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Bernstein-Vazirani Algorithm Implementation in Qiskit

It is a restricted version of the Deutsch-Jozsa algorithm where instead of distinguishing between two different classes of functions, it tries to learn a string encoded in a function.

Here is implementation for Bernstein-Vaziarini algorithm:

from qiskit import *
%matplotlib inline
from qiskit.tools.visualization import plot_histogram

num = '101001'
circuit = QuantumCircuit(len(num)+1, len(num))
circuit.h(range(len(num)))
circuit.x(len(num))
circuit.h(len(num))
circuit.barrier()

<qiskit.circuit.instructionset.InstructionSet at 0x6370a60b4e80>

for i, val in enumerate(reversed(num)):
    if val == "1":
        circuit.cx(i,6)

circuit.barrier()
circuit.h(range(len(num)))

<qiskit.circuit.instructionset.InstructionSet at 0x6370a60b4e20>

circuit.measure(range(len(num)), range(len(num)))

<qiskit.circuit.instructionset.InstructionSet at 0x6370e006d5a0>

sim = Aer.get_backend('qasm_simulator')
result = execute(circuit, sim, shots = 1).result()
counts = result.get_counts()
print(counts)

{'101001': 1}