def main():
global shots
shots = 1024
provider = IBMQ.load_account()
num_qubits = 5
def backendFilter(x):
nonlocal num_qubits
a = x.configuration().n_qubits >= num_qubits
b = x.configuration().simulator
c = x.status().operational == True
return a and not b and c
qc = least_busy(provider.backends(filters=backendFilter))
simulator = Aer.get_backend('qasm_simulator')
noisy = QasmSimulator.from_backend(qc)
circuits = []
for i in range(1, 3):
for _ in range(10 * num_qubits):
circuits.append(random_gated_circuit(qc, i, 0))
random.shuffle(circuits)
training = circuits[:math.ceil(.8 * len(circuits))]
holdout = circuits[math.ceil(.8 * len(circuits)):]
calibration_circuits = generate_calibration_circuits(
noisy, simulator, 3, 5, 3)
def SimW(cir):
simulator_qasm = BasicAer.get_backend('qasm_simulator')
noise_simulator = QasmSimulator.from_backend(device_backend)
if intro_noise == 0:
simulator = simulator_qasm
else:
simulator = noise_simulator
result = execute(cir, simulator, shots=num_shot).result()
counts = result.get_counts(cir)
#plot_histogram(counts, title='Bell-State counts')
return counts
def startIBMQ():
global Q, backend
# Written to work with versions of IBMQ-Provider both before and after 0.3
sQPV = IBMQVersion['qiskit-ibmq-provider']
pd = '.'
dot1 = [pos for pos, char in enumerate(sQPV) if char == pd][0]
dot2 = [pos for pos, char in enumerate(sQPV) if char == pd][1]
IBMQP_Vers = float(sQPV[dot1 + 1:dot2])
print('IBMQ Provider v', IBMQP_Vers)
if not UseLocal:
print('Pinging IBM Quantum Experience before start')
p = ping('https://api.quantum-computing.ibm.com', 1, 0.5, True)
#p=ping('https://quantum-computing.ibm.com/',1,0.5,True)
try:
print("requested backend: ", backendparm)
except:
sleep(0)
# specify the simulator as the backend
backend = 'ibmq_qasm_simulator'
if p == 200:
if (
IBMQP_Vers > 2
): # The new authentication technique with provider as the object
provider0 = IBMQ.load_account()
try:
Q = provider0.get_backend(backendparm)
except:
Q = provider0.get_backend(backend)
else:
interval = 300
else: # The older IBMQ authentication technique
IBMQ.load_accounts()
try:
Q = IBMQ.get_backend(backendparm)
except:
Q = IBMQ.get_backend(backend)
else:
interval = 300
else:
exit()
else: # THIS IS THE CASE FOR USING LOCAL SIMULATOR
backend = 'local aer qasm_simulator'
print("Building ", backend, "with requested attributes...")
if not AddNoise:
Q = Aer.get_backend('qasm_simulator')
else:
fake_backend = fake_qc()
Q = QasmSimulator.from_backend(fake_backend)
def __init__(
self,
backend_name: str,
hub: Optional[str] = None,
group: Optional[str] = None,
project: Optional[str] = None,
):
"""Construct an IBMQEmulatorBackend. Identical to :py:class:`IBMQBackend`
constructor, except there is no `monitor` parameter. See :py:class:`IBMQBackend`
docs for more details.
"""
self._ibmq = IBMQBackend(backend_name, hub, group, project)
qasm_sim = QasmSimulator.from_backend(self._ibmq._backend)
super().__init__(noise_model=NoiseModel.from_backend(qasm_sim))
self._backend = qasm_sim
def set_vqe_circuit(self, backend = None):
#Check https://qiskit.org/documentation/tutorials/algorithms/03_vqe_simulation_with_noise.html
#seed = 170
iterations = self.vqe_options['maxiter']
#aqua_globals.random_seed = seed
if backend is None:
backend = 'statevector_simulator'
backend = Aer.get_backend(backend)
counts = []
values = []
stds = []
def store_intermediate_result(eval_count, parameters, mean, std):
counts.append(eval_count)
values.append(mean)
stds.append(std)
var_form = TwoLocal(reps = self.vqe_options['n_steps'],
rotation_blocks = 'ry',
entanglement_blocks = 'cx',
entanglement = 'linear',
insert_barriers = True)
spsa = SPSA(maxiter=iterations)
if self.vqe_options['noise']:
os.environ['QISKIT_IN_PARALLEL'] = 'TRUE'
device = QasmSimulator.from_backend(device_backend)
coupling_map = device.configuration().coupling_map
noise_model = NoiseModel.from_backend(device)
basis_gates = noise_model.basis_gates
qi = QuantumInstance(backend=backend,
coupling_map=coupling_map,
noise_model=noise_model)
else:
qi = QuantumInstance(backend=backend)
vqe = VQE(var_form=var_form, optimizer=spsa, callback=store_intermediate_result, quantum_instance=qi)
result = vqe.compute_minimum_eigenvalue(operator=self.H)
return vqe.get_optimal_circuit(), vqe.optimal_params, vqe.get_optimal_vector(), vqe.get_optimal_cost()
from qiskit import IBMQ, execute
from qiskit import QuantumCircuit
from qiskit.providers.aer import QasmSimulator
from qiskit.tools.visualization import plot_histogram
from qiskit.test.mock import FakeSantiago
from qiskit.test.mock import FakeAthens
if __name__ == '__main__':
#device_backend = FakeVigo()
device_backend = FakeAthens()
vigo_simulator = QasmSimulator.from_backend(device_backend)
print(isinstance(1, int))
print(tuple([1]))
print(device_backend.properties().gate_error(gate="cx", qubits=(0, 1)))
print(device_backend.properties().gate_error(gate="cx", qubits=(4, 3)))
print(device_backend.properties().gate_error(gate="cx", qubits=(1, 2)))
print(device_backend.properties().gate_error(gate="cx", qubits=(2, 3)))
print(device_backend.properties().gate_error(gate="u2", qubits=2))
print(device_backend.properties().gate_error(gate="u2", qubits=1))
print(device_backend.properties().gate_error(gate="u2", qubits=0))
print(device_backend.properties().gate_error(gate="u2", qubits=3))