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Fix act-on specialization for all the Clifford simulators (quantumlib…
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…#4748)

Fixes quantumlib#4639, ref [tinyurl.com/clifford-simulators-refactor](https://tinyurl.com/clifford-simulators-refactor)

This change makes the Clifford simulators more consistent with other simulators. Rather than the gate having all the logic of how to update the simulator state, which seemed out-of-place and limited the ability to reuse in any new kinds of Clifford simulators, this PR moves all the logic to the simulators themselves.

It also creates an ABC for Clifford simulator states, allowing reuse of the evolution logic in the base class, such that the subclasses just have to implement the specific gate applicators.

Note I *tried* doing this via a new Clifford protocol as well ([link](https://github.com/quantumlib/Cirq/compare/master...daxfohl:clifford3?expand=1)) as we originally discussed, and it works but I didn't like the result. The protocol ended up just duplicating all the information of the gate, in a weird structure, and felt like an extra, unnecessary, hacky wrapper around just using the gate itself. So I prefer the approach in this PR that just uses the gate instances directly, though I'm open to suggestion.

@tanujkhattar @viathor (cc @ybc1991)
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@daxfohl @rht
daxfohl authored and rht committed May 1, 2023
1 parent 02d9b00 commit b5af9da
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1 change: 1 addition & 0 deletions cirq-core/cirq/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -414,6 +414,7 @@
ActOnCliffordTableauArgs,
ActOnDensityMatrixArgs,
ActOnStabilizerCHFormArgs,
ActOnStabilizerArgs,
ActOnStateVectorArgs,
StabilizerStateChForm,
CIRCUIT_LIKE,
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10 changes: 0 additions & 10 deletions cirq-core/cirq/ops/common_channels.py
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Original file line number Diff line number Diff line change
Expand Up @@ -316,16 +316,6 @@ def __str__(self) -> str:
return f"depolarize(p={self._p})"
return f"depolarize(p={self._p},n_qubits={self._n_qubits})"

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']) -> bool:
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
if args.prng.random() < self._p:
gate = args.prng.choice([pauli_gates.X, pauli_gates.Y, pauli_gates.Z])
protocols.act_on(gate, args, qubits)
return True
return NotImplemented

def _circuit_diagram_info_(self, args: 'protocols.CircuitDiagramInfoArgs') -> Tuple[str, ...]:
result: Tuple[str, ...]
if args.precision is not None:
Expand Down
247 changes: 0 additions & 247 deletions cirq-core/cirq/ops/common_gates.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,12 +62,6 @@
"""


def _act_with_gates(args, qubits, *gates: 'cirq.SupportsActOnQubits') -> None:
"""Act on the given args with the given gates in order."""
for gate in gates:
assert gate._act_on_(args, qubits)


def _pi(rads):
return sympy.pi if protocols.is_parameterized(rads) else np.pi

Expand Down Expand Up @@ -108,35 +102,6 @@ def _apply_unitary_(self, args: 'protocols.ApplyUnitaryArgs') -> Optional[np.nda
args.available_buffer *= p
return args.available_buffer

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']):
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
tableau = args.tableau
q = args.qubit_map[qubits[0]]
effective_exponent = self._exponent % 2
if effective_exponent == 0.5:
tableau.xs[:, q] ^= tableau.zs[:, q]
tableau.rs[:] ^= tableau.xs[:, q] & tableau.zs[:, q]
elif effective_exponent == 1:
tableau.rs[:] ^= tableau.zs[:, q]
elif effective_exponent == 1.5:
tableau.rs[:] ^= tableau.xs[:, q] & tableau.zs[:, q]
tableau.xs[:, q] ^= tableau.zs[:, q]
return True

if isinstance(args, clifford.ActOnStabilizerCHFormArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
_act_with_gates(args, qubits, H, ZPowGate(exponent=self._exponent), H)
# Adjust the global phase based on the global_shift parameter.
args.state.omega *= np.exp(1j * np.pi * self.global_shift * self.exponent)
return True

return NotImplemented

def in_su2(self) -> 'Rx':
"""Returns an equal-up-global-phase gate from the group SU2."""
return Rx(rads=self._exponent * _pi(self._exponent))
Expand Down Expand Up @@ -362,51 +327,6 @@ def _apply_unitary_(self, args: 'protocols.ApplyUnitaryArgs') -> Optional[np.nda
args.available_buffer *= p
return args.available_buffer

