def decompose_to_target_gateset(self, op: 'cirq.Operation',
moment_idx: int) -> DecomposeResult:
if not 1 <= protocols.num_qubits(op) <= 2:
return self._decompose_multi_qubit_operation(op, moment_idx)
if protocols.num_qubits(op) == 1:
return self._decompose_single_qubit_operation(op, moment_idx)
new_optree = self._decompose_two_qubit_operation(op, moment_idx)
if new_optree is NotImplemented or new_optree is None:
return new_optree
new_optree = [*ops.flatten_to_ops_or_moments(new_optree)]
op_untagged = op.untagged
old_optree = ([*op_untagged.circuit]
if isinstance(op_untagged, circuits.CircuitOperation)
and self._intermediate_result_tag in op.tags else [op])
old_2q_gate_count = sum(1 for o in ops.flatten_to_ops(old_optree)
if len(o.qubits) == 2)
new_2q_gate_count = sum(1 for o in ops.flatten_to_ops(new_optree)
if len(o.qubits) == 2)
switch_to_new = (any(
protocols.num_qubits(op) == 2 and op not in self
for op in ops.flatten_to_ops(old_optree))
or new_2q_gate_count < old_2q_gate_count)
if switch_to_new:
return new_optree
mapped_old_optree: List['cirq.OP_TREE'] = []
for old_op in ops.flatten_to_ops(old_optree):
if old_op in self:
mapped_old_optree.append(old_op)
else:
decomposed_op = self._decompose_single_qubit_operation(
old_op, moment_idx)
if decomposed_op is None or decomposed_op is NotImplemented:
return NotImplemented
mapped_old_optree.append(decomposed_op)
return mapped_old_optree
def _translate_cirq_operation_to_braket_instruction(
op: cirq_ops.Operation,
) -> List[Instruction]:
"""Converts the Cirq operation to an equivalent Braket instruction or list
of instructions.
Args:
op: Cirq operation to convert.
Raises:
ValueError: If the operation cannot be converted to Braket.
"""
nqubits = protocols.num_qubits(op)
if nqubits == 1:
return _translate_one_qubit_cirq_operation_to_braket_instruction(op)
elif nqubits == 2:
return _translate_two_qubit_cirq_operation_to_braket_instruction(op)
elif nqubits == 3:
qubits = [q.x for q in op.qubits]
if op == cirq_ops.TOFFOLI.on(*op.qubits):
return [Instruction(braket_gates.CCNot(), qubits)]
elif op == cirq_ops.FREDKIN.on(*op.qubits):
return [Instruction(braket_gates.CSwap(), qubits)]
else:
_raise_cirq_to_braket_error(op)
# Unsupported gates.
else:
_raise_cirq_to_braket_error(op)
def assert_has_consistent_apply_unitary(val: Any,
*,
qubit_count: Optional[int] = None,
atol: float = 1e-8) -> None:
"""Tests whether a value's _apply_unitary_ is correct.
Contrasts the effects of the value's `_apply_unitary_` with the
matrix returned by the value's `_unitary_` method.
Args:
val: The value under test. Should have a `__pow__` method.
qubit_count: Usually inferred. The number of qubits the value acts on.
This argument isn't needed if the gate has a unitary matrix or
implements `cirq.SingleQubitGate`/`cirq.TwoQubitGate`/
`cirq.ThreeQubitGate`.
atol: Absolute error tolerance.
"""
expected = protocols.unitary(val, default=None)
qubit_counts = [
qubit_count,
# Only fall back to using the unitary size if num_qubits or qid_shape
# protocols are not defined.
protocols.num_qubits(val,
default=expected.shape[0].bit_length() -
1 if expected is not None else None),
_infer_qubit_count(val)
]
qubit_counts = [e for e in qubit_counts if e is not None]
if not qubit_counts:
raise NotImplementedError(
'Failed to infer qubit count of <{!r}>. Specify it.'.format(val))
assert len(set(qubit_counts)) == 1, (
'Inconsistent qubit counts from different methods: {}'.format(
qubit_counts))
n = cast(int, qubit_counts[0])
qid_shape = protocols.qid_shape(val, default=(2, ) * n)
eye = linalg.eye_tensor((2, ) + qid_shape, dtype=np.complex128)
actual = protocols.apply_unitary(
unitary_value=val,
args=protocols.ApplyUnitaryArgs(target_tensor=eye,
available_buffer=np.ones_like(eye) *
float('nan'),
axes=list(range(1, n + 1))),
default=None)
