def run_IBM(H=None,
backend=None,
num_samples=100,
qaoa_steps=3,
variables=None):
num_vars = len(list(H.linear))
qubit_op, offset = get_ising_opt_qubitops(H, variables)
if backend == None:
backend = BasicAer.get_backend('qasm_simulator')
quantum_instance = QuantumInstance(backend)
spsa = SPSA(max_trials=10)
qaoa = QAOA(qubit_op, spsa, qaoa_steps)
result = qaoa.run(quantum_instance)
circ = qaoa.get_optimal_circuit()
q = circ.qregs[0]
c = ClassicalRegister(num_vars, 'c')
circ.cregs.append(c)
circ.measure(q, c)
job = execute(circ, backend, shots=num_samples, memory=True)
return job.result().get_counts(circ)
def libraryoptimize(qubo,
edges,
cedges,
n,
p,
plotoptangles=False,
modulo=False):
if (qubo == "qubo1"):
H = makeNPMatrix1(edges, cedges, n)
if (qubo == "qubo2"):
H = makeNPMatrix2(edges, cedges, n)
if (qubo == "qubo3"):
H = makeNPMatrix2(edges, cedges, n)
optimizer = COBYLA()
qaoa_mes = QAOA(H,
p=p,
optimizer=optimizer,
quantum_instance=Aer.get_backend('statevector_simulator'))
results = qaoa_mes.run()
qc1 = qaoa_mes.get_optimal_circuit()
print(type(results.optimal_parameters))
print(type(results.optimal_parameters.items()))
i = 0
for key, value in results.optimal_parameters.items():
if (i == 0):
gamma = value
i += 1
else:
beta = value
print("beta", beta)
print("gamma", gamma)
print('optimal params: ', results.optimal_parameters)
print('optimal value: ', results.optimal_value)
qcl = qaoa_mes.get_optimal_circuit()
optgammasbetas = []
isgamma = 0
for key, value in results.optimal_parameters.items():
if (modulo):
if (isgamma < p):
optgammasbetas.append(value % (2 * math.pi))
isgamma += 1
else:
optgammasbetas.append(value % (math.pi))
else:
optgammasbetas.append(value)
if (plotoptangles):
plottheoptangles(optgammasbetas, p)
if (qubo == "qubo1"):
qc = makeCircuit1(n, edges, cedges, optgammasbetas, p)
if (qubo == "qubo2"):
qc = makeCircuit2(n, edges, cedges, optgammasbetas, p)
if (qubo == "qubo3"):
qc = makeCircuit3(n, edges, cedges, optgammasbetas, p)
ans = ClassicalRegister(n)
sol = QuantumRegister(n)
QAOA2 = QuantumCircuit(sol, ans)
QAOA2.append(qc1, range(n))
return qc, optgammasbetas