Quantum Squid Game - method1

SquidGame.py

from matplotlib import pyplot as plt
import numpy as np
from qiskit import *
from qiskit.circuit.library.standard_gates import XGate

# Creating the circuit with 4 classical bits and 4 qbits
qc = QuantumCircuit(4,4)
# Creating the entanglement between players qubits
qc.h(1)
qc.cx(1,0)

# Applying X gate power raised to (-0.25)
new_gate = XGate().power(-0.25)
qc.append(new_gate, [0])
qc.barrier()

# Initialize input qubits randomly
qc.h(2)
qc.h(3)
qc.barrier()

# Players applying a controlled sqrt(x) gate to their qubits
# taking input qubits as controllers
qc.csx(2,0)
qc.csx(3,1)
qc.barrier()

# Players measure their qubits and inform the result to guards
qc.measure(0,0)
qc.measure(1,1)

# measuring the input qubits to calculate xy
qc.measure(2,2)
qc.measure(3,3)

# un-comment the following line to display the circuit.
display(qc.draw(output='mpl'))

# Executing the circuit in a simulator 1000 times
result = execute(qc,Aer.get_backend('qasm_simulator'),shots=1000).result()

# Calculate the XOR of measurement results 
winCount = 0
for key, value in result.get_counts().items():
    # calculate xy
    xy = int(key[0]) * int(key[1])
    # calculate xor of player outputs
    xor = int(key[2], 2) ^ int(key[3], 2) 
    # count as a win of xy = xor of player outputs
    if xy == xor:
        winCount += value
print("Win probability : ", winCount/10)