkfiJWiWNmT2kwRkXoZmjW1kZS2hwQ4hKIYC1VKJrGIHPD/DNIgNxjRTq9m8K6PBMd5Ip7yx42BXDRWaoRERLPp+/bsSNFODburE+DFgCk6Wuul1bZGwff1JIPv7aaYG1SDHj2XZgkn8/IsjCecXhmHAs4XZT93SifLjWG7I7CwJ+NnjjJoh1k/kRPSpZK3pRYMdAvDXgPGnLicN13WR0TJgGIZIP8Cbmp9nw7+r9hF5Mej2Azw/lmWJmW1aEiTk9FxQyOpfuEnxkwUZeSMfFLLm9BwYMFWfTXesDPTzA0eS/BRTCQptFV2B67rE+PnZxcDPUOA4DjF+siB72UVCC5UjQgSKoUAzyCxUjogRb9bxImZtrzZknNk+5uiWDsVQiJ2kz7C9lC4Jd11DYdomNFMjogvGJyhktbTAj4S7fh+/UFQ39aCglSQ/gRNg2iYMy4DlWET6WbYF3dJhORYUXSHKj2d52I4N3fTmjlEMhajjg2d5WI4FwzJgOzbyep6IrKIPx3JwXIfYUU8cy8F2bKgWmV1ZHMvBdV2iugKL7gBfv349XnzxRXz44YdQFAXNzc3Yd999sWDBAsgymRdD0tFN74RJQj3CUPgnTFILk3VLh2VbxM39w7FccOdFoh/P8lAMBQzDwHTIW/rD92NZlsilSXiOR17Pg2M5GLaBhEDWqs9++/mBI2lzdwmcgLyRB8/yMGyDPD9WgGIoSEVSxGSM++Nnj+uj9UT6SYKEjJZBQ6wBLBt+XmXMV9eHHnoIP/3pT7Fq1Sq0trZi8uTJiEQi6Onpwbp16yDLMk477TR897vfxfTp06vpPOHI6TliAwnA6+IgpXtjKFRDJeJgGojACVANFZZjkenHC96dKwMwIK+LMvADiOxCFTkxmESSRD+BE4LpIlzXJc5P5L32y+t5wCWnC9VH5MVgBCBJWTsfid/RFUjajQDg+eV0b409EqYrGVOws++++0IURZx55pl4/PHHMXXq1ILf67qOlStX4pFHHsEBBxyA22+/HSeffHJVhCcapmUSl2Luj2mbxBSGDoXlWNAMjYhRTgMRORFpPQ3VVImcO0lgBSiaAs3SiMs6Adv9dM+PxC5egRO8k7lJxsl8IIGfpRPZfjzLI2fl0Gf1EXl+4VgOlmPBtEyi/UgNdvyuNs3UiDg+xhRKX3/99XjllVfwta99bVCgAwCSJOHwww/HnXfeiXfffRc777xzxUUnKppFxtwXw+HXdJCaeTIsA4ZtEOnndw/ljTyxfoZjEJtZZBgGlu1N1EfqzYA/JJ7E9gM8v5xG5vYFtg9+UMmY8mAoeI4nqsh2IP6cXqQiciKy2uA5vcJgTJmdhQsXjvkDGxsb0djYWLLQxw1FV4hMgftopkZEF8d/Vv8HP136U7z75ruIx+M46jNH4YJvXwAdeujtt3rFaix/ajnee+M9fPTBR2hqa8Jv/u83ALyLjaIrcOGCQe0dNVXD08uexsvPvYz176+HpmiYPG0yjvn8MTjm88cALqDq4RYRPvLLR/Dy8y9j60dboeQVNLc146BPHoQvnvNFuKJX5Ogi/JMlAOQyOZx9/NlI96Txg5/8ALsfsrs330mIh8e3z/o23lj1xqDn9z90f1zy40uIuFibponH738cf//z39GxpQOxeAyz9pyFM759BhzZGf0DqkT75nacuejMYX9/9OeOxnk/PA+WHV5NpeM4+MPDf8DjDz2Ojz78CJFoBHP2nIOvfP0r2GPeHjtumAkMGP05s8KeTBUooUDZZ9u2bdi2bRscp3BHnTt3btlSHxdc10XeyIe+EwyH67pQTTX0u8L33noP533pPMzYdQYu+eEl2Na+DQ/c/QA+Wv8RLv3ppeDZcAu7n/vbc3jh/17ArrvviobmhoLfOa4DhvUyFGFs5/ZN7bhj6R2YN38eTjzjRERjUaxesRq/uOYXePf1d3Had04LMihh7Yfvv/0+dp69Mz616FOIxCL46IOP8OTjT+LVF17FFfdeARcuLNsCx4c/LPk3t/0Gulo42SHgdUdzQnh+Ta1NOOsbZxU819jSCMd14LouTNsMbVi3ZVr40dd+hLf/8zaOOekYzNxtJnKZHN59/V3kM3mIsui1n1h7v7r6Onz7um8Pen7VP1fhub89hwMOPQCmY8K0zdCCnVuvuxUP3fMQjv3csTj59JORzWTx+MOP45xTzsGvHvsVps2eFurxOxICJyCn5YgIxoreeqtXr8aSJUvwzjvvBKkphmGCAjjbJnOKbRIxbROWYxHZHwwgGBoa9k562023IZFK4O5H7kY84Y3YmLTTJFzzvWuw6qVV2P/Q/UP1O+sbZ+GiKy4CL/D40fk/woa1GwB4szq7rgvXdYddeLPa1DfV444/3IEZu84InjvuC8fh5stuxtPLnsaRpx6JeHPcW7wS4Wzny265bNBzu++zO6655BqsfnE19jxsz9Darz8b3t+Av/3ub/jSuV/CA7c9ANd1YTnePEphLy0QS8Rw5PFHFjznui62ZraCZdhQ2++PD/wRb6x6Az/5zU8we+/ZBX7tmXZv4dyQ2k+OyoPaDQCe+dMziMajOPjwg6G5WrCda41lWfj9g7/HkcceiatvuTp4/qjjjsL/HPY/eOpPT+Gc75wD0xl64VcScOEOuzBtLSk62Pnyl7+M3XbbDb/61a/Q2toaevfGeMa0TVi2hZhIXvEq4A2XthwLUbZ6xav//te/cfPVN2Ptu2vR3NaMJecuQde2Ltz907uxesNq5LI5vPzSyzjt7NOCQAcAPnPiZ/CTq3+CF595EfM/Ob9qfm++9ibuuvEubHh/A5pamvD5sz6Pnq4ePHTHQ3jqjacAeHfQQ2E5VnBHXa2T5Wh+qfoUUvWpQe875MhD8PSyp7Fp/Sbs2bJnaH7D0Tq5FQCQy+bAM3zVTpbF+N15w5045NOHYK/99wLgBbO2bYPn+KqtA1SMn23ZMAwDkahXDGraZuAXVvs5joNlDy3DIUcegtl7z4Zt2TBNE3JEhuVYwZQWhm0ghsqfB0vZ/7o7u/H6v17HkccfCVESYegGdEtHApWfWmC0859lWdA1HY1NheeYhkZvOLckS+BZHpqhIRUZfJyTAM/yUA0V9bH6cD2KfcMHH3yAxx9/HLvuums1fD5WmLbpdXMQGjD6J8hq+b3/7vs4//TzUd9Yj/+96H9h2zbuuuUuNDTt6Apa+95a2JaN3ffeveC9gihg1zm7Yv1766s2ZHX9f9fjB+f+AKn6FBaftxi2bePB2x9EXWPdmN5v2RZc1/WG2Jo6EnJlT5bl+PV29QIAYskYBEHw1qGq8ICOYvxc10WmLwPbtrHlwy2499Z7wXIsdttnN4iC136o8ICOYvxe+L8X8Paat3H3n+5Gx5YOAF4Xlu3a3lpPIftt3rAZJxx0AkzTRH1jPRadtAgnfvlEOK7jraVUhcnxxuK3cd1GdG/rxszdZuKnV/wUf//z32GaJmbMmoGzv3U2Wma3BO1X6eHxpR4fy59cDsdxcMRxRwDwLtaaqVXcbyznP1mWsde8vfCX3/8Fe++3N/Y9cF/kMjn88ue/RCKVwIlfOhE8x0OzKu9XKQRegGqqcBwn1Ck4ig52jjzySPznP/+hwU4F0EyNmOnRh0I39arOfXHnzXcCLnDP7+7BpCmTAABHHnMkTll4SvCarm1dAIDmluZB769vqsdHGz6qmp/fVfHjX/8YLZNaAACf+H+fwFdP/OqY3m/ZVrDOjmEbcFynou1Zqp9pmvjjg39Ey+QWzJgzAxzLwbTMUP16u3vxpSO+FPzc1NqEb1z9DbRObwXLsrBsC7ZrB+t61dJP13Tc85N78LnTP4e2KW1BsON3vXAs5/k5dkWP57H6TZo6CfsctA9mzJoBTdXw0tMv4bd3/xYbPtiAJT9cApb1urHC8Nu8cTMArysrkUrgwh9dCAB49J5HceUFV+J7d3wPu87ZNfCrZF1MqcfHc397Dg3NDZg3fx4Ab/uatllxv7Gc/wDgmluvwfcu+B4uu2hHd++UaVNw7+/vxU7TdvKm3zA1IoqAh0JghaBIWWLDK9koesvdc889WLJkCd58803stddeEITC4tX/+Z//qZjcRMZ13WB2U1LRLK1qxb+2bWPlCytx+NGHBwc6AMzcdSYO/uTB+Odz/wTgXWgAL5MzEE7gYOhG1fxWr1iNBZ9eEJwoAWDaztOw/yH7418v/mvUz9AtHRzDgWd46I5e0SLCcvxuv/Z2bFy3Ed+86ZsQBRE8y0O3w/VLpBK47u7rYBom1r6zFiueXYFsLuu1Xz+/ShUpF+P3u1/9DpZl4YvnfLHgMyzbCvxUW61oEXAxfpdcdUnBe486/ij89Iqf4snHn8SnTvwU9py3JxRLCcVPVbyRfmpexW2P3YbmNu+mZd78eTjr2LPwzCPPYM5Vc4JZ0CsVTJR6fGzasAnvv/0+Pnf654IsBM/yUE214n5jOf8BQDQWxS677YK5+83FgYcciO7Obtx/5/345v9+E/c8dg/q6utg2zaxRco8x8PSvC79MJcEKfo2buXKlfjnP/+JK6+8EieffDJOOOGE4PG5z32uGo4TEsd1iFr4biC2Y1d15t/e7l7omo6pMwfP2zRj5xnBvyXZOzhMo7DmwHEd6Loe/L7SpHvT0DUdU6ZNGfS7nWbsNOr7XdeF5VrgWC4oEB04cjEMv8fuewxPPv4kzrjgDOy5YE+wLAuO4WC74foJgoD9FuyH+Z+aj9O+ehrO/8H5uOe6e/DGyjc8P8eG61Ru+PlY/do3t+P39/8eZ154ZlAL42M7trfCOMPCcZyKziVS7v534pITAQDvrn4XLMMGhfK19pMk7/jcY989gkAHAFomtWC3ubth3VvrwDCMdz5E+MfHc397DgDw6eM+HTzndw3ZqFwR9VjPf5Zl4bzF5yGeiOO7V30Xn170aZx8+sm448E7sGnjJjxw1wM7/EIukh8JF+EN0vAp+kp24YUXYvHixdi6dSscxyl40JFYY8d2bNiuTdwU6T5+MBa2X1NLEwCgc1tnwfO2Y6O3s3fQUG9ScFwHruOCZVjvZOQi9Llinl72NO695V4c94XjcMo5pxRM0e+6bkUvNuUye+5spBpTeOWZV7wnGITi98BtD6CxpRFzD5yL9s3taN/cHtQ7ZXoz6GnvCYJEktqvqdU7bpSsN8eOCzcYJl9L/OL9gXUyrusiUZ8I/PwRvWHz3BPPYacZO2HWnrMG/a6SNwNj5bVXX8O699bhk0d9suD5aTOnYeYuM7Fm9RrvCQahBxMjwYAJZf/rT9E5ue7ublx88cVobW2ths/HBsd14LhORWsQKont2BWv4ehPfWM9JFnCR+sH19xs+GBD8O9ddtsFHM/hnTfewdGfOTp43tANrP/vehx29GFV8UvVpyDJUlBz0J9NGzaN+n6//fy7rkpfbIr1W/mPlbj1iltx6FGH4vwfnA/b3V4jwXungEpfbMptP9d1YRom1PyOCQ/DaL9tW7dhy8YtOPOYMwe97oGbHwAA3P303XAFt6IXw3Lbb8tHWwAAyfokgMpfbMbqN2PWDPA8j+6O7oLXOK6Dvq4+JOp2FO1XMjNRSvu9+/q72LJxC04///Qhf1/JYGKs57+ezh4AgGMP3naWZcG2PCcGTCjB2FhhGCb04edFX8lOPPFEPPfcc9Vw+Vjhd2uQuEAksP1O361eNxvHcVjwyQV4/unnsXXz1uD59WvX4+UXXg5+TiQTmH/ofDzxxyeQz+WD559Y9gQ0RcMnjy6846mk3/6H7I+V/1iJbVu3Bc9v/GAjVq9YPer7/eDGDxYrfbEpxu+NVW9g6XeWYu/998Z3rv8OWHZ7twYKR29U8mIzVj9N0aCpg0cKvfTMS1CyCnaes2PpmUpebMbqt+TCJfjRrT8qeJxxwRkAgIWnLsQ3ln4DUkTyurJC2L75XB6GUVi35rouHrn7EQDA3PneJK8Mw1R0eoGx+kVjURx42IF4+z9v46MPdlzYP1z3Ida+uRZ7HeQN42cZtqI9A6Ucv8894V3X/FFYBZ/HVHb6iLGe/6bv7C2q/X9/+b+C97/z5jv48IMPMXtPb94ilmFhWNWpX6wEfpF3mBSd2dltt91w6aWX4qWXXsLee+89qED561//esXkJjK2Y4c6xfxoVDol6rou/tvxX7y5+U1YjoUZTTNw9jfOxsrlK/GVL3wFJy8+GbZt49H7H8XOs3bG++++H7z3a9/+Gr584pdxzinn4MRTT/RmUP7lA9jn4H1w4GEHVszvg64P8F77ezAtEzs17IRTzj0Fq/65Ct9a8i185pTPwLZt/PnhP2P6LtOx/r/rg/d+8N4HePl57wS1ZeMWKFkFj979KHJ6DrPmzMJ+h+1X9sXGdV2s716Pd7e+6/nVj82vY0sHrvj6FWAYBp/4f5/Ai//3IgBvWoG0msZuu++GabtOK/ti47ouNnRvwDtb34FpmZhSP2VMfps3bsal51yKTy78JKbOnAqGZfD+W+/jH3/7BxrbGrHoi4sAIKjbKcfvo96P8NaWt2CYBibVT8IX/vcLo/rttd9egz4rlvTmg5k+ezoO/NSBYBgGrMPCssrbvpv6NuHNzW/CMA201bWNyW/tO2tx/Xeux+HHHI7J0ybD0A3889l/4u1/v43Djj8sCBZZtvztu7lvM97c/CZ0U0dLqmVMfgBw5jfOxJpX1uC7X/kuPvulzwIAlj20DLFEDP+zxBvQwjJs2cHElr4teH3z69ANHc2pZnz+fz8/Jj/AKxh+4akXMGfuHEyeOnnQZ/uzjJfDpt5NWPXhKqiGikl1k7DkgiWjnv9233t3zD9sPv76+F+Rz+Vx8GEHo2tbFx799aOQZAlf+rI3gpFlWaJrdsZlsHPPPfcgHo9j+fLlWL58ecHvGIaperBz22234aabbkJ7ezv22Wcf/PznP8dBBx007Osfe+wxXHbZZdiwYQNmzZqFG264Accee2xVHcdC2P2Xo1FJP9VQccfzd+BfH/7Lm48E3sG5S9MuuOL2K/CbW3+DO2+5Ey1tLTj34nPRta2rINjZfa/dcftDt+Pn1/8cN199M6LxKI496ViccM4JFfHTDA0PvvIg/r3x39AsL8vAMiymNUzDxT+5GH+4/Q944LYH0NTahMVfW4yerp6Ck+Xad9biN7/4TcFnPnzHwwCAw449DPsdtl9ZFxvd0vHQKw9h9YbVBX47NeyEi266CH+884/D+rVvbkc+62XEbrv2tkGffeLZJwbBTqkXG8My8NtXf4tX17/qzefCeOeCKXVT8I2bvoFldy4b1q+ptQmHHnUo/vPqf/D3P/8dtmWjZXILjvnCMTj8C4cjkfK6Ocq52Ji2iUdefQQvf/Bygd/k1GRceMOF+PPdfx5x+46EnxljmdIvNpZt4Xerfod/rvtnMB8OwzCYlJyEr93wNfzt7r8N69c6qRV77bcXVvxjBXq7esGwDKbNnIavfv+r2Of/7RP4lZOZsB0bv1/9e7z4/otQDW8dMAYMWpOt+Nr1X8Pffjm8HwBM32U6brzvRtx7y7347d2/Bcuy2OvAvfCZr3wmqMkrZ/+zXRt/fO2PeP6/z3t+8Pxaki346tKv4sl7nhx1+/775X+jt7t30Ig7H9+vlLlsHNfBI/96BE++8STy+o7sdFuqDZf85BIsu2vZiOe/m395Mx64+wE8/ZensWL5CgiCgH0P2hfnXXIeZuwyw/NjWZi2SexcOwzDhN6bUXSws3792E4C1eDRRx/FJZdcgjvvvBPz58/HrbfeioULF+K9995DS0vLoNevWLECp556KpYuXYrPfOYzePjhh3HCCSfgtddew157Db5jqyWu64KQtQ2HpJLBzkMvP4SX3n8J9fF6tMRbwDAMdEvHfzv+CwC4b9l9BUPw77rlrkGfse+B++Lex+8Nfs5qWWzLbhv0ulL403/+hJXrViIVTaEh1uCtBm4ZWN+1Hg4c/PihHxcs6fHA7Q8UvP/oE47G0SccXfBcXs+jK9uFuOzN+lxON9ZfX/8r/vn+Pwv9bAMbuzZiubMcNz1wE2Rxx4yA/f32OXCfIWeKzet5dGY7g4kOGZRes/PkG0/ihfdfQDKSLPD7qOcjLHeX44YHbkBU3DELd3+/VH0K37j8G0P6deW6gp/L6SZ66s2n8Px/n0dS3uFn2iY2927Gcnc5rv/N9YhJO2bvHbh9B7LPgfvgD6v/gG2ZHfufP6KoFJ555xn8491/IC7H0RDd4bclvQXL3eW49tfXIiknh/Rr26kNP/jJDwZ9pmIoBX5A6QXUz773LP7+zt8RFaOYXDc58GvPtON553lcc/81BbP3DtV+s/aYhaW/XBr8rBrqoOPXHzFW7MV6+bvL8fRbTyMiRjA5NTnIom7LbMNyezmuuu8q1Ed3zN47lN8Bhx4w4ozeYFDy8fH3t/+OP772R0TFKKbWT/XazzHRnm7H087TuPmhm9GS3HH9Gnj+k2UZ53z9HJzz9XNG0GNKbr9a4J//whykUbEQa+vWrbjxxhsr9XFDcvPNN+Occ87BWWedhT322AN33nknotEo7r333iFf/9Of/hSLFi3Ct7/9bey+++64+uqrsd9+++EXv/hFVT3Hgrv9v4lOV64LL619CYlIAgkpERyIEi+hLdWGD7o+wGsbXwvNL62m8fIHLyMqRRGX4oGfyItoSbZgU88mvLFp8IrSozFw+5a64nlGy2DFuhWIiJFCP87z29y3GWs2rSnpswc6lXKxzut5vLj2RciCXLB9RU5EW6oNW/q24N8f/bskv0qgGipefP9FyLyMhLzDT+AEtKZasTW9taT9b6gLXynBhGZqWP7f5RB5EUk5WeDXlmrDtsw2rN4weo3YWCn2gq1bOpa/txw8yyMVSRX4TUpNQme2E//aMPqcU4M8Bp77Srw+m7aJ5//7PFiGLfDjWR5tqTZ05brwyvpXSvvwAr3SRlTajo0n33oSDMOgPlq/o/1YAVPqpqAr650fJzokBGAlrY01FB9++CFeffVVfOc73ylbaigMw8Dq1atx6aWXBs+xLIujjjoKK1euHPI9K1euxCWXFE64tXDhQixbtmzY79F1Hbq+Y1XjTCZTnvgIkLADVJuNPRuR1bOYVDdp0O8kXoLt2NjQtQHzZxa3vlWl5g3Z1LsJOT2H5sTgGZpFToTjOtjYuxEHzDig+A8fsHlLCW639G1BTs2hIT54iL3ACXAdFxt7N+JgHFy8Xz9K3Re39m1FVssW3Dn78CwPx3XwUfdHwC7Ff/bA7VtKMLE1sxUZLYOUPHjdIJ7l4bouPuz+EIfNKn5UXyWO323ZbUiraSSkwUuJcAwHuMCHPR8W/bmDjg0GJWWSu7Jd6Mv3BRnK/rAMCzDAhq4NxX/wUI7wjpFibgy6c93oznUP68ewDNZ3htcb0ZXrQmemsyAz58MyLFiWDTLc5cAwDByEmzkhnaKDnd7e3oKfbdvGBx98gHfeeQe33357xcQG0tXVBdu2Bw15b21txbvvvjvke9rb24d8fXt7+7Dfs3TpUlx55ZXlC1MAeCdsf9I1bB/YdaB+IBLu9pN7BMBbwF/e+kvwnvfWvAcA+Mv9f0Et+HL0y4ADDHktjQH4AHj5gx0jJDa97Q1dffnxl4d4QyHtKNzX1qP4E++Z0TM9t6HOY3EAG4CXN5TmN5AN2FC8X+RMz22okos4gI+Alz+qTPttxMai/ZbIS7x/DOe3udClnPYrxe8M6YyR/baW7leJ9lssLR7eLwZgG8F+UQDdldu+a7Cm6Pd8gfuCd3xsH3SYZbL4l+RlwxzHqegSFJThYdwKTa5x7bXX4qWXXsKTTz5ZiY8bxJYtWzBlyhSsWLECCxYsCJ7/zne+g+XLl+OVVwanKkVRxK9//WuceuqpwXO33347rrzySnR0dAz5PUNldqZOnYp0Oo1kcnB0Xio9+R5s7dsa+kqww9Gn9KEj01H2SrqqoeKiRy9CRsugNVEYeGb1LBRDwRXHX4HZbbOL+ly/ZmeoO6Zi0EwNV/7lSvQqvWhJFNZ9KYaCvJ7Hxf/vYuzWultRn5vTc+jKdgU1MZqpQeCEgr75sWBYBq7661XozHaiNVnYfqqhIqtlceFRF2LPSXsW9bkDa4o0UwPP8YO+YzRM28Q1f7sG7X3taE0VvlczNaTVNC789IXYa0pxNXJ+zU5c8vx0y1unrS3VVtTn2I6Na5+4Fpt6Ng16r2Zq6FP68LUjvoZ5U+cV7de/5km3dIABJqcGj+QZ0c+1cf0T12ND9wZMShVmP3VTR4/Sg69+6qvYf/r+RX2uX7NTrp/jOrjhqRuwrnMdJiUnFWSzDMtAV74L//vJ/8VBM4YfJDIUfs1OsH1tHXCBSalJRWXMXNfFT57+Cd5pfyeo1wn8bANduS58+RNfxiE7H1KU30A0SwMcYErDlKLmHnNdF1f/9Wqs2bgGUxumDvJrT7fj/CPOx5G7H1mWn27pcB0X0xqnETmdiW7psG0bM5tnhrZqQMVa5dRTT8Xzzz9fqY8bRFNTEziOGxSkdHR0oK1t6BNgW1tbUa8HvOnNk8lkwaMalFrDUSsq1cUWESP47LzPwnZsdGQ7YNgGLNdCr9KL3lwv5s+YX3Qg4VOJOF0WZBy9x9FwXRed2U4YtgHbtZFW0+jJ92DulLnYtaX4RW+Z7f8FriWml0VexMI9F4JlWGzLbgsWFE2raXTnu7HXlL0wp21OSZ89cBcsZZ8UOAEL91roHZuZDhjWDr+uXBf2mLwHdp+0++gfNAT9t2+p25pjOSzaaxEETijwy6gZdOW6MGfSHOw5ubhAERj6+GBLOJ1yDIdFey6CyInoSHdAt3Q4roOslkVnrhNz2uZg7yl7F/25lYJlWCzacxFkXkZHpgO6ucNvW3YbdmvZDfvstE/5X+SipLodhmGwcK+FiIpRtGfaC/0y27Bz887Yb6f9yvcDglFoxfp9dt5nEZfj2Ny3GZqpeecXLY2tfVuxW+tuOHiX8rqgxwOu6w46J9aaigU7//nPf7DvvvtW6uMGIYoi9t9/fzz77LPBc47j4Nlnny3I9PRnwYIFBa8HgGeeeWbY19cShmGInmenkjvlMXsdgzMPORN1kTp0ZjuxtW8rGDA4du9jce6nzi0psGIYpmIB2eGzD8cXD/wiUtEUenI96Mh4AfIRs4/AkkOXlDyLdP8Ax3XdkmfL/sSun8AXD/wi6qJ16M31oj3THnif9YmzSvrcgTMmOyh9tuwFMxfg1INORWO8Eb15z8+Fi0/O+iS+8omvlHQnFyyzsR0Xbsl3hAdOPxCnLTgNzYlmzy/dDsd18IlZn8BXDvtKSYvxMig8fsuZbXz/Gfvj9AWnoznZjD6lD+3pdliOhUN2OQRfOewrJS3uOKj9XBc8U1p3yb7T9sWZh5yJtlQb+tQdfgfPPBj/+6n/LRipOFaGCxZLOab3nrI3zjzkTExKTQr8TMfEgTMPxHmfOq9gpGLJuIPbdKzsM3UfXPDpCzC1cSp6lB5s6d0C0zKxYJcF+NbR30JMjI3+IaPpuS4YtnLnxErjwg2mfAiLoruxBhb8Al625E9/+hOOO+44TJmyY+G1m2++uXzDfjz66KNYsmQJ7rrrLhx00EG49dZb8bvf/Q7vvvsuWltbccYZZ2DKlClYutQb4rhixQp86lOfwvXXX4/jjjsOjzzyCK677rqihp5nMhmkUqmKd2NltSw+7P4QDTEy13bK63ls7t2MZKRyf7NqqPhvx39huzamN05HY6yx5M9SDAVb+raU3c3WH83QsK5rHWzHxk51Ow1ZFDzmzzI1dGQ6gjR9Ts+hLlpXlq9mbvezbUypm4LGeOntN9Avb+SRkBNDFhqPFd3Ssa5zHSzbwuTUZDQlmsr2i4kxMAzj+UmJsrp9dUvHB50fwLRNtKXaBnVbFvtZ7en2wE8xFMSkWFnHs2EZWNe5DoZtYFJyUtFdngP9OjIdiAgRsAwLxVAQFaJoTJS+z5i2iXWd66BbOloTrUV3KfbHsAy0Z9p3+JkKInykrH3GtE180PkBNEtDS6JlULdgOSiGAlmQi+7m7Y9lW/hvx3+hmArakm3YqX70BV3HSl7PQxZkTKkfvPApCeT1PCRewrTGaaE5FB3q//vfQw8jPfDAA7Ft2zZs2+bNnVCNCO6UU05BZ2cnfvSjH6G9vR3z5s3DU089FRQhb9y4saC/8pBDDsHDDz+MH/7wh/j+97+PWbNmYdmyZaHPsQN46WtSo3DAu4txUdl5GyJiBPtMrUDKGwhWm66knyzKJXVpDIV/F+jf8VdinTFZkIuuzRnVb/skX47jgGfLK5SUeAl7TNqjYn79t6/jOuC48vr6JV4quUttIAyYYLv6q8aXW4sg8mLF/FiG3TF3EuNlnvx10EpF4ITSu0yH8Ot/XDhO+dtX4ISia//GiuOWf3zwHI89Jlfm+BiI67olZShrhe3YZbdfuRT97WGvi3XBBRfgggsuGPJ3Q9UMnXzyyTj55JOrbFU8LOsd7LZT/kmyGrAsC47hiF2s1B+2SaofwzAFFxsGDFGFg8HFBg5YeIFt2Cvc96fgYri9t52k7cyxXBCM9X+OFFiGBcduP37BVXVR31JgGGbHKE12ezdbyBfDkXBcskdN2W74wcRIOK5TUndsJSFn7/+YwTFccDIikf7BBImwLAsWBPv1u9gEzxF0uBVcbLAjU0EKLLsjMwaAuJlh/Tlc+m9f0vz8jA5AXrDNsV5m269rIy3YHgqSgu2hKDczVk2quaj0WBnT3rVo0SK8/PLocxJks1nccMMNuO22wWvwUAphWRYcylvcsJoE8+MQGkz43YCk+vXvxvIv1CRdDPtfbAI/girm+2d2gO3BGWnBYv9g2wU4kHOxYRgGPMMXZJ5Iaj8A4Bme2GB7IH4BMMmEHUyMBAMmdL8x5b1OPvlknHTSSUilUjj++ONxwAEHYPLkyZBlGb29vXj77bfx0ksv4YknnsBxxx2Hm266qdre4x6O5cBx4a8EOxwsy0LgBG9+DgJhGIZ4P57lvaGmrNdVGfbBPhCBE6AaKmzW9oJvwu4MBU6AaZtBVy9JmQnAq7HJabmgXoc0P4ETgqHOLMsS58fzPFRT9brY2NJGOtUCvwuQ1MyOP6ybpGC7P35XftjnvzEFO2effTYWL16Mxx57DI8++ijuvvtupNNpAN5JfY899sDChQvxr3/9C7vvXpkCu48DUTFasNghaUSECHJ6LmyNYZF4CYqhhK0xLLIgI2/kYTvexYa0PnWJl5DTc0EwQZqfyIvI6llYrgWO4YirmRB5bzkRyyHTT+AFuK4Ly7HAMzxxfiInwsUOP4Ens8DWcizwLE9sAbDlWOA58ravj2mbEDgBIhduzc6YW0eSJCxevBiLF3tTc6fTaaiqisbGRggCmTsB6Ui8VJGJ8aoFqScfH/9kTiocy4GBtwJz/0U8ScEPbmzHDoZQkwTP8mDAwLZtRIUocd0cPMt7K2zbVjCEmiR4lgcYb0kfiZeIy0z4d/qWbRHp52PbNgReCD0zMRyWY0HgBGLP136wGHYwVvLRmUql0NbWRgOdMhA4IRj+SyI8511sSK2LETgBLMsSW/fEszxYhoVpmaGPRBgKjuXAMRwM2yDyRMlzXvvplg5RILT9WA6mZUISip9Yr9rwLA+O5WBYBrF+PMtDt3Qi/Xwsx4LMV2BiwiphWiYiQiRsjWExbRNRMRr6zRRZtyIfM0Re9OoSHDLrdgTWu1uw7KFW2AsfnuXBMzy5wc72i7Xt2iXPXltNeM67GNq2DYElMNhheXAcR8QcHUPhBxOk+vldk6ZjEtkF4+9/fjcMqTiuQ2T7+ZAwrHskHNeBLIQfLNJgJ0R4zusHJjaY4HiInAjLIdOPYzkvGCPUzx9+zoAhrvgX2OEHhsxhq/6IIhKKG4fCL0J3QeYcMQzDBBMJkth+wI6uaFK7sPziZFKDMX8kJYk3K8CONe1ICBZpsBMycSkOwzLC1hiWiBAhdsQY4M3KTGqwA+wY4k3ixRDYMcSbWL/tk2+ScLIcCn+KAVIvhozrTSlAavv5Q/hJ7EYFvJXJ/Qw3iRi2AZETifcLuzgZoMFO6ETEyKBFGUnCX0SP1LodkReJritiGAYxKUasH+CNCiTWzwXR7ccwDOJSnNjjFwyQkBPE1gXCBRIRcv1My0REihCbeTIsA1ExSmywrZs6omKUiGCs6GBnyZIleOGFF6rh8rFEFmRInATN0sJWGRKJlyDxErHZJ4mXIHACkX5+X39MiBGZHfP7+hNSglg/gReQEBNEbl+/+4XU7Ky/0nkykoRhk+nHsZznR2D7Ad4+GBHJLf61HRtRKRq2xrD4I1FJoOhgJ51O46ijjsKsWbNw3XXXYfPmzdXw+tjAsRxicozYg51jOcREcv1YhkVMIjOYMCwDEi+hLlZHpp9tQOIkpKIpIrdv4BdLEXmxNmxv+9bH6okcZGA6prf/Rcjc/0zHhMiJqIvUEdkVTcr8MMNh2iYEXoDEkzmSzW8/EoqTgRKCnWXLlmHz5s0477zz8Oijj2LGjBk45phj8Pvf/x6mSd4BNR6ISTFiRxQBCO5sSE3Vy4IM13WJ8zNtEzEphogYIdPPMhGTY8GwUNK6ikzLRFSKkutnm4iIEa8rmsCuVNPa4eePGiMJ0zIhCzKiUpRIPz+YJbXeSbd0yLxM7Egs3dQRESLE+JVUs9Pc3IxLLrkE//nPf/DKK69g1113xemnn47Jkyfj4osvxvvvv19pzwmNxEsQeZHYpQ8kQQLP8UTeHQJe3Y7IiUT5+cGNLMjE+jmuA0mQdkyBQJif67qQRTkocCQp++S6LmzHhizKxHalWo7ltR+B2xfw/KJi1Nu+PFnbF/AmO4xJsbA1hsWyLcRlMrqIhsKwDSTkROjz6/iUVaC8detWPPPMM3jmmWfAcRyOPfZYvPHGG9hjjz1wyy23VMpxwuPXTaiGGrbKkAicgJgUg2aSWVfEszyiUpSoYFG3dIi86AWK2/1Iaj/d0iFxEmReBsd6dSe6SVD72TpETiz0I2j7+l1sMi+DZVji/HRrR/uR6OeP0pEECQzDICEliOqqNGwDAkd2FxHP8cROduh3YZFU71R0sGOaJh5//HF85jOfwfTp0/HYY4/hoosuwpYtW/DrX/8af//73/G73/0OV111VTV8JywJOQEAxI5K8P1ISzX7+EV6pPjplo6EnAhGcUSlKFGzPeuWjkQkEcy/EhEjZPmZhX5+Vwcpc1Lppo64HA9GwUQlb0QMSX4xKbbDb/uIHVKyO76f30UkCzJR2THd1BETY8R0wQxENVQkpASxM08rhoK4FCemXgcoYm0sn0mTJsFxHJx66ql49dVXMW/evEGvOeKII1BXV1cBvY8PUdGrTVBNlcjUqczLiIgRaKZG/UbBv+uKijtGSci8jIhAhp8/Y23/uy6Jl8jyY/mCE6XIid7xYaihD7P1F3Ydqv0UQ0GcC7drwfeLiTu2o8iLiIkxZLVs6DUotusF1AP9omIUWS0beoBhuzZcuKEfB8Ph14aR2oXlOA4cx0EqkgpbpYCiMzu33HILtmzZgttuu23IQAcA6urqsH79+nLdPlawLIu6aB1Rqeb+sCyLVCQFy7GIK7QFdsx3Yjt26H6aqSEuxgtO2gzDIC6T4xcVogUpet+PhO3rz80xyI+g7RsRIoO6OPz5bMIuVNas7X4D7vr9i3fYfrqpIyIO9otLcbhwQ88u+oW1pGZNNFPzCs8JXQ9LNdVgYAFJFB3snH766ZBlclJTE4mYGIPES0TVdvQnInqV9ST1rfcnIka8QtYQ/fwLyVBzX/jFymEGtI7r3XUNdVfoX8DD9PMLf2Py4FXYSWg/3y8uD17FXhZkyKIcau2T67pB4eqQfkL4fqZtIiENLlyVBC87Fvb2NW0TSTlJ3Cr2PoZlIBlJgmXJ9NMtHXWROuL8yLL5mCPwAlKRFBRDCVtlSAROQEJKEBuM8SyPuBwP1U8zteCiMhCe5UMvFNVMDbI4tB/HckjIidD9JEEa1i8VSUE39dCyO37h+VCFlyzDBhM0hunnd6kNhGVYJGQC/Dhp+PaTE7Ds8LKLQeE+QbUm/dEsDRIvISqQlTXx0UzPj8QuQBrsEEYqkoLIi8QGFIlIAgInENvdFpfjELlw7v4d14FlW95d1zB3hXE57s2YHcL2dVwHpm0iFUkN6xeTwssu+n51kbphp+f3uz/C2L6u63p3rdHh/aJSNLTsU4HfMAt/+u0Xxvb1/VLR1LB+UTEKWZShmrUfmer7JSKJ0OvChsJ1XWiGhlQ0RcTyC0OhGArqo/Wh110NBQ12CEMSJNRH6onN7vgzspIajAmcgGQkCc3Uan53qBpecflIfdUCJyARSYSSnfCL30fzS0W8GZXD8IuIkRGnvxc4IahtC8MvKkZH9ONZHnXROmLbj2d5pCIpmLZZ89qdsdz1cyyHpJwMxc/PivkjT0lDszTIvIyERKafaqiQeZm4wmQfGuwQSCqagsyHc3czFhKRBEReJNbPz07U8u7admzYrj1iVscnLsdrnp2wXRuO44zJz89O1DKgtV0btm0jFR0+6+QTFaOIiJGa7n/9s3ajLQoZlp9pm0jJqVH9/Fm9azmvl+M6MGwD9dH6YbM6PjEphpgUq6nfWLJiYeK6LnRTR12sjsisjuu6UE0VjfFGIv0AGuwQiciLqI/VQzXU0EeeDIXACaiP1ody9zoW/OxELe/+FUNBQkqMaYREGHf/qrE9KzGGvn7fr5Z3135WbCztF8bd/1iydj7+4paWbdXOz8/ajWFRSJbxRlbajl2zkU9jyYr5sAyLpJyE4zo19RstKxYm/ggnUrNOiqEgIkSI9QNosEMsqUgqmLeDROKSl50gObtTq7tr0zbBMAyScnLMU6P7d/+12L7+cPJUJFW0Xy3urv3h5GPJOvnU8u7fdmw47tiyYj5RMYqYFKvJ9rWdsWftfCJixGu/GhwfxWTtfPx5x2rSfq4d1LKNlhULA9u1YViGV8tGYNbJcRzolo6meBORtU4+4yLY2bBhA84++2zMnDkTkUgEu+yyCy6//HIYxshDjA8//HAwDFPw+OpXv1oj6/LgOR5N8SYYlkHMrKz94TkejbFGWI5F5IrF/sgd27Gr2n6u60IxFCTlJGRx7CM4fD+/e6Safnk9j1QkVdQIE47lUBetC7pHqklOzyEpJ4uaN8TPTrhwq+6XN/Il+wGo+qzAOT2HhJwoaoQOy7BIRWvjl9fyRfsxDOMFRyxbE7+knCRuXhifvJZHMpJEXCJzEsGMlkFKThGd1QHGSbDz7rvvwnEc3HXXXXjrrbdwyy234M4778T3v//9Ud97zjnnYOvWrcHjxhtvrIFxZUhGkmiINSCjZcJWGZK4FEcqkkJez4etMiQxMYZkJIm8ka9ad5FiKoiIkZKK8qJi1Gu/KvqppgqJl4rK6gz0Uwylen7Gdr9oaX51kbqq+4msWJJfRIygLlJX1e5ozdQgcaVt34gQCQYbVKu7TTM1iJyIumgdsX4CJxSVdaolmqWB4zg0xBqIm7cG8M4vPMejKdFEpF9/yM059WPRokVYtGhR8PPOO++M9957D3fccQd+/OMfj/jeaDSKtra2aitWBYZh0BhvhKIrUAyFuDsPhmFQH/Vqi0j1S0VSUA01qBmoJJZjwXEc1CXqSkrfMgyDZCQJ1ayen+3YaEqVnl5ORVPQLA2KoVR87gzbsWE5FlqSLSUvYZCIJKCaatX8TNtEa6q1ZD9/+1bLz7AMtCZbSx7qm4wkg+1b6cyB7drQLb0sv4TszeuV1/MVzxz09yNxwU/btaEZGtpSbUTO++M4DlRDxaTUJKIW/BwOskOxEUin02hoaBj1dQ899BCampqw11574dJLL4WijNwHrOs6MplMwSNMRF5EU6IJuqkT2Z0l8iIa4+R2ZwmcgPpYfcW7s/p3D5UzwZdf7E2qH8/yqI/WV6U7y+++6r9GUrH4xdTV6M7KG177lePHsRzqo/Vw4Va8Oyan55CMJMsKovzuSqDy3Vl+91A5QRTHclXrzvL9SJwAD9jRfZWUk2GrDElWyyIlp1AfrQ9bZUyMy2Bn7dq1+PnPf45zzz13xNd96UtfwoMPPojnnnsOl156KR544AEsXrx4xPcsXboUqVQqeEydOrWS6iXRvzuLxNFPfndWTssR6VeN7qz+3VfFpucHUo3uLMVUSu6+Gs6vkt1FiqGU3H01lJ/fnVWp7o5yuq8G0r87q5J+pXZfDfKrQndROd1Xw/mpZuXaj/juK1MDz/FEd19xHDcuuq98GDfEq9P3vvc93HDDDSO+5p133sGcOXOCnzdv3oxPfepTOPzww3HPPfcU9X3/+Mc/cOSRR2Lt2rXYZZddhnyNruvQ9R3zn2QyGUydOhXpdBrJZHgRtmEZ2Ny3GZqpETlpk2mbaE+3QzM1IgvVTNtEZ7azIn6apcF2bLQkWirW9WQ5FjqznVANtTJ+to2WJJl+uuVlKZuTzWVlTQb6dWW7kNe9u+Fy/UzbREuypWJ+tmOjM9tZET/DNqCbOlqSLRXrevL9/GxbOQFK4JdoqdjK3LZjoyvXhayWLdvPtE1oplZRv0pi2iZUQ0VrqpXYc31Oy2Fy3WTUx8ZHVgcIOdjp7OxEd3f3iK/ZeeedIYpef++WLVtw+OGH4+CDD8b9999fdESZz+cRj8fx1FNPYeHChWN6TyaTQSqVCj3YAQBFV7CpbxNYhiWuPgbwov2tfVsBgEg/zdTQmemEC7fkPmbLsaDoClqSLRUP6nRLx7b0NjhwSm4/36850Vz2RXVIv8w2OG55fnk9j+Z4czAaqFIYloGOTIe3kGiJXRO2YyOn59AUbwq6d0jzy+t5NMYbK+5n2ia2ZbfBtMzS/VwbOa067ef7GZZRcpDn+zXGGiuSdao0tmsjq2bRHG9GQ7yBOD/HcdCn9qEl0YLmRDNxfiMRaoFyc3Mzmpubx/TazZs344gjjsD++++P++67r6TU2Zo1awAAkyZNKvq9JBCVomhNtGJz32ZwLEdcUV1EiKA50YytfVthWAZx66PIgoyGeENwwizWz3a9C01DrKEqw0AlXirLz3Ed5PU86qP1VcmuSbyExngjOjIdwdT6pfpVOhADtte3xZvQkS3dL6fnUBepq8odte+3LbstWDC2VL9qtJ/ACWiINWBbpjQ/13WR06rv15npLMsvFUlVpHuy0riui6yaRSqSQn2snki/tJZGfbQejfFG4vxGY1x0tm3evBmHH344pk2bhh//+Mfo7OxEe3s72tvbC14zZ84cvPrqqwCAdevW4eqrr8bq1auxYcMG/PnPf8YZZ5yBT37yk5g7d25Yf0rZpKIptCRakNfzNZtdtBgScgJNiSZopkZkwXJMinkjyEy1qPbzC36TcrKqJ8qYFENjrNFrvyIKll3XRVbLIiEnUBer3h1rVIyiMdZYdMG8f6GJS/Gq+kXECBpjjTAso+iCZd+vPl69C01EjKAh1gDTNov2y+t5zy9WX7U6k4hQul9Oz3nHV7X94p5fsQXLeT0fHP8k1ulktSxiUgxNcTLrYDJaBjExhuZEM5GTG47GuBh6/swzz2Dt2rVYu3Ytdtppp4Lf+b1wpmnivffeC0ZbiaKIv//977j11luRz+cxdepUnHTSSfjhD39Yc/9K45+MuvPdqIvUEXdg1EW8pQb6lD7EpThxB0YqkoLlWOjL9yEuj80vp+eCC0G1Z1lNyImg/WJSbOx+Itl+kuBlhqrtF5fisGwL3fnuMe9/OT0HkRdr0n6+X0++B6zEjskvr+eDzEa1j6eEnAj8GJEZ07QFeT0Pga2NX1yKw4ya6FF6wDLs2PyMPHjWK/glcZbfnJ6DwAloijcRubZUTsuBZ/myphEIm1BrdsYDJNXs9MeyLXRkOtCb70VdlLyAx3ZsbMtsQ0bLICEniLuTsh0b3bluZLTMqBfErJaFwAloSbbUrOvQdmz05HuQVtKjBmQ53TsR1dLPcR1057rH7sfwaE4212y+EMd1gvYbLSDL63lwDFdzv958L3qV3lH3v8Av0VzULN2V8BtLQJs38uDgjcyp1XwrruuiV+lFb753VD/FUMCAQXOimcj5YPJ6HmCAtmQbkcPg83oeLlxMTk0msqB7rJB1BaKMGZ7zouxUJIU+tQ+OU5sFB8cKx3on56ScREbN1GxBxLHCsRwa441IyAnk9NywXVr+HVdzormmNVIc682amowkR/XjGb7mfizD7vDThvfL6/nAr5YTo7EMG9QGjeYXBBK19ovVBzOQD+tn5MEyLJoSTTULdPr71UXrRvRTDAUs2JoGOoA3IWddtA510boRjw9/ba1a+40VxVAABmhNthIb6Diug0mpSeM60AFosDOu4Tkek+omISWn0KeQF/DwnHeRS0VSyGpZ4mqMRgp4/BoYnq39hXqgX1Ie+oKd1bKhBBKD/IYJKHJ6ruYZiYF+DbEGpKJDBxR+oFPrQMKnf8A4rB+40DISQUAWTSGn5wbVaOWNPBgwoQUSvl99tB55PT+sX3OimcjRoX7GpDXZSuS6V/0DHRKnEykW8jovKUXhBzwsy6JX6UVSThLVJ+0HPMD2AjcpBp4lyI/1FlxlwCCjZhCX42AZNqgxaYo3hTrqzQ8oGMbzi0kxsAyLrJ6FyImhBTrD+