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#initialization
import matplotlib.pyplot as plt
import numpy as np
# importing Qiskit
from qiskit import IBMQ, Aer, assemble, transpile
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister
from qiskit.providers.ibmq import least_busy
# import basic plot tools
from qiskit.visualization import plot_histogram
def initialize_s(qc, qubits):
"""Apply a H-gate to 'qubits' in qc"""
for q in qubits:
qc.h(q)
return qc
def diffuser(nqubits):
qc = QuantumCircuit(nqubits)
# Apply transformation |s> -> |00..0> (H-gates)
for qubit in range(nqubits):
qc.h(qubit)
# Apply transformation |00..0> -> |11..1> (X-gates)
for qubit in range(nqubits):
qc.x(qubit)
# Do multi-controlled-Z gate
qc.h(nqubits-1)
qc.mct(list(range(nqubits-1)), nqubits-1) # multi-controlled-toffoli
qc.h(nqubits-1)
# Apply transformation |11..1> -> |00..0>
for qubit in range(nqubits):
qc.x(qubit)
# Apply transformation |00..0> -> |s>
for qubit in range(nqubits):
qc.h(qubit)
# We will return the diffuser as a gate
U_s = qc.to_gate()
U_s.name = "U$_s$"
return U_s
def grover(n):
qc = QuantumCircuit(3)
qc.cz(0, 2)
qc.cz(1, 2)
oracle_ex3 = qc.to_gate()
oracle_ex3.name = "U$_\omega$"
grover_circuit = QuantumCircuit(n)
grover_circuit = initialize_s(grover_circuit, [0,1,2])
grover_circuit.append(oracle_ex3, [0,1,2])
grover_circuit.append(diffuser(n), [0,1,2])
grover_circuit.measure_all()
return grover_circuit
def eval_counts_grover(counts):
shots = 0
p110 = 0
p101 = 0
for i in counts:
shots += counts[i]
if i == "110" or i == 6 or i =="6":
p110 = counts[i]
elif i == "101" or i == 5 or i == "5":
p101 = counts[i]
p110 /= shots
p101 /= shots
return p110 + p101 # probabillity of a correct state