# If you don't have a unitary, you shouldn't be able to apply a unitary.
if expected is None:
assert actual is None
else:
expected = np.kron(np.eye(2), expected)
# If you applied a unitary, it should match the one you say you have.
if actual is not None:
np.testing.assert_allclose(actual.reshape((np.prod(
(2, ) + qid_shape, dtype=int), ) * 2),
expected,
atol=atol)
def route_circuit(circuit: circuits.Circuit,
device_graph: nx.Graph,
*,
algo_name: Optional[str] = None,
router: Optional[Callable[..., SwapNetwork]] = None,
**kwargs) -> SwapNetwork:
"""Routes a circuit on a given device.
Args:
circuit: The circuit to route.
device_graph: The device's graph, in which each vertex is a qubit and
each edge indicates the ability to do an operation on those qubits.
algo_name: The name of a routing algorithm. Must be in ROUTERS.
router: The function that actually does the routing.
**kwargs: Arguments to pass to the routing algorithm.
Exactly one of algo_name and router must be specified.
"""
if any(protocols.num_qubits(op) > 2 for op in circuit.all_operations()):
raise ValueError('Can only route circuits with operations that act on'
' at most 2 qubits.')
if len(list(circuit.all_qubits())) > device_graph.number_of_nodes():
raise ValueError('Number of logical qubits is greater than number'
' of physical qubits.')
if not (algo_name is None or router is None):
raise ValueError(
'At most one of algo_name or router can be specified.')
if algo_name is not None:
router = ROUTERS[algo_name]
elif router is None:
raise ValueError(f'No routing algorithm specified.')
return router(circuit, device_graph, **kwargs)
def __init__(
self,
gate: Union[Type[raw_types.Gate], raw_types.Gate],
*,
name: Optional[str] = None,
description: Optional[str] = None,
max_parallel_allowed: Optional[int] = None,
) -> None:
"""Inits ParallelGateFamily
Args:
gate: The gate which can act in parallel. It can be a python `type` inheriting from
`cirq.Gate` or a non-parameterized instance of a `cirq.Gate`. If an instance of
`cirq.ParallelGate` is passed, then the corresponding `gate.sub_gate` is used.
name: The name of the gate family.
description: Human readable description of the gate family.
max_parallel_allowed: The maximum number of qubits on which a given gate `g`
can act on. If None, then any number of qubits are allowed.
"""
if isinstance(gate, parallel_gate.ParallelGate):
if not max_parallel_allowed:
max_parallel_allowed = protocols.num_qubits(gate)
gate = cast(parallel_gate.ParallelGate, gate).sub_gate
self._max_parallel_allowed = max_parallel_allowed
super().__init__(gate, name=name, description=description)
def _predicate(self, gate: raw_types.Gate) -> bool:
if (self._max_parallel_allowed is not None
and protocols.num_qubits(gate) > self._max_parallel_allowed):
return False
gate = gate.sub_gate if isinstance(
gate, parallel_gate.ParallelGate) else gate
return super()._predicate(gate)
def map_func(op: 'cirq.Operation', _) -> 'cirq.OP_TREE':
op_untagged = op.untagged
if (
deep
and isinstance(op_untagged, circuits.CircuitOperation)
and merged_circuit_op_tag not in op.tags
):
return op_untagged.replace(
circuit=_rewrite_merged_k_qubit_unitaries(
op_untagged.circuit,
context=context,
k=k,
rewriter=rewriter,
merged_circuit_op_tag=merged_circuit_op_tag,
).freeze()
).with_tags(*op.tags)
if not (protocols.num_qubits(op) <= k and protocols.has_unitary(op)):
return op
if rewriter:
return rewriter(
cast(circuits.CircuitOperation, op_untagged)
if merged_circuit_op_tag in op.tags
else circuits.CircuitOperation(circuits.FrozenCircuit(op))
)
return ops.MatrixGate(protocols.unitary(op)).on(*op.qubits)
def assert_has_consistent_qid_shape(val: Any) -> None:
"""Tests whether a value's `_qid_shape_` and `_num_qubits_` are correct and
consistent.
