def controlled(
self,
num_controls: int = None,
control_values: Optional[Sequence[Union[int, Collection[int]]]] = None,
control_qid_shape: Optional[Tuple[int, ...]] = None,
) -> raw_types.Gate:
"""Returns a controlled `XPowGate` with two additional controls.
The `controlled` method of the `Gate` class, of which this class is a
child, returns a `ControlledGate` with `sub_gate = self`. This method
overrides this behavior to return a `ControlledGate` with
`sub_gate = XPowGate`.
"""
if num_controls == 0:
return self
return controlled_gate.ControlledGate(
controlled_gate.ControlledGate(
common_gates.XPowGate(exponent=self._exponent,
global_shift=self._global_shift),
num_controls=2,
),
num_controls=num_controls,
control_values=control_values,
control_qid_shape=control_qid_shape,
)
def _apply_unitary_(self, args: protocols.ApplyUnitaryArgs) -> np.ndarray:
if protocols.is_parameterized(self):
return NotImplemented
p = 1j**(2 * self._exponent * self._global_shift)
if p != 1:
args.target_tensor *= p
return protocols.apply_unitary(controlled_gate.ControlledGate(
controlled_gate.ControlledGate(pauli_gates.X**self.exponent)),
protocols.ApplyUnitaryArgs(
args.target_tensor,
args.available_buffer, args.axes),
default=NotImplemented)
def _apply_unitary_to_tensor_(self,
target_tensor: np.ndarray,
available_buffer: np.ndarray,
axes: Sequence[int],
) -> np.ndarray:
return protocols.apply_unitary_to_tensor(
controlled_gate.ControlledGate(
controlled_gate.ControlledGate(
common_gates.X**self.exponent)),
target_tensor,
available_buffer,
axes,
default=NotImplemented)
def gate(self) -> Optional['cirq.ControlledGate']:
if self.sub_operation.gate is None:
return None
return controlled_gate.ControlledGate(
self.sub_operation.gate,
control_values=self.control_values,
control_qid_shape=[q.dimension for q in self.controls])
def _apply_unitary_(self,
args: 'protocols.ApplyUnitaryArgs') -> np.ndarray:
return protocols.apply_unitary(
controlled_gate.ControlledGate(swap_gates.SWAP),
protocols.ApplyUnitaryArgs(args.target_tensor,
args.available_buffer, args.axes),
default=NotImplemented)
def _apply_unitary_to_tensor_(
self,
target_tensor: np.ndarray,
available_buffer: np.ndarray,
axes: Sequence[int],
) -> np.ndarray:
if protocols.is_parameterized(self):
return NotImplemented
p = 1j**(2 * self._exponent * self._global_shift)
if p != 1:
target_tensor *= p
return protocols.apply_unitary_to_tensor(
controlled_gate.ControlledGate(
controlled_gate.ControlledGate(common_gates.X**self.exponent)),
target_tensor,
available_buffer,
axes,
default=NotImplemented)
def controlled(
self,
num_controls: int = None,
control_values: Optional[Sequence[Union[int, Collection[int]]]] = None,
control_qid_shape: Optional[Tuple[int, ...]] = None,
) -> raw_types.Gate:
"""Returns a controlled `SWAP` with one additional control.
The `controlled` method of the `Gate` class, of which this class is a
child, returns a `ControlledGate` with `sub_gate = self`. This method
overrides this behavior to return a `ControlledGate` with
`sub_gate = SWAP`.
"""
if num_controls == 0:
return self
return controlled_gate.ControlledGate(
controlled_gate.ControlledGate(swap_gates.SWAP, num_controls=1),
num_controls=num_controls,
control_values=control_values,
control_qid_shape=control_qid_shape,
)