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']):
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
tableau = args.tableau
q = args.qubit_map[qubits[0]]
effective_exponent = self._exponent % 2
if effective_exponent == 0.5:
tableau.rs[:] ^= tableau.xs[:, q] & (~tableau.zs[:, q])
(tableau.xs[:, q], tableau.zs[:, q]) = (
tableau.zs[:, q].copy(),
tableau.xs[:, q].copy(),
)
elif effective_exponent == 1:
tableau.rs[:] ^= tableau.xs[:, q] ^ tableau.zs[:, q]
elif effective_exponent == 1.5:
tableau.rs[:] ^= ~(tableau.xs[:, q]) & tableau.zs[:, q]
(tableau.xs[:, q], tableau.zs[:, q]) = (
tableau.zs[:, q].copy(),
tableau.xs[:, q].copy(),
)
return True

if isinstance(args, clifford.ActOnStabilizerCHFormArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
effective_exponent = self._exponent % 2
state = args.state
Z = ZPowGate()
if effective_exponent == 0.5:
_act_with_gates(args, qubits, Z, H)
state.omega *= (1 + 1j) / (2 ** 0.5)
elif effective_exponent == 1:
_act_with_gates(args, qubits, Z, H, Z, H)
state.omega *= 1j
elif effective_exponent == 1.5:
_act_with_gates(args, qubits, H, Z)
state.omega *= (1 - 1j) / (2 ** 0.5)
# Adjust the global phase based on the global_shift parameter.
args.state.omega *= np.exp(1j * np.pi * self.global_shift * self.exponent)
return True
return NotImplemented

def in_su2(self) -> 'Ry':
"""Returns an equal-up-global-phase gate from the group SU2."""
return Ry(rads=self._exponent * _pi(self._exponent))
Expand Down Expand Up @@ -580,42 +500,6 @@ def _apply_unitary_(self, args: 'protocols.ApplyUnitaryArgs') -> Optional[np.nda
args.target_tensor *= p
return args.target_tensor

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']):
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
tableau = args.tableau
q = args.qubit_map[qubits[0]]
effective_exponent = self._exponent % 2
if effective_exponent == 0.5:
tableau.rs[:] ^= tableau.xs[:, q] & tableau.zs[:, q]
tableau.zs[:, q] ^= tableau.xs[:, q]
elif effective_exponent == 1:
tableau.rs[:] ^= tableau.xs[:, q]
elif effective_exponent == 1.5:
tableau.rs[:] ^= tableau.xs[:, q] & (~tableau.zs[:, q])
tableau.zs[:, q] ^= tableau.xs[:, q]
return True

if isinstance(args, clifford.ActOnStabilizerCHFormArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
q = args.qubit_map[qubits[0]]
effective_exponent = self._exponent % 2
state = args.state
for _ in range(int(effective_exponent * 2)):
# Prescription for S left multiplication.
# Reference: https://arxiv.org/abs/1808.00128 Proposition 4 end
state.M[q, :] ^= state.G[q, :]
state.gamma[q] = (state.gamma[q] - 1) % 4
# Adjust the global phase based on the global_shift parameter.
args.state.omega *= np.exp(1j * np.pi * self.global_shift * self.exponent)
return True

return NotImplemented

def _decompose_into_clifford_with_qubits_(self, qubits):
from cirq.ops.clifford_gate import SingleQubitCliffordGate

Expand Down Expand Up @@ -899,49 +783,6 @@ def _apply_unitary_(self, args: 'protocols.ApplyUnitaryArgs') -> Optional[np.nda
args.target_tensor *= np.sqrt(2) * p
return args.target_tensor

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']):
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
tableau = args.tableau
q = args.qubit_map[qubits[0]]
if self._exponent % 2 == 1:
(tableau.xs[:, q], tableau.zs[:, q]) = (
tableau.zs[:, q].copy(),
tableau.xs[:, q].copy(),
)
tableau.rs[:] ^= tableau.xs[:, q] & tableau.zs[:, q]
return True

if isinstance(args, clifford.ActOnStabilizerCHFormArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
q = args.qubit_map[qubits[0]]
state = args.state
if self._exponent % 2 == 1:
# Prescription for H left multiplication
# Reference: https://arxiv.org/abs/1808.00128
# Equations 48, 49 and Proposition 4
t = state.s ^ (state.G[q, :] & state.v)
u = state.s ^ (state.F[q, :] & (~state.v)) ^ (state.M[q, :] & state.v)

alpha = sum(state.G[q, :] & (~state.v) & state.s) % 2
beta = sum(state.M[q, :] & (~state.v) & state.s)
beta += sum(state.F[q, :] & state.v & state.M[q, :])
beta += sum(state.F[q, :] & state.v & state.s)
beta %= 2

delta = (state.gamma[q] + 2 * (alpha + beta)) % 4

state.update_sum(t, u, delta=delta, alpha=alpha)
# Adjust the global phase based on the global_shift parameter.
args.state.omega *= np.exp(1j * np.pi * self.global_shift * self.exponent)
return True

return NotImplemented

def _decompose_(self, qubits):
q = qubits[0]

Expand Down Expand Up @@ -1063,52 +904,6 @@ def _apply_unitary_(
args.target_tensor *= p
return args.target_tensor

