def test_get_instructions_for_qargs(self):
with self.assertRaises(KeyError):
self.empty_target.operations_for_qargs((0, ))
expected = [RZGate(self.theta), IGate(), SXGate(), XGate(), Measure()]
res = self.ibm_target.operations_for_qargs((0, ))
for gate in expected:
self.assertIn(gate, res)
expected = [ECRGate()]
res = self.fake_backend_target.operations_for_qargs((1, 0))
for gate in expected:
self.assertIn(gate, res)
expected = [CXGate()]
res = self.fake_backend_target.operations_for_qargs((0, 1))
self.assertEqual(expected, res)
ideal_sim_expected = [
UGate(self.theta, self.phi, self.lam),
RXGate(self.theta),
RYGate(self.theta),
RZGate(self.theta),
CXGate(),
ECRGate(),
CCXGate(),
Measure(),
]
for gate in ideal_sim_expected:
self.assertIn(gate,
self.ideal_sim_target.operations_for_qargs(None))
def _generate_xxyy_test_case(self):
"""
Generates a random pentuple of values (a_source, b_source), beta, (a_target, b_target) s.t.
CAN(a_source, b_source) * exp(-i(s ZI + t IZ)) * CAN(beta)
=
exp(-i(u ZI + v IZ)) * CAN(a_target, b_target) * exp(-i(x ZI + y IZ))
admits a solution in (s, t, u, v, x, y).
Returns (source_coordinate, interaction, target_coordinate).
"""
source_coordinate = [self.rng.random(), self.rng.random(), 0.0]
source_coordinate = [
source_coordinate[0] * np.pi / 8,
source_coordinate[1] * source_coordinate[0] * np.pi / 8,
0.0,
]
interaction = [self.rng.random() * np.pi / 8]
z_angles = [
self.rng.random() * np.pi / 8,
self.rng.random() * np.pi / 8
]
prod = (canonical_matrix(*source_coordinate) @ np.kron(
RZGate(2 * z_angles[0]).to_matrix(),
RZGate(2 * z_angles[1]).to_matrix()) @ canonical_matrix(
interaction[0], 0.0, 0.0))
target_coordinate = weyl_coordinates(prod)
self.assertAlmostEqual(target_coordinate[-1], 0.0, delta=EPSILON)
return source_coordinate, interaction, target_coordinate
def test_commutative_circuit3(self):
"""
A simple circuit where three CNOTs commute, the first and the last cancel,
also two X gates cancel and two Rz gates combine.
qr0:-------.------------------.------------- qr0:-------------
| |
qr1:------(+)------(+)--[X]--(+)-------[X]-- = qr1:--------(+)--
| |
qr2:------[Rz]--.---.----.---[Rz]-[T]--[S]-- qr2:--[U1]---.---
| |
qr3:-[Rz]--[X]-(+)------(+)--[X]-[Rz]------- qr3:--[Rz]-------
"""
qr = QuantumRegister(4, "qr")
circuit = QuantumCircuit(qr)
circuit.cx(qr[0], qr[1])
circuit.rz(np.pi / 3, qr[2])
circuit.rz(np.pi / 3, qr[3])
circuit.x(qr[3])
circuit.cx(qr[2], qr[3])
circuit.cx(qr[2], qr[1])
circuit.cx(qr[2], qr[3])
circuit.rz(np.pi / 3, qr[2])
circuit.t(qr[2])
circuit.x(qr[3])
circuit.rz(np.pi / 3, qr[3])
circuit.s(qr[2])
circuit.x(qr[1])
circuit.cx(qr[0], qr[1])
circuit.x(qr[1])
passmanager = PassManager()
passmanager.append(
[
CommutationAnalysis(),
CommutativeCancellation(),
Size(),
FixedPoint("size")
],
do_while=lambda property_set: not property_set["size_fixed_point"],
)
new_circuit = passmanager.run(circuit)
expected = QuantumCircuit(qr)
expected.append(RZGate(np.pi * 17 / 12), [qr[2]])
expected.append(RZGate(np.pi * 2 / 3), [qr[3]])
expected.cx(qr[2], qr[1])
self.assertEqual(
expected,
new_circuit,
msg=f"expected:\n{expected}\nnew_circuit:\n{new_circuit}")
def test_gates_with_parameters(self):
"""Check commutativity between (non-parameterized) gates with parameters."""
comm_checker = CommutationChecker()
res = comm_checker.commute(RZGate(0), [0], [], XGate(), [0], [])
self.assertTrue(res)
res = comm_checker.commute(RZGate(np.pi / 2), [0], [], XGate(), [0],
[])
self.assertFalse(res)
res = comm_checker.commute(RZGate(np.pi / 2), [0], [], RZGate(0), [0],
[])
self.assertTrue(res)
def test_parameterized_gates_do_not_cancel(self):
"""Test that parameterized gates do not cancel.
This test should be modified when inverse and commutativity checking
get improved to handle parameterized gates.
"""
gate = RZGate(Parameter("Theta"))
circuit = QuantumCircuit(1)
circuit.append(gate, [0])
circuit.append(gate.inverse(), [0])
passmanager = PassManager(CommutativeInverseCancellation())
new_circuit = passmanager.run(circuit)
self.assertEqual(circuit, new_circuit)
def test_is_identity(self):
""" The is_identity function determines whether a pair of gates
forms the identity, when ignoring control qubits.
"""
seq = [DAGNode({'type': 'op', 'op': XGate().control()}),
DAGNode({'type': 'op', 'op': XGate().control(2)})]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [DAGNode({'type': 'op', 'op': RZGate(-pi/2).control()}),
DAGNode({'type': 'op', 'op': RZGate(pi/2).control(2)})]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [DAGNode({'type': 'op', 'op': CSwapGate()}),
DAGNode({'type': 'op', 'op': SwapGate()})]
self.assertTrue(HoareOptimizer()._is_identity(seq))
def test_is_identity(self):
"""The is_identity function determines whether a pair of gates
forms the identity, when ignoring control qubits.
