def test_backend_change(self, user_expectation):
"""Test that VQE works when backend changes."""
vqe = VQE(
ansatz=TwoLocal(rotation_blocks=["ry", "rz"],
entanglement_blocks="cz"),
optimizer=SLSQP(maxiter=2),
expectation=user_expectation,
quantum_instance=BasicAer.get_backend("statevector_simulator"),
)
result0 = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
if user_expectation is not None:
with self.subTest("User expectation kept."):
self.assertEqual(vqe.expectation, user_expectation)
vqe.quantum_instance = BasicAer.get_backend("qasm_simulator")
# works also if no expectation is set, since it will be determined automatically
result1 = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
if user_expectation is not None:
with self.subTest(
"Change backend with user expectation, it is kept."):
self.assertEqual(vqe.expectation, user_expectation)
with self.subTest("Check results."):
self.assertEqual(len(result0.optimal_point),
len(result1.optimal_point))
def test_callback(self):
"""Test the callback on VQE."""
history = {"eval_count": [], "parameters": [], "mean": [], "std": []}
def store_intermediate_result(eval_count, parameters, mean, std):
history["eval_count"].append(eval_count)
history["parameters"].append(parameters)
history["mean"].append(mean)
history["std"].append(std)
optimizer = COBYLA(maxiter=3)
wavefunction = self.ry_wavefunction
vqe = VQE(
ansatz=wavefunction,
optimizer=optimizer,
callback=store_intermediate_result,
quantum_instance=self.qasm_simulator,
)
vqe.compute_minimum_eigenvalue(operator=self.h2_op)
self.assertTrue(
all(isinstance(count, int) for count in history["eval_count"]))
self.assertTrue(
all(isinstance(mean, float) for mean in history["mean"]))
self.assertTrue(all(isinstance(std, float) for std in history["std"]))
for params in history["parameters"]:
self.assertTrue(all(isinstance(param, float) for param in params))
def test_with_two_qubit_reduction(self):
"""Test the VQE using TwoQubitReduction."""
qubit_op = PauliSumOp.from_list([
("IIII", -0.8105479805373266),
("IIIZ", 0.17218393261915552),
("IIZZ", -0.22575349222402472),
("IZZI", 0.1721839326191556),
("ZZII", -0.22575349222402466),
("IIZI", 0.1209126326177663),
("IZZZ", 0.16892753870087912),
("IXZX", -0.045232799946057854),
("ZXIX", 0.045232799946057854),
("IXIX", 0.045232799946057854),
("ZXZX", -0.045232799946057854),
("ZZIZ", 0.16614543256382414),
("IZIZ", 0.16614543256382414),
("ZZZZ", 0.17464343068300453),
("ZIZI", 0.1209126326177663),
])
tapered_qubit_op = TwoQubitReduction(num_particles=2).convert(qubit_op)
for simulator in [self.qasm_simulator, self.statevector_simulator]:
with self.subTest(f"Test for {simulator}."):
vqe = VQE(
self.ry_wavefunction,
SPSA(maxiter=300, last_avg=5),
quantum_instance=simulator,
)
result = vqe.compute_minimum_eigenvalue(tapered_qubit_op)
energy = -1.868 if simulator == self.qasm_simulator else self.h2_energy
self.assertAlmostEqual(result.eigenvalue.real,
energy,
places=2)
def test_qasm_aux_operators_normalized(self):
"""Test VQE with qasm_simulator returns normalized aux_operator eigenvalues."""
wavefunction = self.ry_wavefunction
vqe = VQE(ansatz=wavefunction, quantum_instance=self.qasm_simulator)
_ = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
opt_params = [
3.50437328,
3.87415376,
0.93684363,
5.92219622,
-1.53527887,
1.87941418,
-4.5708326,
0.70187027,
]
vqe._ret.optimal_point = opt_params
vqe._ret.optimal_parameters = dict(
zip(sorted(wavefunction.parameters, key=lambda p: p.name),
opt_params))
with self.assertWarns(DeprecationWarning):
optimal_vector = vqe.get_optimal_vector()
self.assertAlmostEqual(sum(v**2 for v in optimal_vector.values()),
1.0,
places=4)
def test_basic_aer_statevector(self):
"""Test the VQE on BasicAer's statevector simulator."""
