def test_deprecated_qft(self):
"""Test the QPE algorithm on the deprecated QFT component."""
qubit_op = self._dict['QUBIT_OP_SIMPLE']
exact_eigensolver = NumPyMinimumEigensolver(qubit_op)
results = exact_eigensolver.run()
ref_eigenval = results.eigenvalue
ref_eigenvec = results.eigenstate
state_in = Custom(qubit_op.num_qubits, state_vector=ref_eigenvec)
warnings.filterwarnings('ignore', category=DeprecationWarning)
iqft = Standard(5)
qpe = QPE(qubit_op,
state_in,
iqft,
num_time_slices=1,
num_ancillae=5,
expansion_mode='suzuki',
expansion_order=2,
shallow_circuit_concat=True)
backend = BasicAer.get_backend('qasm_simulator')
quantum_instance = QuantumInstance(backend,
shots=100,
seed_transpiler=1,
seed_simulator=1)
# run qpe
result = qpe.run(quantum_instance)
warnings.filterwarnings('always', category=DeprecationWarning)
self.assertAlmostEqual(result.eigenvalue.real,
ref_eigenval.real,
delta=2e-2)
def run_qpe_algo(self,
num_ancillae: int = 1,
backend: BaseBackend = None,
print_eig: bool = False,
shots: int = 1024) -> dict:
""" Runs the QPE algorithm directly.
Args:
num_ancillae (int, optional): ancillary qubit number, the higher the more accurate, but use more computing resources. Defaults to 1.
backend (BaseBackend, optional): Choose the backend to run this algorithm. Defaults to None.
print_eig (bool, optional): whether or not print the eigenvalue. Defaults to False.
shots (int, optional): Indicate how many shots to take. Defaults to 1024.
Returns:
dict: returns the results dictionary of the QPE algorithm. Use the 'energy' key to get the eigenvalue.
"""
if backend is None: # Default backend to Aer.get_backend('qasm_simulator').
backend = Aer.get_backend('qasm_simulator')
# QPE
m, n = self.matrix.shape
qpe = QPE(operator=MatrixOperator(matrix=self.matrix),
state_in=Custom(m),
iqft=Standard(num_ancillae),
num_time_slices=50,
num_ancillae=num_ancillae,
expansion_mode='suzuki',
expansion_order=2,
shallow_circuit_concat=True)
results = qpe.run(
QuantumInstance(backend=backend,
skip_qobj_validation=False,
shots=shots))
if print_eig: print("ENERGY:", results['energy'])
return results
def execute_qpe_circuit(self,
num_ancillae: int = 1,
backend: BaseBackend = None,
shots: int = 1024,
print_eig: bool = False) -> Result:
"""Runs the QPE algorithm by constructing the circuit explicitly.
Args:
num_ancillae (int, optional): ancillary qubit number, the higher the more accurate, but use more computing resources. Defaults to 1.
backend (BaseBackend, optional): Choose the backend to run this algorithm. Defaults to None.
shots (int, optional): Indicate how many shots to take. Defaults to 1024.
print_eig (bool, optional): whether or not print the eigenvalue. Defaults to False.
Returns:
Result: returns a Qiskit.result object. Use get_counts() to get a dictionary for the qubits' probabilities.
"""
if backend is None: # Default backend to Aer.get_backend('qasm_simulator').