"""
seq = [DAGOpNode(op=XGate().control()), DAGOpNode(op=XGate().control(2))]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [
DAGOpNode(op=RZGate(-pi / 2).control()),
DAGOpNode(op=RZGate(pi / 2).control(2)),
]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [DAGOpNode(op=CSwapGate()), DAGOpNode(op=SwapGate())]
self.assertTrue(HoareOptimizer()._is_identity(seq))
def test_grz_equivalence(self):
"""Test global RZ gate is same as 3 individual RZ gates."""
circuit = GRZ(num_qubits=3, phi=2 * np.pi / 3)
expected = QuantumCircuit(3, name="grz")
for i in range(3):
expected.append(RZGate(phi=2 * np.pi / 3), [i])
self.assertEqual(expected, circuit)
def exp_i(self) -> OperatorBase:
""" Return a ``CircuitOp`` equivalent to e^-iH for this operator H. """
# if only one qubit is significant, we can perform the evolution
corrected_x = self.primitive.x[::-1] # type: ignore
corrected_z = self.primitive.z[::-1] # type: ignore
# pylint: disable=import-outside-toplevel,no-member
sig_qubits = np.logical_or(corrected_x, corrected_z)
if np.sum(sig_qubits) == 0:
# e^I is just a global phase, but we can keep track of it! Should we?
# For now, just return identity
return PauliOp(self.primitive)
if np.sum(sig_qubits) == 1:
sig_qubit_index = sig_qubits.tolist().index(True)
coeff = np.real(self.coeff) \
if not isinstance(self.coeff, ParameterExpression) \
else self.coeff
# Y rotation
if corrected_x[sig_qubit_index] and corrected_z[sig_qubit_index]:
rot_op = PrimitiveOp(RYGate(coeff))
# Z rotation
elif corrected_z[sig_qubit_index]:
rot_op = PrimitiveOp(RZGate(coeff))
# X rotation
elif corrected_x[sig_qubit_index]:
rot_op = PrimitiveOp(RXGate(coeff))
from ..operator_globals import I
left_pad = I.tensorpower(sig_qubit_index)
right_pad = I.tensorpower(self.num_qubits - sig_qubit_index - 1)
# Need to use overloaded operators here in case left_pad == I^0
return left_pad ^ rot_op ^ right_pad
else:
from ..evolutions.evolved_op import EvolvedOp
return EvolvedOp(self)
def test_commutative_circuit2(self):
"""
A simple circuit where three CNOTs commute, the first and the last cancel,
also two X gates cancel and two Rz gates combine.
qr0:----.---------------.-------- qr0:-------------
| |
qr1:---(+)---(+)--[X]--(+)--[X]-- = qr1:--------(+)--
| |
qr2:---[Rz]---.---[Rz]-[T]--[S]-- qr2:--[U1]---.---
"""
qr = QuantumRegister(3, "qr")
circuit = QuantumCircuit(qr)
circuit.cx(qr[0], qr[1])
circuit.rz(np.pi / 3, qr[2])
circuit.cx(qr[2], qr[1])
circuit.rz(np.pi / 3, qr[2])
circuit.t(qr[2])
circuit.s(qr[2])
circuit.x(qr[1])
circuit.cx(qr[0], qr[1])
circuit.x(qr[1])
passmanager = PassManager()
passmanager.append(CommutativeCancellation())
new_circuit = passmanager.run(circuit)
expected = QuantumCircuit(qr)
expected.append(RZGate(np.pi * 17 / 12), [qr[2]])
expected.cx(qr[2], qr[1])
expected.global_phase = (np.pi * 17 / 12 - (2 * np.pi / 3)) / 2
self.assertEqual(expected, new_circuit)
def test_operations(self):
self.assertEqual(self.empty_target.operations, [])
ibm_expected = [
RZGate(self.theta),
IGate(),
SXGate(),
XGate(),
CXGate(),
Measure()
]
for gate in ibm_expected:
self.assertIn(gate, self.ibm_target.operations)
aqt_expected = [
RZGate(self.theta),
RXGate(self.theta),
RYGate(self.theta),
RGate(self.theta, self.phi),
RXXGate(self.theta),
]
for gate in aqt_expected:
self.assertIn(gate, self.aqt_target.operations)
fake_expected = [
UGate(self.fake_backend._theta, self.fake_backend._phi,
self.fake_backend._lam),
CXGate(),
Measure(),
ECRGate(),
RXGate(math.pi / 6),
RXGate(self.fake_backend._theta),
]
for gate in fake_expected:
self.assertIn(gate, self.fake_backend_target.operations)
ideal_sim_expected = [
UGate(self.theta, self.phi, self.lam),
RXGate(self.theta),
RYGate(self.theta),
RZGate(self.theta),
CXGate(),
ECRGate(),
CCXGate(),
Measure(),
]
for gate in ideal_sim_expected:
self.assertIn(gate, self.ideal_sim_target.operations)
def gate_to_qiskit(gate2):
if gate2.name == 'X':
return XGate()
elif gate2.name == 'Ry':
return RYGate(-gate2.arg)
elif gate2.name == 'Rz':
return RZGate(-gate2.arg)
elif gate2.name == 'R1':
return U1Gate(gate2.arg)
else:
raise RuntimeError("Can't implement: %s" % gate2)
def rz_matrix(phi: float) -> np.ndarray:
"""
Computes an RZ rotation by the angle of ``phi``.
Args:
phi: rotation angle.
Returns:
an RZ rotation matrix.
"""
return RZGate(phi).to_matrix()
def test_decompose_xxyy(self):
"""
Test that decompose_xxyy_into_xxyy_xx correctly recovers decompositions.
"""
for _ in range(100):
source_coordinate, interaction, target_coordinate = self._generate_xxyy_test_case(
)
r, s, u, v, x, y = decompose_xxyy_into_xxyy_xx(
target_coordinate[0],
target_coordinate[1],
source_coordinate[0],
source_coordinate[1],
interaction[0],
)
prod = (
np.kron(RZGate(2 * r).to_matrix(),
RZGate(2 * s).to_matrix())
@ canonical_matrix(*source_coordinate) @ np.kron(
RZGate(2 * u).to_matrix(),
RZGate(2 * v).to_matrix()) @ canonical_matrix(
interaction[0], 0.0, 0.0) @ np.kron(
RZGate(2 * x).to_matrix(),
RZGate(2 * y).to_matrix()))
expected = canonical_matrix(*target_coordinate)
self.assertTrue(np.all(np.abs(prod - expected) < EPSILON))
def test_parameterized_gates(self):
"""Check commutativity between parameterized gates, both with free and with
bound parameters."""
comm_checker = CommutationChecker()
# gate that has parameters but is not considered parameterized
rz_gate = RZGate(np.pi / 2)
self.assertEqual(len(rz_gate.params), 1)
self.assertFalse(rz_gate.is_parameterized())
# gate that has parameters and is considered parameterized
rz_gate_theta = RZGate(Parameter("Theta"))
rz_gate_phi = RZGate(Parameter("Phi"))
self.assertEqual(len(rz_gate_theta.params), 1)
self.assertTrue(rz_gate_theta.is_parameterized())
# gate that has no parameters and is not considered parameterized
cx_gate = CXGate()
self.assertEqual(len(cx_gate.params), 0)
self.assertFalse(cx_gate.is_parameterized())
# We should detect that these gates commute
res = comm_checker.commute(rz_gate, [0], [], cx_gate, [0, 1], [])
self.assertTrue(res)
# We should detect that these gates commute
res = comm_checker.commute(rz_gate, [0], [], rz_gate, [0], [])
self.assertTrue(res)
# We should detect that parameterized gates over disjoint qubit subsets commute
res = comm_checker.commute(rz_gate_theta, [0], [], rz_gate_theta, [1],
[])
self.assertTrue(res)
# We should detect that parameterized gates over disjoint qubit subsets commute
res = comm_checker.commute(rz_gate_theta, [0], [], rz_gate_phi, [1],
[])
self.assertTrue(res)
# We should detect that parameterized gates over disjoint qubit subsets commute
res = comm_checker.commute(rz_gate_theta, [2], [], cx_gate, [1, 3], [])
self.assertTrue(res)
# However, for now commutativity checker should return False when checking
# commutativity between a parameterized gate and some other gate, when
# the two gates are over intersecting qubit subsets.
# This check should be changed if commutativity checker is extended to
# handle parameterized gates better.
res = comm_checker.commute(rz_gate_theta, [0], [], cx_gate, [0, 1], [])
self.assertFalse(res)
res = comm_checker.commute(rz_gate_theta, [0], [], rz_gate, [0], [])
self.assertFalse(res)
class TestParameterCtrlState(QiskitTestCase):
"""Test gate equality with ctrl_state parameter."""
@data((RXGate(0.5), CRXGate(0.5)), (RYGate(0.5), CRYGate(0.5)),
(RZGate(0.5), CRZGate(0.5)), (XGate(), CXGate()),
(YGate(), CYGate()), (ZGate(), CZGate()),
(U1Gate(0.5), CU1Gate(0.5)), (SwapGate(), CSwapGate()),
(HGate(), CHGate()), (U3Gate(0.1, 0.2, 0.3), CU3Gate(0.1, 0.2, 0.3)))
@unpack
def test_ctrl_state_one(self, gate, controlled_gate):
"""Test controlled gates with ctrl_state
See https://github.com/Qiskit/qiskit-terra/pull/4025
"""
self.assertEqual(gate.control(1, ctrl_state='1'), controlled_gate)
def test_parameterized_circuit_for_simulator(self):
"""Verify that a parameterized circuit can be transpiled for a simulator backend."""
qr = QuantumRegister(2, name='qr')
qc = QuantumCircuit(qr)
theta = Parameter('theta')
qc.rz(theta, qr[0])
transpiled_qc = transpile(qc, backend=BasicAer.get_backend('qasm_simulator'))
expected_qc = QuantumCircuit(qr)
expected_qc.append(RZGate(theta), [qr[0]])
self.assertEqual(expected_qc, transpiled_qc)
def test_parameter_expression_circuit_for_simulator(self):
"""Verify that a circuit including expressions of parameters can be
transpiled for a simulator backend."""
qr = QuantumRegister(2, name='qr')
qc = QuantumCircuit(qr)
theta = Parameter('theta')
square = theta * theta
qc.rz(square, qr[0])
transpiled_qc = transpile(qc, backend=BasicAer.get_backend('qasm_simulator'))
expected_qc = QuantumCircuit(qr)
expected_qc.append(RZGate(square), [qr[0]])
self.assertEqual(expected_qc, transpiled_qc)
def test_compose_one_liner(self):
"""Test building a circuit in one line, for fun.
"""
circ = QuantumCircuit(3)
h = HGate()
rz = RZGate(0.1)
cx = CXGate()
ccx = CCXGate()
circ = circ.compose(h, [0]).compose(cx, [0, 2]).compose(ccx, [2, 1, 0]).compose(rz, [1])
expected = QuantumCircuit(3)
expected.h(0)
expected.cx(0, 2)
expected.ccx(2, 1, 0)
expected.rz(0.1, 1)
self.assertEqual(circ, expected)
def test_instruction_schedule_map_ideal_sim_backend(self):
ideal_sim_target = Target(num_qubits=3)
theta = Parameter("theta")
phi = Parameter("phi")
lam = Parameter("lambda")
for inst in [
UGate(theta, phi, lam),
RXGate(theta),
RYGate(theta),
RZGate(theta),
CXGate(),
ECRGate(),
CCXGate(),
Measure(),
]:
ideal_sim_target.add_instruction(inst, {None: None})
inst_map = ideal_sim_target.instruction_schedule_map()
self.assertEqual(InstructionScheduleMap(), inst_map)
def _define(self):
# The y angle matrix stands for the absolute value, while the z angles stand for phases
# The difficulty lies in the "global" phases that must be later accounted for in each subspace
y_angle_matrix = self._to_angle_matrix_y()
z_angle_matrix, global_phases = self._to_angle_matrix_z()
# As the subspace phase correction is a very expensive module, we only want to do it if the
# z rotation matrix is non-zero!
no_z_rotations = abs(sparse.linalg.norm(z_angle_matrix)) < 1e-6
control = QuantumRegister(self.num_controls_qb, "q^c")
target = QuantumRegister(self.num_targets_qb, "q^t")
qc_y = QuantumCircuit(control, target, name=self.name)
qc_z = QuantumCircuit(control, target, name=self.name)
for l in range(1, self.num_targets_qb + 1):
qargs = list(control) + target[0:l]
# If there are no z-rotations we save a lot of gates, so we want to rule that out
if not no_z_rotations:
angles_z: sparse.spmatrix = z_angle_matrix[range(ControlledStatePreparationGate._chi(l) - 1, ControlledStatePreparationGate._chi(l + 1) - 1), :]
angles_z = angles_z.reshape(-1, 1)
gate_z = UniformRotationGate(gate=lambda a: RZGate(a), alpha=angles_z.todok())
qc_z.append(gate_z, qargs)
qc_z.barrier()
# The uniform rotation for the y rotation will take care of the absolute value
angles_y: sparse.spmatrix = y_angle_matrix[range(ControlledStatePreparationGate._chi(l) - 1, ControlledStatePreparationGate._chi(l + 1) - 1), :]
angles_y = angles_y.reshape(-1, 1)
gate_y = UniformRotationGate(gate=lambda a: RYGate(a), alpha=angles_y.todok())
qc_y.append(gate_y, qargs)
qc_y.barrier()
if not no_z_rotations:
# A relative phase correction is pretty intensive: a state preparation on the control
global_phase_correction = MöttönenStatePreparationGate(
sparse.dok_matrix(np.exp(1.0j * global_phases.T.toarray())),
neglect_absolute_value=True
)
qc_z.append(global_phase_correction, qargs=control)
qc_z.barrier()
qc = qc_y + qc_z
self._definition = qc
def test_all_gates(self):
"""Test all gates on 1 and 2 qubits
q0:-[H]-[H]--[x]-[x]--[y]-[y]--[rz]-[rz]--[u1]-[u1]-[rx]-[rx]---.--.--.--.--.--.-
| | | | | |
q1:-------------------------------------------------------------X--X--Y--Y--.--.-
=
qr0:---[u1]---
qr1:----------
"""
qr = QuantumRegister(2, "q")
circuit = QuantumCircuit(qr)