wavefunction = self.ryrz_wavefunction
vqe = VQE(
ansatz=wavefunction,
optimizer=L_BFGS_B(),
quantum_instance=QuantumInstance(
BasicAer.get_backend("statevector_simulator"),
basis_gates=["u1", "u2", "u3", "cx", "id"],
coupling_map=[[0, 1]],
seed_simulator=algorithm_globals.random_seed,
seed_transpiler=algorithm_globals.random_seed,
),
)
result = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
with self.subTest(msg="test eigenvalue"):
self.assertAlmostEqual(result.eigenvalue.real, self.h2_energy)
with self.subTest(msg="test dimension of optimal point"):
self.assertEqual(len(result.optimal_point), 16)
with self.subTest(msg="assert cost_function_evals is set"):
self.assertIsNotNone(result.cost_function_evals)
with self.subTest(msg="assert optimizer_time is set"):
self.assertIsNotNone(result.optimizer_time)
def test_backend_change(self, user_expectation):
"""Test that VQE works when backend changes."""
vqe = VQE(
ansatz=TwoLocal(rotation_blocks=["ry", "rz"],
entanglement_blocks="cz"),
optimizer=SLSQP(maxiter=2),
expectation=user_expectation,
quantum_instance=BasicAer.get_backend("statevector_simulator"),
)
result0 = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
if user_expectation is not None:
with self.subTest("User expectation kept."):
self.assertEqual(vqe.expectation, user_expectation)
else:
with self.subTest("Expectation created."):
self.assertIsInstance(vqe.expectation, ExpectationBase)
try:
vqe.quantum_instance = BasicAer.get_backend("qasm_simulator")
except Exception as ex: # pylint: disable=broad-except
self.fail("Failed to change backend. Error: '{}'".format(str(ex)))
return
result1 = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
if user_expectation is not None:
with self.subTest(
"Change backend with user expectation, it is kept."):
self.assertEqual(vqe.expectation, user_expectation)
else:
with self.subTest(
"Change backend without user expectation, one created."):
self.assertIsInstance(vqe.expectation, ExpectationBase)
with self.subTest("Check results."):
self.assertEqual(len(result0.optimal_point),
len(result1.optimal_point))
def test_chc_vscf(self):
""" chc vscf test """
co2_2modes_2modals_2body = [
[[[[0, 0, 0]], 320.8467332810141], [[[0, 1, 1]],
1760.878530705873],
[[[1, 0, 0]], 342.8218290247543], [[[1, 1, 1]],
1032.396323618631]],
[[[[0, 0, 0], [1, 0, 0]], -57.34003649795117],
[[[0, 0, 1], [1, 0, 0]], -56.33205925807966],
[[[0, 1, 0], [1, 0, 0]], -56.33205925807966],
[[[0, 1, 1], [1, 0, 0]], -60.13032761856809],
[[[0, 0, 0], [1, 0, 1]], -65.09576309934431],
[[[0, 0, 1], [1, 0, 1]], -62.2363839133389],
[[[0, 1, 0], [1, 0, 1]], -62.2363839133389],
[[[0, 1, 1], [1, 0, 1]], -121.5533969109279],
[[[0, 0, 0], [1, 1, 0]], -65.09576309934431],
[[[0, 0, 1], [1, 1, 0]], -62.2363839133389],
[[[0, 1, 0], [1, 1, 0]], -62.2363839133389],
[[[0, 1, 1], [1, 1, 0]], -121.5533969109279],
[[[0, 0, 0], [1, 1, 1]], -170.744837386338],
[[[0, 0, 1], [1, 1, 1]], -167.7433236025723],
[[[0, 1, 0], [1, 1, 1]], -167.7433236025723],
[[[0, 1, 1], [1, 1, 1]], -179.0536532281924]]
]
num_modes = 2
num_modals = [2, 2]
vibrational_op_labels = _create_labels(co2_2modes_2modals_2body)
vibr_op = VibrationalOp(vibrational_op_labels, num_modes, num_modals)
converter = QubitConverter(DirectMapper())
qubit_op = converter.convert_match(vibr_op)
