def __call__(self,
state: tf.Tensor,
is_density_matrix: bool = False) -> tf.Tensor:
TensorflowGate.__call__(self, state, is_density_matrix)
if self.rank == 1:
return op.apply_gate(state, self.matrix, self.qubits_tensor,
self.nqubits, self.target_qubits[0])
if self.rank == 2:
return op.apply_two_qubit_gate(state, self.matrix,
self.qubits_tensor, self.nqubits,
*self.target_qubits)
def test_apply_pauli_gate(nqubits, target, gate, compile):
"""Check ``apply_x``, ``apply_y`` and ``apply_z`` kernels."""
matrices = {"x": np.array([[0, 1], [1, 0]], dtype=np.complex128),
"y": np.array([[0, -1j], [1j, 0]], dtype=np.complex128),
"z": np.array([[1, 0], [0, -1]], dtype=np.complex128)}
state = utils.random_tensorflow_complex((2 ** nqubits,), dtype=tf.float64)
target_state = tf.cast(state.numpy(), dtype=state.dtype)
qubits = qubits_tensor(nqubits, [target])
target_state = op.apply_gate(state, matrices[gate], qubits, nqubits, target, get_threads())
def apply_operator(state):
qubits = qubits_tensor(nqubits, [target])
return getattr(op, "apply_{}".format(gate))(state, qubits, nqubits, target, get_threads())
if compile:
apply_operator = tf.function(apply_operator)
state = apply_operator(state)
np.testing.assert_allclose(target_state.numpy(), state.numpy())
def apply_operator(state):
qubits = qubits_tensor(nqubits, [nqubits - 1], controls)
return op.apply_gate(state, xgate, qubits, nqubits, nqubits - 1)
def apply_operator(state, gate):
qubits = qubits_tensor(nqubits, [target])
return op.apply_gate(state, gate, qubits, nqubits, target)
def __call__(self,
state: tf.Tensor,
is_density_matrix: bool = False) -> tf.Tensor:
super(MatrixGate, self).__call__(state, is_density_matrix)
return op.apply_gate(state, self.matrix, self.qubits_tensor,
self.nqubits, self.target_qubits[0])
def apply_operator(state): qubits = qubits_tensor(nqubits, [target], controls) return op.apply_gate(state, gate, qubits, nqubits, target, get_threads())