circuit.h(qr[0])
circuit.h(qr[0])
circuit.x(qr[0])
circuit.x(qr[0])
circuit.y(qr[0])
circuit.y(qr[0])
circuit.rz(0.5, qr[0])
circuit.rz(0.5, qr[0])
circuit.append(U1Gate(0.5),
[qr[0]]) # TODO this should work with Phase gates too
circuit.append(U1Gate(0.5), [qr[0]])
circuit.rx(0.5, qr[0])
circuit.rx(0.5, qr[0])
circuit.cx(qr[0], qr[1])
circuit.cx(qr[0], qr[1])
circuit.cy(qr[0], qr[1])
circuit.cy(qr[0], qr[1])
circuit.cz(qr[0], qr[1])
circuit.cz(qr[0], qr[1])
passmanager = PassManager()
passmanager.append(CommutativeCancellation())
new_circuit = passmanager.run(circuit)
expected = QuantumCircuit(qr)
expected.append(RZGate(2.0), [qr[0]])
expected.rx(1.0, qr[0])
self.assertEqual(expected, new_circuit)
def test_instructions(self):
self.assertEqual(self.empty_target.instructions, [])
ibm_expected = [
(IGate(), (0, )),
(IGate(), (1, )),
(IGate(), (2, )),
(IGate(), (3, )),
(IGate(), (4, )),
(RZGate(self.theta), (0, )),
(RZGate(self.theta), (1, )),
(RZGate(self.theta), (2, )),
(RZGate(self.theta), (3, )),
(RZGate(self.theta), (4, )),
(SXGate(), (0, )),
(SXGate(), (1, )),
(SXGate(), (2, )),
(SXGate(), (3, )),
(SXGate(), (4, )),
(XGate(), (0, )),
(XGate(), (1, )),
(XGate(), (2, )),
(XGate(), (3, )),
(XGate(), (4, )),
(CXGate(), (3, 4)),
(CXGate(), (4, 3)),
(CXGate(), (3, 1)),
(CXGate(), (1, 3)),
(CXGate(), (1, 2)),
(CXGate(), (2, 1)),
(CXGate(), (0, 1)),
(CXGate(), (1, 0)),
(Measure(), (0, )),
(Measure(), (1, )),
(Measure(), (2, )),
(Measure(), (3, )),
(Measure(), (4, )),
]
self.assertEqual(ibm_expected, self.ibm_target.instructions)
ideal_sim_expected = [
(UGate(self.theta, self.phi, self.lam), None),
(RXGate(self.theta), None),
(RYGate(self.theta), None),
(RZGate(self.theta), None),
(CXGate(), None),
(ECRGate(), None),
(CCXGate(), None),
(Measure(), None),
]
self.assertEqual(ideal_sim_expected,
self.ideal_sim_target.instructions)
def setUp(self):
super().setUp()
self.target = Target()
# U gate in qubit 0.
self.theta = Parameter("theta")
self.phi = Parameter("phi")
self.lam = Parameter("lambda")
u_props = {
(0, ): InstructionProperties(duration=5.23e-8, error=0.00038115),
}
self.target.add_instruction(UGate(self.theta, self.phi, self.lam),
u_props)
# Rz gate in qubit 1.
rz_props = {
(1, ): InstructionProperties(duration=0.0, error=0),
}
self.target.add_instruction(RZGate(self.phi), rz_props)
# X gate in qubit 1.
x_props = {
(1, ):
InstructionProperties(duration=3.5555555555555554e-08,
error=0.00020056469709026198),
}
self.target.add_instruction(XGate(), x_props)
# SX gate in qubit 1.
sx_props = {
(1, ):
InstructionProperties(duration=3.5555555555555554e-08,
error=0.00020056469709026198),
}
self.target.add_instruction(SXGate(), sx_props)
cx_props = {
(0, 1): InstructionProperties(duration=5.23e-7, error=0.00098115),
(1, 0): InstructionProperties(duration=4.52e-7, error=0.00132115),
}
self.target.add_instruction(CXGate(), cx_props)
def test_multiple_gate_error_matrix(self):
"""Test error matrix ona small target with multiple gets on each qubit generates"""
target = Target(num_qubits=3)
phi = Parameter("phi")
lam = Parameter("lam")
theta = Parameter("theta")
target.add_instruction(
RZGate(phi), {(i, ): InstructionProperties(duration=0, error=0)
for i in range(3)})
target.add_instruction(
UGate(theta, phi, lam),
{(i, ): InstructionProperties(duration=1e-7, error=1e-2)
for i in range(3)},
)
cx_props = {
(0, 1): InstructionProperties(error=1e-3),
(0, 2): InstructionProperties(error=1e-3),
(1, 0): InstructionProperties(error=1e-3),
(1, 2): InstructionProperties(error=1e-3),
(2, 0): InstructionProperties(error=1e-3),
(2, 1): InstructionProperties(error=1e-3),
}
target.add_instruction(CXGate(), cx_props)
ecr_props = {
(0, 1): InstructionProperties(error=2e-2),
(1, 2): InstructionProperties(error=2e-2),
(2, 0): InstructionProperties(error=2e-2),
}
target.add_instruction(ECRGate(), ecr_props)
expected_error_matrix = np.array([
[1e-2, 2e-2, 1e-3],
[1e-3, 1e-2, 2e-2],
[2e-2, 1e-3, 1e-2],
])
np.testing.assert_array_equal(expected_error_matrix,
DenseLayout(target=target).error_mat)
class TestCollect2qBlocks(QiskitTestCase):
"""
Tests to verify that blocks of 2q interactions are found correctly.
"""
def test_blocks_in_topological_order(self):
"""the pass returns blocks in correct topological order
______
q0:--[p]-------.---- q0:-------------| |--
| ______ | U2 |
q1:--[u]--(+)-(+)--- = q1:---| |--|______|--
| | U1 |
q2:--------.-------- q2:---|______|------------
"""
qr = QuantumRegister(3, "qr")
qc = QuantumCircuit(qr)
qc.p(0.5, qr[0])
qc.u(0.0, 0.2, 0.6, qr[1])
qc.cx(qr[2], qr[1])
qc.cx(qr[0], qr[1])
dag = circuit_to_dag(qc)
topo_ops = list(dag.topological_op_nodes())
block_1 = [topo_ops[1], topo_ops[2]]
block_2 = [topo_ops[0], topo_ops[3]]
pass_ = Collect2qBlocks()
pass_.run(dag)
self.assertTrue(pass_.property_set["block_list"], [block_1, block_2])
def test_block_interrupted_by_gate(self):
"""Test that blocks interrupted by a gate that can't be added
to the block can be collected correctly
This was raised in #2775 where a measure in the middle of a block
stopped the block collection from working properly. This was because
the pass didn't expect to have measures in the middle of the circuit.