init_state = VSCF(num_modals)
num_qubits = sum(num_modals)
excitations = []
excitations += generate_vibration_excitations(num_excitations=1,
num_modals=num_modals)
excitations += generate_vibration_excitations(num_excitations=2,
num_modals=num_modals)
chc_ansatz = CHC(num_qubits,
ladder=False,
excitations=excitations,
initial_state=init_state)
backend = QuantumInstance(
BasicAer.get_backend('statevector_simulator'),
seed_transpiler=2,
seed_simulator=2)
optimizer = COBYLA(maxiter=1000)
algo = VQE(chc_ansatz, optimizer=optimizer, quantum_instance=backend)
vqe_result = algo.compute_minimum_eigenvalue(qubit_op)
energy = vqe_result.optimal_value
self.assertAlmostEqual(energy, self.reference_energy, places=4)
def test_qasm_eigenvector_normalized(self):
"""Test VQE with qasm_simulator returns normalized eigenvector."""
wavefunction = self.ry_wavefunction
vqe = VQE(ansatz=wavefunction, quantum_instance=self.qasm_simulator)
result = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
amplitudes = list(result.eigenstate.values())
self.assertAlmostEqual(np.linalg.norm(amplitudes), 1.0, places=4)
def test_missing_varform_params(self):
"""Test specifying a variational form with no parameters raises an error."""
circuit = QuantumCircuit(self.h2_op.num_qubits)
vqe = VQE(
ansatz=circuit,
quantum_instance=BasicAer.get_backend("statevector_simulator"))
with self.assertRaises(RuntimeError):
vqe.compute_minimum_eigenvalue(operator=self.h2_op)
def test_aux_operator_std_dev_aer_pauli(self):
"""Test non-zero standard deviations of aux operators with AerPauliExpectation."""
wavefunction = self.ry_wavefunction
vqe = VQE(
ansatz=wavefunction,
expectation=AerPauliExpectation(),
optimizer=COBYLA(maxiter=0),
quantum_instance=QuantumInstance(
backend=Aer.get_backend("qasm_simulator"),
shots=1,
seed_simulator=algorithm_globals.random_seed,
seed_transpiler=algorithm_globals.random_seed,
),
)
# Go again with two auxiliary operators
aux_op1 = PauliSumOp.from_list([("II", 2.0)])
aux_op2 = PauliSumOp.from_list([("II", 0.5), ("ZZ", 0.5), ("YY", 0.5),
("XX", -0.5)])
aux_ops = [aux_op1, aux_op2]
result = vqe.compute_minimum_eigenvalue(self.h2_op,
aux_operators=aux_ops)
self.assertEqual(len(result.aux_operator_eigenvalues), 2)
# expectation values
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][0],
2.0,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][0],
0.6698863565455391,
places=6)
# standard deviations
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][1],
0.0,
places=6)
# Go again with additional None and zero operators
aux_ops = [*aux_ops, None, 0]
result = vqe.compute_minimum_eigenvalue(self.h2_op,
aux_operators=aux_ops)
self.assertEqual(len(result.aux_operator_eigenvalues), 4)
# expectation values
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][0],
2.0,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][0],
0.6036400943063891,
places=6)
self.assertEqual(result.aux_operator_eigenvalues[2][0], 0.0)
self.assertEqual(result.aux_operator_eigenvalues[3][0], 0.0)
# standard deviations
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][1],
0.0,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[2][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[3][1], 0.0)
def test_optimizer_callable(self):
"""Test passing a optimizer directly as callable."""
