def _apply_channel_(self, args: cirq.ApplyChannelArgs):
zero_left = cirq.slice_for_qubits_equal_to(args.left_axes, 0)
one_left = cirq.slice_for_qubits_equal_to(args.left_axes, 1)
zero_right = cirq.slice_for_qubits_equal_to(args.right_axes, 0)
one_right = cirq.slice_for_qubits_equal_to(args.right_axes, 1)
args.out_buffer[:] = 0
np.copyto(dst=args.auxiliary_buffer0, src=args.target_tensor)
for krauss_op in [
np.sqrt(0.5) * np.eye(2, dtype=np.complex128),
np.sqrt(0.5) * x
]:
np.copyto(dst=args.target_tensor, src=args.auxiliary_buffer0)
cirq.apply_matrix_to_slices(args.target_tensor,
krauss_op, [zero_left, one_left],
out=args.auxiliary_buffer1)
cirq.apply_matrix_to_slices(args.auxiliary_buffer1,
np.conjugate(krauss_op),
[zero_right, one_right],
out=args.target_tensor)
args.out_buffer += args.target_tensor
return args.out_buffer
def _apply_channel_(self, args: cirq.ApplyChannelArgs):
args.target_tensor = 0.5 * args.target_tensor + 0.5 * np.dot(
np.dot(x, args.target_tensor), x)
return args.target_tensor