blocks : [['cx', 'id', 'id', 'id'], ['id', 'cx']]
┌───┐┌───┐┌─┐ ┌───┐┌───┐
q_0: |0>┤ X ├┤ I ├┤M├─────┤ I ├┤ X ├
└─┬─┘├───┤└╥┘┌───┐└───┘└─┬─┘
q_1: |0>──■──┤ I ├─╫─┤ I ├───────■──
└───┘ ║ └───┘
c_0: 0 ═══════════╩════════════════
"""
qc = QuantumCircuit(2, 1)
qc.cx(1, 0)
qc.i(0)
qc.i(1)
qc.measure(0, 0)
qc.i(0)
qc.i(1)
qc.cx(1, 0)
dag = circuit_to_dag(qc)
pass_ = Collect2qBlocks()
pass_.run(dag)
# list from Collect2QBlocks of nodes that it should have put into blocks
good_names = ["cx", "u1", "u2", "u3", "id"]
dag_nodes = [
node for node in dag.topological_op_nodes()
if node.name in good_names
]
# we have to convert them to sets as the ordering can be different
# but equivalent between python 3.5 and 3.7
# there is no implied topology in a block, so this isn't an issue
dag_nodes = [set(dag_nodes[:4]), set(dag_nodes[4:])]
pass_nodes = [set(bl) for bl in pass_.property_set["block_list"]]
self.assertEqual(dag_nodes, pass_nodes)
def test_block_with_classical_register(self):
"""Test that only blocks that share quantum wires are added to the block.
It was the case that gates which shared a classical wire could be added to
the same block, despite not sharing the same qubits. This was fixed in #2956.
┌─────────────────────┐
q_0: |0>────────────────────┤ U2(0.25*pi,0.25*pi) ├
┌─────────────┐└──────────┬──────────┘
q_1: |0>──■──┤ U1(0.25*pi) ├───────────┼───────────
┌─┴─┐└──────┬──────┘ │
q_2: |0>┤ X ├───────┼──────────────────┼───────────
└───┘ ┌──┴──┐ ┌──┴──┐
c0_0: 0 ═════════╡ = 0 ╞════════════╡ = 0 ╞════════
└─────┘ └─────┘
Previously the blocks collected were : [['cx', 'u1', 'u2']]
This is now corrected to : [['cx', 'u1']]
"""
qasmstr = """
OPENQASM 2.0;
include "qelib1.inc";
qreg q[3];
creg c0[1];
cx q[1],q[2];
if(c0==0) u1(0.25*pi) q[1];
if(c0==0) u2(0.25*pi, 0.25*pi) q[0];
"""
qc = QuantumCircuit.from_qasm_str(qasmstr)
pass_manager = PassManager()
pass_manager.append(Collect2qBlocks())
pass_manager.run(qc)
self.assertEqual(
[["cx"]], [[n.name for n in block]
for block in pass_manager.property_set["block_list"]])
def test_do_not_merge_conditioned_gates(self):
"""Validate that classically conditioned gates are never considered for
inclusion in a block. Note that there are cases where gates conditioned
on the same (register, value) pair could be correctly merged, but this is
not yet implemented.
┌────────┐┌────────┐┌────────┐ ┌───┐
qr_0: |0>┤ P(0.1) ├┤ P(0.2) ├┤ P(0.3) ├──■───┤ X ├────■───
└────────┘└───┬────┘└───┬────┘┌─┴─┐ └─┬─┘ ┌─┴─┐
qr_1: |0>──────────────┼─────────┼─────┤ X ├───■────┤ X ├─
│ │ └───┘ │ └─┬─┘
qr_2: |0>──────────────┼─────────┼─────────────┼──────┼───
┌──┴──┐ ┌──┴──┐ ┌──┴──┐┌──┴──┐
cr_0: 0 ═══════════╡ ╞═══╡ ╞═══════╡ ╞╡ ╞
│ = 0 │ │ = 0 │ │ = 0 ││ = 1 │
cr_1: 0 ═══════════╡ ╞═══╡ ╞═══════╡ ╞╡ ╞
└─────┘ └─────┘ └─────┘└─────┘
Previously the blocks collected were : [['p', 'p', 'p', 'cx', 'cx', 'cx']]
This is now corrected to : [['cx']]
"""
# ref: https://github.com/Qiskit/qiskit-terra/issues/3215
qr = QuantumRegister(3, "qr")
cr = ClassicalRegister(2, "cr")
qc = QuantumCircuit(qr, cr)
qc.p(0.1, 0)
qc.p(0.2, 0).c_if(cr, 0)
qc.p(0.3, 0).c_if(cr, 0)
qc.cx(0, 1)
qc.cx(1, 0).c_if(cr, 0)
qc.cx(0, 1).c_if(cr, 1)
pass_manager = PassManager()
pass_manager.append(Collect2qBlocks())
pass_manager.run(qc)
self.assertEqual(
[["cx"]], [[n.name for n in block]
for block in pass_manager.property_set["block_list"]])
@unpack
@data(
(CXGate(), U1Gate(0.1), U2Gate(0.2, 0.3)),
(RXXGate(pi / 2), RZGate(0.1), RXGate(pi / 2)),
(
Gate("custom2qgate", 2, []),
Gate("custom1qgate1", 1, []),
Gate("custom1qgate2", 1, []),
),
)
def test_collect_arbitrary_gates(self, twoQ_gate, oneQ_gate1, oneQ_gate2):
"""Validate we can collect blocks irrespective of gate types in the circuit."""