backend = Aer.get_backend('qasm_simulator')
# QPE Circuit
m, n = self.matrix.shape
qpe = QPE(operator=MatrixOperator(matrix=self.matrix),
state_in=Custom(m),
iqft=Standard(num_ancillae),
num_time_slices=50,
num_ancillae=num_ancillae,
expansion_mode='suzuki',
expansion_order=2,
shallow_circuit_concat=True)
results = execute(qpe.construct_circuit(measurement=True),
backend=backend).result()
if print_eig: print(results.get_counts())
return results
def test_qpe(self, qubit_op, simulator, num_time_slices, n_ancillae):
""" QPE test """
self.log.debug('Testing QPE')
tmp_qubit_op = qubit_op.copy()
exact_eigensolver = ExactEigensolver(qubit_op, k=1)
results = exact_eigensolver.run()
ref_eigenval = results['eigvals'][0]
ref_eigenvec = results['eigvecs'][0]
self.log.debug('The exact eigenvalue is: %s', ref_eigenval)
self.log.debug('The corresponding eigenvector: %s', ref_eigenvec)
state_in = Custom(qubit_op.num_qubits, state_vector=ref_eigenvec)
iqft = Standard(n_ancillae)
qpe = QPE(qubit_op,
state_in,
iqft,
num_time_slices,
n_ancillae,
expansion_mode='suzuki',
expansion_order=2,
shallow_circuit_concat=True)
backend = BasicAer.get_backend(simulator)
quantum_instance = QuantumInstance(backend, shots=100)
# run qpe
result = qpe.run(quantum_instance)
# report result
self.log.debug('top result str label: %s',
result['top_measurement_label'])
self.log.debug('top result in decimal: %s',
result['top_measurement_decimal'])
self.log.debug('stretch: %s', result['stretch'])
self.log.debug('translation: %s',
result['translation'])
self.log.debug('final eigenvalue from QPE: %s', result['energy'])
self.log.debug('reference eigenvalue: %s', ref_eigenval)
self.log.debug('ref eigenvalue (transformed): %s',
(ref_eigenval + result['translation']) *
result['stretch'])
self.log.debug(
'reference binary str label: %s',
decimal_to_binary((ref_eigenval.real + result['translation']) *
result['stretch'],
max_num_digits=n_ancillae + 3,
fractional_part_only=True))
np.testing.assert_approx_equal(result['energy'],
ref_eigenval.real,
significant=2)
self.assertEqual(tmp_qubit_op, qubit_op,
"Operator is modified after QPE.")
def test_qpe(self, qubit_op, simulator, num_time_slices, n_ancillae):
"""Test the QPE algorithm."""
self.log.debug('Testing QPE')
qubit_op = self._dict[qubit_op]
exact_eigensolver = NumPyMinimumEigensolver(qubit_op)
results = exact_eigensolver.run()
ref_eigenval = results.eigenvalue
ref_eigenvec = results.eigenstate
self.log.debug('The exact eigenvalue is: %s', ref_eigenval)
self.log.debug('The corresponding eigenvector: %s', ref_eigenvec)
state_in = Custom(qubit_op.num_qubits, state_vector=ref_eigenvec)
iqft = QFT(n_ancillae).inverse()
qpe = QPE(qubit_op,
state_in,
iqft,
num_time_slices,
n_ancillae,
expansion_mode='suzuki',
expansion_order=2,
shallow_circuit_concat=True)
backend = BasicAer.get_backend(simulator)
quantum_instance = QuantumInstance(backend,
shots=100,
seed_transpiler=1,
seed_simulator=1)
# run qpe
result = qpe.run(quantum_instance)
# report result
self.log.debug('top result str label: %s',
result.top_measurement_label)
self.log.debug('top result in decimal: %s',
result.top_measurement_decimal)
self.log.debug('stretch: %s', result.stretch)
self.log.debug('translation: %s', result.translation)
self.log.debug('final eigenvalue from QPE: %s', result.eigenvalue)
self.log.debug('reference eigenvalue: %s', ref_eigenval)
self.log.debug('ref eigenvalue (transformed): %s',
