def test_set_packing_vqe(self):
try:
from qiskit import Aer
except Exception as e:
self.skipTest(
"Aer doesn't appear to be installed. Error: '{}'".format(
str(e)))
return
algorithm_cfg = {
'name': 'VQE',
'operator_mode': 'grouped_paulis',
'max_evals_grouped': 2
}
optimizer_cfg = {'name': 'SPSA', 'max_trials': 200}
var_form_cfg = {'name': 'RY', 'depth': 5, 'entanglement': 'linear'}
params = {
'problem': {
'name': 'ising',
'random_seed': 100
},
'algorithm': algorithm_cfg,
'optimizer': optimizer_cfg,
'variational_form': var_form_cfg
}
backend = Aer.get_backend('qasm_simulator')
result = run_algorithm(params, self.algo_input, backend=backend)
x = setpacking.sample_most_likely(len(self.list_of_subsets),
result['eigvecs'][0])
ising_sol = setpacking.get_solution(x)
oracle = self.brute_force()
self.assertEqual(np.count_nonzero(ising_sol), oracle)
def test_set_packing_vqe(self):
algorithm_cfg = {
'name': 'VQE',
'operator_mode': 'grouped_paulis',
'batch_mode': True
}
optimizer_cfg = {'name': 'SPSA', 'max_trials': 200}
var_form_cfg = {'name': 'RY', 'depth': 5, 'entanglement': 'linear'}
params = {
'problem': {
'name': 'ising',
'random_seed': 100
},
'algorithm': algorithm_cfg,
'optimizer': optimizer_cfg,
'variational_form': var_form_cfg
}
backend = Aer.get_backend('qasm_simulator')
result = run_algorithm(params, self.algo_input, backend=backend)
x = setpacking.sample_most_likely(len(self.list_of_subsets),
result['eigvecs'][0])
ising_sol = setpacking.get_solution(x)
oracle = self.brute_force()
self.assertEqual(np.count_nonzero(ising_sol), oracle)
def test_set_packing_direct(self):
algo = ExactEigensolver(self.algo_input.qubit_op, k=1, aux_operators=[])
result = algo.run()
x = setpacking.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
ising_sol = setpacking.get_solution(x)
np.testing.assert_array_equal(ising_sol, [0, 1, 1])
oracle = self.brute_force()
self.assertEqual(np.count_nonzero(ising_sol), oracle)
def test_set_packing(self):
params = {
'problem': {'name': 'ising'},
'algorithm': {'name': 'ExactEigensolver'}
}
result = run_algorithm(params, self.algo_input)
x = setpacking.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
ising_sol = setpacking.get_solution(x)
np.testing.assert_array_equal(ising_sol, [0, 1, 1])
oracle = self.brute_force()
self.assertEqual(np.count_nonzero(ising_sol), oracle)