ansatz = RealAmplitudes(1, reps=1)
vqe = VQE(ansatz=ansatz,
optimizer=_mock_optimizer,
quantum_instance=self.statevector_simulator)
result = vqe.compute_minimum_eigenvalue(Z)
self.assertTrue(
np.all(result.optimal_point == np.zeros(ansatz.num_parameters)))
def test_aux_operators_list(self):
"""Test list-based aux_operators."""
wavefunction = self.ry_wavefunction
vqe = VQE(ansatz=wavefunction,
quantum_instance=self.statevector_simulator)
# Start with an empty list
result = vqe.compute_minimum_eigenvalue(self.h2_op, aux_operators=[])
self.assertAlmostEqual(result.eigenvalue.real,
self.h2_energy,
places=6)
self.assertIsNone(result.aux_operator_eigenvalues)
# Go again with two auxiliary operators
aux_op1 = PauliSumOp.from_list([("II", 2.0)])
aux_op2 = PauliSumOp.from_list([("II", 0.5), ("ZZ", 0.5), ("YY", 0.5),
("XX", -0.5)])
aux_ops = [aux_op1, aux_op2]
result = vqe.compute_minimum_eigenvalue(self.h2_op,
aux_operators=aux_ops)
self.assertAlmostEqual(result.eigenvalue.real,
self.h2_energy,
places=6)
self.assertEqual(len(result.aux_operator_eigenvalues), 2)
# expectation values
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][0],
2,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][0],
0,
places=6)
# standard deviations
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][1], 0.0)
# Go again with additional None and zero operators
extra_ops = [*aux_ops, None, 0]
result = vqe.compute_minimum_eigenvalue(self.h2_op,
aux_operators=extra_ops)
self.assertAlmostEqual(result.eigenvalue.real,
self.h2_energy,
places=6)
self.assertEqual(len(result.aux_operator_eigenvalues), 4)
# expectation values
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][0],
2,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][0],
0,
places=6)
self.assertEqual(result.aux_operator_eigenvalues[2][0], 0.0)
self.assertEqual(result.aux_operator_eigenvalues[3][0], 0.0)
# standard deviations
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[2][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[3][1], 0.0)
def test_set_optimizer_to_none(self):
"""Tests that setting the optimizer to None results in the default behavior"""
vqe = VQE(
ansatz=self.ryrz_wavefunction,
optimizer=L_BFGS_B(),
quantum_instance=self.statevector_simulator,
)
vqe.optimizer = None
self.assertIsInstance(vqe.optimizer, SLSQP)
def test_circuit_input(self):
"""Test running the VQE on a plain QuantumCircuit object."""
wavefunction = QuantumCircuit(2).compose(EfficientSU2(2))
optimizer = SLSQP(maxiter=50)
vqe = VQE(self.h2_op, wavefunction, optimizer=optimizer)
result = vqe.run(self.statevector_simulator)
self.assertAlmostEqual(result.eigenvalue.real,
self.h2_energy,
places=5)
def test_optimizer_scipy_callable(self):
"""Test passing a SciPy optimizer directly as callable."""
vqe = VQE(
optimizer=partial(scipy_minimize,
method="L-BFGS-B",
options={"maxiter": 2}),
quantum_instance=self.statevector_simulator,
)
result = vqe.compute_minimum_eigenvalue(Z)
self.assertEqual(result.cost_function_evals, 20)
def test_end2end_h2(self):
""" end to end h2 """
backend = BasicAer.get_backend('statevector_simulator')
shots = 1
optimizer = COBYLA(maxiter=1000)
ryrz = TwoLocal(rotation_blocks=['ry', 'rz'], entanglement_blocks='cz')
quantum_instance = QuantumInstance(backend, shots=shots)
vqe = VQE(ryrz, optimizer=optimizer, quantum_instance=quantum_instance)
result = vqe.compute_minimum_eigenvalue(self.qubit_op, aux_operators=self.aux_ops)
self.assertAlmostEqual(result.eigenvalue.real, self.reference_energy, places=4)
def _optimize(self, optimizer):
""" launch vqe """
qe = QuantumInstance(BasicAer.get_backend('statevector_simulator'),
seed_simulator=aqua_globals.random_seed,
seed_transpiler=aqua_globals.random_seed)
vqe = VQE(var_form=RealAmplitudes(),
optimizer=optimizer,
quantum_instance=qe)
result = vqe.compute_minimum_eigenvalue(operator=self.qubit_op)
self.assertAlmostEqual(result.eigenvalue.real, -1.857, places=1)
def test_basic_aer_qasm(self):
"""Test the VQE on BasicAer's QASM simulator."""