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']):
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
tableau = args.tableau
q1 = args.qubit_map[qubits[0]]
q2 = args.qubit_map[qubits[1]]
if self._exponent % 2 == 1:
(tableau.xs[:, q2], tableau.zs[:, q2]) = (
tableau.zs[:, q2].copy(),
tableau.xs[:, q2].copy(),
)
tableau.rs[:] ^= tableau.xs[:, q2] & tableau.zs[:, q2]
tableau.rs[:] ^= (
tableau.xs[:, q1]
& tableau.zs[:, q2]
& (~(tableau.xs[:, q2] ^ tableau.zs[:, q1]))
)
tableau.xs[:, q2] ^= tableau.xs[:, q1]
tableau.zs[:, q1] ^= tableau.zs[:, q2]
(tableau.xs[:, q2], tableau.zs[:, q2]) = (
tableau.zs[:, q2].copy(),
tableau.xs[:, q2].copy(),
)
tableau.rs[:] ^= tableau.xs[:, q2] & tableau.zs[:, q2]
return True

if isinstance(args, clifford.ActOnStabilizerCHFormArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
q1 = args.qubit_map[qubits[0]]
q2 = args.qubit_map[qubits[1]]
state = args.state
if self._exponent % 2 == 1:
# Prescription for CZ left multiplication.
# Reference: https://arxiv.org/abs/1808.00128 Proposition 4 end
state.M[q1, :] ^= state.G[q2, :]
state.M[q2, :] ^= state.G[q1, :]
# Adjust the global phase based on the global_shift parameter.
args.state.omega *= np.exp(1j * np.pi * self.global_shift * self.exponent)
return True

return NotImplemented

def _pauli_expansion_(self) -> value.LinearDict[str]:
if protocols.is_parameterized(self):
return NotImplemented
Expand Down Expand Up @@ -1291,48 +1086,6 @@ def _apply_unitary_(self, args: 'protocols.ApplyUnitaryArgs') -> Optional[np.nda
args.target_tensor *= p
return args.target_tensor

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']):
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
tableau = args.tableau
q1 = args.qubit_map[qubits[0]]
q2 = args.qubit_map[qubits[1]]
if self._exponent % 2 == 1:
tableau.rs[:] ^= (
tableau.xs[:, q1]
& tableau.zs[:, q2]
& (~(tableau.xs[:, q2] ^ tableau.zs[:, q1]))
)
tableau.xs[:, q2] ^= tableau.xs[:, q1]
tableau.zs[:, q1] ^= tableau.zs[:, q2]
return True

if isinstance(args, clifford.ActOnStabilizerCHFormArgs):
if not protocols.has_stabilizer_effect(self):
return NotImplemented
q1 = args.qubit_map[qubits[0]]
q2 = args.qubit_map[qubits[1]]
state = args.state
if self._exponent % 2 == 1:
# Prescription for CX left multiplication.
# Reference: https://arxiv.org/abs/1808.00128 Proposition 4 end
state.gamma[q1] = (
state.gamma[q1]
+ state.gamma[q2]
+ 2 * (sum(state.M[q1, :] & state.F[q2, :]) % 2)
) % 4
state.G[q2, :] ^= state.G[q1, :]
state.F[q1, :] ^= state.F[q2, :]
state.M[q1, :] ^= state.M[q2, :]
# Adjust the global phase based on the global_shift parameter.
args.state.omega *= np.exp(1j * np.pi * self.global_shift * self.exponent)
return True

return NotImplemented

def _pauli_expansion_(self) -> value.LinearDict[str]:
if protocols.is_parameterized(self):
return NotImplemented
Expand Down
14 changes: 0 additions & 14 deletions cirq-core/cirq/ops/global_phase_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,20 +87,6 @@ def _apply_unitary_(self, args) -> np.ndarray:
def _has_stabilizer_effect_(self) -> bool:
return True

def _act_on_(self, args: 'cirq.ActOnArgs', qubits):
from cirq.sim import clifford

if isinstance(args, clifford.ActOnCliffordTableauArgs):
# Since CliffordTableau does not keep track of the global phase,
# it's safe to just ignore it here.
return True

if isinstance(args, clifford.ActOnStabilizerCHFormArgs):
args.state.omega *= self.coefficient
return True

return NotImplemented

def __str__(self) -> str:
return str(self.coefficient)

Expand Down
15 changes: 0 additions & 15 deletions cirq-core/cirq/ops/random_gate_channel.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,6 @@
cast,
SupportsFloat,
Optional,
Sequence,
)

import numpy as np
Expand Down Expand Up @@ -123,20 +122,6 @@ def _trace_distance_bound_(self) -> float:
result *= float(self.probability)
return result

def _act_on_(self, args: 'cirq.ActOnArgs', qubits: Sequence['cirq.Qid']):
from cirq.sim import clifford

if self._is_parameterized_():
return NotImplemented
if isinstance(args, clifford.ActOnCliffordTableauArgs):
if args.prng.random() < self.probability:
# Note: because we're doing this probabilistically, it's not
# safe to fallback to other strategies if act_on fails. Those
# strategies could double-count the probability.
protocols.act_on(self.sub_gate, args, qubits)
return True
return NotImplemented

def _json_dict_(self) -> Dict[str, Any]:
return protocols.obj_to_dict_helper(self, ['sub_gate', 'probability'])

Expand Down
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