def test_pauli_error_1q_unitary_from_pauli(self):
"""Test single-qubit pauli error as unitary qobj from Pauli obj"""
paulis = [Pauli.from_label(s) for s in ['I', 'X', 'Y', 'Z']]
probs = [0.4, 0.3, 0.2, 0.1]
error = pauli_error(zip(paulis, probs), standard_gates=False)
target_unitaries = [
standard_gate_unitary('x'),
standard_gate_unitary('y'),
standard_gate_unitary('z')
]
target_probs = probs.copy()
target_identity_count = 0
for j in range(len(paulis)):
circ, p = error.error_term(j)
name = circ[0]['name']
self.assertIn(name, ('unitary', 'id'))
self.assertEqual(circ[0]['qubits'], [0])
self.remove_if_found(p, target_probs)
if name == "unitary":
self.remove_if_found(circ[0]['params'][0], target_unitaries)
else:
target_identity_count += 1
self.assertEqual(target_probs, [], msg="Incorrect probabilities")
self.assertEqual(target_unitaries, [], msg="Incorrect unitaries")
self.assertEqual(target_identity_count, 1, msg="Incorrect identities")
def test_pauli_error_2q_gate_from_pauli(self):
"""Test two-qubit pauli error as gate qobj from Pauli obj"""
paulis = [Pauli.from_label(s) for s in ['XZ', 'YX', 'ZY']]
probs = [0.5, 0.3, 0.2]
error = pauli_error(zip(paulis, probs), standard_gates=True)
target_circs = [[{
"name": "z",
"qubits": [0]
}, {
"name": "x",
"qubits": [1]
}], [{
"name": "x",
"qubits": [0]
}, {
"name": "y",
"qubits": [1]
}], [{
"name": "y",
"qubits": [0]
}, {
"name": "z",
"qubits": [1]
}]]
target_probs = probs.copy()
for j in range(len(paulis)):
circ, p = error.error_term(j)
self.remove_if_found(p, target_probs)
self.remove_if_found(circ, target_circs)
self.assertEqual(target_probs, [], msg="Incorrect probabilities")
self.assertEqual(target_circs, [], msg="Incorrect circuits")
def test_pauli_error_2q_unitary_from_pauli(self):
"""Test two-qubit pauli error as unitary qobj from Pauli obj"""
paulis = [Pauli.from_label(s) for s in ['XY', 'YZ', 'ZX']]
probs = [0.5, 0.3, 0.2]
error = pauli_error(zip(paulis, probs), standard_gates=False)
X = standard_gate_unitary('x')
Y = standard_gate_unitary('y')
Z = standard_gate_unitary('z')
target_unitaries = [np.kron(X, Y), np.kron(Y, Z), np.kron(Z, X)]
target_probs = probs.copy()
for j in range(len(paulis)):
circ, p = error.error_term(j)
name = circ[0]['name']
self.assertIn(name, 'unitary')
self.assertEqual(circ[0]['qubits'], [0, 1])
self.remove_if_found(p, target_probs)
self.remove_if_found(circ[0]['params'], target_unitaries)
self.assertEqual(target_probs, [], msg="Incorrect probabilities")
self.assertEqual(target_unitaries, [], msg="Incorrect unitaries")
def run_exp(num_reps=1):
# choice of Hi basis
H_basis = [Pauli.from_label(p) for p in ['II', 'ZI', 'IZ', 'ZZ', 'YY', 'XX']]
num_qubits = 2
evo_time = 1
epsilon = 0.1
L = 32 ## number of local hamiltonian terms
############################################################
# Generate a random Hamiltonian H as the sum of m basis Hi operators
############################################################
hs = np.random.random(L)
indexes = np.random.randint(low=0, high=6, size=L)
## H in matrix form
H_matrix = np.zeros((2 ** num_qubits, 2 ** num_qubits))
## H as a list of pauli operators (unweighted)
H_list = []
for i in range(L):
H_matrix = H_matrix + hs[i] * H_basis[indexes[i]].to_matrix()
H_list.append(H_basis[indexes[i]])
print('matrix H: \n', H_matrix)
# H as a pauli operator
H_qubitOp = op_converter.to_weighted_pauli_operator(MatrixOperator(matrix=H_matrix))
# Generate an initial state
state_in = Custom(num_qubits, state='random')
############################################################
# Ground truth and benchmarks
############################################################
# Ground truth
state_in_vec = state_in.construct_circuit('vector')
groundtruth = expm(-1.j * H_matrix * evo_time) @ state_in_vec
print('The directly computed groundtruth evolution result state is')
print('{}\n.'.format(groundtruth))
# Build circuit using Qiskit's evolve algorithm, which based on Trotter-Suzuki.
quantum_registers = QuantumRegister(num_qubits)
circuit = state_in.construct_circuit('circuit', quantum_registers)
circuit += H_qubitOp.evolve(
None, evo_time, num_time_slices=10,
quantum_registers=quantum_registers,
expansion_mode='suzuki',
expansion_order=1
)
# Simulate Trotter-Suzuki circuit and print it
backend = BasicAer.get_backend('statevector_simulator')
job = q_execute(circuit, backend)
circuit_execution_result = np.asarray(job.result().get_statevector(circuit))
print('The simulated (suzuki) evolution result state is')
print('{}\n'.format(circuit_execution_result))
# The difference between the ground truth and the simulated state
# measured by "Fidelity"
fidelity_suzuki = state_fidelity(groundtruth, circuit_execution_result)
print('Fidelity between the groundtruth and the circuit result states is {}.'.format(fidelity_suzuki))
print('\n')
############################################################
# Our qdrift implementation
############################################################
quantum_registers = QuantumRegister(num_qubits)
circuit = state_in.construct_circuit('circuit', quantum_registers)
# Contruct the circuit which implements qdrift
circuit = time_evolve_qubits(quantum_registers, circuit, num_qubits, H_list, hs, evo_time, epsilon, num_reps)
# Simulate circuit and print it
backend = BasicAer.get_backend('statevector_simulator')
job = q_execute(circuit, backend)
circuit_execution_result = np.asarray(job.result().get_statevector(circuit))
print('The simulated (qdrift) evolution result state is\n{}.'.format(circuit_execution_result))
print('\n')
# Measure the fidelity
fidelity_qdrift = state_fidelity(groundtruth, circuit_execution_result)
print('Fidelity between the groundtruth and the circuit result states is {}.'.format(fidelity_qdrift))
print('\n')
print('benchmark, suzuki:', fidelity_suzuki)
print('qdrift:', fidelity_qdrift)
return fidelity_qdrift, fidelity_suzuki