optimizer = SPSA(maxiter=300, last_avg=5)
wavefunction = self.ry_wavefunction
vqe = VQE(self.h2_op, wavefunction, optimizer, max_evals_grouped=1)
# TODO benchmark this later.
result = vqe.run(self.qasm_simulator)
self.assertAlmostEqual(result.eigenvalue.real, -1.86823, places=2)
def test_max_evals_grouped(self, optimizer, places, max_evals_grouped):
""" VQE Optimizers test """
vqe = VQE(var_form=self.ryrz_wavefunction,
optimizer=optimizer,
max_evals_grouped=max_evals_grouped,
quantum_instance=self.statevector_simulator)
result = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
self.assertAlmostEqual(result.eigenvalue.real,
self.h2_energy,
places=places)
def test_reuse(self):
"""Test re-using a VQE algorithm instance."""
vqe = VQE()
with self.subTest(msg="assert running empty raises AlgorithmError"):
with self.assertRaises(AlgorithmError):
_ = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
ansatz = TwoLocal(rotation_blocks=["ry", "rz"],
entanglement_blocks="cz")
vqe.ansatz = ansatz
with self.subTest(msg="assert missing operator raises AlgorithmError"):
with self.assertRaises(AlgorithmError):
_ = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
vqe.expectation = MatrixExpectation()
vqe.quantum_instance = self.statevector_simulator
with self.subTest(msg="assert VQE works once all info is available"):
result = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
self.assertAlmostEqual(result.eigenvalue.real,
self.h2_energy,
places=5)
operator = PrimitiveOp(
np.array([[1, 0, 0, 0], [0, -1, 0, 0], [0, 0, 2, 0], [0, 0, 0,
3]]))
with self.subTest(msg="assert minimum eigensolver interface works"):
result = vqe.compute_minimum_eigenvalue(operator=operator)
self.assertAlmostEqual(result.eigenvalue.real, -1.0, places=5)
def test_nft(self):
""" Test NFT optimizer by using it """
vqe = VQE(var_form=RealAmplitudes(),
optimizer=NFT(),
quantum_instance=QuantumInstance(
BasicAer.get_backend('statevector_simulator'),
seed_simulator=algorithm_globals.random_seed,
seed_transpiler=algorithm_globals.random_seed))
result = vqe.compute_minimum_eigenvalue(operator=self.qubit_op)
self.assertAlmostEqual(result.eigenvalue.real, -1.857275, places=6)
def test_list(self):
""" test AQGD optimizer with the parameters as lists. """
q_instance = QuantumInstance(Aer.get_backend('statevector_simulator'),
seed_simulator=algorithm_globals.random_seed,
seed_transpiler=algorithm_globals.random_seed)
aqgd = AQGD(maxiter=[1000, 1000, 1000], eta=[1.0, 0.5, 0.3], momentum=[0.0, 0.5, 0.75])
vqe = VQE(ansatz=RealAmplitudes(),
optimizer=aqgd,
quantum_instance=q_instance)
result = vqe.compute_minimum_eigenvalue(operator=self.qubit_op)
self.assertAlmostEqual(result.eigenvalue.real, -1.857, places=3)
def test_max_evals_grouped(self, optimizer, places, max_evals_grouped):
"""VQE Optimizers test"""
with self.assertWarns(DeprecationWarning):
vqe = VQE(
ansatz=self.ryrz_wavefunction,
optimizer=optimizer,
max_evals_grouped=max_evals_grouped,
quantum_instance=self.statevector_simulator,
sort_parameters_by_name=True,
)
result = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
self.assertAlmostEqual(result.eigenvalue.real, self.h2_energy, places=places)
def test_aux_operator_std_dev_pauli(self):
"""Test non-zero standard deviations of aux operators with PauliExpectation."""