Verifies that the entries in the shape are all positive integers and the
length of shape equals `_num_qubits_` (and also equals `len(qubits)` if
`val` has `qubits`.
Args:
val: The value under test. Should have `_qid_shape_` and/or
`num_qubits_` methods. Can optionally have a `qubits` property.
"""
default = (-1, )
qid_shape = protocols.qid_shape(val, default)
num_qubits = protocols.num_qubits(val, default)
if qid_shape is default or num_qubits is default:
return # Nothing to check
assert all(
d >= 1 for d in
qid_shape), f'Not all entries in qid_shape are positive: {qid_shape}'
assert (
len(qid_shape) == num_qubits
), f'Length of qid_shape and num_qubits disagree: {qid_shape}, {num_qubits}'
if isinstance(val, ops.Operation):
assert num_qubits == len(
val.qubits
), f'Length of num_qubits and val.qubits disagrees: {num_qubits}, {len(val.qubits)}'
def state_vector_has_stabilizer(state_vector: np.ndarray,
stabilizer: DensePauliString) -> bool:
"""Checks that the state_vector is stabilized by the given stabilizer.
The stabilizer should not modify the value of the state_vector, up to the
global phase.
Args:
state_vector: An input state vector. Is not mutated by this function.
stabilizer: A potential stabilizer of the above state_vector as a
DensePauliString.
Returns:
Whether the stabilizer stabilizes the supplied state.
"""
qubits = LineQubit.range(protocols.num_qubits(stabilizer))
args = state_vector_simulation_state.StateVectorSimulationState(
available_buffer=np.empty_like(state_vector),
qubits=qubits,
prng=np.random.RandomState(),
initial_state=state_vector.copy(),
dtype=state_vector.dtype,
)
protocols.act_on(stabilizer, args, qubits)
return np.allclose(args.target_tensor, state_vector)
def _commutes_(self, other: Any, atol: Union[int, float] = 1e-8
) -> Union[bool, NotImplementedType]:
if (isinstance(other, ops.Gate) and
isinstance(other, ops.InterchangeableQubitsGate) and
protocols.num_qubits(other) == 2):
return True
return NotImplemented
def assert_pauli_expansion_is_consistent_with_unitary(val: Any) -> None:
"""Checks Pauli expansion against unitary matrix."""
# Check to see if the protocol is supported without doing a fallback
# to unitary, otherwise the test is vacuous.
method = getattr(val, '_pauli_expansion_', None)
if method is None:
return
pauli_expansion = protocols.pauli_expansion(val, default=None)
if pauli_expansion is None:
return
unitary = protocols.unitary(val, None)
if unitary is None:
return
num_qubits = protocols.num_qubits(val,
default=unitary.shape[0].bit_length() -
1)
basis = operator_spaces.kron_bases(operator_spaces.PAULI_BASIS,
repeat=num_qubits)
recovered_unitary = operator_spaces.matrix_from_basis_coefficients(
pauli_expansion, basis)
assert np.allclose(unitary, recovered_unitary, rtol=0, atol=1e-12)
def _strat_act_from_single_qubit_decompose(
self, val: Any, qubits: Sequence['cirq.Qid']
) -> bool:
if num_qubits(val) == 1:
if not has_unitary(val):
return NotImplemented
u = unitary(val)
clifford_gate = SingleQubitCliffordGate.from_unitary(u)
if clifford_gate is not None:
# Gather the effective unitary applied so as to correct for the
# global phase later.
final_unitary = np.eye(2)
for axis, quarter_turns in clifford_gate.decompose_rotation():
gate = axis ** (quarter_turns / 2)
self._strat_apply_gate(gate, qubits)
final_unitary = np.matmul(unitary(gate), final_unitary)