UXFKDiWK8iIhe3XEPOG8PYpfYiJsR1+rBBaINbfrzHeCJZh0af0ISJGwLO8V2PC8KFnJPyAjAFT4KcYShAohu3nz/Xi+wmcgLy+IyNGYqCT03NgGZbYjE5Wy4JhGEyumzwhAh2ABjsTAr9Li2VYdOe7EZNiRA1L5zmvnoRlWaSVNGRBJqrILbjgsCx68j2wbAv1sXo0xBqIaEf/gu1vX8u2UBetQ2O8kRg//4Ld368h1kDEmj5BwAMGPfkemLaJVDSFxlgjEX7+BZthGHTnuon187evYRlIRpJoioWTERvJryvfBdMyvVGhcfK6rhzXQVbNQhIkb1JSiaxAzHVdpNU0JE5Ca6p13Hdd9YcGOxMEP+AROAHbsttgOzZRdzQcy6E53gyBFdCV64LlWMT5JeVkMOolJpIVMHIsF3S3kejHMiwScgKKocBiLcTEGBEXah+WYZGMJKEYCniWJ9IvISeg6Ao4jiPWL6/nwTCM50dAoOMT+Ble1yRp7Qd4gw786SGa4k2QBHKOX8Ab9JJRM0hEEmhNthLXfuVCR2ONAqmjsUYiraSxLbsNlmOVPbV6NchqWXRmO2E7NuJSnAg/zdSgWzqa483gOR7d+e7gDpEUP8My0BhrhMAL5PlZGnRDR2O8ESIvoiffA8M2kJDI8muINUASJPL9lB7opk7MSEbd0qEaqpdtEmV057uJ9GuINkAWZfQqvcHSMCT4GbYBVVeDjCxJpQaA1355PY/GWCOaE83E+VWCifcXUZCKpiBwAjqyHUTW8STkBHiOR1e2C2nVG7ocVh2PP6svy7JBIR7DMBB4gQg/13WR03NgGAatqdYgeO3vF5NiELhw5ubwJ1sEA7TVtQV+Ii+S5QcEaw3198toXp1RqH5GHnAL/SRBCtaCIsWvJdmC+mj9jvbLdQV1ZGH6+QvA9veTBRmduU5i/GzHRnOimbhpQvzjw3IstCXbiF14tBLQzM4ojMfMjo9hGejOdaMn3wORF4krhDNtEz35HvQpfRA4oebdWoZtQNEVxOU4GqONiEiF/fu+X1pNg2f50Pz8WZUH9u+btunNhaL2gWM4RMVoTbMUo/lZthXMJcOxtfczbTOYNXc0P5ZlERNjofhFJW9W6oHHZ9h+lmMhp+VG9OtT+tCr9AZdW2H4RcQIGuONg0Y02Y6NPqUPPfkeAKh5Ftn3kwUZTYkm4kZcWbaFjJYJlvmpxhIfJEGDnVEYz8EO4EXuGTWDrmwXVEslLsvjZy66c93QLb0mo7X8bA4DJhiaPNykZIFfvhuaodUky9M/G1GsXy3uYvv71Ue9ocnD7VP+a7vyXTX3c+GiIdowJr+efA8UQ6mdn5GH67qoj3pz2Yx0TOb1PLpz3VBNtSZZHt/PcRzUR+tRH6sf1c9vv1r5+dkSv/1GmnVYMRR057pr7mc5FhqiDaP6hUFOywV+DfEGogaMVAsa7IzCeA92fAZmeWp9lz0ahmWgV+kNsjwRIVIVP79vf7hszmh+aTVd1SyK7zdcNmI4apXlGS2bM5JfX76v6lme/n4NsYYxZzP7+1UzizJaNmc4/CxPn9pX1SxKf7+GWMOYv2dglicqRqtSK+P7+dmcYvzSajrI8vhTOFTLz8/m1DrbNRqmbSKrZYNsDik1f7WABjujMFGCHaBflifXBdVUEREjiAjkDM3sn6XQTR0iL1bMzz8JCbyA+kj9iNmS0fx68j3QTI1Yv958L1RThciLkHm5Iiczy7GQ1/LgeR51ct2I2ZKR/IIsgKlA4iTIQmX9OI4L2q9Uv16lF4qhQOTEqvjVRepGzeYMR/8sSqX9FF0By7JIyalRszlj8avkTYvt2MHcOalIquRsiWIo6Ml5fjzHE+dXLSzbCub2qYvUfWyyOf2hwc4oTKRgx8e/y+nN90KzNETFKFHDDC3bQlbLok/tg27qiIiRkodZDzyJJyPJsod8+ieOPqUPuqVDFuSS/QaeJBORRNnbwh/i6vtJvFTyZ9qODUVXwDAMknISyWiyIn5+UFYJP7/9EnICqWiqcn5KLzRDgyzIpfu5NvJafkf7RZJlz/3S36/cm4Jq+eX1fDCirFw/RVfgui6SkSRSkVTZfo7j7Ni+Zd609PdLyAnURerGnC2uBf62cFwHqUgK9dF64ub2qRU02BmFiRjs+BiWgbSSRq/aC8MyiAt6TNtEVs2iV+mF5VhFBRV+kMMwjHcRrMBJcji/PrUPpm0W7acaakVP4iP5GZYR+I0p7d/Pr1oncT+l3qcU72c7NhSjuhcZv4Azraahm3rRfqqhwnZtJOUk6iJ1kMXKZGEq6ee4DuJy3Gs/sbJdx/5NQa/inV+KyTT294tJMdRH66vm598UFO1nqrBtG3E5XhW/cvCPD8v2ph+pj9UjJpHVpVZraLAzChM52PHRTR1pNe2dNLffaUeECDFDEHVLR1bNIqNlYNomeJZHRIwM6nN3XRe6pUO3dHCsN7GYH0RU8yD3/bJ6FoZlgGd5yII8qBvKdV3otg7d1L2Jz6Ta+BmWgazmtd9Y/DRD8ybek2JIRpJVr+8yLAM5LYe05u1/AiuMyS8qRZGKpGrml9Eywb4VESLDb19j+2vECOqidcT4Ad6+qhkaWJZFVIwiFU1Vva7ED7r7+8mCPGShf2h+WhYZ1Ts+WJYlyq8YNFODZmoAvNFnddE6xKU4MefyMKHBziiMFuzYtg3TNEMwqzymZUI1VWS1LFRTBQBvaQdOBMuzoR8wpm1CMRRk1AwUQwEDJrgoqqYKy7Yg87J3gZZqn6Uazo9lWGiWRoSfaqhIq2mohgowgMwX+km85AUQUnTMWYJKYdlWQfv199MtHaZtBn4RMVKxepVy/CReAsdwBX5Jecf2rbWfaqrIqJlg7iOJl8CxHHRzh19CTiAmxUL18+fG8Y9f30/kRSTlZCh+fjYko2Wg6IV+hmUE2amElEBcilc8U1eOtz8pqr//JeQEUZkmEqDBzigMF+y4rov29nb09fWFJ1clXNeFCxeu68JxHfi7CB/hkWpIhR702LaNjJ5Bd7YbWS0L13URESNoSjQhJacgCuEW3jmOg4yWQXeuGxk1Q5yfv/6N7+e4jucXb0JdpI4Yv968NzqPRL+MmgnmiPL9GmONqIvUQRLDXQagwE/1/CTeW9S2PlJPjF9vvhe9aq8XVPAyGuONxPjl9Bx6sj3oUXuI8wO8Gxfd1GHYRpDJ87OIH7fC47FCg51RGC7Y2bp1K/r6+tDS0oJolKxh3JXEcR04jgMlr6CjswMO74CP8xB5ETzHQ2CFqgc/ruvCciyYtgnDMuC6bjB83q+RsWwLeT0P3daD34ftFxEiQTG0bXuFgpqtAS5C8bNsC7qlw3Edz4+PBOsbkeJn2AZsxx7Rz3VdSLxEjB8DJigaDtqXEyHwQuh+fh1Yfz8XLgRWqJkf4F2cB/rJvBwUBjuuM8iP53gvq1wDP8vefvxu9/NHkpHmZ9omLMcK/BJyIqjVCvsmlHRosDMKQwU7tm3jv//9L1paWtDY2BiyYe3o6upCx7YONE9phmIqwcHnuq63hAEngGM5cCwHlmGLHjrtOA5s14bjOrAdG6ZtwnEdAIDACcECjlEpCpmXBw3t9NO5qqEib+RhWEbV/WzHBsuw4Dm+ZD/HdcAy7CA/lmGLCqIdx/HcXBuO4wQnbgbe8hL9/SReGnQHONDPtLyTv+M63hIBnFjQduX6+Sfu/n5RMRoUyg/lp5s6VFNFTs/V1I/n+OAC43exDPRzHMdrP1NFXt++fR1vH2EYJrhAVtLPdm3ARVl+wTFWZT9/+47mp1kaclqO+g3j1//4mKg32dWABjujMFSwo2ka1q9fjxkzZiASIWeYYbVRVRUbNmzAzJkzIcvyjrshy4Bu6d6sprYNG3YQGPiBBvy9zD82h/iZZb0LPMdwQQGgLMgQOCF4FHNw9/czLAOKqcCyLOL8/JT0WPxcDPZ1XRcMmEF+EcG7s6+mH9ztbRSyn2EZyBv5ivv5F5VK+CmGAtMyS/ZjGMYLhivkZzt2EHBX00/ghMCxEn4OvJsN38+F9/1h+BWcXyrk59/oDHV80OxN6ZCzbsA45OMWVQ/8e3mO9ybm6jdk2nF2HOhBJmT7HQvgHezB520/wP07oXLuyodi3PghAkQmvt9Az4r6AWhCU+DnZ99I8gNAlJ8/YqzSfv7/a+HX//9h+Pkjy0r16/85lfajFEKDHUpFYVlv1JYAcmYP7Q/1K4/x4kcq1K88qB+lVOhWqTKu6+L1Ta/jF//4BW5++mYsf285LNsq6bP6+vpw/fXXV9iQQqFQKJSJDc3sVBHXdXH3C3fjly/+Elkt6xVicgIW7bUI15xwTdHLFvjBzve+970qGVMoFAqFMvGgmZ0q8taWt3DPi/eAAYNZLbMwq3UWGuONeOKNJ/DX1/864ntPO+00HHDAAZg7dy6OO+44tLe346tf/Sqy2SzmzZuHAw44AACwdu1aHHXUUZg7dy7mzZuHZcuWBZ/BMAyuvfZazJ8/HzNmzMCyZcuwdOlSHHDAAZg1axaef/55AEBnZyeOPvpo7L333pg7dy7OOuusajUJhUKhUCg1hwY7VeSfa/+JrJZFa7I1KDZLyAm4cPGPd/8x4ntvvfVWrFq1Cq+//joOO+wwXHHFFbjzzjuRSCSwZs0arFq1CoAXFJ188sl4/fXX8dhjj+Hss8/Ghx9+GHxOPB7HK6+8gl/96ldYvHgxJk2ahFWrVuG6667Dt7/9bQDAgw8+iJkzZ+KNN97A66+/jp/85CdVahEKhUKhUGrPuAl2ZsyYAYZhCh6j1a9omobzzz8fjY2NiMfjOOmkk9DR0VEjY28xRWDwKCaGYWBYxojvffjhh3HAAQdgr732wj333IM1a9YMek02m8Vrr72Gs88+GwAwa9YsfOITn8CLL74YvOaUU04BABxwwAHI5/P44he/CAA46KCD8P777wMADj74YDz55JP45je/iT/96U+IxWKl/cEUCoVCoRDIuAl2AOCqq67C1q1bg8eFF1444usvvvhi/OUvf8Fjjz2G5cuXY8uWLTjxxBNrZAscMP0AyIKMPqUveE4zNdiOjcNmHTbs+1566SX87Gc/wxNPPIE333wTN998MzRNG9N3DgysZNkbFslx3KCfLcsLxhYsWIA1a9Zg/vz5+MMf/oADDzwQtm2P+e+kUCgUCoVkxlWBciKRQFtb25hem06n8atf/QoPP/wwPv3pTwMA7rvvPuy+++54+eWXcfDBBw/5Pl3Xoet68HMmkynZ98AZB+Kz8z6Lx197HF25LjAMA9d1MX/GfJyw7wnDvq+3txeJRAKNjY0wDAN33XUXACCZTEJVVRiGAVEUkUgksN9+++G+++7DOeecg7Vr1waBUjGsX78eU6ZMwRe+8AUsWrQILS0tyOVySKVSJf/tFAqFQqGQwrjK7Fx//fVobGzEvvvui5tuuinITAzF6tWrYZomjjrqqOC5OXPmYNq0aVi5cuWw71u6dClSqVTwmDp1asm+LMviss9chhs/fyM+M/czOHLOkfjhcT/EL077BZKRwSuo+yxatAizZ8/G7Nmzcdhhh2HevHkAgIaGBpxxxhmYO3duUKD80EMP4dFHH8U+++yDz3/+87jnnnswbdq0ojyff/557L///pg3bx4OOeQQ3HTTTTTQoVAoFMqEYdwsF3HzzTdjv/32Q0NDA1asWIFLL70UZ511Fm6++eYhX//www/jrLPOKsjSAF6tyhFHHIEbbrhhyPcNldmZOnXqkMtF+MsmfFz4uP7dFAqFQhnfhNqN9b3vfW/YoMPnnXfewZw5c3DJJZcEz82dOxeiKOLcc8/F0qVLIUnFzVczEpIkVfTzKBQKhUKhhEuowc43v/lNnHnmmSO+Zueddx7y+fnz58OyLGzYsAGzZ88e9Pu2tjYYhoG+vj7U1dUFz3d0dIy57odCoVAoFMr4J9Rgp7m5Gc3NzSW9d82aNWBZFi0tLUP+fv/994cgCHj22Wdx0kknAQDee+89bNy4EQsWLCjZuT+O41Tkc8YLH7e/l0KhUCgTg3ExGmvlypV45ZVXcMQRRyCRSGDlypW4+OKLsXjxYtTX1wMANm/ejCOPPBK/+c1vcNBBByGVSuHss8/GJZdcgoaGBiSTSVx44YVYsGDBsCOxxoooimBZFlu2bEFzczNEUZzQK9S6rgvDMNDZ2QmWZSGKYthKFAqFQqGMmXER7EiShEceeQRXXHEFdF3HzJkzcfHFFxfU8Zimiffeew+KogTP3XLLLWBZFieddBJ0XcfChQtx++23l+3DsixmzpyJrVu3YsuWLWV/3nghGo1i2rRpdFVfCoVCoYwrxs1orLDIZDJIpVIFo7F8XNeFZVkfiwn4OI4Dz/MTOoNFoVAolInJuMjskArDMBAEAYIghK1CoVAoFAplGGh/BIVCoVAolAkNDXYoFAqFQqFMaGg31ij4JU3lrJFFoVAoFAqleiQSiRFrSmmwMwrZbBYAyloji0KhUCgUSvUYahBRf+horFFwHAdbtmwZNWqsNP6aXB999NGIG/DjCG2bkaHtMzy0bUaGts/w0LYZmbDbh2Z2yoRlWey0006hfX8ymaQH1jDQthkZ2j7DQ9tmZGj7DA9tm5EhtX1ogTKFQqFQKJQJDQ12KBQKhUKhTGhosEMokiTh8ssvhyRJYasQB22bkaHtMzy0bUaGts/w0LYZGdLbhxYoUygUCoVCmdDQzA6FQqFQKJQJDQ12KBQKhUKhTGhosEOhUCgUCmVCQ4MdCoVCoVAoExoa7BDItddei0MOOQTRaBR1dXVDvoZhmEGPRx55pLaiITCWttm4cSOOO+44RKNRtLS04Nvf/jYsy6qtKCHMmDFj0H5y/fXXh60VGrfddhtmzJgBWZYxf/58vPrqq2Erhc4VV1wxaB+ZM2dO2Fqh8cILL+D444/H5MmTwTAMli1bVvB713Xxox/9CJMmTUIkEsFRRx2F999/PxzZGjNa25x55pmD9qVFixaFIzsAGuwQiGEYOPnkk3HeeeeN+Lr77rsPW7duDR4nnHBCbQRDZLS2sW0bxx13HAzDwIoVK/DrX/8a999/P370ox/V2JQcrrrqqoL95MILLwxbKRQeffRRXHLJJbj88svx2muvYZ999sHChQuxbdu2sNVCZ8899yzYR1566aWwlUIjn89jn332wW233Tbk72+88Ub87Gc/w5133olXXnkFsVgMCxcuhKZpNTatPaO1DQAsWrSoYF/67W9/W0PDEXApxHLfffe5qVRqyN8BcP/4xz/W1IckhmubJ554wmVZ1m1vbw+eu+OOO9xkMunqul5DQzKYPn26e8stt4StQQQHHXSQe/755wc/27btTp482V26dGmIVuFz+eWXu/vss0/YGkQy8DzrOI7b1tbm3nTTTcFzfX19riRJ7m9/+9sQDMNjqGvQkiVL3M9+9rOh+IwGzeyMY84//3w0NTXhoIMOwr333guXTpmElStXYu+990Zra2vw3MKFC5HJZPDWW2+FaBYe119/PRobG7Hvvvvipptu+lh26RmGgdWrV+Ooo44KnmNZFkcddRRWrlwZohkZvP/++5g8eTJ23nlnnHbaadi4cWPYSkSyfv16tLe3F+xHqVQK8+fPp/vRdp5//nm0tLRg9uzZOO+889Dd3R22EgC6EOi45aqrrsKnP/1pRKNRPP300/ja176GXC6Hr3/962GrhUp7e3tBoAMg+Lm9vT0MpVD5+te/jv322w8NDQ1YsWIFLr30UmzduhU333xz2Go1paurC7ZtD7lvvPvuuyFZkcH8+fNx//33Y/bs2di6dSuuvPJKHHbYYXjzzTeRSCTC1iMK/xwy1H70cTy/DGTRokU48cQTMXPmTKxbtw7f//73ccwxx2DlypXgOC5UNxrs1Ijvfe97uOGGG0Z8zTvvvDPmwsDLLrss+Pe+++6LfD6Pm266aVwGO5Vum4lOMe11ySWXBM/NnTsXoiji3HPPxdKlS4md1p1SW4455pjg33PnzsX8+fMxffp0/O53v8PZZ58dohllvPHFL34x+Pfee++NuXPnYpdddsHzzz+PI488MkQzGuzUjG9+85s488wzR3zNzjvvXPLnz58/H1dffTV0XR93F7FKtk1bW9ugETYdHR3B7yYC5bTX/PnzYVkWNmzYgNmzZ1fBjkyamprAcVywL/h0dHRMmP2iUtTV1WG33XbD2rVrw1YhDn9f6ejowKRJk4LnOzo6MG/evJCsyGXnnXdGU1MT1q5dS4OdjwvNzc1obm6u2uevWbMG9fX14y7QASrbNgsWLMC1116Lbdu2oaWlBQDwzDPPIJlMYo899qjId4RNOe21Zs0asCwbtM3HBVEUsf/+++PZZ58NRi06joNnn30WF1xwQbhyhJHL5bBu3TqcfvrpYasQx8yZM9HW1oZnn302CG4ymQxeeeWVUUfPfhzZtGkTuru7CwLDsKDBDoFs3LgRPT092LhxI2zbxpo1awAAu+66K+LxOP7yl7+go6MDBx98MGRZxjPPPIPrrrsO3/rWt8IVrwGjtc3RRx+NPfbYA6effjpuvPFGtLe344c//CHOP//8cRkIlsPKlSvxyiuv4IgjjkAikcDKlStx8cUXY/Hixaivrw9br+ZccsklWLJkCQ444AAcdNBBuPXWW5HP53HWWWeFrRYq3/rWt3D88cdj+vTp2LJlCy6//HJwHIdTTz01bLVQyOVyBVmt9evXY82aNWhoaMC0adNw0UUX4ZprrsGsWbMwc+ZMXHbZZZg8efLHYuqPkdqmoaEBV155JU466SS0tbVh3bp1+M53voNdd90VCxcuDNF6O2EPB6MMZsmSJS6AQY/nnnvOdV3XffLJJ9158+a58XjcjcVi7j777OPeeeedrm3b4YrXgNHaxnVdd8OGDe4xxxzjRiIRt6mpyf3mN7/pmqYZnnRIrF692p0/f76bSqVcWZbd3Xff3b3uuutcTdPCVguNn//85+60adNcURTdgw46yH355ZfDVgqdU045xZ00aZIriqI7ZcoU95RTTnHXrl0btlZoPPfcc0OeY5YsWeK6rjf8/LLLLnNbW1tdSZLcI4880n3vvffCla4RI7WNoiju0Ucf7TY3N7uCILjTp093zznnnIJpQMKEcV06XplCoVAoFMrEhc6zQ6FQKBQKZUJDgx0KhUKhUCgTGhrsUCgUCoVCmdDQYIdCoVAoFMqEhgY7FAqFQqFQJjQ02KFQKBQKhTKhocEOhUKhUCiUCQ0NdigUCoVCoUxoaLBDoVAmFL/61a9w9NFHV/17nnrqKcybNw+O41T9uygUSnnQYIdCoUwYNE3DZZddhssvv7zq37Vo0SIIgoCHHnqo6t9FoVDKgwY7FAplwvD73/8eyWQShx56aE2+78wzz8TPfvazmnwXhUIpHRrsUCgU4ujs7ERbWxuuu+664LkVK1ZAFEU8++yzw77vkUcewfHHH1/w3OGHH46LLrqo4LkTTjgBZ555ZvDzjBkzcM011+CMM85APB7H9OnT8ec//xmdnZ347Gc/i3g8jrlz52LVqlUFn3P88cdj1apVWLduXel/LIVCqTo02KFQKMTR3NyMe++9F1dccQVWrVqFbDaL008/HRdccAGOPPLIYd/30ksv4YADDijpO2+55RYceuih+Pe//43jjjsOp59+Os444wwsXrwYr732GnbZZRecccYZ6L928rRp09Da2ooXX3yxpO+kUCi1gQY7FAqFSI499licc845OO200/DVr34VsVgMS5cuHfb1fX19SKfTmDx5csnfd+6552LWrFn40Y9+hEwmgwMPPBAnn3wydtttN3z3u9/FO++8g46OjoL3TZ48GR9++GFJ30mhUGoDDXYoFAqx/PjHP4ZlWXjsscfw0EMPQZKkYV+rqioAQJblkr5r7ty5wb9bW1sBAHvvvfeg57Zt21bwvkgkAkVRSvpOCoVSG2iwQ6FQiGXdunXYsmULHMfBhg0bRnxtY2MjGIZBb2/vqJ9r2/ag5wRBCP7NMMywzw0cat7T04Pm5uZRv5NCoYQHDXYoFAqRGIaBxYsX45RTTsHVV1+Nr3zlK4OyKv0RRRF77LEH3n777UG/G9j19MEHH1TEUdM0rFu3Dvvuu29FPo9CoVQHGuxQKBQi+cEPfoB0Oo2f/exn+O53v4vddtsNX/7yl0d8z8KFC/HSSy8Nev5Pf/oT/vCHP2DdunW49tpr8fbbb+PDDz/E5s2by3J8+eWXIUkSFixYUNbnUCiU6kKDHQqFQhzPP/88br31VjzwwANIJpNgWRYPPPAAXnzxRdxxxx3Dvu/ss8/GE088gXQ6XfD8cccdhxtvvBF77LEHXnjhBdx+++149dVX8cADD5Tl+dvf/hannXYaotFoWZ9DoVCqC+P2H0dJoVAo45yTTz4Z++23Hy699FIA3jw78+bNw6233lrR7+nq6sLs2bOxatUqzJw5s6KfTaFQKgvN7FAolAnFTTfdhHg8XvXv2bBhA26//XYa6FAo4wCa2aFQKBOaamV2KBTK+IEGOxQKhUKhUCY0tBuLQqFQKBTKhIYGOxQKhUKhUCY0NNihUCgUCoUyoaHBDoVCoVAolAkNDXYoFAqFQqFMaGiwQ6FQKBQKZUJDgx0KhUKhUCgTGhrsUCgUCoVCmdD8f2e3ypWpX+hwAAAAAElFTkSuQmCC", 