def optimization_at(self, circuit, index, op):
def find_removable_rz():
"""Finds z rotations that can be removed.
A z rotation is removable iff it is followed by a z-basis measurement.
Returns:
list[int]: moment indices of the z rotations to be removed
"""
remove_indices = []
for idx, moment in enumerate(circuit[index:], start=index):
for x in moment.operations:
if x.qubits == op.qubits:
if isinstance(
x.gate, cirq.ZPowGate
): # add idx to the list, keep looking for more
remove_indices.append(idx)
break
if isinstance(x.gate, cirq.MeasurementGate
): # remove the accumulated indices
return remove_indices
return [] # other operations: do not remove anything
return [] # circuit ends here: do not remove anything
indices = find_removable_rz()
if not indices:
return None
return circuits.PointOptimizationSummary(clear_span=max(indices) + 1 -
index,
clear_qubits=op.qubits,
new_operations=[])
def optimization_at(
self, circuit: circuits.Circuit, index: int,
op: ops.Operation) -> Optional[circuits.PointOptimizationSummary]:
if len(op.qubits) != 2:
return None
old_operations, indices, matrix = (
self._scan_two_qubit_ops_into_matrix(circuit, index, op.qubits))
# Find a max-3-cz construction.
new_operations = decompositions.two_qubit_matrix_to_native_gates(
op.qubits[0], op.qubits[1], matrix, self.allow_partial_czs,
self.tolerance)
old_interaction_count = len(
[old_op for old_op in old_operations if len(old_op.qubits) == 2])
new_interaction_count = len(
[new_op for new_op in new_operations if len(new_op.qubits) == 2])
switch_to_new = False
switch_to_new |= new_interaction_count < old_interaction_count
switch_to_new |= any(not xmon_gates.XmonGate.is_xmon_op(old_op)
for old_op in old_operations)
if not switch_to_new:
return None
converter = convert_to_xmon_gates.ConvertToXmonGates()
new_xmon_operations = [
converter.convert(new_op) for new_op in new_operations
]
return circuits.PointOptimizationSummary(
clear_span=max(indices) + 1 - index,
clear_qubits=op.qubits,
new_operations=new_xmon_operations)
def optimization_at(
self,
circuit: cirq.Circuit,
index: int,
op: cirq.Operation,
) -> Optional[cirq.PointOptimizationSummary]:
"""Describes how to change operations near the given location.
Args:
circuit: The circuit to improve.
index: The index of the moment with the operation to focus on.
op: The operation to focus improvements upon.
Returns:
A description of the optimization to perform, or else None if no
change should be made.
"""
if not isinstance(op.gate, self.ONE_PARAMETER_FAMILIES):
return None
def is_not_mergable(next_op: cirq.Operation) -> bool:
"""Predicate for finding gates that can be merged with op.
A gate is mergable with op iff it (1) belongs to the same gate family,
and (2) is acting on the same qubits.