# Find the entry with the largest magnitude in the input unitary.
k = max(np.ndindex(*u.shape), key=lambda t: abs(u[t]))
# Correct the global phase that wasn't conserved in the above
# decomposition.
self._state.apply_global_phase(u[k] / final_unitary[k])
return True
return NotImplemented
def _strat_act_on_stabilizer_ch_form_from_single_qubit_decompose(
val: Any, args: 'cirq.ActOnStabilizerCHFormArgs') -> bool:
if num_qubits(val) == 1:
if not has_unitary(val):
return NotImplemented
u = unitary(val)
clifford_gate = SingleQubitCliffordGate.from_unitary(u)
if clifford_gate is not None:
# Gather the effective unitary applied so as to correct for the
# global phase later.
final_unitary = np.eye(2)
for axis, quarter_turns in clifford_gate.decompose_rotation():
gate = None # type: Optional[cirq.Gate]
if axis == pauli_gates.X:
gate = common_gates.XPowGate(exponent=quarter_turns / 2)
assert gate._act_on_(args)
elif axis == pauli_gates.Y:
gate = common_gates.YPowGate(exponent=quarter_turns / 2)
assert gate._act_on_(args)
else:
assert axis == pauli_gates.Z
gate = common_gates.ZPowGate(exponent=quarter_turns / 2)
assert gate._act_on_(args)
final_unitary = np.matmul(unitary(gate), final_unitary)
# Find the entry with the largest magnitude in the input unitary.
k = max(np.ndindex(*u.shape), key=lambda t: abs(u[t]))
# Correct the global phase that wasn't conserved in the above
# decomposition.
args.state.omega *= u[k] / final_unitary[k]
return True
return NotImplemented
def _translate_cirq_operation_to_braket_instruction(
op: cirq_ops.Operation, ) -> List[Instruction]:
"""Converts the Cirq operation to an equivalent Braket instruction or list
of instructions.
Args:
op: Cirq operation to convert.
Raises:
ValueError: If the operation cannot be converted to Braket.
"""
nqubits = protocols.num_qubits(op)
if nqubits == 1:
return _translate_one_qubit_cirq_operation_to_braket_instruction(op)
elif nqubits == 2:
return _translate_two_qubit_cirq_operation_to_braket_instruction(op)
elif nqubits == 3:
qubits = [q.x for q in op.qubits]
if isinstance(op.gate, cirq_ops.TOFFOLI):
return [Instruction(braket_gates.CCNot(), qubits)]
elif isinstance(op.gate, cirq_ops.FREDKIN):
return [Instruction(braket_gates.CSwap(), qubits)]
# Unsupported gates.
else:
raise ValueError(
f"Unable to convert {op} to Braket. If you think this is a bug, "
"you can open an issue on the Mitiq GitHub at"
" https://github.com/unitaryfund/mitiq.")
def can_merge_moment(m: 'cirq.Moment'):
return all(
protocols.num_qubits(op) == 1
and protocols.has_unitary(op)
and tags_to_ignore.isdisjoint(op.tags)
for op in m
)
def state_vector_has_stabilizer(state_vector: np.ndarray,
stabilizer: DensePauliString) -> bool:
"""Checks that the state_vector is stabilized by the given stabilizer.
The stabilizer should not modify the value of the state_vector, up to the
global phase.
Args:
state_vector: An input state vector. Is not mutated by this function.
stabilizer: A potential stabilizer of the above state_vector as a
DensePauliString.
Returns:
Whether the stabilizer stabilizes the supplied state.
"""
args = act_on_state_vector_args.ActOnStateVectorArgs(
target_tensor=state_vector.copy(),
available_buffer=np.empty_like(state_vector),
axes=range(protocols.num_qubits(stabilizer)),
prng=np.random.RandomState(),
log_of_measurement_results={},
)
protocols.act_on(stabilizer, args)
return np.allclose(args.target_tensor, state_vector)
def assert_has_consistent_qid_shape(val: Any,
qubit_count: Optional[int] = None) -> None:
"""Tests whether a value's `_qid_shape_` and `_num_qubits_` are correct and
consistent.
Verifies that the entries in the shape are all positive integers and the
length of shape equals `_num_qubits_` (and also equals `len(qubits)` if
`val` has `qubits`.
