def test_exact_cover_vqe(self):
algorithm_cfg = {
'name': 'VQE',
'operator_mode': 'matrix',
'max_evals_grouped': 2
}
optimizer_cfg = {
'name': 'COBYLA'
}
var_form_cfg = {
'name': 'RYRZ',
'depth': 5
}
params = {
'problem': {'name': 'ising', 'random_seed': 10598},
'algorithm': algorithm_cfg,
'optimizer': optimizer_cfg,
'variational_form': var_form_cfg
}
backend = BasicAer.get_backend('statevector_simulator')
result = run_algorithm(params, self.algo_input, backend=backend)
x = exact_cover.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
ising_sol = exact_cover.get_solution(x)
oracle = self.brute_force()
self.assertEqual(exact_cover.check_solution_satisfiability(ising_sol, self.list_of_subsets), oracle)
def test_exact_cover_direct(self):
algo = ExactEigensolver(self.algo_input.qubit_op, k=1, aux_operators=[])
result = algo.run()
x = exact_cover.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
ising_sol = exact_cover.get_solution(x)
np.testing.assert_array_equal(ising_sol, [0, 1, 1, 0])
oracle = self.brute_force()
self.assertEqual(exact_cover.check_solution_satisfiability(ising_sol, self.list_of_subsets), oracle)
def test_exact_cover(self):
params = {
'problem': {'name': 'ising'},
'algorithm': {'name': 'ExactEigensolver'}
}
result = run_algorithm(params, self.algo_input)
x = exact_cover.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
ising_sol = exact_cover.get_solution(x)
np.testing.assert_array_equal(ising_sol, [0, 1, 1, 0])
oracle = self.brute_force()
self.assertEqual(exact_cover.check_solution_satisfiability(ising_sol, self.list_of_subsets), oracle)