"""
if not isinstance(next_op.gate, type(op.gate)):
return True
if isinstance(op.gate,
ops.gate_features.InterchangeableQubitsGate):
# same qubits in any order
return set(op.qubits) != set(next_op.qubits)
# same qubits in the same order
return op.qubits != next_op.qubits
# start searching from op onwards
start_frontier = {q: index for q in op.qubits}
op_list = circuit.findall_operations_until_blocked(
start_frontier, is_blocker=is_not_mergable)
if len(op_list) == 1:
return None # just the one gate found, no changes
indices, operations = zip(*op_list)
# all the gates are in the same family so we may simply sum their parameters (mod periodicity)
par = sum(o.gate.exponent for o in operations)
# zero parameter (mod period) corresponds to identity
# due to floating point errors we may be just a little below the period, which should also be
# considered close to zero so let's shift away from the troublesome point before taking the modulo
par = self._normalize_par(par)
if abs(par) <= self.GATE_MERGING_TOLERANCE:
rewritten = []
else:
rewritten = op.gate.__class__(exponent=par).on(*op.qubits)
return circuits.PointOptimizationSummary(clear_span=max(indices) + 1 -
index,
clear_qubits=op.qubits,
new_operations=rewritten)
def optimization_at(self, circuit, index, op):
if not isinstance(op.gate, circuit.device.DECOMPOSE_FINALLY):
return None # no changes
rewritten = circuit.device.operation_final_decomposer(op)
return circuits.PointOptimizationSummary(clear_span=1,
clear_qubits=op.qubits,
new_operations=rewritten)
def optimization_at(self, circuit, index, op):
converted = self.convert(op)
if len(converted) == 1 and converted[0] is op:
return None
return circuits.PointOptimizationSummary(clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def optimization_at(
self, circuit: 'cirq.Circuit', index: int,
op: 'cirq.Operation') -> Optional['cirq.PointOptimizationSummary']:
if not isinstance(op, ops.GateOperation):
return None
gate = op.gate
# Check for a SWAP and ZZPowGate together
if isinstance(gate, ops.ZZPowGate) or gate == ops.SWAP:
gate2 = None
rads = None
next_index = circuit.next_moment_operating_on(op.qubits, index + 1)
if next_index is not None:
ops_in_front = list(
{circuit.operation_at(q, next_index)
for q in op.qubits})
if len(ops_in_front) == 1 and isinstance(
ops_in_front[0], ops.GateOperation):
gate2 = ops_in_front[0].gate
else:
next_index = 0
if isinstance(gate, ops.SwapPowGate) and isinstance(
gate2, ops.ZZPowGate):
rads = gate2.exponent * np.pi / 2
if isinstance(gate, ops.ZZPowGate) and gate2 == ops.SWAP:
rads = gate.exponent * np.pi / 2
if rads is not None:
return circuits.PointOptimizationSummary(
clear_span=next_index - index + 1,
clear_qubits=op.qubits,
new_operations=swap_rzz(rads, op.qubits[0], op.qubits[1]),
)
converted = self.convert(op)
if len(converted) == 1 and converted[0] is op:
return None
return circuits.PointOptimizationSummary(clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def optimization_at(self, circuit, index, op):
if isinstance(op.gate, ops.MatrixGate) and len(op.qubits) == 1:
return None
converted = self.convert(op)
if len(converted) == 1 and converted[0] is op:
return None
return circuits.PointOptimizationSummary(clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def test_clears_small():
m = circuits.DropNegligible(0.001)
q = ops.QubitId()
c = circuits.Circuit([circuits.Moment([ops.Z(q)**0.000001])])
assert (m.optimization_at(c, 0, c.operation_at(q, 0)) ==
circuits.PointOptimizationSummary(clear_span=1,
clear_qubits=[q],
new_operations=[]))
m.optimize_circuit(c)
assert c == circuits.Circuit([circuits.Moment()])
def optimization_at(
self,
circuit: cirq.Circuit,
index: int,
op: cirq.Operation,
) -> Optional[cirq.PointOptimizationSummary]:
"""Describes how to change operations near the given location.
Args:
circuit: The circuit to improve.
index: The index of the moment with the operation to focus on.
op: The operation to focus improvements upon.
Returns:
A description of the optimization to perform, or else None if no
change should be made.
"""
def find_removable_rz() -> list[int]:
"""Finds z rotations that can be removed.
A z rotation is removable iff it is followed by a z-basis measurement.
