def optimization_at(self, circuit, index, op):
converted = self.convert(op)
if len(converted) == 1 and converted[0] is op:
return None
return PointOptimizationSummary(clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def optimization_at(self, circuit, index, op):
decomposition = self._decompose(op)
if decomposition is op:
return None
return PointOptimizationSummary(clear_span=1,
clear_qubits=op.qubits,
new_operations=decomposition)
def optimization_at(self, circuit, index, op):
if not (isinstance(op.gate, ops.BoundedEffectGate) and
op.gate.trace_distance_bound() <= self.tolerance):
return None
return PointOptimizationSummary(
clear_span=1,
new_operations=(),
clear_qubits=op.qubits)
def optimization_at(
self, circuit: 'cirq.Circuit', index: int,
op: 'cirq.Operation') -> Optional['cirq.PointOptimizationSummary']:
converted = self.convert(op)
if len(converted) == 1 and converted[0] is op:
return None
return PointOptimizationSummary(clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def optimization_at(self, circuit: Circuit, index: int, op: ops.Operation
) -> Optional[PointOptimizationSummary]:
converted = self.convert(op)
if converted is op:
return None
return PointOptimizationSummary(
clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def optimization_at(self, circuit, index, op):
decomposition = protocols.decompose(op, keep=self.no_decomp,
on_stuck_raise=None)
if decomposition is op:
return None
return PointOptimizationSummary(
clear_span=1,
clear_qubits=op.qubits,
new_operations=decomposition)
def optimization_at(
self, circuit: 'cirq.Circuit', index: int,
op: 'cirq.Operation') -> Optional['cirq.PointOptimizationSummary']:
decomposition = protocols.decompose(op,
keep=self.no_decomp,
on_stuck_raise=None)
if decomposition == [op]:
return None
return PointOptimizationSummary(clear_span=1,
clear_qubits=op.qubits,
new_operations=decomposition)
def optimization_at(
self, circuit: Circuit, index: int,
op: ops.Operation) -> Optional[PointOptimizationSummary]:
converted = protocols.decompose(
op,
intercepting_decomposer=self._decompose_two_qubit_unitaries,
keep=self._keep,
on_stuck_raise=(None
if self.ignore_failures else self._on_stuck_raise))
if converted == [op]:
return None
return PointOptimizationSummary(clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def optimization_at(
self, circuit: Circuit, index: int,
op: ops.Operation) -> Optional[PointOptimizationSummary]:
if len(op.qubits) != 1:
return None
q = op.qubits[0]
indices, operations = _scan_single_qubit_ops(circuit, index, q)
if not operations:
return None
single_op = _merge_into_matrix_gate_op(q, operations)
return PointOptimizationSummary(clear_span=max(indices) + 1 - index,
clear_qubits=op.qubits,
new_operations=[single_op])
def optimization_at(
self, circuit: Circuit, index: int,
op: ops.Operation) -> Optional[PointOptimizationSummary]:
if len(op.qubits) != 1:
return None
indices, gates = self._scan_single_qubit_ops(circuit, index,
op.qubits[0])
if not gates:
return None
# Replace the gates with a max-2-op XY + Z construction.
operations = self._merge_rotations(op.qubits[0], gates)
return PointOptimizationSummary(clear_span=max(indices) + 1 - index,
clear_qubits=op.qubits,
new_operations=operations)
