bernstein-vazirani.py

# initialization
import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'svg' # Makes the images look nice
import numpy as np

# importing Qiskit
from qiskit import IBMQ, BasicAer
from qiskit.providers.ibmq import least_busy
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister, execute

# import basic plot tools
from qiskit.visualization import plot_histogram

nQubits = 2 # number of physical qubits used to represent s
s = 3       # the hidden integer 

# make sure that a can be represented with nqubits
s = s % 2**(nQubits)

# Creating registers
# qubits for querying the oracle and finding the hidden integer
qr = QuantumRegister(nQubits)
# bits for recording the measurement on qr
cr = ClassicalRegister(nQubits)

bvCircuit = QuantumCircuit(qr, cr)
barriers = True

# Apply Hadamard gates before querying the oracle
for i in range(nQubits):
    bvCircuit.h(qr[i])
    
# Apply barrier 
if barriers:
    bvCircuit.barrier()

# Apply the inner-product oracle
for i in range(nQubits):
    if (s & (1 << i)):
        bvCircuit.z(qr[i])
    else:
        bvCircuit.iden(qr[i])
        
# Apply barrier 
if barriers:
    bvCircuit.barrier()

#Apply Hadamard gates after querying the oracle
for i in range(nQubits):
    bvCircuit.h(qr[i])
    
# Apply barrier 
if barriers:
    bvCircuit.barrier()

# Measurement
bvCircuit.measure(qr, cr)

bvCircuit.draw(output='mpl')

# use local simulator
backend = BasicAer.get_backend('qasm_simulator')
shots = 1024
results = execute(bvCircuit, backend=backend, shots=shots).result()
answer = results.get_counts()

plot_histogram(answer)

# Load our saved IBMQ accounts and get the least busy backend device with less than or equal to 5 qubits
IBMQ.load_account()
provider = IBMQ.get_provider(hub='ibm-q')
provider.backends()
backend = least_busy(provider.backends(filters=lambda x: x.configuration().n_qubits <= 5 and
                                   x.configuration().n_qubits >= 2 and
                                   not x.configuration().simulator and x.status().operational==True))
print("least busy backend: ", backend)

# Run our circuit on the least busy backend. Monitor the execution of the job in the queue
from qiskit.tools.monitor import job_monitor

shots = 1024
job = execute(bvCircuit, backend=backend, shots=shots)

job_monitor(job, interval = 2)

# Get the results from the computation
results = job.result()
answer = results.get_counts()

plot_histogram(answer)