Returns:
moment indices of the z rotations to be removed
"""
# op is a ZPowGate
remove_indices = []
for idx, moment in enumerate(circuit[index:], start=index):
for x in moment.operations:
if op.qubits[0] in x.qubits:
# x acts on the same qubit as op
if isinstance(x.gate, cirq.ZPowGate):
# add idx to the list, keep looking for more
remove_indices.append(idx)
break # to next moment
if isinstance(x.gate, cirq.MeasurementGate):
# follows the ZPowGates, remove the accumulated indices
return remove_indices
return [] # other operations: do not remove anything
# circuit ends here
if self.drop_final:
return remove_indices
return []
if not isinstance(op.gate, cirq.ZPowGate):
return None # shortcut
indices = find_removable_rz()
if not indices:
return None
return circuits.PointOptimizationSummary(clear_span=max(indices) + 1 -
index,
clear_qubits=op.qubits,
new_operations=[])
def test_combines_sequence():
m = MergeRotations(0.000001)
q = ops.QubitId()
c = circuits.Circuit([
circuits.Moment([ops.X(q)**0.5]),
circuits.Moment([ops.Z(q)**0.5]),
circuits.Moment([ops.X(q)**-0.5]),
])
assert (m.optimization_at(c, 0, c.operation_at(
q,
0)) == circuits.PointOptimizationSummary(clear_span=3,
clear_qubits=[q],
new_operations=ops.Y(q)**0.5))
def optimization_at(self,
circuit: circuits.Circuit,
index: int,
op: ops.Operation
) -> Optional[circuits.PointOptimizationSummary]:
if len(op.qubits) != 2:
return None
old_operations, indices, matrix = (
self._scan_two_qubit_ops_into_matrix(circuit, index, op.qubits))
old_interaction_count = len([old_op for old_op in old_operations
if len(old_op.qubits) == 2])
switch_to_new = False
switch_to_new |= any(len(old_op.qubits) == 2 and
not (isinstance(old_op, ops.GateOperation) and
isinstance(old_op.gate, ops.CZPowGate))
for old_op in old_operations)
if not self.allow_partial_czs:
switch_to_new |= any(isinstance(old_op, ops.GateOperation) and
isinstance(old_op.gate, ops.CZPowGate)
and old_op.gate.exponent != 1
for old_op in old_operations)
# This point cannot be optimized using this method
if not switch_to_new and old_interaction_count <= 1:
return None
# Find a max-3-cz construction.
new_operations = (
two_qubit_decompositions.two_qubit_matrix_to_operations(
op.qubits[0],
op.qubits[1],
matrix,
self.allow_partial_czs,
self.tolerance,
False))
new_interaction_count = len([new_op for new_op in new_operations
if len(new_op.qubits) == 2])
switch_to_new |= new_interaction_count < old_interaction_count
if not switch_to_new:
return None
return circuits.PointOptimizationSummary(
clear_span=max(indices) + 1 - index,
clear_qubits=op.qubits,
new_operations=new_operations)
def optimization_at(
self, circuit: circuits.Circuit, index: int,
op: ops.Operation) -> Optional[circuits.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 circuits.PointOptimizationSummary(clear_span=1,
new_operations=converted,
clear_qubits=op.qubits)
def test_stopped_at_2qubit():
m = MergeRotations(0.000001)
q = ops.QubitId()
q2 = ops.QubitId()
c = circuits.Circuit([
circuits.Moment([ops.Z(q)]),
circuits.Moment([ops.H(q)]),
circuits.Moment([ops.X(q)]),
circuits.Moment([ops.H(q)]),
circuits.Moment([ops.CZ(q, q2)]),
circuits.Moment([ops.H(q)]),
])
assert (m.optimization_at(c, 0, c.operation_at(
q, 0)) == circuits.PointOptimizationSummary(clear_span=4,
clear_qubits=[q],
new_operations=[]))
def optimization_at(self, circuit: 'cirq.Circuit', index: int, op: 'cirq.Operation'):
if isinstance(op.gate, AcquaintanceOpportunityGate):
logical_indices = tuple(self.mapping[q] for q in op.qubits)
logical_operations = self.execution_strategy.get_operations(logical_indices, op.qubits)
clear_span = int(not self.execution_strategy.keep_acquaintance)
return circuits.PointOptimizationSummary(
clear_span=clear_span, clear_qubits=op.qubits, new_operations=logical_operations
)
if isinstance(op, ops.GateOperation) and isinstance(op.gate, PermutationGate):
op.gate.update_mapping(self.mapping, op.qubits)
return
raise TypeError(
'Can only execute a strategy consisting of gates that '
'are instances of AcquaintanceOpportunityGate or '
'PermutationGate.'
)
def optimization_at(self, circuit, index, op):
if not isinstance(op.gate, self.one_parameter_families):
return None
def is_not_mergable(next_op):
"""Predicate for finding gates that can be merged with op.
