def test_evolution(self):
SIZE = 2
#SPARSITY = 0
#X = [[0, 1], [1, 0]]
#Y = [[0, -1j], [1j, 0]]
Z = [[1, 0], [0, -1]]
I = [[1, 0], [0, 1]]
h1 = np.kron(
I, Z
) # + 0.5 * np.kron(Y, X)# + 0.3 * np.kron(Z, X) + 0.4 * np.kron(Z, Y)
# np.random.seed(2)
temp = np.random.random((2**SIZE, 2**SIZE))
h1 = temp + temp.T
qubitOp = Operator(matrix=h1)
temp = np.random.random((2**SIZE, 2**SIZE))
h1 = temp + temp.T
evoOp = Operator(matrix=h1)
state_in = get_initial_state_instance('CUSTOM')
state_in.init_args(SIZE, state='random')
evo_time = 1
num_time_slices = 100
dynamics = get_algorithm_instance('Dynamics')
dynamics.setup_quantum_backend()
# self.log.debug('state_out:\n\n')
dynamics.init_args(qubitOp, 'paulis', state_in, evoOp, evo_time,
num_time_slices)
ret = dynamics.run()
self.log.debug('Evaluation result: {}'.format(ret))
def test_evolution(self):
SIZE = 2
temp = np.random.random((2**SIZE, 2**SIZE))
h1 = temp + temp.T
qubitOp = Operator(matrix=h1)
temp = np.random.random((2**SIZE, 2**SIZE))
h1 = temp + temp.T
evoOp = Operator(matrix=h1)
state_in = get_initial_state_instance('CUSTOM')
state_in.init_args(SIZE, state='random')
evo_time = 1
num_time_slices = 100
dynamics = get_algorithm_instance('Dynamics')
dynamics.setup_quantum_backend(skip_transpiler=True)
# self.log.debug('state_out:\n\n')
dynamics.init_args(qubitOp, 'paulis', state_in, evoOp, evo_time,
num_time_slices)
ret = dynamics.run()
self.log.debug('Evaluation result: {}'.format(ret))
def test_grover(self, input_file, num_iterations=1):
self.log.debug('Testing Grover search with {} iteration(s) on SAT problem instance: \n{}'.format(
num_iterations, open(input_file).read(),
))
# get ground-truth
with open(input_file) as f:
header = f.readline()
self.assertGreaterEqual(header.find('solution'), 0, 'Ground-truth info missing.')
self.groundtruth = [
''.join([
'1' if i > 0 else '0'
for i in sorted([int(v) for v in s.strip().split() if v != '0'], key=abs)
])[::-1]
for s in header.split('solutions:' if header.find('solutions:') >= 0 else 'solution:')[-1].split(',')
]
sat_oracle = get_oracle_instance('SAT')
with open(input_file) as f:
sat_oracle.init_args(f.read())
grover = get_algorithm_instance('Grover')
grover.setup_quantum_backend(backend='local_qasm_simulator', shots=100)
grover.init_args(sat_oracle, num_iterations=num_iterations)
ret = grover.run()
self.log.debug('Ground-truth Solutions: {}.'.format(self.groundtruth))
self.log.debug('Measurement result: {}.'.format(ret['measurements']))
top_measurement = max(ret['measurements'].items(), key=operator.itemgetter(1))[0]
self.log.debug('Top measurement: {}.'.format(top_measurement))
self.log.debug('Search Result: {}.'.format(ret['result']))
self.assertIn(top_measurement, self.groundtruth)
def test_ee_direct(self):
algo = get_algorithm_instance('ExactEigensolver')
algo.init_args(self.algo_input.qubit_op, k=1, aux_operators=[])
result = algo.run()
self.assertAlmostEqual(result['energy'], -1.85727503)
np.testing.assert_array_almost_equal(result['energies'], [-1.85727503])
np.testing.assert_array_almost_equal(result['eigvals'],
[-1.85727503 + 0j])
def test_ee_direct_k4(self):
algo = get_algorithm_instance('ExactEigensolver')
algo.init_args(self.algo_input.qubit_op, k=4, aux_operators=[])
result = algo.run()