wavefunction = self.ry_wavefunction
vqe = VQE(
ansatz=wavefunction,
expectation=PauliExpectation(),
optimizer=COBYLA(maxiter=0),
quantum_instance=self.qasm_simulator,
)
# Go again with two auxiliary operators
aux_op1 = PauliSumOp.from_list([("II", 2.0)])
aux_op2 = PauliSumOp.from_list([("II", 0.5), ("ZZ", 0.5), ("YY", 0.5),
("XX", -0.5)])
aux_ops = [aux_op1, aux_op2]
result = vqe.compute_minimum_eigenvalue(self.h2_op,
aux_operators=aux_ops)
self.assertEqual(len(result.aux_operator_eigenvalues), 2)
# expectation values
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][0],
2.0,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][0],
0.6796875,
places=6)
# standard deviations
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][1],
0.02534712219145965,
places=6)
# Go again with additional None and zero operators
aux_ops = [*aux_ops, None, 0]
result = vqe.compute_minimum_eigenvalue(self.h2_op,
aux_operators=aux_ops)
self.assertEqual(len(result.aux_operator_eigenvalues), 4)
# expectation values
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][0],
2.0,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][0],
0.57421875,
places=6)
self.assertEqual(result.aux_operator_eigenvalues[2][0], 0.0)
self.assertEqual(result.aux_operator_eigenvalues[3][0], 0.0)
# # standard deviations
self.assertAlmostEqual(result.aux_operator_eigenvalues[0][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[1][1],
0.026562146577166837,
places=6)
self.assertAlmostEqual(result.aux_operator_eigenvalues[2][1], 0.0)
self.assertAlmostEqual(result.aux_operator_eigenvalues[3][1], 0.0)
def test_basic_aer_qasm(self):
"""Test the VQE on BasicAer's QASM simulator."""
optimizer = SPSA(maxiter=300, last_avg=5)
wavefunction = self.ry_wavefunction
vqe = VQE(var_form=wavefunction,
optimizer=optimizer,
max_evals_grouped=1,
quantum_instance=self.qasm_simulator)
# TODO benchmark this later.
result = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
self.assertAlmostEqual(result.eigenvalue.real, -1.86823, places=2)
def test_int_values(self):
""" test AQGD with int values passed as eta and momentum. """
q_instance = QuantumInstance(Aer.get_backend('statevector_simulator'),
seed_simulator=algorithm_globals.random_seed,
seed_transpiler=algorithm_globals.random_seed)
aqgd = AQGD(maxiter=1000, eta=1, momentum=0)
vqe = VQE(ansatz=RealAmplitudes(),
optimizer=aqgd,
gradient=Gradient('lin_comb'),
quantum_instance=q_instance)
result = vqe.compute_minimum_eigenvalue(operator=self.qubit_op)
self.assertAlmostEqual(result.eigenvalue.real, -1.857, places=3)
def test_simple(self):
""" test AQGD optimizer with the parameters as single values."""
