Delete summing constraint in DetuningMap

pulser-core/pulser/register/_reg_drawer.py

@@ -88,10 +88,7 @@ def _draw_2D(
         ):
             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
-            }
+            dmm_qubits = {masked_qubit: 1.0 for masked_qubit in masked_qubits}
 
         if dmm_qubits:
             dmm_pos = []

pulser-core/pulser/register/base_register.py

@@ -214,8 +214,7 @@ def define_detuning_map(
 
         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).
+                and detuning weights (between 0 and 1).
             slug: An optional identifier for the detuning map.
 
         Returns:

pulser-core/pulser/register/mappable_reg.py

@@ -132,8 +132,7 @@ def define_detuning_map(
 
         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).
+                and detuning weights (between 0 and 1).
             slug: An optional identifier for the detuning map.
 
         Returns:

pulser-core/pulser/register/register_layout.py

@@ -108,8 +108,7 @@ def define_detuning_map(
 
         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).
+                and detuning weights (between 0 and 1).
             slug: An optional identifier for the detuning map.
 
         Returns:

pulser-core/pulser/register/weight_maps.py

@@ -37,11 +37,9 @@
 class WeightMap(Traps, 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.
+        weights: A list of weights (between 0 and 1) to associate to the traps.
     """
 
     weights: tuple[float, ...]
@@ -56,10 +54,10 @@ def __init__(
         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(weights) >= 0):
-            raise ValueError("All weights must be non-negative.")
-        if not np.isclose(sum(weights), 1.0, atol=1e-16):
-            raise ValueError("The sum of the weights should be 1.")
+        if not (
+            np.all(np.array(weights) >= 0) and np.all(np.array(weights) <= 1)
+        ):
+            raise ValueError("All weights must be between 0 and 1.")
         object.__setattr__(self, "weights", tuple(weights))
 
     @property
@@ -173,10 +171,11 @@ def _to_abstract_repr(self) -> dict[str, Any]:
 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.
+    A DetuningMap associates a detuning weight (a value between 0 and 1)
+    to the coordinates of a trap.
 
     Args:
         trap_coordinates: An array containing the coordinates of the traps.
-        weights: A list of detuning weights to associate to the traps.
+        weights: A list of detuning weights (between 0 and 1) to associate
+            to the traps.
     """

pulser-core/pulser/sequence/sequence.py

@@ -496,10 +496,9 @@ def set_magnetic_field(
         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)
+                qubit: (1.0 if qubit in targets else 0)
                 for qubit in self.register.qubit_ids
             }
         )
@@ -538,7 +537,7 @@ def config_slm_mask(
         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
+        the detuning of each masked qubit is 1.0. 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
@@ -598,8 +597,8 @@ def config_detuning_map(
             ``MockDevice`` DMM can be repeatedly declared if needed.
 
         Args:
-            detuning_map: A DetuningMap defining atoms to act on and bottom
-                detuning to modulate.
+            detuning_map: A DetuningMap defining the amont of detuning each
+                atom receives.
             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.

tests/test_abstract_repr.py

@@ -859,13 +859,13 @@ def test_parametrized_fails_validation(self):
     @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}
+        det_map = {"q0": 1.0, "q1": 0.5, "q2": 0.5, "q3": 0.0}
         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"
+                reg.define_detuning_map(det_map, "det_map"), "dmm_0"
             )
             seq.add_dmm_detuning(ConstantWaveform(100, -10), "dmm_0_1")
             seq.declare_channel("rydberg_global", "rydberg_global")
@@ -900,7 +900,7 @@ def test_dmm_slm_mask(self, triangular_lattice, is_empty):
                     "x": reg._coords[i][0],
                     "y": reg._coords[i][1],
                 }
-                for i, weight in enumerate(list(dmm.values()))
+                for i, weight in enumerate(list(det_map.values()))
             ]
             assert (
                 abstract["operations"][1]["detuning_map"]["slug"] == "det_map"
@@ -1121,8 +1121,8 @@ def test_deserialize_seq_with_slm_mask_xy(self):
 
     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": 1.0, "x": -2.0, "y": 9.0},
+            {"weight": 1.0, "x": 0.0, "y": 2.0},
             {"weight": 0, "x": 12.0, "y": 0.0},
         ]
         op = [

tests/test_dmm.py

@@ -43,7 +43,7 @@ def map_reg(self, layout: RegisterLayout) -> MappableRegister:
 
