In [15]:
#initialization
import matplotlib.pyplot as plt
import numpy as np
import math
from qiskit.visualization import plot_distribution

# importing Qiskit
from qiskit import transpile, assemble
from qiskit_aer import Aer
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister

# import basic plot tools and circuits
from qiskit.visualization import plot_histogram
from qiskit.circuit.library import QFT
from qiskit.visualization import plot_bloch_multivector
In [16]:
qpe = QuantumCircuit(3, 2)
qpe.x(2)
qpe.draw()
Out[16]:
          
q_0: ─────
          
q_1: ─────
     ┌───┐
q_2: ┤ X ├
     └───┘
c: 2/═════
In [17]:
for qubit in range(2):
    qpe.h(qubit)
qpe.draw()
Out[17]:
     ┌───┐
q_0: ┤ H ├
     ├───┤
q_1: ┤ H ├
     ├───┤
q_2: ┤ X ├
     └───┘
c: 2/═════
In [18]:
repetitions = 1
angle       = 4*math.pi/3
for counting_qubit in range(2):
    for i in range(repetitions):
        qpe.cp(angle, counting_qubit, 2); # controlled-T
    repetitions *= 2
qpe.draw()
Out[18]:
     ┌───┐                              
q_0: ┤ H ├─■────────────────────────────
     ├───┤ │                            
q_1: ┤ H ├─┼─────────■─────────■────────
     ├───┤ │P(4π/3)  │P(4π/3)  │P(4π/3) 
q_2: ┤ X ├─■─────────■─────────■────────
     └───┘                              
c: 2/═══════════════════════════════════
In [19]:
qpe.barrier()
# Apply inverse QFT
qpe = qpe.compose(QFT(2, inverse=True), [0,1])
# Measure
qpe.barrier()
for n in range(2):
    qpe.measure(n,n)

qpe.draw()
Out[19]:
     ┌───┐                               ░ ┌──────────┐ ░ ┌─┐   
q_0: ┤ H ├─■─────────────────────────────░─┤0         ├─░─┤M├───
     ├───┤ │                             ░ │  IQFT_dg │ ░ └╥┘┌─┐
q_1: ┤ H ├─┼─────────■─────────■─────────░─┤1         ├─░──╫─┤M├
     ├───┤ │P(4π/3)  │P(4π/3)  │P(4π/3)  ░ └──────────┘ ░  ║ └╥┘
q_2: ┤ X ├─■─────────■─────────■─────────░──────────────░──╫──╫─
     └───┘                               ░              ░  ║  ║ 
c: 2/══════════════════════════════════════════════════════╩══╩═
                                                           0  1
In [20]:
aer_sim = Aer.get_backend('aer_simulator')
shots = 2048
t_qpe = transpile(qpe, aer_sim)
results = aer_sim.run(t_qpe, shots=shots).result()
answer = results.get_counts()

plot_distribution(answer)
Out[20]:
In [ ]: