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Add noise amplification transformer #6665

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merged 16 commits into from
Jul 12, 2024
112 changes: 112 additions & 0 deletions cirq-core/cirq/transformers/noise_adding.py
Original file line number Diff line number Diff line change
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# Copyright 2024 The Cirq Developers
#
# 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
#
# https://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 collections.abc import Mapping

from cirq import ops, circuits
from cirq.transformers import transformer_api
import numpy as np


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def _gate_in_moment(gate: ops.Gate, moment: circuits.Moment) -> bool:
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nit for performance:

return any(op.gate == gate for op in moment)

"""Check whether `gate` is in `moment`."""
return any(op.gate == gate for op in moment)


@transformer_api.transformer
class DepolerizingNoiseTransformer:
"""Add local depolarizing noise after two-qubit gates in a specified circuit. More specifically,
with probability p, append a random non-identity two-qubit Pauli operator after each specified
two-qubit gate.

Attrs:
p: The probability with which to add noise.
target_gate: Add depolarizing nose after this type of gate
"""

def __init__(
self, p: float | Mapping[tuple[ops.Qid, ops.Qid], float], target_gate: ops.Gate = ops.CZ
):
"""Initialize the depolarizing noise transformer with some depolarizing probability and
target gate.

Args:
p: The depolarizing probability, either a single float or a mapping from pairs of qubits
to floats.
target_gate: The gate after which to add depolarizing noise.

Raises:
TypeError: If `p` is not either be a float or a mapping from sorted qubit pairs to
floats.
"""

if not isinstance(p, (Mapping, float)):
raise TypeError( # pragma: no cover
"p must either be a float or a mapping from" # pragma: no cover
+ "sorted qubit pairs to floats" # pragma: no cover
) # pragma: no cover
self.p = p
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you can resolve p here and then use it in call as self.p_func(pair)

Suggested change
self.p = p
self.p_func = lambda _: p if isinstance(p, (int, float)) else lambda pair: p.get(pair, 0)

self.target_gate = target_gate

def __call__(
self,
circuit: circuits.AbstractCircuit,
rng: np.random.Generator | None = None,
*,
context: transformer_api.TransformerContext | None = None,
):
"""Apply the transformer to the given circuit.

Args:
circuit: The circuit to add noise to.
context: Not used; to satisfy transformer API.

Returns:
The transformed circuit.
"""
if rng is None:
rng = np.random.default_rng()
p = self.p
target_gate = self.target_gate

# add random Pauli gates with probability p after each of the specified gate
assert target_gate.num_qubits() == 2, "`target_gate` must be a two-qubit gate."
paulis = [ops.I, ops.X, ops.Y, ops.Z]
new_moments = []
for moment in circuit:
new_moments.append(moment)
if _gate_in_moment(target_gate, moment):
# add a new moment with the Paulis
target_pairs = {
tuple(sorted(op.qubits)) for op in moment.operations if op.gate == target_gate
}
added_moment_ops = []
for pair in target_pairs:
if isinstance(p, float):
p_i = p
elif isinstance(p, Mapping):
pair_sorted_tuple = (pair[0], pair[1])
p_i = p[pair_sorted_tuple]
apply = rng.choice([True, False], p=[p_i, 1 - p_i])
if apply:
choices = [
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[optional suggestion] this creates 17 objects for each pair, 16 pauli pairs + the numpy array. consider doing it this way

pauli_a_idx = np.choice(4)
if pauli_a_idx == 0:
   pauli_b_idx = np.choice(3) + 1
else:
   pauli_b_idx = np.choice(4)
paulit_to_apply = paulis[pauli_a_idx](pair[0]), paulis[pauli_b_idx](pair[1])

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@eliottrosenberg eliottrosenberg Jul 12, 2024

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Thanks, Nour. I agree that this would be more efficient code, but I'm going to leave it as is for now so that I can move on. (It is already very fast as written.)

(pauli_a(pair[0]), pauli_b(pair[1]))
for pauli_a in paulis
for pauli_b in paulis
][1:]
pauli_to_apply = rng.choice(np.array(choices, dtype=object))
added_moment_ops.append(pauli_to_apply)
if len(added_moment_ops) > 0:
new_moments.append(circuits.Moment(*added_moment_ops))
return circuits.Circuit.from_moments(*new_moments)
53 changes: 53 additions & 0 deletions cirq-core/cirq/transformers/noise_adding_test.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,53 @@
# Copyright 2024 The Cirq Developers
#
# 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
#
# https://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 cirq import ops, circuits, devices
import cirq.transformers.noise_adding as na
import numpy as np


def test_noise_adding():
qubits = devices.LineQubit.range(4)
one_layer = circuits.Circuit(ops.CZ(*qubits[:2]), ops.CZ(*qubits[2:]))
circuit = one_layer * 10

# test that p=0 does nothing
transformed_circuit_p0 = na.DepolerizingNoiseTransformer(0.0)(circuit)
assert transformed_circuit_p0 == circuit

# test that p=1 doubles the circuit depth
transformed_circuit_p1 = na.DepolerizingNoiseTransformer(1.0)(circuit)
assert len(transformed_circuit_p1) == 20

# test that we get a deterministic result when using a specific rng
rng = np.random.default_rng(0)
transformed_circuit_p0_03 = na.DepolerizingNoiseTransformer(0.03)(circuit, rng=rng)
expected_circuit = (
one_layer * 2
+ circuits.Circuit(ops.I(qubits[2]), ops.Z(qubits[3]))
+ one_layer * 4
+ circuits.Circuit(ops.Z(qubits[0]), ops.X(qubits[1]))
+ one_layer * 4
+ circuits.Circuit(ops.I(qubits[2]), ops.X(qubits[3]))
)
assert transformed_circuit_p0_03 == expected_circuit

# test that supplying a dictionary for p works
transformed_circuit_p_dict = na.DepolerizingNoiseTransformer(
{tuple(qubits[:2]): 1.0, tuple(qubits[2:]): 0.0}
)(circuit)
assert len(transformed_circuit_p_dict) == 20 # depth should be doubled
assert transformed_circuit_p_dict[1::2].all_qubits() == frozenset(
qubits[:2]
) # no single-qubit gates get added to qubits[2:]