q_instance = QuantumInstance(Aer.get_backend('statevector_simulator'),
seed_simulator=algorithm_globals.random_seed,
seed_transpiler=algorithm_globals.random_seed)
aqgd = AQGD(momentum=0.0)
vqe = VQE(ansatz=RealAmplitudes(),
optimizer=aqgd,
gradient=Gradient('fin_diff'),
quantum_instance=q_instance)
result = vqe.compute_minimum_eigenvalue(operator=self.qubit_op)
self.assertAlmostEqual(result.eigenvalue.real, -1.857, places=3)
def test_chc_vscf(self):
""" chc vscf test """
co2_2modes_2modals_2body = [[[[[0, 0, 0]], 320.8467332810141],
[[[0, 1, 1]], 1760.878530705873],
[[[1, 0, 0]], 342.8218290247543],
[[[1, 1, 1]], 1032.396323618631]],
[[[[0, 0, 0], [1, 0, 0]], -57.34003649795117],
[[[0, 0, 1], [1, 0, 0]], -56.33205925807966],
[[[0, 1, 0], [1, 0, 0]], -56.33205925807966],
[[[0, 1, 1], [1, 0, 0]], -60.13032761856809],
[[[0, 0, 0], [1, 0, 1]], -65.09576309934431],
[[[0, 0, 1], [1, 0, 1]], -62.2363839133389],
[[[0, 1, 0], [1, 0, 1]], -62.2363839133389],
[[[0, 1, 1], [1, 0, 1]], -121.5533969109279],
[[[0, 0, 0], [1, 1, 0]], -65.09576309934431],
[[[0, 0, 1], [1, 1, 0]], -62.2363839133389],
[[[0, 1, 0], [1, 1, 0]], -62.2363839133389],
[[[0, 1, 1], [1, 1, 0]], -121.5533969109279],
[[[0, 0, 0], [1, 1, 1]], -170.744837386338],
[[[0, 0, 1], [1, 1, 1]], -167.7433236025723],
[[[0, 1, 0], [1, 1, 1]], -167.7433236025723],
[[[0, 1, 1], [1, 1, 1]], -179.0536532281924]]]
basis = [2, 2]
bosonic_op = BosonicOperator(co2_2modes_2modals_2body, basis)
qubit_op = bosonic_op.mapping('direct', threshold=1e-5)
with warnings.catch_warnings():
warnings.filterwarnings('ignore', category=DeprecationWarning)
init_state = VSCF(basis)
num_qubits = sum(basis)
uvcc_varform = UVCC(num_qubits, basis, [0, 1])
excitations = uvcc_varform.excitations_in_qubit_format()
chc_varform = CHC(num_qubits, ladder=False, excitations=excitations,
initial_state=init_state)
backend = QuantumInstance(BasicAer.get_backend('statevector_simulator'),
seed_transpiler=2, seed_simulator=2)
optimizer = COBYLA(maxiter=1000)
algo = VQE(chc_varform,
optimizer=optimizer,
quantum_instance=backend)
vqe_result = algo.compute_minimum_eigenvalue(qubit_op)
energy = vqe_result['optimal_value']
self.assertAlmostEqual(energy, self.reference_energy, places=4)
def test_construct_circuit(self, expectation, num_circuits):
"""Test construct circuits returns QuantumCircuits and the right number of them."""
try:
wavefunction = EfficientSU2(2, reps=1)
vqe = VQE(self.h2_op, wavefunction, expectation=expectation)
params = [0] * wavefunction.num_parameters
circuits = vqe.construct_circuit(params)
self.assertEqual(len(circuits), num_circuits)
for circuit in circuits:
self.assertIsInstance(circuit, QuantumCircuit)
except MissingOptionalLibraryError as ex:
self.skipTest(str(ex))
return
def test_construct_eigenstate_from_optpoint(self):
"""Test constructing the eigenstate from the optimal point, if the default ansatz is used."""
# use Hamiltonian yielding more than 11 parameters in the default ansatz
hamiltonian = Z ^ Z ^ Z
optimizer = SPSA(maxiter=1, learning_rate=0.01, perturbation=0.01)
quantum_instance = QuantumInstance(
backend=BasicAer.get_backend("statevector_simulator"),
basis_gates=["u3", "cx"])
vqe = VQE(optimizer=optimizer, quantum_instance=quantum_instance)
result = vqe.compute_minimum_eigenvalue(hamiltonian)
optimal_circuit = vqe.ansatz.bind_parameters(result.optimal_point)
self.assertTrue(Statevector(result.eigenstate).equiv(optimal_circuit))