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", 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", 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Est. time left: 00:00:00:08\n", + "60.0%. Run time: 10.56s. Est. time left: 00:00:00:07\n", + "70.0%. Run time: 12.01s. Est. time left: 00:00:00:05\n", + "80.0%. Run time: 13.47s. Est. time left: 00:00:00:03\n", + "90.0%. Run time: 14.71s. Est. time left: 00:00:00:01\n", + "Total run time: 15.92s\n" ] }, { "data": { - "image/png": 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", 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", 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", 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", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -823,7 +791,7 @@ "\n", "phase_diagram(seq)\n", "\n", - "simul = QutipEmulator.from_sequence(seq, sampling_rate=0.2)\n", + "simul = QutipEmulator.from_sequence(seq, sampling_rate=0.4)\n", "\n", "occup_list = [occupation(reg, j) for j in range(len(reg.qubits))]\n", "\n", @@ -855,7 +823,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.11.3" } }, "nbformat": 4, diff --git a/tutorials/quantum_simulation/Shadow estimation for VQS.ipynb b/tutorials/quantum_simulation/Shadow estimation for VQS.ipynb index bc9258ce..bcb1e904 100644 --- a/tutorials/quantum_simulation/Shadow estimation for VQS.ipynb +++ b/tutorials/quantum_simulation/Shadow estimation for VQS.ipynb @@ -342,12 +342,18 @@ "[[0.5+0.j 0.5+0.j 0. +0.j 0. +0.j]\n", " [0.5+0.j 0.5+0.j 0. +0.j 0. +0.j]\n", " [0. +0.j 0. +0.j 0. +0.j 0. +0.j]\n", - " [0. +0.j 0. +0.j 0. +0.j 0. +0.j]]\n", + " [0. +0.j 0. +0.j 0. +0.j 0. +0.j]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Shadow reconstruction :\n", - "[[ 0.5 +0.j 0.52-0.01j 0. +0.02j 0.01-0.01j]\n", - " [ 0.52+0.01j 0.51+0.j 0.03+0.j 0. -0.01j]\n", - " [ 0. -0.02j 0.03-0.j -0. +0.j -0.01+0.01j]\n", - " [ 0.01+0.01j 0. +0.01j -0.01-0.01j -0. +0.j ]]\n" + "[[0.49+0.j 0.51+0.j 0.01+0.j 0.02+0.01j]\n", + " [0.51-0.j 0.5 +0.j 0. -0.01j 0. -0.01j]\n", + " [0.01-0.j 0. +0.01j 0.01+0.j 0. +0.j ]\n", + " [0.02-0.01j 0. +0.01j 0. -0.j 0. +0.j ]]\n" ] } ], @@ -390,14 +396,12 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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", 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", 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cLgcAgJBna3gpKCho9xkvxhj/z/Hx8XrzzTftLCnkZGRkqLi4mEG7AAAEKORule5quOMIAABrCC8OawwvjHkBACAwhBeH0fMCAIA1hBeH/fBZLwAAoH2EF4fR8wIAgDWEF4cx5gUAAGsILw5rDC9VVVVNHt4HAABaRnhxWGJionr27CmJS0cAAASC8BICGLQLAEDgCC8hgEG7AAAEjvASAhi0CwBA4AgvIYCeFwAAAkd4CQGMeQEAIHCElxBw1llnSZI8Ho/DlQAAEPoILyFgyJAhkqSSkhKHKwEAIPQRXkJAbm6uJOno0aP69ttvHa4GAIDQRngJAQkJCcrMzJQkFRcXO1wNAAChjfASIhp7XwgvAAC0jfASIggvAAAEhvASIoYNGyZJ+uKLLxyuBACA0EZ4CRH0vAAAEBjCS4hoDC9ffvmlqqurHa4GAIDQRXgJEf369VNSUpLq6+tVWlrqdDkAAIQswkuIcLlc/t4Xxr0AANA6wksIYdwLAADtI7yEEMILAADtI7yEEG6XBgCgfYSXENLY81JSUiJjjMPVAAAQmggvISQrK0uSVFVVJZ/P53A1AACEJsJLCImPj5fb7ZYkHT582OFqAAAITYSXEJORkSFJKi8vd7gSAABCE+ElxPTr108S4QUAgNYQXkJMY3jhshEAAC0jvIQYLhsBANA2wkuI4bIRAABtI7yEGMILAABtI7yEGMa8AADQNsJLiGHMCwAAbSO8hJjGnpeqqipVVlY6XA0AAKGH8BJiEhISlJCQIIneFwAAWkJ4CUEM2gUAoHWElxDEuBcAAFpHeAlB9LwAANA6wksI4nZpAABaR3gJQVw2AgCgdbaFlxUrVmjChAnq0aOHkpOTA17viy++0OWXXy63262ePXvqggsukMfjsavMkMRlIwAAWmdbeKmpqdHs2bO1cOHCgNcpLS3VxRdfrNzcXG3cuFG7du3Svffeq+7du9tVZkjishEAAK2LsWvDy5cvlyQVFBQEvM6///u/65//+Z/10EMP+ecNHjw42KWFPHpeAABoXciMeWloaNDatWs1ZMgQTZs2TX369NG4ceP08ssvt7ledXW1fD5fkyncNY558Xq9OnXqlMPVAAAQWkImvBw7dkxVVVV68MEHNX36dL311luaNWuWrrrqKm3atKnV9fLz8+V2u/1T//79O7FqeyQlJSk+Pl4SvS8AAPwjS+Fl6dKlcrlcbU7FxcUdKqShoUGSdMUVV+jOO+/UOeeco6VLl+pf/uVf9OSTT7a6Xl5enrxer386ePBgh74/lLhcLv+lo0OHDjlcDQAAocXSmJfFixdr3rx5bbbJzs7uUCGpqamKiYnR8OHDm8wfNmyY3nvvvVbXi4uLU1xcXIe+M5T1799fX375pcrKypwuBQCAkGIpvKSlpSktLc2WQmJjY3XBBReopKSkyfw9e/YoKyvLlu8MZQMGDJCkLnebOAAA7bHtbiOPx6MTJ07I4/Govr5eRUVFkqScnBz/W5Nzc3OVn5+vWbNmSZKWLFmia665RhMnTtSll16qN954Q6+++qo2btxoV5khi/ACAEDLbAsvy5YtU2Fhof/z2LFjJUkbNmzQpEmTJEklJSXyer3+NrNmzdKTTz6p/Px83X777Ro6dKj+9re/6eKLL7arzJBFeAEAoGUuY4xxuohg8vl8crvd8nq9SkpKcrqcDnvjjTc0Y8YMjR49Wp988onT5QAAYCsr5++QuVUaTTXe8k3PCwAATRFeQlRjeKmoqFBlZaXD1QAAEDoILyEqKSnJ/0LLSHh2DQAAwUJ4CWEM2gUAoDnCSwgjvAAA0BzhJYQRXgAAaI7wEsIILwAANEd4CWGEFwAAmiO8hDDCCwAAzRFeQljjs17KyspUX1/vcDUAAIQGwksIy8jIUFRUlGpra3X06FGnywEAICQQXkJYTEyMzjrrLElcOgIAoBHhJcQx7gUAgKYILyGuMbzccMMNcrvdrU7p6elau3atw9UCAGA/wkuIu/TSSyVJp0+fls/na3U6evSonnvuOYerBQDAfjFOF4C2zZ8/XzNnztR3333Xapt169bp1ltv1b59+zqxMgAAnEF4CQMZGRltLj958qQkqbS0tDPKAQDAUVw2igDZ2dmSpOPHj6uiosLZYgAAsBnhJQIkJiaqb9++kuh9AQBEPsJLhMjJyZEkxr0AACIe4SVCDB48WBLhBQAQ+QgvEaKx54XLRgCASEd4iRBcNgIAdBWElwjBZSMAQFdBeIkQjT0v5eXl/ue+AAAQiQgvEaJ3797q1auXJOnLL790uBoAAOxDeIkgjZeOGLQLAIhkhJcIwqBdAEBXQHiJIAzaBQB0BYSXCMKzXgAAXQHhJYJw2QgA0BUQXiJI42Ujj8ejmpoah6sBAMAehJcIkp6erh49eqihoUFfffWV0+UAAGALwksEcblcXDoCAEQ8wkuE4VkvAIBIR3iJMPS8AAAiHeElwnC7NAAg0hFeIgwPqgMARDrCS4Rp7Hn58ssvVV9f73A1AAAEH+ElwmRmZio2Nla1tbUqKytzuhwAAIKO8BJhoqOjNWjQIElcOgIARCbCSwTijiMAQCQjvEQgnvUCAIhkhJcIRM8LACCS2RpeVqxYoQkTJqhHjx5KTk4OaB2Xy9XitHLlSjtLjSg86wUAEMli7Nx4TU2NZs+erfHjx2vVqlUBrVNeXt7k89///nfddNNNuvrqq+0oMSL98FkvzzzzTIttJk6cqIEDB3ZiVQAABIfLGGPs/pKCggLdcccdqqiosLzulVdeqcrKSq1fvz6g9j6fT263W16vV0lJSZa/LxLU1NSoZ8+eqqura7XNkCFDVFJS0olVAQDQOivnb1t7Xs7U0aNHtXbtWhUWFrbaprq6WtXV1f7PPp+vM0oLabGxsfr973+vNWvWtLj8jTfe0J49e/TNN98oNTW1k6sDAODMhHR4KSwsVGJioq666qpW2+Tn52v58uWdWFV4WLhwoRYuXNjispycHJWWluqTTz7R5MmTO7kyAADOjOUBu0uXLm11UG3jVFxcHJTinnrqKc2ZM0fdu3dvtU1eXp68Xq9/OnjwYFC+O5KNGTNGkvTJJ584XAkAANZZ7nlZvHix5s2b12ab7Ozsjtbjt3nzZpWUlOiFF15os11cXJzi4uLO+Pu6kjFjxuill14ivAAAwpLl8JKWlqa0tDQ7amli1apVOu+88/y9BAgeel4AAOHM1ue8eDweFRUVyePxqL6+XkVFRSoqKlJVVZW/TW5urlavXt1kPZ/PpxdffFE333yzneV1Weecc44k6fPPP1dNTY2zxQAAYJGtA3aXLVvW5E6hsWPHSpI2bNigSZMmSZJKSkrk9XqbrPf888/LGKNrr73WzvK6rAEDBig5OVkVFRUqLi7W6NGjnS4JAICAdcpzXjoTz3kJzCWXXKJ3331XhYWFmjt3rtPlAAC6OCvnb95t1EUx7gUAEK4IL10U4QUAEK5C+iF1sM8Pw8sPn0ocHR2tnj17OlUWAADtouelixoxYoSioqL0zTffyO12+6eEhATdf//9TpcHAECrCC9dVHx8vK655poWl/3ud7/T6dOnO7kiAAACQ3jpwp577jmdOnXKP508eVJnnXWWKioqtHbtWqfLAwCgRYSXLq579+7+qUePHpozZ44k6c9//rPDlQEA0DLCC5q4/vrrJUmvv/66vvnmG4erAQCgOcILmhg5cqTGjh2r2tradl+KCQCAE7hVGs3MnTtXO3fu1D333KP/+q//OuPtXXjhhXrqqafkcrmCUB0AoKvj9QBo5ujRo8rJyWnyAs0z9dlnn2n48OFB2x4AILJYOX/T84Jm+vbtq88++0ylpaVnvK3bb79du3fvJrwAAIKG8IIWDRgwQAMGDDjj7VxwwQXavXu3du/erdmzZwehMgBAV8eAXdhq5MiRkr6/bAQAQDAQXmCrESNGSCK8AACCh/ACWzX2vOzdu1fV1dUOVwMAiASEF9gqIyNDbrdb9fX1KikpcbocAEAEILzAVi6Xi0tHAICgIrzAdo2Xjnbv3u1wJQCASEB4ge3oeQEABBPhBbbjdmkAQDARXmC7xp6X0tJSnTp1yuFqAADhjifswnZ9+vRRSkqKjh8/rvvuu099+vSxtP7EiRN14YUX2lQdACDcEF5gO5fLpTFjxuidd97RypUrLa+fmJiosrIyXrQJAJBEeEEneeihh/TEE0+otrbW0nrr1q1TeXm5nn/+eS1YsMCm6gAA4cRljDFOFxFMVl6pjdD38MMP65e//KXOP/98bd++3elyAAA2sXL+ZsAuQtoNN9yg2NhYffTRR9q5c6fT5QAAQgDhBSEtNTVVs2bNkiT96U9/crgaAEAoYMwLQt78+fP1wgsvqLCwUHv37u3wdsaPH68HHnggiJUBAJzAmBeEvIaGBo0YMULFxcVnvK39+/dr4MCBZ14UACCorJy/6XlByIuKitK6deu0efNmdTRr33PPPTpw4IBKSkoILwAQ5ggvCAuZmZm69tprO7z+X//6V394mTZtWhArAwB0NgbsoksYOnSoJKmkpMThSgAAZ4rwgi6B8AIAkYPwgi6B8AIAkYPwgi5hyJAhkqSysjKdPHnS4WoAAGeC8IIuISUlRSkpKZKkPXv2OFwNAOBMEF7QZXDpCAAiA+EFXQbhBQAiA+EFXQbhBQAiA+EFXQbhBQAiA+EFXUZjeNmzZ0+HXzMAAHAe4QVdxuDBgxUdHa2qqiodPnzY6XIAAB3Eu43QZcTGxmrQoEHat2+fLrnkEsXHxztaj9vt1nXXXafrr79eiYmJjtYCAOGE8IIu5aKLLtK+fftUWlrqdCmSpPfff19Lly7VmjVrNGnSJKfLAYCw4DI2XfxfsWKF1q5dq6KiIsXGxqqioqLddaqqqrR06VK9/PLLOn78uAYNGqTbb79dt9xyS8Df6/P55Ha75fV6lZSUdAZ7gEhUXV2tbdu2qa6uzulS9Omnn+rxxx/X3r17NXnyZL399ttOlwQAjrFy/rYtvNx3331KTk5WWVmZVq1aFVB4WbBggd555x39z//8jwYOHKi33npLt956q1566SVdfvnlAX0v4QXhpLi4WMOGDVNcXJy+/fZbxy9lAYBTrJy/bRuwu3z5ct15550aNWpUwOt88MEHuuGGGzRp0iQNHDhQCxYs0JgxY/Thhx/aVSbgqKFDhyozM1PV1dXavHmz0+UAQFgIqbuNJkyYoDVr1ujQoUMyxmjDhg3as2ePpk6d2uo61dXV8vl8TSYgXLhcLv34xz+WJK1bt87hagAgPIRUeHnsscc0fPhwZWZmKjY2VtOnT9fjjz+uiRMntrpOfn6+3G63f+rfv38nVgycucbw8tZbbzlcCQCEB0vhZenSpXK5XG1OxcXFHS7mscce09atW7VmzRrt2LFDDz/8sBYtWtTmQMa8vDx5vV7/dPDgwQ5/P+CEyZMnS5J27dqlo0ePOlwNAIQ+SwN2v/76ax0/frzNNtnZ2YqNjfV/Ligo0B133NHugN1Tp07J7XZr9erVmjlzpn/+zTffrLKyMr3xxhsB1ciAXYSjc889Vzt37tSzzz6rOXPmOF0OAHQ6K+dvS895SUtLU1pa2hkV15ra2lrV1tYqKqppZ1B0dLQaGhps+U4gVPz4xz/Wzp079Yc//KHdZ9BMnjxZF110USdVBgChx7aH1Hk8Hp04cUIej0f19fUqKiqSJOXk5CghIUGSlJubq/z8fM2aNUtJSUm65JJLtGTJEsXHxysrK0ubNm3SM888o0ceecSuMoGQMG3aND300EPaunWrtm7d2mbb+++/X48//rgWLlzYSdUBQGix7Tkv8+bNU2FhYbP5GzZs8D9J1OVy6emnn9a8efMkSUeOHFFeXp7eeustnThxQllZWVqwYIHuvPNOuVyugL6Xy0YIR8YYPfzww+32ung8Hr3++uuSvn8u0tlnn91m+9TUVF199dW8fgBAyAuJh9Q5hfCCSGaM0QMPPKD7778/4HXcbrfmz5+vpUuXKiUlxb7iAOAMEF4IL4hwf/vb37RmzRq19+u7bds27dmzR5KUmZmp5557Tj/60Y86o0QAsITwQngBJEkNDQ16/fXXtXjxYu3Zs0dRUVE6//zz5XK5FB8frz59+qhXr15NBsr/4yXaH35u/NnlcmnGjBmaMWNG5+wIgIhHeCG8AE1UVlZq0aJF+vOf/xy0bXbv3l0ej8e2OxABdC2EF8IL0KLt27ervLxcknTy5EkdO3asyTOYfvjnoLWfJenFF19UcXGx7r33Xj3wwAP2Fg2gSyC8EF4AW/31r3/V7Nmz1atXL3k8Hv/jDwCgo0LirdIAItesWbOUk5Ojb7/9VqtWrXK6HABdDD0vADrkj3/8o2655Ralpqbq4osv9s93uVzKysrS6NGjddlllykrK8vBKgGECy4bEV4A250+fVrZ2dn+MTQtiYuL069+9Svdddddio6O7sTqAIQbwgvhBegUe/bs0caNG5vMq6ur0969e/X+++9r+/btkqTBgwcH5a6k9PR0rVy5Ujk5OWe8LQChhfBCeAEcZ4xRQUGB7rzzTnm93qBtNysrS++9954yMzODtk0AziO8EF6AkPH1119ry5Yt7T4NuD0NDQ26++67tXfvXuXm5mrZsmVyuVztTlFRUQG1O9NpwIAB6tu3b5D+XwO6HsIL4QWISAcOHNDFF1+ssrIyp0tpUVZWloYOHdrkicU/NGzYMM2fP1/Dhg3r5MqA0Ed4IbwAEWvPnj2699579fXXX8sYY/vU0NDQbpv6+nodPnw44N6lkSNHKj4+PqC20dHRysnJ0ciRI9W7d+9W2yUmJsrtdisuLq7dbSYkJCg9PV29evWSy+VSTEyMunfvHlA9gF0IL4QXAJ3M5/Np+/btrfYK1dbW6rXXXtOrr76qhoaGTq6ubS6XS+eee66mTp2qjIyMJvN/+L8tzWtrmdV5MTExysjIUGZmpuLj49u99PeP87t37x5QeENoIrwQXgCEqEOHDqmoqCjg9qdPn1ZxcbE+++wznTx5ssU2DQ0NqqqqktfrVW1tbZvbM8bI5/PpyJEj7bYNN1FRURo+fLjOPffcoD31+R9fVMp2vtetWzf953/+Z1BqaUR4IbwAQJuMMTp9+rQk6cSJE1q/fr02btzoD0iNp4aW3nEVyLKObKO6ulqHDh1SWVmZqqurm12+Q+iIi4vz//sJFivn75igfjMAICy4XC7/uJuzzjpLc+fO1dy5cx2uqn1tjUc6fvy4duzYoU8//VQ1NTW2fLdd7Nq2Xdt1+qGT9LwAAADH8WJGAAAQsSL3stHJkxLvUgEAIDy0MiC9JZEbXn5wux8AAIgcXDYCAABhJXJ7Xg4flhiwCwBAePD5Ar5qErnhpWfP7ycAABD66usDbsplIwAAEFYILwAAIKwQXgAAQFghvAAAgLBCeAEAAGGF8AIAAMIK4QUAAISViHvOS+NLsn0+n8OVAACAQDWetxvP422JuPBSWVkpSerfv7/DlQAAAKsqKyvldrvbbOMygUScMNLQ0KDDhw8rMTFRLpcrqNv2+Xzq37+/Dh48qKQIffVApO9jpO+fxD5GgkjfP4l9jATB3j9jjCorK5WRkaGoqLZHtURcz0tUVJQyMzNt/Y6kpKSI/If4Q5G+j5G+fxL7GAkiff8k9jESBHP/2utxacSAXQAAEFYILwAAIKwQXiyIi4vTfffdp7i4OKdLsU2k72Ok75/EPkaCSN8/iX2MBE7uX8QN2AUAAJGNnhcAABBWCC8AACCsEF4AAEBYIbwAAICwQnix4PHHH9fAgQPVvXt3jRs3Th9++KHTJXVIfn6+LrjgAiUmJqpPnz668sorVVJS0qTNpEmT5HK5mky33HKLQxVbd//99zerPzc317/89OnTWrRokVJSUpSQkKCrr75aR48edbBiawYOHNhs/1wulxYtWiQpPI/fu+++q3/9139VRkaGXC6XXn755SbLjTFatmyZ+vXrp/j4eE2ZMkV79+5t0ubEiROaM2eOkpKSlJycrJtuuklVVVWduBdta2sfa2trdffdd2vUqFHq2bOnMjIyNHfuXB0+fLjJNlo69g8++GAn70nL2juG8+bNa1b79OnTm7QJ52MoqcXfS5fLpZUrV/rbhPIxDOT8EMjfT4/Ho5kzZ6pHjx7q06ePlixZorq6uqDVSXgJ0AsvvKC77rpL9913nz7++GONGTNG06ZN07Fjx5wuzbJNmzZp0aJF2rp1q9atW6fa2lpNnTpVJ0+ebNJu/vz5Ki8v908PPfSQQxV3zIgRI5rU/9577/mX3XnnnXr11Vf14osvatOmTTp8+LCuuuoqB6u1Zvv27U32bd26dZKk2bNn+9uE2/E7efKkxowZo8cff7zF5Q899JB+//vf68knn9S2bdvUs2dPTZs2TadPn/a3mTNnjj777DOtW7dOr732mt59910tWLCgs3ahXW3t43fffaePP/5Y9957rz7++GO99NJLKikp0eWXX96s7QMPPNDk2P785z/vjPLb1d4xlKTp06c3qf0vf/lLk+XhfAwlNdm38vJyPfXUU3K5XLr66qubtAvVYxjI+aG9v5/19fWaOXOmampq9MEHH6iwsFAFBQVatmxZ8Ao1CMiFF15oFi1a5P9cX19vMjIyTH5+voNVBcexY8eMJLNp0yb/vEsuucT84he/cK6oM3TfffeZMWPGtLisoqLCdOvWzbz44ov+eV988YWRZLZs2dJJFQbXL37xCzN48GDT0NBgjAn/4yfJrF692v+5oaHBpKenm5UrV/rnVVRUmLi4OPOXv/zFGGPM559/biSZ7du3+9v8/e9/Ny6Xyxw6dKjTag/UP+5jSz788EMjyRw4cMA/Lysryzz66KP2FhcELe3fDTfcYK644opW14nEY3jFFVeYyy67rMm8cDmGxjQ/PwTy9/P11183UVFR5siRI/42TzzxhElKSjLV1dVBqYuelwDU1NRox44dmjJlin9eVFSUpkyZoi1btjhYWXB4vV5JUu/evZvM/9///V+lpqZq5MiRysvL03fffedEeR22d+9eZWRkKDs7W3PmzJHH45Ek7dixQ7W1tU2OZ25urgYMGBCWx7OmpkbPPvusfvaznzV5GWm4H78f2r9/v44cOdLkmLndbo0bN85/zLZs2aLk5GSdf/75/jZTpkxRVFSUtm3b1uk1B4PX65XL5VJycnKT+Q8++KBSUlI0duxYrVy5Mqjd8XbbuHGj+vTpo6FDh2rhwoU6fvy4f1mkHcOjR49q7dq1uummm5otC5dj+I/nh0D+fm7ZskWjRo1S3759/W2mTZsmn8+nzz77LCh1RdyLGe3wzTffqL6+vsmBkKS+ffuquLjYoaqCo6GhQXfccYcuuugijRw50j//uuuuU1ZWljIyMrRr1y7dfffdKikp0UsvveRgtYEbN26cCgoKNHToUJWXl2v58uX60Y9+pN27d+vIkSOKjY1tdkLo27evjhw54kzBZ+Dll19WRUWF5s2b558X7sfvHzUel5Z+BxuXHTlyRH369GmyPCYmRr179w7L43r69Gndfffduvbaa5u89O7222/Xueeeq969e+uDDz5QXl6eysvL9cgjjzhYbWCmT5+uq666SoMGDVJpaanuuecezZgxQ1u2bFF0dHTEHcPCwkIlJiY2uyQdLsewpfNDIH8/jxw50uLvauOyYCC8dHGLFi3S7t27m4wHkdTkGvOoUaPUr18/TZ48WaWlpRo8eHBnl2nZjBkz/D+PHj1a48aNU1ZWlv7v//5P8fHxDlYWfKtWrdKMGTOUkZHhnxfux6+rq62t1U9+8hMZY/TEE080WXbXXXf5fx49erRiY2P1b//2b8rPzw/5x9D/9Kc/9f88atQojR49WoMHD9bGjRs1efJkByuzx1NPPaU5c+aoe/fuTeaHyzFs7fwQCrhsFIDU1FRFR0c3G0199OhRpaenO1TVmbvtttv02muvacOGDcrMzGyz7bhx4yRJ+/bt64zSgi45OVlDhgzRvn37lJ6erpqaGlVUVDRpE47H88CBA3r77bd18803t9ku3I9f43Fp63cwPT292QD6uro6nThxIqyOa2NwOXDggNatW9ek16Ul48aNU11dnb766qvOKTCIsrOzlZqa6v93GSnHUJI2b96skpKSdn83pdA8hq2dHwL5+5ment7i72rjsmAgvAQgNjZW5513ntavX++f19DQoPXr12v8+PEOVtYxxhjddtttWr16td555x0NGjSo3XWKiookSf369bO5OntUVVWptLRU/fr103nnnadu3bo1OZ4lJSXyeDxhdzyffvpp9enTRzNnzmyzXbgfv0GDBik9Pb3JMfP5fNq2bZv/mI0fP14VFRXasWOHv80777yjhoYGf3gLdY3BZe/evXr77beVkpLS7jpFRUWKiopqdrklHJSVlen48eP+f5eRcAwbrVq1Suedd57GjBnTbttQOobtnR8C+fs5fvx4ffrpp02CaGMQHz58eNAKRQCef/55ExcXZwoKCsznn39uFixYYJKTk5uMpg4XCxcuNG6322zcuNGUl5f7p++++84YY8y+ffvMAw88YD766COzf/9+88orr5js7GwzceJEhysP3OLFi83GjRvN/v37zfvvv2+mTJliUlNTzbFjx4wxxtxyyy1mwIAB5p133jEfffSRGT9+vBk/frzDVVtTX19vBgwYYO6+++4m88P1+FVWVpqdO3eanTt3GknmkUceMTt37vTfafPggw+a5ORk88orr5hdu3aZK664wgwaNMicOnXKv43p06ebsWPHmm3btpn33nvPnH322ebaa691apeaaWsfa2pqzOWXX24yMzNNUVFRk9/Nxjs0PvjgA/Poo4+aoqIiU1paap599lmTlpZm5s6d6/Cefa+t/ausrDS//OUvzZYtW8z+/fvN22+/bc4991xz9tlnm9OnT/u3Ec7HsJHX6zU9evQwTzzxRLP1Q/0Ytnd+MKb9v591dXVm5MiRZurUqaaoqMi88cYbJi0tzeTl5QWtTsKLBY899pgZMGCAiY2NNRdeeKHZunWr0yV1iKQWp6efftoYY4zH4zETJ040vXv3NnFxcSYnJ8csWbLEeL1eZwu34JprrjH9+vUzsbGx5qyzzjLXXHON2bdvn3/5qVOnzK233mp69eplevToYWbNmmXKy8sdrNi6N99800gyJSUlTeaH6/HbsGFDi/8ub7jhBmPM97dL33vvvaZv374mLi7OTJ48udm+Hz9+3Fx77bUmISHBJCUlmRtvvNFUVlY6sDcta2sf9+/f3+rv5oYNG4wxxuzYscOMGzfOuN1u0717dzNs2DDzH//xH01O/k5qa/++++47M3XqVJOWlma6detmsrKyzPz585v9B2A4H8NGf/zjH018fLypqKhotn6oH8P2zg/GBPb386uvvjIzZsww8fHxJjU11SxevNjU1tYGrU7X/y8WAAAgLDDmBQAAhBXCCwAACCuEFwAAEFYILwAAIKwQXgAAQFghvAAAgLBCeAEAAGGF8AIAAMIK4QUAAIQVwgsAAAgrhBcAABBWCC8AACCs/D8m/7qANeh5qwAAAABJRU5ErkJggg==", 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", 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41, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -1404,7 +1400,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.11.3" } }, "nbformat": 4, From 9e05982721283d909fe18e137c5e00ba3a95a1ff Mon Sep 17 00:00:00 2001 From: Antoine Cornillot <61453516+a-corni@users.noreply.github.com> Date: Fri, 22 Sep 2023 17:10:55 +0200 Subject: [PATCH 14/18] Adding register_is_from_calibrated_layout and is_calibrated_layout to Device (#586) * Adding register_is_from_calibrated_layout * Fix descr, testing type of register * Introducing any, modifying instance check --- pulser-core/pulser/devices/_device_datacls.py | 42 +++++++++++++++++++ tests/test_devices.py | 32 +++++++++++--- 2 files changed, 69 insertions(+), 5 deletions(-) diff --git a/pulser-core/pulser/devices/_device_datacls.py b/pulser-core/pulser/devices/_device_datacls.py index 2cef6d0b..c5812006 100644 --- a/pulser-core/pulser/devices/_device_datacls.py +++ b/pulser-core/pulser/devices/_device_datacls.py @@ -538,6 +538,48 @@ def calibrated_register_layouts(self) -> dict[str, RegisterLayout]: """Register layouts already calibrated on this device.""" return {str(layout): layout for layout in self.pre_calibrated_layouts} + def is_calibrated_layout(self, register_layout: RegisterLayout) -> bool: + """Checks whether a layout is within the calibrated layouts. + + Args: + register_layout: The RegisterLayout to check. + + Returns: + True if register_layout is found among calibrated_register_layouts, + False otherwise. + """ + return any( + [ + register_layout == layout + for layout in list(self.calibrated_register_layouts.values()) + ] + ) + + def register_is_from_calibrated_layout( + self, register: BaseRegister | MappableRegister + ) -> bool: + """Checks whether a register was constructed from a calibrated layout. + + If the register is a BaseRegister, checks that it has a layout. If so, + or if it is a MappableRegister, check that its layout is within the + calibrated layouts. + + Args: + register_layout: the Register or MappableRegister to check. + + Returns: + True if register has a layout and it is found among + calibrated_register_layouts, False otherwise. + """ + if not isinstance(register, (BaseRegister, MappableRegister)): + raise TypeError( + "The register to check must be of type " + "BaseRegister or MappableRegister." + ) + if isinstance(register, BaseRegister) and register.layout is None: + return False + return self.is_calibrated_layout(cast(RegisterLayout, register.layout)) + def to_virtual(self) -> VirtualDevice: """Converts the Device into a VirtualDevice.""" params = self._params() diff --git a/tests/test_devices.py b/tests/test_devices.py index d3d0c742..54d8aa69 100644 --- a/tests/test_devices.py +++ b/tests/test_devices.py @@ -25,7 +25,10 @@ from pulser.devices import Chadoq2, Device, VirtualDevice from pulser.register import Register, Register3D from pulser.register.register_layout import RegisterLayout -from pulser.register.special_layouts import TriangularLatticeLayout +from pulser.register.special_layouts import ( + SquareLatticeLayout, + TriangularLatticeLayout, +) @pytest.fixture @@ -336,6 +339,8 @@ def test_calibrated_layouts(): pre_calibrated_layouts=(TriangularLatticeLayout(201, 3),), ) + layout100 = TriangularLatticeLayout(100, 6.8) + layout200 = TriangularLatticeLayout(200, 5) TestDevice = Device( name="TestDevice", dimensions=2, @@ -344,15 +349,32 @@ def test_calibrated_layouts(): max_radial_distance=50, min_atom_distance=4, channel_objects=(), - pre_calibrated_layouts=( - TriangularLatticeLayout(100, 6.8), - TriangularLatticeLayout(200, 5), - ), + pre_calibrated_layouts=(layout100, layout200), ) assert TestDevice.calibrated_register_layouts.keys() == { "TriangularLatticeLayout(100, 6.8µm)", "TriangularLatticeLayout(200, 5.0µm)", } + with pytest.raises( + TypeError, + match="The register to check must be of type ", + ): + TestDevice.register_is_from_calibrated_layout(layout100) + assert TestDevice.is_calibrated_layout(layout100) + register = layout200.define_register(*range(10)) + assert TestDevice.register_is_from_calibrated_layout(register) + # Checking a register not built from a layout returns False + assert not TestDevice.register_is_from_calibrated_layout( + Register.triangular_lattice(4, 25, 6.8) + ) + # Checking Layouts that don't match calibrated layouts returns False + square_layout = SquareLatticeLayout(10, 10, 6.8) + layout125 = TriangularLatticeLayout(125, 6.8) + compact_layout = TriangularLatticeLayout(100, 3) + for bad_layout in (square_layout, layout125, compact_layout): + assert not TestDevice.is_calibrated_layout(bad_layout) + register = bad_layout.define_register(*range(10)) + assert not TestDevice.register_is_from_calibrated_layout(register) def test_device_with_virtual_channel(): From 3e40319f18f2518036b12dccb79a6dda8e396937 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Henrique=20Silv=C3=A9rio?