self.assertAlmostEqual(result['energy'], -1.85727503)
self.assertEqual(len(result['eigvals']), 4)
self.assertEqual(len(result['eigvecs']), 4)
np.testing.assert_array_almost_equal(
result['energies'],
[-1.85727503, -1.24458455, -0.88272215, -0.22491125])
def test_grover(self):
sat_oracle = get_oracle_instance('SAT')
with open(self.input_file) as f:
sat_oracle.init_args(f.read())
grover = get_algorithm_instance('Grover')
grover.setup_quantum_backend(backend='local_qasm_simulator', shots=100)
grover.init_args(sat_oracle, num_iterations=2)
ret = grover.run()
self.log.debug('Ground-truth Solutions: {}.'.format(self.groundtruth))
self.log.debug('Measurement result: {}.'.format(
ret['measurements']))
top_measurement = max(ret['measurements'].items(),
key=operator.itemgetter(1))[0]
self.log.debug('Top measurement: {}.'.format(top_measurement))
self.log.debug('Search Result: {}.'.format(ret['result']))
self.assertIn(top_measurement, self.groundtruth)
def test_qaoa(self, w, p, solutions):
self.log.debug('Testing {}-step QAOA with MaxCut on graph\n{}'.format(
p, w))
optimizer = get_optimizer_instance('COBYLA')
qubitOp, offset = maxcut.get_maxcut_qubitops(w)
qaoa = get_algorithm_instance('QAOA')
qaoa.init_args(qubitOp, 'matrix', p, optimizer)
qaoa.setup_quantum_backend(backend='local_statevector_simulator',
shots=100)
result = qaoa.run()
x = maxcut.sample_most_likely(result['eigvecs'][0])
graph_solution = maxcut.get_graph_solution(x)
self.log.debug('energy: {}'.format(result['energy']))
self.log.debug('time: {}'.format(result['eval_time']))
self.log.debug('maxcut objective: {}'.format(result['energy'] +
offset))
self.log.debug('solution: {}'.format(graph_solution))
self.log.debug('solution objective: {}'.format(
maxcut.maxcut_value(x, w)))
self.assertIn(''.join([str(int(i)) for i in graph_solution]),
solutions)
def test_svm_qkernel_directly(self):
svm = get_algorithm_instance("SVM_QKernel")
svm.setup_quantum_backend(backend='local_qasm_simulator', shots=1024)
svm.random_seed = self.random_seed
svm.init_args(self.training_data,
self.testing_data,
None,
print_info=False)
result = svm.run()
np.testing.assert_array_almost_equal(result['kernel_matrix_training'],
self.ref_kernel_matrix_training,
decimal=4)
np.testing.assert_array_almost_equal(result['kernel_matrix_testing'],
self.ref_kernel_matrix_testing,
decimal=4)
self.assertEqual(len(result['svm']['support_vectors']), 4)
np.testing.assert_array_almost_equal(result['svm']['support_vectors'],
self.ref_support_vectors,
decimal=4)
self.assertEqual(result['test_success_ratio'], 0.5)
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
num_iterations = 12
iqpe = get_algorithm_instance('IQPE')
iqpe.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)
iqpe.init_args(
self.qubitOp,
state_in,
num_time_slices,
num_iterations,
paulis_grouping='random',
expansion_mode='suzuki',
expansion_order=2,
)
result = iqpe.run()
# self.log.debug('operator paulis:\n{}'.format(self.qubitOp.print_operators('paulis')))
# self.log.debug('qpe circuit:\n\n{}'.format(result['circuit']['complete'].qasm()))
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=num_iterations + 3,
fractional_part_only=True)))
np.testing.assert_approx_equal(self.ref_eigenval,
result['energy'],
significant=2)
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)