A gate is mergable with op iff it (1) belongs to the same gate family,
and (2) is acting on the same qubits.
"""
if not isinstance(next_op.gate, type(op.gate)):
return True
if isinstance(op.gate,
ops.gate_features.InterchangeableQubitsGate):
# same qubits in any order
return set(op.qubits) != set(next_op.qubits)
# same qubits in the same order
return op.qubits != next_op.qubits
# start searching from op onwards
start_frontier = {q: index for q in op.qubits}
op_list = circuit.findall_operations_until_blocked(
start_frontier, is_blocker=is_not_mergable)
if len(op_list) == 1:
return None # just the one gate found, no changes
indices, operations = zip(*op_list)
# all the gates are in the same family so we may simply sum their parameters (mod periodicity)
par = sum(o.gate.exponent for o in operations)
# zero parameter (mod period) corresponds to identity
# due to floating point errors we may be just a little below the period, which should also be
# considered close to zero so let's shift away from the troublesome point before taking the modulo
par = operator.mod(par + 1, 2) - 1
if abs(par) <= GATE_MERGING_TOLERANCE:
rewritten = []
else:
rewritten = op.gate.__class__(exponent=par).on(*op.qubits)
return circuits.PointOptimizationSummary(clear_span=max(indices) + 1 -
index,
clear_qubits=op.qubits,
new_operations=rewritten)
def optimization_at(
self, circuit: circuits.Circuit, index: int, op: ops.Operation
) -> Optional[circuits.PointOptimizationSummary]:
if len(op.qubits) != 2:
return None
old_operations, indices, matrix = self._scan_two_qubit_ops_into_matrix(
circuit, index, op.qubits
)
old_interaction_count = len(
[old_op for old_op in old_operations if len(old_op.qubits) == 2]
)
switch_to_new = False
switch_to_new |= any(
len(old_op.qubits) == 2 and not self._may_keep_old_op(old_op)
for old_op in old_operations
)
# This point cannot be optimized using this method
if not switch_to_new and old_interaction_count <= 1:
return None
# Find a (possibly ideal) decomposition of the merged operations.
new_operations = self._two_qubit_matrix_to_cz_operations(op.qubits[0], op.qubits[1], matrix)
new_interaction_count = len(
[new_op for new_op in new_operations if len(new_op.qubits) == 2]
)
switch_to_new |= new_interaction_count < old_interaction_count
if not switch_to_new:
return None
return circuits.PointOptimizationSummary(
clear_span=max(indices) + 1 - index,
clear_qubits=op.qubits,
new_operations=new_operations,
)
def optimization_at(
self, circuit: circuits.Circuit, index: int,
op: ops.Operation) -> Optional[circuits.PointOptimizationSummary]:
if len(op.qubits) != 1:
return None
start = {op.qubits[0]: index}
op_list = circuit.findall_operations_until_blocked(
start,
is_blocker=lambda next_op: len(
next_op.qubits) != 1 or not protocols.has_unitary(next_op))
operations = [op for idx, op in op_list]
indices = [idx for idx, op in op_list]
rewritten = self._rewrite(operations)
if rewritten is None:
return None
return circuits.PointOptimizationSummary(clear_span=max(indices) + 1 -
index,
clear_qubits=op.qubits,
new_operations=rewritten)
def optimization_at(
self, circuit: circuits.Circuit, index: int,
op: ops.Operation) -> Optional[circuits.PointOptimizationSummary]:
if len(op.qubits) != 1:
return None
start = {op.qubits[0]: index}
end = circuit.reachable_frontier_from(
start,
is_blocker=lambda next_op: len(
next_op.qubits) != 1 or not protocols.has_unitary(next_op))
operations_indexed = circuit.findall_operations_between(start, end)
operations = [e for _, e in operations_indexed]
indices = [e for e, _ in operations_indexed]
rewritten = self._rewrite(operations)
if rewritten is None:
return None
return circuits.PointOptimizationSummary(clear_span=max(indices) + 1 -
index,
clear_qubits=op.qubits,
new_operations=rewritten)