= Date: Mon, 25 Sep 2023 11:25:24 +0200 Subject: [PATCH 15/18] Deprecate legacy serializer + Improve error messages (#585) * Improve serialization error messages * Deprecate the legacy serializer * Update serialization tutorial * UT updates * Import sorting * Add reminder to remove legacy serializer * Fix typo in tutorial * Fix typo in tutorial text --- pulser-core/pulser/sequence/sequence.py | 101 +++++- tests/test_abstract_repr.py | 28 ++ tests/test_json.py | 56 ++- tests/test_paramseq.py | 8 +- tests/test_sequence.py | 12 +- .../advanced_features/Serialization.ipynb | 338 ++++++++---------- 6 files changed, 340 insertions(+), 203 deletions(-) diff --git a/pulser-core/pulser/sequence/sequence.py b/pulser-core/pulser/sequence/sequence.py index 39bf5533..81eae094 100644 --- a/pulser-core/pulser/sequence/sequence.py +++ b/pulser-core/pulser/sequence/sequence.py @@ -33,6 +33,7 @@ overload, ) +import jsonschema import matplotlib.pyplot as plt import numpy as np from numpy.typing import ArrayLike @@ -48,6 +49,7 @@ ) from pulser.json.abstract_repr.serializer import serialize_abstract_sequence from pulser.json.coders import PulserDecoder, PulserEncoder +from pulser.json.exceptions import AbstractReprError from pulser.json.utils import obj_to_dict from pulser.parametrized import Parametrized, Variable from pulser.parametrized.variable import VariableItem @@ -1560,6 +1562,39 @@ def build( def serialize(self, **kwargs: Any) -> str: """Serializes the Sequence into a JSON formatted string. + Other Parameters: + kwargs: Valid keyword-arguments for ``json.dumps()``, except for + ``cls``. + + Returns: + The sequence encoded in a JSON formatted string. + + Warning: + This method has been deprecated and is scheduled for removal + in Pulser v1.0.0. For sequence serialization and deserialization, + use ``Sequence.to_abstract_repr()`` and + ``Sequence.from_abstract_repr()`` instead. + + See Also: + ``json.dumps``: Built-in function for serialization to a JSON + formatted string. + """ + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + DeprecationWarning( + "`Sequence.serialize()` and `Sequence.deserialize()` have " + "been deprecated and will be removed in Pulser v1.0.0. " + "Use `Sequence.to_abstract_repr()` and " + "`Sequence.from_abstract_repr()` instead." + ) + ) + + return self._serialize(**kwargs) + + def _serialize(self, **kwargs: Any) -> str: + """Serializes the Sequence into a JSON formatted string. + Other Parameters: kwargs: Valid keyword-arguments for ``json.dumps()``, except for ``cls``. @@ -1599,16 +1634,62 @@ def to_abstract_repr( Returns: str: The sequence encoded as an abstract JSON object. + """ + try: + return serialize_abstract_sequence( + self, seq_name, json_dumps_options, **defaults + ) + except jsonschema.exceptions.ValidationError as e: + if self.is_parametrized(): + raise AbstractReprError( + "The serialization of the parametrized sequence failed, " + "potentially due to an error that only appears at build " + "time. Check that no errors appear when building with " + "`Sequence.build()` or when providing the `defaults` to " + "`Sequence.to_abstract_repr()`." + ) from e + raise e # pragma: no cover + + @staticmethod + def deserialize(obj: str, **kwargs: Any) -> Sequence: + """Deserializes a JSON formatted string. + + Args: + obj: The JSON formatted string to deserialize, coming from + the serialization of a ``Sequence`` through + ``Sequence.serialize()``. + + Other Parameters: + kwargs: Valid keyword-arguments for ``json.loads()``, except for + ``cls`` and ``object_hook``. + + Returns: + The deserialized Sequence object. + + Warning: + This method has been deprecated and is scheduled for removal + in Pulser v1.0.0. For sequence serialization and deserialization, + use ``Sequence.to_abstract_repr()`` and + ``Sequence.from_abstract_repr()`` instead. See Also: - ``serialize`` + ``json.loads``: Built-in function for deserialization from a JSON + formatted string. """ - return serialize_abstract_sequence( - self, seq_name, json_dumps_options, **defaults - ) + with warnings.catch_warnings(): + warnings.simplefilter("always") + warnings.warn( + DeprecationWarning( + "`Sequence.serialize()` and `Sequence.deserialize()` have " + "been deprecated and will be removed in Pulser v1.0.0. " + "Use `Sequence.to_abstract_repr()` and " + "`Sequence.from_abstract_repr()` instead." + ) + ) + return Sequence._deserialize(obj, **kwargs) @staticmethod - def deserialize(obj: str, **kwargs: Any) -> Sequence: + def _deserialize(obj: str, **kwargs: Any) -> Sequence: """Deserializes a JSON formatted string. Args: @@ -1627,6 +1708,11 @@ def deserialize(obj: str, **kwargs: Any) -> Sequence: ``json.loads``: Built-in function for deserialization from a JSON formatted string. """ + if not isinstance(obj, str): + raise TypeError( + "The serialized sequence must be given as a string. " + f"Instead, got object of type {type(obj)}." + ) if "Sequence" not in obj: raise ValueError( "The given JSON formatted string does not encode a Sequence." @@ -1645,6 +1731,11 @@ def from_abstract_repr(obj_str: str) -> Sequence: Returns: Sequence: The Pulser sequence. """ + if not isinstance(obj_str, str): + raise TypeError( + "The serialized sequence must be given as a string. " + f"Instead, got object of type {type(obj_str)}." + ) return deserialize_abstract_sequence(obj_str) @seq_decorators.screen diff --git a/tests/test_abstract_repr.py b/tests/test_abstract_repr.py index e7d8392c..cf4e5cee 100644 --- a/tests/test_abstract_repr.py +++ b/tests/test_abstract_repr.py @@ -819,6 +819,23 @@ def test_mappable_reg_with_local_ops( getattr(seq, op)(*args) seq.to_abstract_repr() + def test_parametrized_fails_validation(self): + seq_ = Sequence(Register.square(1, prefix="q"), MockDevice) + vars = seq_.declare_variable("vars", dtype=int, size=2) + seq_.declare_channel("ryd", "rydberg_global") + seq_.delay(vars, "ryd") # vars has size 2, the build will fail + with pytest.raises( + AbstractReprError, + match=re.escape( + "The serialization of the parametrized sequence failed, " + "potentially due to an error that only appears at build " + "time. Check that no errors appear when building with " + "`Sequence.build()` or when providing the `defaults` to " + "`Sequence.to_abstract_repr()`." + ), + ): + seq_.to_abstract_repr() + @pytest.mark.parametrize("is_empty", [True, False]) def test_dmm_slm_mask(self, triangular_lattice, is_empty): mask = {"q0", "q2", "q4", "q5"} @@ -1965,3 +1982,14 @@ def test_legacy_device(self, device): ) seq = Sequence.from_abstract_repr(json.dumps(s)) assert seq.device == device + + def test_bad_type(self): + s = _get_serialized_seq() + with pytest.raises( + TypeError, + match=re.escape( + "The serialized sequence must be given as a string. " + f"Instead, got object of type {dict}." + ), + ): + Sequence.from_abstract_repr(s) diff --git a/tests/test_json.py b/tests/test_json.py index c8a4f16e2..661021fb 100644 --- a/tests/test_json.py +++ b/tests/test_json.py @@ -12,10 +12,12 @@ # See the License for the specific language governing permissions and # limitations under the License. import json +import re import numpy as np import pytest +import pulser from pulser import Register, Register3D, Sequence from pulser.devices import Chadoq2, MockDevice from pulser.json.coders import PulserDecoder, PulserEncoder @@ -136,7 +138,7 @@ def test_mappable_register(): assert seq.is_register_mappable() mapped_seq = seq.build(qubits={"q0": 2, "q1": 1}) assert not mapped_seq.is_register_mappable() - new_mapped_seq = Sequence.deserialize(mapped_seq.serialize()) + new_mapped_seq = Sequence._deserialize(mapped_seq._serialize()) assert not new_mapped_seq.is_register_mappable() @@ -154,8 +156,15 @@ def test_rare_cases(patch_plt_show): s = encode(wf()) s = encode(wf) + with pytest.raises( + TypeError, + match="The serialized sequence must be given as a string. " + f"Instead, got object of type {dict}.", + ): + wf_ = Sequence._deserialize(json.loads(s)) + with pytest.raises(ValueError, match="not encode a Sequence"): - wf_ = Sequence.deserialize(s) + wf_ = Sequence._deserialize(s) wf_ = decode(s) seq._variables["var"]._assign(-10) @@ -208,31 +217,43 @@ def test_sequence_module(): # Check that the sequence module is backwards compatible after refactoring seq = Sequence(Register.square(2), Chadoq2) - obj_dict = json.loads(seq.serialize()) + obj_dict = json.loads(seq._serialize()) assert obj_dict["__module__"] == "pulser.sequence" # Defensively check that the standard format runs - Sequence.deserialize(seq.serialize()) + Sequence._deserialize(seq._serialize()) # Use module being used in v0.7.0-0.7.2.0 obj_dict["__module__"] == "pulser.sequence.sequence" # Check that it also works s = json.dumps(obj_dict) - Sequence.deserialize(s) + Sequence._deserialize(s) + + +def test_type_error(): + s = Sequence(Register.square(1), MockDevice)._serialize() + with pytest.raises( + TypeError, + match=re.escape( + "The serialized sequence must be given as a string. " + f"Instead, got object of type {dict}." + ), + ): + Sequence._deserialize(json.loads(s)) -def test_deprecation(): +def test_deprecated_device_args(): seq = Sequence(Register.square(1), MockDevice) - seq_dict = json.loads(seq.serialize()) + seq_dict = json.loads(seq._serialize()) dev_dict = seq_dict["__kwargs__"]["device"] assert "_channels" not in dev_dict["__kwargs__"] dev_dict["__kwargs__"]["_channels"] = [] s = json.dumps(seq_dict) - new_seq = Sequence.deserialize(s) + new_seq = Sequence._deserialize(s) assert new_seq.device == MockDevice ids = dev_dict["__kwargs__"].pop("channel_ids") @@ -241,5 +262,22 @@ def test_deprecation(): assert seq_dict["__kwargs__"]["device"] == dev_dict s = json.dumps(seq_dict) - new_seq = Sequence.deserialize(s) + new_seq = Sequence._deserialize(s) assert new_seq.device == MockDevice + + +def test_deprecation_warning(): + msg = re.escape( + "`Sequence.serialize()` and `Sequence.deserialize()` have " + "been deprecated and will be removed in Pulser v1.0.0. " + "Use `Sequence.to_abstract_repr()` and " + "`Sequence.from_abstract_repr()` instead." + ) + seq = Sequence(Register.square(1), MockDevice) + with pytest.warns(DeprecationWarning, match=msg): + s = seq.serialize() + + with pytest.warns(DeprecationWarning, match=msg): + Sequence.deserialize(s) + + assert pulser.__version__ < "1.0", "Remove legacy serializer methods" diff --git a/tests/test_paramseq.py b/tests/test_paramseq.py index 58c7e4b4..e311426b 100644 --- a/tests/test_paramseq.py +++ b/tests/test_paramseq.py @@ -200,12 +200,12 @@ def test_build(): assert seq.current_phase_ref("q0") == 0.0 assert seq._measurement == "ground-rydberg" - s = sb.serialize() - sb_ = Sequence.deserialize(s) + s = sb._serialize() + sb_ = Sequence._deserialize(s) assert str(sb) == str(sb_) - s2 = sb_.serialize() - sb_2 = Sequence.deserialize(s2) + s2 = sb_._serialize() + sb_2 = Sequence._deserialize(s2) assert str(sb) == str(sb_2) diff --git a/tests/test_sequence.py b/tests/test_sequence.py index 3f560b49..7f48fb38 100644 --- a/tests/test_sequence.py +++ b/tests/test_sequence.py @@ -305,8 +305,8 @@ def test_magnetic_field(reg): with pytest.raises(ValueError, match="can only be set on an empty seq"): seq3.set_magnetic_field() - seq3_str = seq3.serialize() - seq3_ = Sequence.deserialize(seq3_str) + seq3_str = seq3._serialize() + seq3_ = Sequence._deserialize(seq3_str) assert seq3_._in_xy assert str(seq3) == str(seq3_) assert np.all(seq3_.magnetic_field == np.array((1.0, 0.0, 0.0))) @@ -1290,9 +1290,9 @@ def test_sequence(reg, device, patch_plt_show): seq.draw(draw_phase_area=True) seq.draw(draw_phase_curve=True) - s = seq.serialize() + s = seq._serialize() assert json.loads(s)["__version__"] == pulser.