qc = QuantumCircuit(3)
# Block 1 - q[0] and q[1]
qc.append(oneQ_gate1, [0])
qc.append(oneQ_gate2, [1])
qc.append(twoQ_gate, [0, 1])
qc.append(oneQ_gate1, [0])
qc.append(oneQ_gate2, [1])
# Block 2 - q[1] and q[2]
qc.append(oneQ_gate1, [1])
qc.append(oneQ_gate2, [2])
qc.append(twoQ_gate, [1, 2])
qc.append(oneQ_gate1, [1])
qc.append(oneQ_gate2, [2])
# Block 3 - q[0] and q[1]
qc.append(oneQ_gate1, [0])
qc.append(oneQ_gate2, [1])
qc.append(twoQ_gate, [0, 1])
qc.append(oneQ_gate1, [0])
qc.append(oneQ_gate2, [1])
pass_manager = PassManager()
pass_manager.append(Collect2qBlocks())
pass_manager.run(qc)
self.assertEqual(len(pass_manager.property_set["block_list"]), 3)
def setUp(self):
super().setUp()
self.fake_backend = FakeBackendV2()
self.fake_backend_target = self.fake_backend.target
self.theta = Parameter("theta")
self.phi = Parameter("phi")
self.ibm_target = Target()
i_props = {
(0, ): InstructionProperties(duration=35.5e-9, error=0.000413),
(1, ): InstructionProperties(duration=35.5e-9, error=0.000502),
(2, ): InstructionProperties(duration=35.5e-9, error=0.0004003),
(3, ): InstructionProperties(duration=35.5e-9, error=0.000614),
(4, ): InstructionProperties(duration=35.5e-9, error=0.006149),
}
self.ibm_target.add_instruction(IGate(), i_props)
rz_props = {
(0, ): InstructionProperties(duration=0, error=0),
(1, ): InstructionProperties(duration=0, error=0),
(2, ): InstructionProperties(duration=0, error=0),
(3, ): InstructionProperties(duration=0, error=0),
(4, ): InstructionProperties(duration=0, error=0),
}
self.ibm_target.add_instruction(RZGate(self.theta), rz_props)
sx_props = {
(0, ): InstructionProperties(duration=35.5e-9, error=0.000413),
(1, ): InstructionProperties(duration=35.5e-9, error=0.000502),
(2, ): InstructionProperties(duration=35.5e-9, error=0.0004003),
(3, ): InstructionProperties(duration=35.5e-9, error=0.000614),
(4, ): InstructionProperties(duration=35.5e-9, error=0.006149),
}
self.ibm_target.add_instruction(SXGate(), sx_props)
x_props = {
(0, ): InstructionProperties(duration=35.5e-9, error=0.000413),
(1, ): InstructionProperties(duration=35.5e-9, error=0.000502),
(2, ): InstructionProperties(duration=35.5e-9, error=0.0004003),
(3, ): InstructionProperties(duration=35.5e-9, error=0.000614),
(4, ): InstructionProperties(duration=35.5e-9, error=0.006149),
}
self.ibm_target.add_instruction(XGate(), x_props)
cx_props = {
(3, 4): InstructionProperties(duration=270.22e-9, error=0.00713),
(4, 3): InstructionProperties(duration=305.77e-9, error=0.00713),
(3, 1): InstructionProperties(duration=462.22e-9, error=0.00929),
(1, 3): InstructionProperties(duration=497.77e-9, error=0.00929),
(1, 2): InstructionProperties(duration=227.55e-9, error=0.00659),
(2, 1): InstructionProperties(duration=263.11e-9, error=0.00659),
(0, 1): InstructionProperties(duration=519.11e-9, error=0.01201),
(1, 0): InstructionProperties(duration=554.66e-9, error=0.01201),
}
self.ibm_target.add_instruction(CXGate(), cx_props)
measure_props = {
(0, ): InstructionProperties(duration=5.813e-6, error=0.0751),
(1, ): InstructionProperties(duration=5.813e-6, error=0.0225),
(2, ): InstructionProperties(duration=5.813e-6, error=0.0146),
(3, ): InstructionProperties(duration=5.813e-6, error=0.0215),
(4, ): InstructionProperties(duration=5.813e-6, error=0.0333),
}
self.ibm_target.add_instruction(Measure(), measure_props)
self.aqt_target = Target(description="AQT Target")
rx_props = {
(0, ): None,
(1, ): None,
(2, ): None,
(3, ): None,
(4, ): None,
}
self.aqt_target.add_instruction(RXGate(self.theta), rx_props)
ry_props = {
(0, ): None,
(1, ): None,
(2, ): None,
(3, ): None,
(4, ): None,
}
self.aqt_target.add_instruction(RYGate(self.theta), ry_props)
rz_props = {
(0, ): None,
(1, ): None,
(2, ): None,
(3, ): None,
(4, ): None,
}
self.aqt_target.add_instruction(RZGate(self.theta), rz_props)
r_props = {
(0, ): None,
(1, ): None,
(2, ): None,
(3, ): None,
(4, ): None,
}
self.aqt_target.add_instruction(RGate(self.theta, self.phi), r_props)
rxx_props = {
(0, 1): None,
(0, 2): None,
(0, 3): None,
(0, 4): None,
(1, 0): None,
(2, 0): None,
(3, 0): None,
(4, 0): None,
(1, 2): None,
(1, 3): None,
(1, 4): None,
(2, 1): None,
(3, 1): None,
(4, 1): None,
(2, 3): None,
(2, 4): None,
(3, 2): None,
(4, 2): None,
(3, 4): None,
(4, 3): None,
}
self.aqt_target.add_instruction(RXXGate(self.theta), rxx_props)
measure_props = {
(0, ): None,
(1, ): None,
(2, ): None,
(3, ): None,
(4, ): None,
}
self.aqt_target.add_instruction(Measure(), measure_props)
self.empty_target = Target()
self.ideal_sim_target = Target(num_qubits=3,
description="Ideal Simulator")
self.lam = Parameter("lam")
for inst in [
UGate(self.theta, self.phi, self.lam),
RXGate(self.theta),
RYGate(self.theta),
RZGate(self.theta),
CXGate(),
ECRGate(),
CCXGate(),
Measure(),
]:
self.ideal_sim_target.add_instruction(inst, {None: None})
def convert(
self,
operator: CircuitStateFn,
params: Optional[Union[ParameterExpression, ParameterVector,
List[ParameterExpression]]] = None,
) -> ListOp:
r"""
Args:
operator: The operator corresponding to the quantum state :math:`|\psi(\omega)\rangle`
for which we compute the QFI.
params: The parameters :math:`\omega` with respect to which we are computing the QFI.
Returns:
A ``ListOp[ListOp]`` where the operator at position ``[k][l]`` corresponds to the matrix
element :math:`k, l` of the QFI.
Raises:
AquaError: If one of the circuits could not be constructed.
TypeError: If ``operator`` is an unsupported type.
"""
# QFI & phase fix observable
qfi_observable = ~StateFn(4 * Z ^ (I ^ operator.num_qubits))
phase_fix_observable = ~StateFn((X + 1j * Y)
^ (I ^ operator.num_qubits))
# see https://arxiv.org/pdf/quant-ph/0108146.pdf
# Check if the given operator corresponds to a quantum state given as a circuit.
if not isinstance(operator, CircuitStateFn):
raise TypeError(
'LinCombFull is only compatible with states that are given as CircuitStateFn'
)
# If a single parameter is given wrap it into a list.
if not isinstance(params, (list, np.ndarray)):
params = [params]
state_qc = operator.primitive
# First, the operators are computed which can compensate for a potential phase-mismatch
# between target and trained state, i.e.〈ψ|∂lψ〉
phase_fix_states = None
# Add working qubit
qr_work = QuantumRegister(1, 'work_qubit')
work_q = qr_work[0]
additional_qubits: Tuple[List[Qubit], List[Qubit]] = ([work_q], [])
for param in params:
# Get the gates of the given quantum state which are parameterized by param
param_gates = state_qc._parameter_table[param]
# Loop through the occurrences of param in the quantum state
for m, param_occurence in enumerate(param_gates):
# Get the coefficients and gates for the linear combination gradient for each
# occurrence, see e.g. https://arxiv.org/abs/2006.06004
coeffs_i, gates_i = LinComb._gate_gradient_dict(
param_occurence[0])[param_occurence[1]]