     @pytest.fixture
     def det_dict(self) -> dict[int, float]:
-        return {0: 0.7, 1: 0.3, 2: 0}
+        return {0: 1.0, 1: 0.3, 2: 0}
 
     @pytest.fixture
     def det_map(
@@ -53,7 +53,7 @@ def det_map(
 
     @pytest.fixture
     def slm_dict(self) -> dict[int, float]:
-        return {0: 1 / 3, 1: 1 / 3, 2: 1 / 3}
+        return {0: 1.0, 1: 1.0, 2: 1.0}
 
     @pytest.fixture
     def slm_map(
@@ -89,7 +89,7 @@ def test_define_detuning_map(
 
     def test_qubit_weight_map(self, register):
         # Purposefully unsorted
-        qid_weight_map = {1: 0.5, 0: 0.1, 3: 0.4}
+        qid_weight_map = {1: 1.0, 0: 0.1, 3: 0.4}
         sorted_qids = sorted(qid_weight_map)
         det_map = register.define_detuning_map(qid_weight_map)
         qubits = register.qubits
@@ -158,16 +158,11 @@ def test_detuning_map_bad_init(
             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."
+                ValueError, match="All weights must be between 0 and 1."
             ):
                 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(
         self,

tests/test_sequence.py

@@ -52,7 +52,7 @@ def reg():
 @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)}
+        {"q" + str(i): (1.0 if i in [0, 1, 3, 4] else 0) for i in range(10)}
     )
 
 
@@ -496,7 +496,7 @@ def init_seq(
     if config_det_map:
         det_map = reg.define_detuning_map(
             {
-                "q" + str(i): (1 / 4 if i in [0, 1, 3, 4] else 0)
+                "q" + str(i): (1.0 if i in [0, 1, 3, 4] else 0)
                 for i in range(10)
             }
         )
@@ -865,7 +865,7 @@ def test_switch_device_up(
                     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)
+                        == (-10.0 if trap_id in mod_trap_ids else 0)
                     )
                 else:
                     # first pulse is covered by SLM Mask
@@ -1339,8 +1339,8 @@ def test_config_slm_mask(qubit_ids, device, det_map):
         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
+    assert seq._schedule["dmm_0"].detuning_map.weights[0] == 1.0
+    assert seq._schedule["dmm_0"].detuning_map.weights[2] == 1.0
 
     with pytest.raises(ValueError, match="configured only once"):
         seq.config_slm_mask(targets)
@@ -1572,7 +1572,7 @@ def test_draw_register_det_maps(reg, ch_name, patch_plt_show):
         [(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}
+        {0: 0, 1: 0, 2: 0, 3: 1.0, 4: 1.0}
     )
     reg = reg_layout.define_register(0, 1, 2, qubit_ids=["q0", "q1", "q2"])
     targets = ["q0", "q2"]

tests/test_simulation.py

@@ -1122,9 +1122,7 @@ def test_mask_local_channel():
         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])
-                ),
+                np.concatenate((-10 * pulse.amplitude.samples, [0])),
             )
         else:
             assert np.all(

tutorials/advanced_features/Local addressability with DMM.ipynb

@@ -40,7 +40,7 @@
    "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",
+    "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 the amount of detuning applied by the `DMM` each site receives.\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."
    ]
@@ -56,7 +56,7 @@
    "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."
+    "A `DetuningMap` associates a set of locations with a set of weights. The locations are the trap coordinates to address and the weights $(\\epsilon_i)_i$ have to be between 0 and 1."
    ]
   },
   {
@@ -66,8 +66,8 @@
    "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"
+    "weights_1 = [1.0, 0.5, 0.5, 0]  # between 0 and 1\n",
+    "weights_2 = [1.0, 1.0, 1.0, 0]  # between 0 and 1"
    ]
   },
   {

tutorials/advanced_features/State Preparation with the SLM Mask.ipynb

@@ -269,9 +269,9 @@
    "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",
+    "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 all the applied detuning to 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 $1/2 = 0.5$:"
+    "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 $1$:"
    ]
   },
   {