__version__ - seq_ = Sequence.deserialize(s) + seq_ = Sequence._deserialize(s) assert str(seq) == str(seq_) @@ -1409,8 +1409,8 @@ def test_slm_mask_in_xy(reg, patch_plt_show): seq_xy5.add(Pulse.ConstantPulse(200, var, 0, 0), "ch") assert seq_xy5.is_parametrized() seq_xy5.config_slm_mask(targets) - seq_xy5_str = seq_xy5.serialize() - seq_xy5_ = Sequence.deserialize(seq_xy5_str) + seq_xy5_str = seq_xy5._serialize() + seq_xy5_ = Sequence._deserialize(seq_xy5_str) assert str(seq_xy5) == str(seq_xy5_) # Check drawing method diff --git a/tutorials/advanced_features/Serialization.ipynb b/tutorials/advanced_features/Serialization.ipynb index 8548c57b..16ab34a1 100644 --- a/tutorials/advanced_features/Serialization.ipynb +++ b/tutorials/advanced_features/Serialization.ipynb @@ -1,182 +1,162 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# JSON Serialization" - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# JSON Serialization" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from pulser import Pulse, Sequence, Register\n", + "from pulser.waveforms import BlackmanWaveform\n", + "from pulser.devices import Chadoq2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Often times, it is useful to import/export a given `Sequence` between different locations. To enable this, the `Sequence` object supports **serialization** and **deserialization** into JSON-formatted strings. This will work for any given `Sequence`. Take for example, this sequence that creates the Bell state $|\\Phi^+\\rangle = \\frac{|00\\rangle + |11\\rangle}{\\sqrt{2}}$:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "qubits = {\"control\": (-2, 0), \"target\": (2, 0)}\n", + "reg = Register(qubits)\n", + "\n", + "seq = Sequence(reg, Chadoq2)\n", + "pulse_time = seq.declare_variable(\"pulse_time\", dtype=int)\n", + "seq.declare_channel(\"digital\", \"raman_local\", initial_target=\"control\")\n", + "seq.declare_channel(\"rydberg\", \"rydberg_local\", initial_target=\"control\")\n", + "\n", + "half_pi_wf = BlackmanWaveform(pulse_time, area=np.pi / 2)\n", + "\n", + "ry = Pulse.ConstantDetuning(amplitude=half_pi_wf, detuning=0, phase=-np.pi / 2)\n", + "ry_dag = Pulse.ConstantDetuning(\n", + " amplitude=half_pi_wf, detuning=0, phase=np.pi / 2\n", + ")\n", + "\n", + "seq.add(ry, \"digital\")\n", + "seq.target(\"target\", \"digital\")\n", + "seq.add(ry_dag, \"digital\")\n", + "\n", + "pi_wf = BlackmanWaveform(pulse_time, np.pi)\n", + "pi_pulse = Pulse.ConstantDetuning(pi_wf, 0, 0)\n", + "\n", + "max_val = Chadoq2.rabi_from_blockade(9)\n", + "two_pi_wf = BlackmanWaveform.from_max_val(max_val, 2 * np.pi)\n", + "two_pi_pulse = Pulse.ConstantDetuning(two_pi_wf, 0, 0)\n", + "\n", + "seq.align(\"digital\", \"rydberg\")\n", + "seq.add(pi_pulse, \"rydberg\")\n", + "seq.target(\"target\", \"rydberg\")\n", + "seq.add(two_pi_pulse, \"rydberg\")\n", + "seq.target(\"control\", \"rydberg\")\n", + "seq.add(pi_pulse, \"rydberg\")\n", + "\n", + "seq.align(\"digital\", \"rydberg\")\n", + "seq.add(ry, \"digital\")\n", + "seq.measure(\"digital\")\n", + "seq1 = seq.build(pulse_time=200)\n", + "seq1.draw()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Serialize" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To serialize, use `Sequence.to_abstract_repr()`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "s_readable = seq.to_abstract_repr(\n", + " json_dumps_options={\"indent\": 1},\n", + " seq_name=\"Sequence_with_defaults\",\n", + ")\n", + "print(s_readable[:350], \"...\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can note that it is possible to provide optional parameters of `json.dumps` such as `indent` via a dictionnary in the argument `json_dumps_options`.\n", + "\n", + "Providing optional arguments to `to_abstract_repr` defines default parameters in the JSON object (like the name of the sequence `seq_name`). This does not change the `Sequence` object in itself, as we'll see in the following part about deserialization." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Deserialize" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The generated strings contain all the necessary information for recreating the original sequence elsewhere (it could, for example, be saved to a file and then imported). To recover the sequence `seq` from `s_readable` (converted into JSON using `Sequence.to_abstract_repr()`), one should use `Sequence.from_abstract_repr()`. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "recovered_seq = Sequence.from_abstract_repr(s_readable)\n", + "recovered_seq.build(pulse_time=200).draw()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "from pulser import Pulse, Sequence, Register\n", - "from pulser.waveforms import BlackmanWaveform\n", - "from pulser.devices import Chadoq2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Often times, it is useful to import/export a given `Sequence` between different locations. To enable this, the `Sequence` object supports **serialization** and **deserialization** into JSON-formatted strings. This will work for any given `Sequence`. Take for example, this sequence that creates the Bell state $|\\Phi^+\\rangle = \\frac{|00\\rangle + |11\\rangle}{\\sqrt{2}}$:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "qubits = {\"control\": (-2, 0), \"target\": (2, 0)}\n", - "reg = Register(qubits)\n", - "\n", - "seq = Sequence(reg, Chadoq2)\n", - "pulse_time = seq.declare_variable(\"pulse_time\", dtype=int)\n", - "seq.declare_channel(\"digital\", \"raman_local\", initial_target=\"control\")\n", - "seq.declare_channel(\"rydberg\", \"rydberg_local\", initial_target=\"control\")\n", - "\n", - "half_pi_wf = BlackmanWaveform(pulse_time, area=np.pi / 2)\n", - "\n", - "ry = Pulse.ConstantDetuning(amplitude=half_pi_wf, detuning=0, phase=-np.pi / 2)\n", - "ry_dag = Pulse.ConstantDetuning(\n", - " amplitude=half_pi_wf, detuning=0, phase=np.pi / 2\n", - ")\n", - "\n", - "seq.add(ry, \"digital\")\n", - "seq.target(\"target\", \"digital\")\n", - "seq.add(ry_dag, \"digital\")\n", - "\n", - "pi_wf = BlackmanWaveform(pulse_time, np.pi)\n", - "pi_pulse = Pulse.ConstantDetuning(pi_wf, 0, 0)\n", - "\n", - "max_val = Chadoq2.rabi_from_blockade(8)\n", - "two_pi_wf = BlackmanWaveform.from_max_val(max_val, 2 * np.pi)\n", - "two_pi_pulse = Pulse.ConstantDetuning(two_pi_wf, 0, 0)\n", - "\n", - "seq.align(\"digital\", \"rydberg\")\n", - "seq.add(pi_pulse, \"rydberg\")\n", - "seq.target(\"target\", \"rydberg\")\n", - "seq.add(two_pi_pulse, \"rydberg\")\n", - "seq.target(\"control\", \"rydberg\")\n", - "seq.add(pi_pulse, \"rydberg\")\n", - "\n", - "seq.align(\"digital\", \"rydberg\")\n", - "seq.add(ry, \"digital\")\n", - "seq.measure(\"digital\")\n", - "seq1 = seq.build(pulse_time=200)\n", - "seq1.draw()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Serialize" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The former version of converting a `Sequence` into a JSON-formatted string was to use the `serialize` method. It is still supported, but a new method named `to_abstract_repr` should be favored to perform serialization. Let's compare both serialization methods:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "s = seq.serialize(indent=1)\n", - "print(s[:350], \"...\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "s_readable = seq.to_abstract_repr(\n", - " json_dumps_options={\"indent\": 1},\n", - " seq_name=\"Sequence_with_defaults\",\n", - ")\n", - "print(s_readable[:350], \"...\")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can note that it is possible to provide optional parameters of `json.dumps` such as `indent` to both methods. In `serialize`, they should be provided as optional arguments whereas for `to_abstract_repr` they should be defined as a dictionnary in the argument `json_dumps_options`.\n", - "\n", - "Providing optional arguments to `to_abstract_repr` defines default parameters in the JSON object (like the name of the sequence `seq_name`). This does not change the `Sequence` object in itself, as will be seen in the following part about deserialization." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Deserialize" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The generated strings contain all the necessary information for recreating the original sequence elsewhere (it could, for example, be saved to a file and then imported). In the case of strings obtained from `Sequence.serialize`, one could recover the sequence `seq` by calling `Sequence.deserialize`. This method is still supported. However, to recover the sequence `seq` from `s_readable` (converted into JSON using `Sequence.to_abstract_repr`), one should use `Sequence.from_abstract_repr`. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "recovered_seq = Sequence.deserialize(s)\n", - "recovered_seq.build(pulse_time=200).draw()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "recovered_seq_from_readable = Sequence.from_abstract_repr(s_readable)\n", - "recovered_seq_from_readable.build(pulse_time=200).draw()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.15" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 4 } From e0943d9451a197e46f4d1eb469eff5e1cd1caa4b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Henrique=20Silv=C3=A9rio?