# Construct the quantum states which are then evaluated for the respective QFI
# element.
for k, gate_to_insert_i in enumerate(gates_i):
grad_state = state_qc.copy()
grad_state.add_register(qr_work)
# apply Hadamard on work_q
LinComb.insert_gate(grad_state,
param_occurence[0],
HGate(),
qubits=[work_q])
# Fix work_q phase such that the gradient is correct.
coeff_i = coeffs_i[k]
sign = np.sign(coeff_i)
is_complex = np.iscomplex(coeff_i)
if sign == -1:
if is_complex:
LinComb.insert_gate(grad_state,
param_occurence[0],
SdgGate(),
qubits=[work_q])
else:
LinComb.insert_gate(grad_state,
param_occurence[0],
ZGate(),
qubits=[work_q])
else:
if is_complex:
LinComb.insert_gate(grad_state,
param_occurence[0],
SGate(),
qubits=[work_q])
# Insert controlled, intercepting gate - controlled by |0>
if isinstance(param_occurence[0], UGate):
if param_occurence[1] == 0:
LinComb.insert_gate(
grad_state, param_occurence[0],
RZGate(param_occurence[0].params[2]))
LinComb.insert_gate(grad_state, param_occurence[0],
RXGate(np.pi / 2))
LinComb.insert_gate(
grad_state,
param_occurence[0],
gate_to_insert_i,
additional_qubits=additional_qubits)
LinComb.insert_gate(grad_state, param_occurence[0],
RXGate(-np.pi / 2))
LinComb.insert_gate(
grad_state, param_occurence[0],
RZGate(-param_occurence[0].params[2]))
elif param_occurence[1] == 1:
LinComb.insert_gate(
grad_state,
param_occurence[0],
gate_to_insert_i,
after=True,
additional_qubits=additional_qubits)
else:
LinComb.insert_gate(
grad_state,
param_occurence[0],
gate_to_insert_i,
additional_qubits=additional_qubits)
else:
LinComb.insert_gate(
grad_state,
param_occurence[0],
gate_to_insert_i,
additional_qubits=additional_qubits)
# Remove unnecessary gates.
grad_state = self.trim_circuit(grad_state,
param_occurence[0])
# Apply the final Hadamard on the working qubit.
grad_state.h(work_q)
# Add the coefficient needed for the gradient as well as the original
# coefficient of the given quantum state.
state = np.sqrt(np.abs(
coeff_i)) * operator.coeff * CircuitStateFn(grad_state)
# Check if the gate parameter corresponding to param is a parameter expression
gate_param = param_occurence[0].params[param_occurence[1]]
if gate_param == param:
state = phase_fix_observable @ state
else:
# If the gate parameter is a parameter expressions the chain rule needs
# to be taken into account.
if isinstance(gate_param, ParameterExpression):
expr_grad = DerivativeBase.parameter_expression_grad(
gate_param, param)
state = (expr_grad * phase_fix_observable) @ state
else:
state *= 0
if m == 0 and k == 0:
phase_fix_state = state
else:
# Take the product rule into account
phase_fix_state += state
# Create a list for the phase fix states
if not phase_fix_states:
phase_fix_states = [phase_fix_state]
else:
phase_fix_states += [phase_fix_state]
# Get 4 * Re[〈∂kψ|∂lψ]
qfi_operators = []
# Add a working qubit
qr_work_qubit = QuantumRegister(1, 'work_qubit')
work_qubit = qr_work_qubit[0]
additional_qubits = ([work_qubit], [])
# create a copy of the original circuit with an additional work_qubit register
circuit = state_qc.copy()
circuit.add_register(qr_work_qubit)
# Apply a Hadamard on the working qubit
LinComb.insert_gate(circuit,
state_qc._parameter_table[params[0]][0][0],
HGate(),
qubits=[work_qubit])
# Get the circuits needed to compute〈∂iψ|∂jψ〉
for i, param_i in enumerate(params): # loop over parameters
qfi_ops = None
for j, param_j in enumerate(params):
# Get the gates of the quantum state which are parameterized by param_i
param_gates_i = state_qc._parameter_table[param_i]
for m_i, param_occurence_i in enumerate(param_gates_i):
coeffs_i, gates_i = LinComb._gate_gradient_dict(
param_occurence_i[0])[param_occurence_i[1]]
for k_i, gate_to_insert_i in enumerate(gates_i):
coeff_i = coeffs_i[k_i]
# Get the gates of the quantum state which are parameterized by param_j
param_gates_j = state_qc._parameter_table[param_j]
for m_j, param_occurence_j in enumerate(param_gates_j):
coeffs_j, gates_j = \
LinComb._gate_gradient_dict(param_occurence_j[0])[
param_occurence_j[1]]
for k_j, gate_to_insert_j in enumerate(gates_j):
coeff_j = coeffs_j[k_j]
# create a copy of the original circuit with the same registers
qfi_circuit = QuantumCircuit(*circuit.qregs)
qfi_circuit.data = circuit.data
# Correct the phase of the working qubit according to coefficient i
# and coefficient j
sign = np.sign(np.conj(coeff_i) * coeff_j)
is_complex = np.iscomplex(
np.conj(coeff_i) * coeff_j)
if sign == -1:
if is_complex:
LinComb.insert_gate(
qfi_circuit,
param_occurence_i[0],
SdgGate(),
qubits=[work_qubit])
else:
LinComb.insert_gate(
qfi_circuit,
param_occurence_i[0],
ZGate(),
qubits=[work_qubit])
else:
if is_complex:
LinComb.insert_gate(
qfi_circuit,
param_occurence_i[0],
SGate(),
qubits=[work_qubit])
LinComb.insert_gate(qfi_circuit,
param_occurence_i[0],
XGate(),
qubits=[work_qubit])
# Insert controlled, intercepting gate i - controlled by |1>
if isinstance(param_occurence_i[0], UGate):
if param_occurence_i[1] == 0:
LinComb.insert_gate(
qfi_circuit, param_occurence_i[0],
RZGate(param_occurence_i[0].
params[2]))
LinComb.insert_gate(
qfi_circuit, param_occurence_i[0],
RXGate(np.pi / 2))
LinComb.insert_gate(
qfi_circuit,
param_occurence_i[0],
gate_to_insert_i,
additional_qubits=additional_qubits
)
LinComb.insert_gate(
qfi_circuit, param_occurence_i[0],
RXGate(-np.pi / 2))
LinComb.insert_gate(
qfi_circuit, param_occurence_i[0],
RZGate(-param_occurence_i[0].
