def init_params(self, params, algo_input):
"""
Initialize via parameters dictionary and algorithm input instance
Args:
params: parameters dictionary
algo_input: EnergyInput instance
"""
if algo_input is None:
raise AlgorithmError("EnergyInput instance is required.")
operator = algo_input.qubit_op
qpe_params = params.get(QuantumAlgorithm.SECTION_KEY_ALGORITHM)
num_time_slices = qpe_params.get(QPE.PROP_NUM_TIME_SLICES)
paulis_grouping = qpe_params.get(QPE.PROP_PAULIS_GROUPING)
expansion_mode = qpe_params.get(QPE.PROP_EXPANSION_MODE)
expansion_order = qpe_params.get(QPE.PROP_EXPANSION_ORDER)
num_ancillae = qpe_params.get(QPE.PROP_NUM_ANCILLAE)
# Set up initial state, we need to add computed num qubits to params
init_state_params = params.get(QuantumAlgorithm.SECTION_KEY_INITIAL_STATE)
init_state_params['num_qubits'] = operator.num_qubits
init_state = get_initial_state_instance(init_state_params['name'])
init_state.init_params(init_state_params)
# Set up iqft, we need to add num qubits to params which is our num_ancillae bits here
iqft_params = params.get(QuantumAlgorithm.SECTION_KEY_IQFT)
iqft_params['num_qubits'] = num_ancillae
iqft = get_iqft_instance(iqft_params['name'])
iqft.init_params(iqft_params)
self.init_args(
operator, init_state, iqft, num_time_slices, num_ancillae,
paulis_grouping=paulis_grouping, expansion_mode=expansion_mode,
expansion_order=expansion_order)
def test_qpe(self, distance):
self.algorithm = 'QPE'
self.log.debug(
'Testing End-to-End with QPE on H2 with interatomic distance {}.'.
format(distance))
cfg_mgr = ConfigurationManager()
pyscf_cfg = OrderedDict([('atom',
'H .0 .0 .0; H .0 .0 {}'.format(distance)),
('unit', 'Angstrom'), ('charge', 0),
('spin', 0), ('basis', 'sto3g')])
section = {}
section['properties'] = pyscf_cfg
driver = cfg_mgr.get_driver_instance('PYSCF')
self.molecule = driver.run(section)
ferOp = FermionicOperator(h1=self.molecule._one_body_integrals,
h2=self.molecule._two_body_integrals)
self.qubitOp = ferOp.mapping(
map_type='PARITY', threshold=1e-10).two_qubit_reduced_operator(2)
exact_eigensolver = get_algorithm_instance('ExactEigensolver')
exact_eigensolver.init_args(self.qubitOp, k=1)
results = exact_eigensolver.run()
self.reference_energy = results['energy']
self.log.debug('The exact ground state energy is: {}'.format(
results['energy']))
num_particles = self.molecule._num_alpha + self.molecule._num_beta
two_qubit_reduction = True
num_orbitals = self.qubitOp.num_qubits + (2 if two_qubit_reduction else
0)
qubit_mapping = 'parity'
num_time_slices = 50
n_ancillae = 9
qpe = get_algorithm_instance('QPE')
qpe.setup_quantum_backend(backend='local_qasm_simulator', shots=100)
state_in = get_initial_state_instance('HartreeFock')
state_in.init_args(self.qubitOp.num_qubits, num_orbitals,
qubit_mapping, two_qubit_reduction, num_particles)
iqft = get_iqft_instance('STANDARD')
iqft.init_args(n_ancillae)
qpe.init_args(self.qubitOp,
state_in,
iqft,
num_time_slices,
n_ancillae,
paulis_grouping='random',
expansion_mode='suzuki',
expansion_order=2,
use_basis_gates=True)
result = qpe.run()
self.log.debug('measurement results: {}'.format(
result['measurements']))
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 energy from QPE: {}'.format(result['energy']))
self.log.debug('reference energy: {}'.format(
self.reference_energy))
self.log.debug('ref energy (transformed): {}'.format(
(self.reference_energy + result['translation']) *
result['stretch']))
self.log.debug('ref binary str label: {}'.format(
decimal_to_binary((self.reference_energy + result['translation']) *
result['stretch'],
max_num_digits=n_ancillae + 3,
fractional_part_only=True)))
np.testing.assert_approx_equal(result['energy'],
self.reference_energy,
significant=2)
def test_qpe(self, qubitOp):
self.algorithm = 'QPE'
self.log.debug('Testing QPE')
self.qubitOp = qubitOp
exact_eigensolver = get_algorithm_instance('ExactEigensolver')
exact_eigensolver.init_args(self.qubitOp, k=1)
results = exact_eigensolver.run()
w = results['eigvals']
v = results['eigvecs']
self.qubitOp._check_representation('matrix')
np.testing.assert_almost_equal(self.qubitOp.matrix @ v[0], w[0] * v[0])
np.testing.assert_almost_equal(
expm(-1.j * 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 = 9
qpe = get_algorithm_instance('QPE')
qpe.setup_quantum_backend(backend='local_qasm_simulator',
shots=100,
skip_transpiler=True)
state_in = get_initial_state_instance('CUSTOM')
state_in.init_args(self.qubitOp.num_qubits,
state_vector=self.ref_eigenvec)
iqft = get_iqft_instance('STANDARD')
iqft.init_args(n_ancillae)
qpe.init_args(self.qubitOp,
state_in,
iqft,
num_time_slices,
n_ancillae,
paulis_grouping='random',
expansion_mode='suzuki',
expansion_order=2)
# run qpe
result = qpe.run()
# self.log.debug('transformed operator paulis:\n{}'.format(self.qubitOp.print_operators('paulis')))
# report result
self.log.debug('measurement results: {}'.format(
result['measurements']))
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 + result['translation']) *
result['stretch'],
max_num_digits=n_ancillae + 3,
fractional_part_only=True)))
np.testing.assert_approx_equal(self.ref_eigenval,
result['energy'],
significant=2)