(ref_eigenval + result.translation) * result.stretch)
self.log.debug(
'reference binary str label: %s',
decimal_to_binary(
(ref_eigenval.real + result.translation) * result.stretch,
max_num_digits=n_ancillae + 3,
fractional_part_only=True))
self.assertAlmostEqual(result.eigenvalue.real,
ref_eigenval.real,
delta=2e-2)
def test_qpe(self, qubit_op, simulator, num_time_slices, n_ancillae, use_circuit_library):
""" QPE test """
self.log.debug('Testing QPE')
qubit_op = self._dict[qubit_op]
exact_eigensolver = NumPyMinimumEigensolver(qubit_op)
results = exact_eigensolver.run()
ref_eigenval = results.eigenvalue
ref_eigenvec = results.eigenstate
self.log.debug('The exact eigenvalue is: %s', ref_eigenval)
self.log.debug('The corresponding eigenvector: %s', ref_eigenvec)
state_in = Custom(qubit_op.num_qubits, state_vector=ref_eigenvec)
if use_circuit_library:
iqft = QFT(n_ancillae).inverse()
else:
# ignore deprecation warnings from QFTs
warnings.filterwarnings(action="ignore", category=DeprecationWarning)
iqft = Standard(n_ancillae)
qpe = QPE(qubit_op, state_in, iqft, num_time_slices, n_ancillae,
expansion_mode='suzuki', expansion_order=2,
shallow_circuit_concat=True)
backend = BasicAer.get_backend(simulator)
quantum_instance = QuantumInstance(backend, shots=100)
# run qpe
result = qpe.run(quantum_instance)
# report result
self.log.debug('top result str label: %s', result.top_measurement_label)
self.log.debug('top result in decimal: %s', result.top_measurement_decimal)
self.log.debug('stretch: %s', result.stretch)
self.log.debug('translation: %s', result.translation)
self.log.debug('final eigenvalue from QPE: %s', result.eigenvalue)
self.log.debug('reference eigenvalue: %s', ref_eigenval)
self.log.debug('ref eigenvalue (transformed): %s',
(ref_eigenval + result.translation) * result.stretch)
self.log.debug('reference binary str label: %s', decimal_to_binary(
(ref_eigenval.real + result.translation) * result.stretch,
max_num_digits=n_ancillae + 3,
fractional_part_only=True
))
np.testing.assert_approx_equal(result.eigenvalue.real, ref_eigenval.real, significant=2)
if not use_circuit_library:
warnings.filterwarnings(action="always", category=DeprecationWarning)
import numpy as np
from qiskit.quantum_info import Operator
from qiskit.extensions import HamiltonianGate
from qiskit.aqua.operators.legacy import MatrixOperator
from qiskit.aqua import QuantumInstance
from qiskit.aqua.algorithms import QPE
from qiskit import Aer
from qiskit.visualization import circuit_drawer
from qiskit.aqua.components.initial_states import Custom
A = .25 * np.array([[15, 9, 5, -3], [9, 15, 3, -5], [5, 3, 15, -9],
[-3, -5, -9, 15]])
t0 = 2 * np.pi
#expA = la.expm(-1.j * A * t0)
op = MatrixOperator(A)
vector = [1 / 2, 1 / 2, 1 / 2, 1 / 2]
init_state = Custom(2, state_vector=vector)
algo = QPE(operator=op, state_in=init_state)
result = algo.run(QuantumInstance(Aer.get_backend('qasm_simulator')))
print(result)
def test_qpe(self, distance):
""" qpe test """
self.log.debug(
'Testing End-to-End with QPE on '
'H2 with inter-atomic distance %s.', distance)
try:
driver = PySCFDriver(
atom='H .0 .0 .0; H .0 .0 {}'.format(distance),
unit=UnitsType.ANGSTROM,
charge=0,
spin=0,
basis='sto3g')
except QiskitChemistryError:
self.skipTest('PYSCF driver does not appear to be installed')
molecule = driver.run()
qubit_mapping = 'parity'
fer_op = FermionicOperator(h1=molecule.one_body_integrals,
h2=molecule.two_body_integrals)