params[2]))
elif param_occurence_i[1] == 1:
LinComb.insert_gate(
qfi_circuit,
param_occurence_i[0],
gate_to_insert_i,
after=True,
additional_qubits=additional_qubits
)
else:
LinComb.insert_gate(
qfi_circuit,
param_occurence_i[0],
gate_to_insert_i,
additional_qubits=additional_qubits
)
else:
LinComb.insert_gate(
qfi_circuit,
param_occurence_i[0],
gate_to_insert_i,
additional_qubits=additional_qubits)
LinComb.insert_gate(qfi_circuit,
gate_to_insert_i,
XGate(),
qubits=[work_qubit],
after=True)
# Insert controlled, intercepting gate j - controlled by |0>
if isinstance(param_occurence_j[0], UGate):
if param_occurence_j[1] == 0:
LinComb.insert_gate(
qfi_circuit, param_occurence_j[0],
RZGate(param_occurence_j[0].
params[2]))
LinComb.insert_gate(
qfi_circuit, param_occurence_j[0],
RXGate(np.pi / 2))
LinComb.insert_gate(
qfi_circuit,
param_occurence_j[0],
gate_to_insert_j,
additional_qubits=additional_qubits
)
LinComb.insert_gate(
qfi_circuit, param_occurence_j[0],
RXGate(-np.pi / 2))
LinComb.insert_gate(
qfi_circuit, param_occurence_j[0],
RZGate(-param_occurence_j[0].
params[2]))
elif param_occurence_j[1] == 1:
LinComb.insert_gate(
qfi_circuit,
param_occurence_j[0],
gate_to_insert_j,
after=True,
additional_qubits=additional_qubits
)
else:
LinComb.insert_gate(
qfi_circuit,
param_occurence_j[0],
gate_to_insert_j,
additional_qubits=additional_qubits
)
else:
LinComb.insert_gate(
qfi_circuit,
param_occurence_j[0],
gate_to_insert_j,
additional_qubits=additional_qubits)
# Remove redundant gates
if j <= i:
qfi_circuit = self.trim_circuit(
qfi_circuit, param_occurence_i[0])
else:
qfi_circuit = self.trim_circuit(
qfi_circuit, param_occurence_j[0])
# Apply final Hadamard gate
qfi_circuit.h(work_qubit)
# Convert the quantum circuit into a CircuitStateFn and add the
# coefficients i, j and the original operator coefficient
term = np.sqrt(
np.abs(coeff_i) *
np.abs(coeff_j)) * operator.coeff
term = term * CircuitStateFn(qfi_circuit)
# Check if the gate parameters i and j are parameter expressions
gate_param_i = param_occurence_i[0].params[
param_occurence_i[1]]
gate_param_j = param_occurence_j[0].params[
param_occurence_j[1]]
meas = deepcopy(qfi_observable)
# If the gate parameter i is a parameter expression use the chain
# rule.
if isinstance(gate_param_i,
ParameterExpression):
expr_grad = DerivativeBase.parameter_expression_grad(
gate_param_i, param_i)
meas *= expr_grad
# If the gate parameter j is a parameter expression use the chain
# rule.
if isinstance(gate_param_j,
ParameterExpression):
expr_grad = DerivativeBase.parameter_expression_grad(
gate_param_j, param_j)
meas *= expr_grad
term = meas @ term
if m_i == 0 and k_i == 0 and m_j == 0 and k_j == 0:
qfi_op = term
else:
# Product Rule
qfi_op += term
# Compute −4 * Re(〈∂kψ|ψ〉〈ψ|∂lψ〉)
def phase_fix_combo_fn(x):
return 4 * (-0.5) * (x[0] * np.conjugate(x[1]) +
x[1] * np.conjugate(x[0]))
phase_fix = ListOp([phase_fix_states[i], phase_fix_states[j]],
combo_fn=phase_fix_combo_fn)
# Add the phase fix quantities to the entries of the QFI
# Get 4 * Re[〈∂kψ|∂lψ〉−〈∂kψ|ψ〉〈ψ|∂lψ〉]
if not qfi_ops:
qfi_ops = [qfi_op + phase_fix]
else:
qfi_ops += [qfi_op + phase_fix]
qfi_operators.append(ListOp(qfi_ops))
# Return the full QFI
return ListOp(qfi_operators)
def _bogoliubov_transform_num_conserving_jw( # pylint: disable=invalid-name
register: QuantumRegister, transformation_matrix: np.ndarray) -> Iterator[
tuple[Gate, tuple[Qubit, ...]]]:
n, _ = transformation_matrix.shape
current_matrix = transformation_matrix
left_rotations = []
right_rotations = []
# compute left and right Givens rotations
for i in range(n - 1):
if i % 2 == 0:
# rotate columns by right multiplication
for j in range(i + 1):
target_index = i - j
row = n - j - 1
if not np.isclose(current_matrix[row, target_index], 0.0):
# zero out element at target index in given row
givens_mat = givens_matrix(
current_matrix[row, target_index + 1],
current_matrix[row, target_index],
)
right_rotations.append(
(givens_mat, (target_index + 1, target_index)))
current_matrix = apply_matrix_to_slices(
current_matrix,
givens_mat,
[(Ellipsis, target_index + 1),
(Ellipsis, target_index)],
)
else:
# rotate rows by left multiplication
for j in range(i + 1):
target_index = n - i + j - 1
col = j
if not np.isclose(current_matrix[target_index, col], 0.0):
# zero out element at target index in given column
givens_mat = givens_matrix(
current_matrix[target_index - 1, col],
current_matrix[target_index, col],
)
left_rotations.append(
(givens_mat, (target_index - 1, target_index)))
current_matrix = apply_matrix_to_slices(
current_matrix, givens_mat,
[target_index - 1, target_index])
# convert left rotations to right rotations
for givens_mat, (i, j) in reversed(left_rotations):
givens_mat = givens_mat.T.conj()
givens_mat[:, 0] *= current_matrix[i, i]
givens_mat[:, 1] *= current_matrix[j, j]
new_givens_mat = givens_matrix(givens_mat[1, 1], givens_mat[1, 0])
right_rotations.append((new_givens_mat.T, (i, j)))
phase_matrix = givens_mat @ new_givens_mat
current_matrix[i, i] = phase_matrix[0, 0]
current_matrix[j, j] = phase_matrix[1, 1]
# yield operations
for i in range(n):
phi = np.angle(current_matrix[i, i])
yield RZGate(phi), (register[i], )
for givens_mat, (i, j) in reversed(right_rotations):
theta = np.arccos(np.real(givens_mat[0, 0]))
phi = np.angle(givens_mat[0, 1])
yield XXPlusYYGate(2 * theta,
phi - np.pi / 2), (register[j], register[i])
def test_controlled_rz(self):
"""Test the creation of a controlled RZ gate."""
theta = 0.5
self.assertEqual(RZGate(theta).control(), CRZGate(theta))
