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Create qaoa.py
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KOSASIH authored Oct 12, 2024
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# qaoa.py
import numpy as np
from qiskit import QuantumCircuit, execute
from qiskit.providers.aer import AerSimulator

class QAOA:
def __init__(self, num_qubits, num_iterations, p):
self.num_qubits = num_qubits
self.num_iterations = num_iterations
self.p = p
self.quantum_backend = AerSimulator()
self.quantum_circuit = QuantumCircuit(num_qubits)

def _generate_quantum_circuit(self):
for i in range(self.num_qubits):
self.quantum_circuit.ry(np.pi / 2, i)
self.quantum_circuit.rz(np.pi / 2, i)
return self.quantum_circuit

def _evaluate_cost(self, X):
# Implement cost function
pass

def _qaoa(self, X):
quantum_circuit = self._generate_quantum_circuit()
fori in range(self.num_iterations):
for j in range(self.p):
quantum_circuit.ry(np.pi / 2, 0)
quantum_circuit.rz(np.pi / 2, 0)
quantum_circuit.barrier()
job = execute(quantum_circuit, self.quantum_backend, shots=1024)
result = job.result()
counts = result.get_counts(quantum_circuit)
return counts

def train(self, X):
counts = self._qaoa(X)
best_solution = max(counts, key=lambda x: self._evaluate_cost(x))
return best_solution

# Example usage:
X = np.random.rand(100, 10)
qaoa = QAOA(num_qubits=10, num_iterations=100, p=2)
best_solution = qaoa.train(X)

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