def test_graph_partition_vqe(self):
algorithm_cfg = {
'name': 'VQE',
'operator_mode': 'matrix',
'batch_mode': True
}
optimizer_cfg = {'name': 'SPSA', 'max_trials': 300}
var_form_cfg = {'name': 'RY', 'depth': 5, 'entanglement': 'linear'}
params = {
'problem': {
'name': 'ising',
'random_seed': 10598
},
'algorithm': algorithm_cfg,
'optimizer': optimizer_cfg,
'variational_form': var_form_cfg
}
backend = get_aer_backend('statevector_simulator')
result = run_algorithm(params, self.algo_input, backend=backend)
x = graphpartition.sample_most_likely(result['eigvecs'][0])
# check against the oracle
ising_sol = graphpartition.get_graph_solution(x)
np.testing.assert_array_equal(ising_sol, [1, 0, 0, 1])
oracle = self.brute_force()
self.assertEqual(graphpartition.objective_value(x, self.w), oracle)
def test_graph_partition_direct(self):
algo = ExactEigensolver(self.algo_input.qubit_op,
k=1,
aux_operators=[])
result = algo.run()
x = graphpartition.sample_most_likely(result['eigvecs'][0])
# check against the oracle
ising_sol = graphpartition.get_graph_solution(x)
np.testing.assert_array_equal(ising_sol, [0, 1, 0, 1])
oracle = self.brute_force()
self.assertEqual(graphpartition.objective_value(x, self.w), oracle)
def test_graph_partition(self):
params = {
'problem': {
'name': 'ising'
},
'algorithm': {
'name': 'ExactEigensolver'
}
}
result = run_algorithm(params, self.algo_input)
x = graphpartition.sample_most_likely(result['eigvecs'][0])
# check against the oracle
ising_sol = graphpartition.get_graph_solution(x)
np.testing.assert_array_equal(ising_sol, [0, 1, 0, 1])
oracle = self.brute_force()
self.assertEqual(graphpartition.objective_value(x, self.w), oracle)