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Código fuente para qiskit.transpiler.passes.optimization.optimize_1q_decomposition

# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2018.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.

"""Optimize chains of single-qubit gates using Euler 1q decomposer"""

import logging
from functools import partial
import numpy as np

from qiskit.transpiler.basepasses import TransformationPass
from qiskit.transpiler.passes.utils import control_flow
from qiskit.quantum_info.synthesis import one_qubit_decompose

logger = logging.getLogger(__name__)


[documentos]class Optimize1qGatesDecomposition(TransformationPass): """Optimize chains of single-qubit gates by combining them into a single gate. The decision to replace the original chain with a new resynthesis depends on: - whether the original chain was out of basis: replace - whether the original chain was in basis but resynthesis is lower error: replace - whether the original chain contains a pulse gate: do not replace - whether the original chain amounts to identity: replace with null Error is computed as a multiplication of the errors of individual gates on that qubit. """ def __init__(self, basis=None, target=None): """Optimize1qGatesDecomposition initializer. Args: basis (list[str]): Basis gates to consider, e.g. `['u3', 'cx']`. For the effects of this pass, the basis is the set intersection between the `basis` parameter and the Euler basis. Ignored if ``target`` is also specified. target (Optional[Target]): The :class:`~.Target` object corresponding to the compilation target. When specified, any argument specified for ``basis_gates`` is ignored. """ super().__init__() self._basis_gates = basis self._target = target self._global_decomposers = None self._local_decomposers_cache = {} if basis: self._global_decomposers = _possible_decomposers(set(basis)) elif target is None: self._global_decomposers = _possible_decomposers(None) self._basis_gates = None def _resynthesize_run(self, run, qubit=None): """ Resynthesizes one `run`, typically extracted via `dag.collect_1q_runs`. Returns the newly synthesized circuit in the indicated basis, or None if no synthesis routine applied. """ operator = run[0].op.to_matrix() for gate in run[1:]: operator = gate.op.to_matrix().dot(operator) if self._target: qubits_tuple = (qubit,) if qubits_tuple in self._local_decomposers_cache: decomposers = self._local_decomposers_cache[qubits_tuple] else: available_1q_basis = set(self._target.operation_names_for_qargs(qubits_tuple)) decomposers = _possible_decomposers(available_1q_basis) self._local_decomposers_cache[qubits_tuple] = decomposers else: decomposers = self._global_decomposers new_circs = [decomposer._decompose(operator) for decomposer in decomposers] if len(new_circs) == 0: return None else: return min(new_circs, key=partial(_error, target=self._target, qubit=qubit)) def _substitution_checks(self, dag, old_run, new_circ, basis, qubit): """ Returns `True` when it is recommended to replace `old_run` with `new_circ` over `basis`. """ if new_circ is None: return False # do we even have calibrations? has_cals_p = dag.calibrations is not None and len(dag.calibrations) > 0 # does this run have uncalibrated gates? uncalibrated_p = not has_cals_p or any(not dag.has_calibration_for(g) for g in old_run) # does this run have gates not in the image of ._decomposers _and_ uncalibrated? if basis is not None: uncalibrated_and_not_basis_p = any( g.name not in basis and (not has_cals_p or not dag.has_calibration_for(g)) for g in old_run ) else: # If no basis is specified then we're always in the basis uncalibrated_and_not_basis_p = False # if we're outside of the basis set, we're obligated to logically decompose. # if we're outside of the set of gates for which we have physical definitions, # then we _try_ to decompose, using the results if we see improvement. return ( uncalibrated_and_not_basis_p or ( uncalibrated_p and _error(new_circ, self._target, qubit) < _error(old_run, self._target, qubit) ) or np.isclose(_error(new_circ, self._target, qubit), 0) )
[documentos] @control_flow.trivial_recurse def run(self, dag): """Run the Optimize1qGatesDecomposition pass on `dag`. Args: dag (DAGCircuit): the DAG to be optimized. Returns: DAGCircuit: the optimized DAG. """ runs = dag.collect_1q_runs() qubit_indices = {bit: index for index, bit in enumerate(dag.qubits)} for run in runs: qubit = qubit_indices[run[0].qargs[0]] new_dag = self._resynthesize_run(run, qubit) if self._target is None: basis = self._basis_gates else: basis = self._target.operation_names_for_qargs((qubit,)) if new_dag is not None and self._substitution_checks(dag, run, new_dag, basis, qubit): dag.substitute_node_with_dag(run[0], new_dag) # Delete the other nodes in the run for current_node in run[1:]: dag.remove_op_node(current_node) return dag
def _possible_decomposers(basis_set): decomposers = [] if basis_set is None: decomposers = [ one_qubit_decompose.OneQubitEulerDecomposer(basis, use_dag=True) for basis in one_qubit_decompose.ONE_QUBIT_EULER_BASIS_GATES ] else: euler_basis_gates = one_qubit_decompose.ONE_QUBIT_EULER_BASIS_GATES for euler_basis_name, gates in euler_basis_gates.items(): if set(gates).issubset(basis_set): decomposer = one_qubit_decompose.OneQubitEulerDecomposer( euler_basis_name, use_dag=True ) decomposers.append(decomposer) return decomposers def _error(circuit, target, qubit): """ Calculate a rough error for a `circuit` that runs on a specific `qubit` of `target` (circuit could also be a list of DAGNodes) Use basis errors from target if available, otherwise use length of circuit as a weak proxy for error. """ if target is None: if isinstance(circuit, list): return len(circuit) else: return len(circuit._multi_graph) - 2 else: if isinstance(circuit, list): gate_fidelities = [ 1 - getattr(target[node.name].get((qubit,)), "error", 0.0) for node in circuit ] else: gate_fidelities = [ 1 - getattr(target[inst.op.name].get((qubit,)), "error", 0.0) for inst in circuit.op_nodes() ] gate_error = 1 - np.product(gate_fidelities) if gate_error == 0.0: if isinstance(circuit, list): return -100 + len(circuit) else: return -100 + len( circuit._multi_graph ) # prefer shorter circuits among those with zero error else: return gate_error