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)