def test_grouped_paulis(self):
n = 3 # number of qubits
pg = pauli_group(n, case='tensor')
self.assertTrue(pg != -1, "Error in pauli_group()")
pg = [[1.0, x] for x in pg] # create paulis with equal weight
self.log.debug("Number of Paulis: {}".format(len(pg)))
hamOpOriginal = Operator(paulis=pg, coloring=None)
hamOpOriginal._paulis_to_grouped_paulis()
gpOriginal = hamOpOriginal.grouped_paulis
hamOpNew = Operator(paulis=pg, coloring="largest-degree")
hamOpNew._paulis_to_grouped_paulis()
gpNew = hamOpNew.grouped_paulis
self.log.debug("#groups in original= {} #groups in new={}".format(
len(gpOriginal), len(gpNew)))
self.log.debug("------- Original --------")
for each in gpOriginal:
for x in each:
self.log.debug('{} {}'.format(x[0], x[1].to_label()))
self.log.debug('---')
self.log.debug("-------- New ------------")
for each in gpNew:
for x in each:
self.log.debug('{} {}'.format(x[0], x[1].to_label()))
self.log.debug('---')
def test_grouped_paulis(self):
""" grouped paulis test """
n = 3 # number of qubits
p_g = pauli_group(n, case='tensor')
self.assertTrue(p_g != -1, "Error in pauli_group()")
p_g = [[1.0, x] for x in p_g] # create paulis with equal weight
self.log.debug("Number of Paulis: %s", len(p_g))
ham_op_original = Operator(paulis=p_g, coloring=None)
ham_op_original._paulis_to_grouped_paulis()
gp_original = ham_op_original.grouped_paulis
ham_op_new = Operator(paulis=p_g, coloring="largest-degree")
ham_op_new._paulis_to_grouped_paulis()
gp_new = ham_op_new.grouped_paulis
self.log.debug("#groups in original= %s #groups in new=%s",
len(gp_original), len(gp_new))
self.log.debug("------- Original --------")
for each in gp_original:
for x in each:
self.log.debug('%s %s', x[0], x[1].to_label())
self.log.debug('---')
self.log.debug("-------- New ------------")
for each in gp_new:
for x in each:
self.log.debug('%s %s', x[0], x[1].to_label())
self.log.debug('---')
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]]
# + 0.5 * np.kron(Y, X)# + 0.3 * np.kron(Z, X) + 0.4 * np.kron(Z, Y)
h1 = np.kron(_I, Z)
# np.random.seed(2)
temp = np.random.random((2**SIZE, 2**SIZE))
h1 = temp + temp.T
qubit_op = Operator(matrix=h1)
# qubit_op_jw.chop_by_threshold(10 ** -10)
if qubit_op.grouped_paulis is None:
qubit_op._matrix_to_paulis()
qubit_op._paulis_to_grouped_paulis()
for ps in qubit_op.grouped_paulis:
for p1 in ps:
for p2 in ps:
if p1 != p2:
np.testing.assert_almost_equal(
p1[1].to_matrix() @ p2[1].to_matrix(),
p2[1].to_matrix() @ p1[1].to_matrix())
state_in = Custom(SIZE, state='random')
evo_time = 1
num_time_slices = 3
# announces params
self.log.debug('evo time: {}'.format(evo_time))
self.log.debug('num time slices: {}'.format(num_time_slices))
self.log.debug('state_in: {}'.format(state_in._state_vector))
# get the exact state_out from raw matrix multiplication
state_out_exact = qubit_op.evolve(
state_in=state_in.construct_circuit('vector'),
evo_time=evo_time,
evo_mode='matrix',
num_time_slices=0)
# self.log.debug('exact:\n{}'.format(state_out_exact))
qubit_op_temp = copy.deepcopy(qubit_op)
for expansion_mode in ['trotter', 'suzuki']:
self.log.debug('Under {} expansion mode:'.format(expansion_mode))
for expansion_order in [1, 2, 3, 4
] if expansion_mode == 'suzuki' else [1]:
# assure every time the operator from the original one
qubit_op = copy.deepcopy(qubit_op_temp)
if expansion_mode == 'suzuki':
self.log.debug(
'With expansion order {}:'.format(expansion_order))
state_out_matrix = qubit_op.evolve(
state_in=state_in.construct_circuit('vector'),
evo_time=evo_time,
evo_mode='matrix',
num_time_slices=num_time_slices,
expansion_mode=expansion_mode,
expansion_order=expansion_order)
quantum_registers = QuantumRegister(qubit_op.num_qubits,
name='q')
qc = QuantumCircuit(quantum_registers)
qc += state_in.construct_circuit('circuit', quantum_registers)
qc += qubit_op.evolve(
evo_time=evo_time,
evo_mode='circuit',
num_time_slices=num_time_slices,
quantum_registers=quantum_registers,
expansion_mode=expansion_mode,
expansion_order=expansion_order,
)
job = q_execute(qc,
BasicAer.get_backend('statevector_simulator'))
state_out_circuit = np.asarray(job.result().get_statevector(
qc, decimals=16))
self.log.debug(
'The fidelity between exact and matrix: {}'.format(
state_fidelity(state_out_exact, state_out_matrix)))
self.log.debug(
'The fidelity between exact and circuit: {}'.format(
state_fidelity(state_out_exact, state_out_circuit)))
f_mc = state_fidelity(state_out_matrix, state_out_circuit)
self.log.debug(
'The fidelity between matrix and circuit: {}'.format(f_mc))
self.assertAlmostEqual(f_mc, 1)