Args:
val: The value under test. Should have `_qid_shape_` and/or
`num_qubits_` methods. Can optionally have a `qubits` property.
qubit_count: The expected number of qubits val should use.
"""
default = (-1,)
qid_shape = protocols.qid_shape(val, default)
num_qubits = protocols.num_qubits(val, default)
if qid_shape is default or num_qubits is default:
return # Nothing to check
assert all(d >= 1 for d in qid_shape), (
f'Not all entries in qid_shape are positive: {qid_shape}')
assert len(qid_shape) == num_qubits, (
f'Length of qid_shape and num_qubits disagree: {qid_shape}, '
f'{num_qubits}')
if qubit_count is not None:
assert qubit_count == num_qubits, (
f'Expected qubits and num_qubits disagree: {qubit_count}, '
f'{num_qubits}')
infer_qubit_count = _infer_qubit_count(val)
if infer_qubit_count is not None:
assert infer_qubit_count == num_qubits, (
f'Length of qubits and num_qubits disagree: {infer_qubit_count}, '
f'{num_qubits}')
def build_entangling_layers(
qubits: Sequence[devices.GridQubit], two_qubit_gate: ops.Gate
) -> List[ops.Moment]:
"""Builds a sequence of gates that entangle all pairs of qubits on a grid.
The qubits are restricted to be physically on a square grid with distinct
row and column indices (not every node of the grid needs to have a
qubit). To entangle all pairs of qubits, a user-specified two-qubit gate
is applied between each and every pair of qubit that are next to each
other. In general, a total of four sets of parallel operations are needed to
perform all possible two-qubit gates. We proceed as follows:
The first layer applies two-qubit gates to qubits (i, j) and (i, j + 1)
where i is any integer and j is an even integer. The second layer
applies two-qubit gates to qubits (i, j) and (i + 1, j) where i is an even
integer and j is any integer. The third layer applies two-qubit gates
to qubits (i, j) and (i, j + 1) where i is any integer and j is an odd
integer. The fourth layer applies two-qubit gates to qubits (i, j) and
(i + 1, j) where i is an odd integer and j is any integer.
After the layers are built as above, any empty layer is ejected.:
Cycle 1: Cycle 2:
q00 ── q01 q02 ── q03 q00 q01 q02 q03
| | | |
q10 ── q11 q12 ── q13 q10 q11 q12 q13
q20 ── q21 q22 ── q23 q20 q21 q22 q23
| | | |
q30 ── q31 q32 ── q33 q30 q31 q32 q33
Cycle 3: Cycle 4:
q00 q01 ── q02 q03 q00 q01 q02 q03
q10 q11 ── q12 q13 q10 q11 q12 q13
| | | |
q20 q21 ── q22 q23 q20 q21 q22 q23
q30 q31 ── q32 q33 q30 q31 q32 q33
Args:
qubits: The grid qubits included in the entangling operations.
two_qubit_gate: The two-qubit gate to be applied between all
neighboring pairs of qubits.
Returns:
A list of ops.Moment, with a maximum length of 4. Each ops.Moment
includes two-qubit gates which can be performed at the same time.
Raises:
ValueError: two-qubit gate is not used.
"""
if protocols.num_qubits(two_qubit_gate) != 2:
raise ValueError('Input must be a two-qubit gate')
interaction_sequence = _default_interaction_sequence(qubits)
return [
ops.Moment([two_qubit_gate(q_a, q_b) for (q_a, q_b) in pairs])
for pairs in interaction_sequence
]
def map_func(op: 'cirq.Operation', _) -> 'cirq.OP_TREE':
if not (protocols.num_qubits(op) <= k and protocols.has_unitary(op)):
return op
if rewriter:
return rewriter(
cast(circuits.CircuitOperation, op.untagged
) if merged_circuit_op_tag in op.tags else circuits.
CircuitOperation(circuits.FrozenCircuit(op)))
return ops.MatrixGate(protocols.unitary(op)).on(*op.qubits)
def validate_args(self, qubits: Sequence[Qid]) -> None:
"""Checks if this gate can be applied to the given qubits.
