def _apply_unitary_strat(
val: Any, args: 'ApplyMixtureArgs', is_density_matrix: bool
) -> Optional[np.ndarray]:
"""Attempt to use `apply_unitary` and return the result.
If `val` does not support `apply_unitary` returns None.
"""
left_args = ApplyUnitaryArgs(
target_tensor=args.target_tensor,
available_buffer=args.auxiliary_buffer0,
axes=args.left_axes,
)
left_result = apply_unitary(val, left_args, None)
if left_result is None:
return None
if not is_density_matrix:
return left_result
# cast is ok, is_density_matrix being false tells us right_axes isn't None.
right_args = ApplyUnitaryArgs(
target_tensor=np.conjugate(left_result),
available_buffer=args.auxiliary_buffer0,
axes=cast(Tuple[int], args.right_axes),
)
right_result = apply_unitary(val, right_args)
np.conjugate(right_result, out=right_result)
return right_result
def _apply_unitary(val: Any, args: 'ApplyChannelArgs') -> Optional[np.ndarray]:
"""Attempt to use `apply_unitary` and return the result.
If `val` does not support `apply_unitary` returns None.
"""
left_args = ApplyUnitaryArgs(target_tensor=args.target_tensor,
available_buffer=args.auxiliary_buffer0,
axes=args.left_axes)
left_result = apply_unitary(val, left_args, None)
if left_result is None:
return None
right_args = ApplyUnitaryArgs(target_tensor=np.conjugate(left_result),
available_buffer=args.out_buffer,
axes=args.right_axes)
right_result = apply_unitary(val, right_args)
np.conjugate(right_result, out=right_result)
return right_result