qubit_op = fer_op.mapping(map_type=qubit_mapping, threshold=1e-10)
qubit_op = Z2Symmetries.two_qubit_reduction(qubit_op, 2)
exact_eigensolver = NumPyMinimumEigensolver(qubit_op)
results = exact_eigensolver.run()
reference_energy = results.eigenvalue.real
self.log.debug('The exact ground state energy is: %s',
results.eigenvalue.real)
num_particles = molecule.num_alpha + molecule.num_beta
two_qubit_reduction = True
num_orbitals = qubit_op.num_qubits + (2 if two_qubit_reduction else 0)
num_time_slices = 1
n_ancillae = 6
state_in = HartreeFock(num_orbitals, num_particles, qubit_mapping,
two_qubit_reduction)
iqft = QFT(n_ancillae).inverse()
qpe = QPE(qubit_op,
state_in,
iqft,
num_time_slices,
n_ancillae,
expansion_mode='suzuki',
expansion_order=2,
shallow_circuit_concat=True)
backend = qiskit.BasicAer.get_backend('qasm_simulator')
quantum_instance = QuantumInstance(backend, shots=100)
result = qpe.run(quantum_instance)
self.log.debug('eigenstate: %s', result.eigenstate)
self.log.debug('top result str label: %s',
result.top_measurement_label)
self.log.debug('top result in decimal: %s',
result.top_measurement_decimal)
self.log.debug('stretch: %s', result.stretch)
self.log.debug('translation: %s', result.translation)
self.log.debug('final energy from QPE: %s', result.eigenvalue.real)
self.log.debug('reference energy: %s', reference_energy)
self.log.debug('ref energy (transformed): %s',
(reference_energy + result.translation) *
result.stretch)
self.log.debug(
'ref binary str label: %s',
decimal_to_binary(
(reference_energy + result.translation) * result.stretch,
max_num_digits=n_ancillae + 3,
fractional_part_only=True))
np.testing.assert_approx_equal(result.eigenvalue.real,
reference_energy,
significant=2)
def test_qpe(self, qubit_op, simulator, num_time_slices, n_ancillae):
""" QPE test """
self.log.debug('Testing QPE')
tmp_qubit_op = qubit_op.copy()
exact_eigensolver = ExactEigensolver(qubit_op, k=1)
results = exact_eigensolver.run()
ref_eigenval = results['eigvals'][0]
ref_eigenvec = results['eigvecs'][0]
self.log.debug('The exact eigenvalue is: %s', ref_eigenval)
self.log.debug('The corresponding eigenvector: %s', ref_eigenvec)
state_in = Custom(qubit_op.num_qubits, state_vector=ref_eigenvec)
iqft = Standard(n_ancillae)
qpe = QPE(qubit_op, iqft, state_in=state_in, num_time_slices=num_time_slices, num_ancillae=n_ancillae,
expansion_mode='suzuki', expansion_order=2,
shallow_circuit_concat=True)
backend = BasicAer.get_backend(simulator)
quantum_instance = QuantumInstance(backend, shots=100)
# run qpe
result = qpe.run(quantum_instance)
# report result
self.log.debug('top result str label: %s', result['top_measurement_label'])
self.log.debug('top result in decimal: %s', result['top_measurement_decimal'])
self.log.debug('stretch: %s', result['stretch'])
self.log.debug('translation: %s', result['translation'])
self.log.debug('final eigenvalue from QPE: %s', result['energy'])
self.log.debug('reference eigenvalue: %s', ref_eigenval)
self.log.debug('ref eigenvalue (transformed): %s',
(ref_eigenval + result['translation']) * result['stretch'])
self.log.debug('reference binary str label: %s', decimal_to_binary(
(ref_eigenval.real + result['translation']) * result['stretch'],
max_num_digits=n_ancillae + 3,
fractional_part_only=True
))
np.testing.assert_approx_equal(result['energy'], ref_eigenval.real, significant=2)
self.assertEqual(tmp_qubit_op, qubit_op, "Operator is modified after QPE.")