By default checks if input is of type Qid and qubit count.
Child classes can override.
Args:
qubits: The collection of qubits to potentially apply the gate to.
Throws:
ValueError: The gate can't be applied to the qubits.
"""
if len(qubits) != protocols.num_qubits(self):
raise ValueError('Wrong number of qubits for <{!r}>. '
'Expected {} qubits but got <{!r}>.'.format(
self, protocols.num_qubits(self), qubits))
if any([not isinstance(qubit, Qid) for qubit in qubits]):
raise ValueError('Gate was called with type different than Qid.')
def _strat_has_stabilizer_effect_from_unitary(val: Any) -> Optional[bool]:
"""Attempts to infer whether val has stabilizer effect from its unitary.
Returns whether unitary of `val` normalizes the Pauli group. Works only for
2x2 unitaries.
"""
# Do not try this strategy if there is no unitary or if the number of
# qubits is not 1 since that would be expensive.
if not protocols.has_unitary(val) or protocols.num_qubits(val) != 1:
return None
unitary = protocols.unitary(val)
return SingleQubitCliffordGate.from_unitary(unitary) is not None
def assert_act_on_clifford_tableau_effect_matches_unitary(val: Any) -> None:
"""Checks that act_on with CliffordTableau generates stabilizers that
stabilize the final state vector. Does not work with Operations or Gates
expecting non-qubit Qids."""
# pylint: disable=unused-variable
__tracebackhide__ = True
# pylint: enable=unused-variable
num_qubits_val = protocols.num_qubits(val)
if not protocols.has_unitary(val) or \
protocols.qid_shape(val) != (2,) * num_qubits_val:
return None
qubits = LineQubit.range(protocols.num_qubits(val) * 2)
qubit_map = {qubit: i for i, qubit in enumerate(qubits)}
circuit = Circuit()
for i in range(num_qubits_val):
circuit.append([
common_gates.H(qubits[i]),
common_gates.CNOT(qubits[i], qubits[-i - 1])
])
if hasattr(val, "on"):
circuit.append(val.on(*qubits[:num_qubits_val]))
else:
circuit.append(val.with_qubits(*qubits[:num_qubits_val]))
tableau = _final_clifford_tableau(circuit, qubit_map)
if tableau is None:
return None
state_vector = np.reshape(final_state_vector(circuit, qubit_order=qubits),
protocols.qid_shape(qubits))
assert all(
state_vector_has_stabilizer(state_vector, stab)
for stab in tableau.stabilizers()), (
"act_on clifford tableau is not consistent with "
"final_state_vector simulation.\n\nval: {!r}".format(val))
def preprocess_transformers(self) -> List['cirq.TRANSFORMER']:
"""List of transformers which should be run before decomposing individual operations."""
return [
_create_transformer_with_kwargs(
expand_composite.expand_composite,
no_decomp=lambda op: protocols.num_qubits(op) <= self.num_qubits,
),
_create_transformer_with_kwargs(
merge_k_qubit_gates.merge_k_qubit_unitaries,
k=self.num_qubits,
rewriter=lambda op: op.with_tags(self._intermediate_result_tag),
),
]
def state_vector_has_stabilizer(state_vector: np.ndarray,
stabilizer: DensePauliString) -> bool:
"""Checks that the stabilizer does not modify the value of the
state_vector, including the global phase. Does not mutate the input
state_vector."""
args = act_on_state_vector_args.ActOnStateVectorArgs(
target_tensor=state_vector.copy(),
available_buffer=np.empty_like(state_vector),
axes=range(protocols.num_qubits(stabilizer)),
prng=np.random.RandomState(),
log_of_measurement_results={})
protocols.act_on(stabilizer, args)
return np.allclose(args.target_tensor, state_vector)
def _known_gate_with_no_decomposition(val: Any):
"""Checks whether `val` is a known gate with no default decomposition to default gateset."""
