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drop_negligible_operations.py
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drop_negligible_operations.py
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# Copyright 2022 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.
"""Transformer pass that removes operations with tiny effects."""
from typing import Optional, TYPE_CHECKING
from cirq import protocols
from cirq.transformers import transformer_api, transformer_primitives
if TYPE_CHECKING:
import cirq
@transformer_api.transformer
def drop_negligible_operations(
circuit: 'cirq.AbstractCircuit',
*,
context: Optional['cirq.TransformerContext'] = None,
atol: float = 1e-8,
) -> 'cirq.Circuit':
"""Removes operations with tiny effects.
An operation `op` is considered to have a tiny effect if
`cirq.trace_distance_bound(op) <= atol`.
Args:
circuit: Input circuit to transform.
context: `cirq.TransformerContext` storing common configurable options for transformers.
atol: Absolute tolerance to determine if an operation `op` is negligible --
i.e. if `cirq.trace_distance_bound(op) <= atol`.
Returns:
Copy of the transformed input circuit.
"""
if context is None:
context = transformer_api.TransformerContext()
def map_func(op: 'cirq.Operation', _: int) -> 'cirq.OP_TREE':
return (
op
if protocols.num_qubits(op) > 10
or protocols.is_measurement(op)
or protocols.trace_distance_bound(op) > atol
else []
)
return transformer_primitives.map_operations(
circuit, map_func, tags_to_ignore=context.tags_to_ignore, deep=context.deep
).unfreeze(copy=False)