#Re-run, now with state_in_circuit_factory
superpose_state_and_flip = FlipSuperposition(state_in)
qpe = QPE(qubit_op, iqft, state_in_circuit_factory=superpose_state_and_flip, num_time_slices=num_time_slices, num_ancillae=n_ancillae, expansion_mode='suzuki', expansion_order=2, shallow_circuit_concat=True)
backend = BasicAer.get_backend(simulator)
quantum_instance = QuantumInstance(backend, shots=100)
# run qpe
result = qpe.run(quantum_instance)
ancilla_counts = result["ancilla_counts"]
if simulator=="qasm_simulator":
self.assertEqual(result['top_measurement_label'], sorted([(ancilla_counts[k], k) for k in ancilla_counts])[::-1][0][-1][::-1])
else:
self.assertEqual(len(ancilla_counts), 1<<n_ancillae)
self.assertEqual(len(result["aux_counts"]), 1<<superpose_state_and_flip.required_ancillas())
def test_qpe(self, qubitOp, simulator):
self.algorithm = 'QPE'
self.log.debug('Testing QPE')
self.qubitOp = qubitOp
exact_eigensolver = ExactEigensolver(self.qubitOp, k=1)
results = exact_eigensolver.run()
w = results['eigvals']
v = results['eigvecs']
self.qubitOp.to_matrix()
np.testing.assert_almost_equal(self.qubitOp._matrix @ v[0],
w[0] * v[0])
np.testing.assert_almost_equal(
expm(-1.j * sparse.csc_matrix(self.qubitOp._matrix)) @ v[0],
np.exp(-1.j * w[0]) * v[0])
self.ref_eigenval = w[0]
self.ref_eigenvec = v[0]
self.log.debug('The exact eigenvalue is: {}'.format(
self.ref_eigenval))
self.log.debug('The corresponding eigenvector: {}'.format(
self.ref_eigenvec))
num_time_slices = 50
n_ancillae = 6
state_in = Custom(self.qubitOp.num_qubits,
state_vector=self.ref_eigenvec)
iqft = Standard(n_ancillae)
qpe = QPE(self.qubitOp,
state_in,
iqft,
num_time_slices,
n_ancillae,
expansion_mode='suzuki',
expansion_order=2,
shallow_circuit_concat=True)
backend = BasicAer.get_backend(simulator)
quantum_instance = QuantumInstance(backend,
shots=100,
pass_manager=PassManager())
# run qpe
result = qpe.run(quantum_instance)
# self.log.debug('transformed operator paulis:\n{}'.format(self.qubitOp.print_operators('paulis')))
# report result
self.log.debug('top result str label: {}'.format(
result['top_measurement_label']))
self.log.debug('top result in decimal: {}'.format(
result['top_measurement_decimal']))
self.log.debug('stretch: {}'.format(
result['stretch']))
self.log.debug('translation: {}'.format(
result['translation']))
self.log.debug('final eigenvalue from QPE: {}'.format(
result['energy']))
self.log.debug('reference eigenvalue: {}'.format(
self.ref_eigenval))
self.log.debug('ref eigenvalue (transformed): {}'.format(
(self.ref_eigenval + result['translation']) * result['stretch']))
self.log.debug('reference binary str label: {}'.format(
decimal_to_binary(
(self.ref_eigenval.real + result['translation']) *
result['stretch'],
max_num_digits=n_ancillae + 3,
fractional_part_only=True)))
np.testing.assert_approx_equal(result['energy'],
self.ref_eigenval.real,
significant=2)
num_orbitals = qubit_op.num_qubits + (2 if two_qubit_reduction else 0)
print('Number of qubits: ', qubit_op.num_qubits)
num_time_slices = 50
n_ancillae = 8
print('Number of ancillae:', n_ancillae)
state_in = HartreeFock(qubit_op.num_qubits, num_orbitals, num_particles,
qubit_mapping, two_qubit_reduction)
iqft = Standard(n_ancillae)
qpe = QPE(qubit_op,
state_in,
iqft,
num_time_slices,
n_ancillae,
expansion_mode='trotter',
expansion_order=2,
shallow_circuit_concat=True)
# backend
#backend = Aer.get_backend('qasm_simulator')
# IBM Q
from qiskit import IBMQ
provider0 = IBMQ.load_account()
#large_enough_devices = IBMQ.backends(filters=lambda x: x.configuration().n_qubits > qubit_op.num_qubits and not x.configuration().simulator)
backend = provider0.get_backend('ibmq_16_melbourne')
#backend = provider0.get_backend('ibmq_qasm_simulator')
#ibmq_16_melbourne
#ibmqx2