if isinstance(val, ops.MatrixGate):
return protocols.qid_shape(val) not in [(2, ), (2, ) * 2, (2, ) * 3]
if isinstance(val,
ops.BaseDensePauliString) and not protocols.has_unitary(val):
return True
if isinstance(val, ops.ControlledGate):
if protocols.is_parameterized(val):
return True
if isinstance(
val.sub_gate,
ops.MatrixGate) and protocols.num_qubits(val.sub_gate) > 1:
return True
if val.control_qid_shape != (2, ) * val.num_controls():
return True
return _known_gate_with_no_decomposition(val.sub_gate)
return False
def _strat_act_from_single_qubit_decompose(
self, val: Any, qubits: Sequence['cirq.Qid']
) -> bool:
if num_qubits(val) == 1:
if not has_unitary(val):
return NotImplemented
u = unitary(val)
gate_and_phase = SingleQubitCliffordGate.from_unitary_with_global_phase(u)
if gate_and_phase is not None:
clifford_gate, global_phase = gate_and_phase
# Apply gates.
for gate in clifford_gate.decompose_gate():
self._strat_apply_gate(gate, qubits)
# Apply global phase.
self._state.apply_global_phase(global_phase)
return True
return NotImplemented
def with_qubits(self, *new_qubits: 'cirq.Qid') -> 'CircuitOperation':
"""Returns a copy of this operation with an updated qubit mapping.
Args:
new_qubits: A list of qubits to target. Qubits in this list are
matched to qubits in the circuit following default qubit order,
ignoring any existing qubit map.
Returns:
A copy of this operation targeting `new_qubits`.
Raises:
ValueError: `new_qubits` has a different number of qubits than
this operation.
"""
expected = protocols.num_qubits(self.circuit)
if len(new_qubits) != expected:
raise ValueError(f'Expected {expected} qubits, got {len(new_qubits)}.')
return self.with_qubit_mapping(dict(zip(self.qubits, new_qubits)))
def _strat_act_on_clifford_tableau_from_single_qubit_decompose(
val: Any, args: 'cirq.ActOnCliffordTableauArgs', qubits: Sequence['cirq.Qid']
) -> bool:
if num_qubits(val) == 1:
if not has_unitary(val):
return NotImplemented
u = unitary(val)
clifford_gate = SingleQubitCliffordGate.from_unitary(u)
if clifford_gate is not None:
for axis, quarter_turns in clifford_gate.decompose_rotation():
if axis == pauli_gates.X:
common_gates.XPowGate(exponent=quarter_turns / 2)._act_on_(args, qubits)
elif axis == pauli_gates.Y:
common_gates.YPowGate(exponent=quarter_turns / 2)._act_on_(args, qubits)
else:
assert axis == pauli_gates.Z
common_gates.ZPowGate(exponent=quarter_turns / 2)._act_on_(args, qubits)
return True
return NotImplemented
def __pow__(self, power):
if power == 1:
return self
if power == -1:
# HACK: break cycle
from cirq.devices import line_qubit
decomposed = protocols.decompose_once_with_qubits(
self,
qubits=line_qubit.LineQubit.range(protocols.num_qubits(self)),
default=None)
if decomposed is None:
return NotImplemented
inverse_decomposed = protocols.inverse(decomposed, None)
if inverse_decomposed is None:
return NotImplemented
return _InverseCompositeGate(self)
return NotImplemented
def entanglement_fidelity(operation: 'cirq.SupportsKraus') -> float:
r"""Returns entanglement fidelity of a given quantum channel.
Entanglement fidelity $F_e$ of a quantum channel $E: L(H) \to L(H)$ is the overlap between
the maximally entangled state $|\phi\rangle = \frac{1}{\sqrt{dim H}} \sum_i|i\rangle|i\rangle$
and the state obtained by sending one half of $|\phi\rangle$ through the channel $E$, i.e.
$$
F_e = \langle\phi|(E \otimes I)(|\phi\rangle\langle\phi|)|\phi\rangle
$$
where $I: L(H) \to L(H)$ is the identity map.
Args:
operation: Quantum channel whose entanglement fidelity is to be computed.
Returns:
Entanglement fidelity of the channel represented by operation.
"""
f = 0.0
for k in protocols.kraus(operation):
f += np.abs(np.trace(k)) ** 2
n_qubits = protocols.num_qubits(operation)
return float(f / 4**n_qubits)
