singleQubitEncoding.py

# Get MNIST Dataset
# Encode the image into a single qubit
# Run the circuit
# Measure the result
# Compare the result with the label
# Calculate the accuracy
# Plot the result

import numpy as np
from qiskit import QuantumCircuit
from qiskit.quantum_info import DensityMatrix
from qiskit.visualization import plot_state_qsphere
#import tensorflow as tf

SAVE_PATH = "./simple_mnist/"
x_encodedImage = []

def TestSingleQubitEncoding():
    # Get MNIST Dataset
    (x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()
    x_train = x_train / 255.0
    x_test = x_test / 255.0
    # Print the information about the single image of the dataset with height and width
    print("x_train.shape: ", x_train.shape)
    x_encodedImage = np.zeros((len(x_train), 1, 28, 28))

    # Encode the image into a single qubit
    # 1. Encode the image into a single qubit with the length dataset
    # 2. Encode the image into a single qubit with the length height and width of the image
    # 3. Start the iteration for the row of the image
    # 4. Start the iteration for the column of the image
    # 5. Encode the pixel into a single qubit

    for i in range(0,10):
        x_train[i] = x_train[i].reshape(1, 28, 28)
        for j in range(0, 28):
            for k in range(0, 28):
                # Collect the pixel value
                # r = (drow + frow); c = (dcol + fcol)
                # drow = 0; frow = 0; dcol = 0; fcol = 0
                # r = 0; c = 0
                r = j
                c = k
                pixel = x_train[i][r][c]
                
                if(r<28 and c<28):
                    #x append value at pixel (r, c) ∈ d
                    x_encodedImage[i][0][r][c] = pixel
                else:
                    pixel.append(0)

        print("x_encodedImage: ", x_encodedImage[i])
        

#TestSingleQubitEncoding()
#Use the qiskit to plot the first quantum image
# Convert the first quantum image to the density matrix
# Plot the density matrix
qc = QuantumCircuit(2)
qc.h([0, 1])
qc.cz(0,1)
qc.ry(np.pi/3, 0)
qc.rx(np.pi/5, 1)
qc.z(1)

matrix = DensityMatrix(qc)
plot_state_qsphere(matrix,
     show_state_phases = True, use_degrees = True)