= Date: Wed, 27 Sep 2023 17:35:27 +0200 Subject: [PATCH 16/18] Override `optimal_detuning_off` on stored calls (#588) * Get rid of DeprecationWarnings * Override `optimal_detuning_off` on stored calls * Override `optimal_detuning_off` when ever`detuning_off` is known --- pulser-core/pulser/sequence/sequence.py | 34 +++++++++++++- tests/test_abstract_repr.py | 59 +++++++++++++++++++------ tests/test_sequence.py | 4 +- 3 files changed, 80 insertions(+), 17 deletions(-) diff --git a/pulser-core/pulser/sequence/sequence.py b/pulser-core/pulser/sequence/sequence.py index 81eae094..504b77b8 100644 --- a/pulser-core/pulser/sequence/sequence.py +++ b/pulser-core/pulser/sequence/sequence.py @@ -648,7 +648,13 @@ def _config_detuning_map( def switch_device( self, new_device: DeviceType, strict: bool = False ) -> Sequence: - """Switch the device of a sequence. + """Replicate the sequence with a different device. + + This method is designed to replicate the sequence with as few changes + to the original contents as possible. + If the `strict` option is chosen, the device switch will fail whenever + it cannot guarantee that the new sequence's contents will not be + modified in the process. Args: new_device: The target device instance. @@ -1002,7 +1008,7 @@ def declare_variable( self._variables[name] = var return var - @seq_decorators.store + @seq_decorators.verify_parametrization @seq_decorators.block_if_measured def enable_eom_mode( self, @@ -1057,6 +1063,7 @@ def enable_eom_mode( on_pulse = Pulse.ConstantPulse( channel_obj.min_duration, amp_on, detuning_on, 0.0 ) + stored_opt_detuning_off = optimal_detuning_off if not isinstance(on_pulse, Parametrized): channel_obj.validate_pulse(on_pulse) amp_on = cast(float, amp_on) @@ -1070,6 +1077,10 @@ def enable_eom_mode( channel_obj.min_duration, 0.0, detuning_off, 0.0 ) channel_obj.validate_pulse(off_pulse) + # Update optimal_detuning_off to match the chosen detuning_off + # This minimizes the changes to the sequence when the device + # is switched + stored_opt_detuning_off = detuning_off if not self.is_parametrized(): phase_drift_params = _PhaseDriftParams( @@ -1085,6 +1096,25 @@ def enable_eom_mode( -drift, *buffer_slot.targets, basis=channel_obj.basis ) + # Manually store the call to "enable_eom_mode" so that the updated + # 'optimal_detuning_off' is stored + call_container = ( + self._to_build_calls if self.is_parametrized() else self._calls + ) + call_container.append( + _Call( + "enable_eom_mode", + (), + dict( + channel=channel, + amp_on=amp_on, + detuning_on=detuning_on, + optimal_detuning_off=stored_opt_detuning_off, + correct_phase_drift=correct_phase_drift, + ), + ) + ) + @seq_decorators.store @seq_decorators.block_if_measured def disable_eom_mode( diff --git a/tests/test_abstract_repr.py b/tests/test_abstract_repr.py index cf4e5cee..c030ec51 100644 --- a/tests/test_abstract_repr.py +++ b/tests/test_abstract_repr.py @@ -1572,14 +1572,24 @@ def test_deserialize_parametrized_pulse(self, op, pulse_cls): assert pulse.kwargs["detuning"] == 1 @pytest.mark.parametrize("correct_phase_drift", (False, True, None)) - def test_deserialize_eom_ops(self, correct_phase_drift): + @pytest.mark.parametrize("var_detuning_on", [False, True]) + def test_deserialize_eom_ops(self, correct_phase_drift, var_detuning_on): + detuning_on = ( + { + "expression": "index", + "lhs": {"variable": "detuning_on"}, + "rhs": 0, + } + if var_detuning_on + else 0.0 + ) s = _get_serialized_seq( operations=[ { "op": "enable_eom_mode", "channel": "global", "amp_on": 3.0, - "detuning_on": 0.0, + "detuning_on": detuning_on, "optimal_detuning_off": -1.0, "correct_phase_drift": correct_phase_drift, }, @@ -1602,29 +1612,52 @@ def test_deserialize_eom_ops(self, correct_phase_drift): "correct_phase_drift": correct_phase_drift, }, ], - variables={"duration": {"type": "int", "value": [100]}}, + variables={ + "duration": {"type": "int", "value": [100]}, + "detuning_on": {"type": "int", "value": [0.0]}, + }, device=json.loads(IroiseMVP.to_abstract_repr()), channels={"global": "rydberg_global"}, ) if correct_phase_drift is None: for op in s["operations"]: del op["correct_phase_drift"] - _check_roundtrip(s) + seq = Sequence.from_abstract_repr(json.dumps(s)) - # init + declare_channel + enable_eom_mode - assert len(seq._calls) == 3 - # add_eom_pulse + disable_eom - assert len(seq._to_build_calls) == 2 + # init + declare_channel + enable_eom_mode (if not var_detuning_on) + assert len(seq._calls) == 3 - var_detuning_on + # add_eom_pulse + disable_eom + enable_eom_mode (if var_detuning_on) + assert len(seq._to_build_calls) == 2 + var_detuning_on + + if var_detuning_on: + enable_eom_call = seq._to_build_calls[0] + optimal_det_off = -1.0 + else: + enable_eom_call = seq._calls[-1] + eom_conf = seq.declared_channels["global"].eom_config + optimal_det_off = eom_conf.calculate_detuning_off( + 3.0, detuning_on, -1.0 + ) + + # Roundtrip will only match if the optimal detuning off matches + # detuning_off from the start + mod_s = deepcopy(s) + mod_s["operations"][0]["optimal_detuning_off"] = optimal_det_off + _check_roundtrip(mod_s) - enable_eom_call = seq._calls[-1] assert enable_eom_call.name == "enable_eom_mode" - assert enable_eom_call.kwargs == { + enable_eom_kwargs = enable_eom_call.kwargs.copy() + detuning_on_kwarg = enable_eom_kwargs.pop("detuning_on") + assert enable_eom_kwargs == { "channel": "global", "amp_on": 3.0, - "detuning_on": 0.0, - "optimal_detuning_off": -1.0, + "optimal_detuning_off": optimal_det_off, "correct_phase_drift": bool(correct_phase_drift), } + if var_detuning_on: + assert isinstance(detuning_on_kwarg, VariableItem) + else: + assert detuning_on_kwarg == detuning_on disable_eom_call = seq._to_build_calls[-1] assert disable_eom_call.name == "disable_eom_mode" @@ -1633,7 +1666,7 @@ def test_deserialize_eom_ops(self, correct_phase_drift): "correct_phase_drift": bool(correct_phase_drift), } - eom_pulse_call = seq._to_build_calls[0] + eom_pulse_call = seq._to_build_calls[var_detuning_on] assert eom_pulse_call.name == "add_eom_pulse" assert eom_pulse_call.kwargs["channel"] == "global" assert isinstance(eom_pulse_call.kwargs["duration"], VariableItem) diff --git a/tests/test_sequence.py b/tests/test_sequence.py index 7f48fb38..ec456410 100644 --- a/tests/test_sequence.py +++ b/tests/test_sequence.py @@ -1558,8 +1558,8 @@ def test_slm_mask_in_ising( seq5.add(Pulse.ConstantPulse(200, var, 0, 0), "ch") assert seq5.is_parametrized() seq5.config_slm_mask(targets) - seq5_str = seq5.serialize() - seq5_ = Sequence.deserialize(seq5_str) + seq5_str = seq5._serialize() + seq5_ = Sequence._deserialize(seq5_str) assert str(seq5) == str(seq5_) From b51a23df16bb86f10348ccd35fc95abf6145d77c Mon Sep 17 00:00:00 2001 From: Antoine Cornillot <61453516+a-corni@users.noreply.github.com> Date: Wed, 27 Sep 2023 18:03:51 +0200 Subject: [PATCH 17/18] Add DMM, methods of RegisterLayout inherited from Traps, Result (#587) * Add DMM, Inherited meth in RegisterLayout, Result * Add inheritance * Add DetuningMap * Fxing syntax * Fix path for DetuningMap * Add QutipResult, fixing typo, generate dmm class * Add QutipResult to rtd --- docs/source/apidoc/core.rst | 22 ++++++++++++++++++- docs/source/apidoc/simulation.rst | 13 ++++++++--- .../pulser_simulation/qutip_result.py | 3 +++ 3 files changed, 34 insertions(+), 4 deletions(-) diff --git a/docs/source/apidoc/core.rst b/docs/source/apidoc/core.rst index 3b39d908..aa25884e 100644 --- a/docs/source/apidoc/core.rst +++ b/docs/source/apidoc/core.rst @@ -30,7 +30,7 @@ The register classes allow for the creation of arbitrary registers. Register layout ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A ``RegisterLayout`` is used to define a register from a set of traps. It is -intended to be given to the user by the hardware provided as a way of showing +intended to be given to the user by the hardware provider as a way of showing which layouts are already available on a given device. In turn, the user can create a ``Register`` by selecting the traps on which to place atoms, or even a ``MappableRegister``, which allows for the creation of sequences whose @@ -38,6 +38,7 @@ register can be defined at build time. .. autoclass:: pulser.register.register_layout.RegisterLayout :members: + :inherited-members: .. autoclass:: pulser.register.mappable_reg.MappableRegister :members: @@ -51,6 +52,17 @@ Special cases :members: :show-inheritance: +DetuningMap +------------------- + +A ``DetuningMap`` is associated to a ``DMM`` in a ``Sequence``. It links a set +of weights to a set of trap coordinates. It is intended to be defined by the user +from a ``RegisterLayout``, a ``Register`` or a ``MappableRegister`` using +``define_detuning_map``. + +.. autoclass:: pulser.register.weight_maps.DetuningMap + :members: + :inherited-members: Pulse ------------------- @@ -114,6 +126,9 @@ Available Channels :members: :show-inheritance: +.. autoclass:: pulser.channels.dmm.DMM + :members: + :show-inheritance: EOM Mode Configuration ^^^^^^^^^^^^^^^^^^^^^^^^ @@ -129,3 +144,8 @@ Sampler .. automodule:: pulser.sampler.samples :members: +Result +------------------ +.. automodule:: pulser.result + :members: + :show-inheritance: \ No newline at end of file diff --git a/docs/source/apidoc/simulation.rst b/docs/source/apidoc/simulation.rst index 46c49f87..74d23392 100644 --- a/docs/source/apidoc/simulation.rst +++ b/docs/source/apidoc/simulation.rst @@ -29,13 +29,20 @@ Simulation Results Depending on the types of noise involved in a simulation, the results are returned as an instance of :class:`SimulationResults`, namely :class:`CoherentResults` -(when the results can still be represented as a state vector or a density matrix, before being measured) -or :class:`NoisyResults` (when they can only be represented as a probability -distribution over the basis states). +(when each result can still be represented as a :class:`QutipResult` i.e. a state vector +or a density matrix, before being measured) or :class:`NoisyResults` (when each of them can only +be represented as :class:`SampledResult` i.e. a probability distribution over the basis states). Both classes feature methods for processing and displaying the results stored within them. +QutipResult +^^^^^^^^^^^^^^^^ + +.. autoclass:: pulser_simulation.qutip_result.QutipResult + :members: + :inherited-members: + CoherentResults ^^^^^^^^^^^^^^^^ diff --git a/pulser-simulation/pulser_simulation/qutip_result.py b/pulser-simulation/pulser_simulation/qutip_result.py index 978bdf33..72ec4678 100644 --- a/pulser-simulation/pulser_simulation/qutip_result.py +++ b/pulser-simulation/pulser_simulation/qutip_result.py @@ -20,6 +20,7 @@ import numpy as np import qutip +from pulser.register import QubitId from pulser.result import Result @@ -37,6 +38,8 @@ class QutipResult(Result): same as the state's basis. """ + atom_order: tuple[QubitId, ...] + meas_basis: str state: qutip.Qobj matching_meas_basis: bool From 5090ec6f995dccb304becaed711dc3bd9d5b92cb Mon Sep 17 00:00:00 2001 From: HGSilveri Date: Wed, 27 Sep 2023 18:05:40 +0200 Subject: [PATCH 18/18] Bump version to v0.15.0 --- VERSION.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION.txt b/VERSION.txt index 9255737a..a5510516 100644 --- a/VERSION.txt +++ b/VERSION.txt @@ -1 +1 @@ -0.15dev1 +0.15.0