| import numpy as np |
| from scipy.integrate import solve_ivp |
| from qiskit import Aer, QuantumCircuit, execute |
| from qiskit.algorithms import Grover, VQE |
| from qiskit.circuit.library import EfficientSU2 |
| from qiskit.utils import QuantumInstance |
| from qiskit.algorithms.optimizers import COBYLA |
| from matplotlib import pyplot as plt |
| import pennylane as qml |
|
|
| class UnifiedQuantumAgent: |
| def __init__(self): |
| # Initialize Quantum Backend |
| self.backend = Aer.get_backend("qasm_simulator") |
| self.quantum_instance = QuantumInstance(self.backend) |
|
|
| # Quantum Optimization (Grover's Search) |
| def grover_search(self, oracle_bits): |
| n_qubits = len(oracle_bits) |
| circuit = QuantumCircuit(n_qubits) |
| circuit.z([i for i, bit in enumerate(oracle_bits) if bit == "1"]) |
| circuit = Grover(circuit).construct_circuit(None) |
| result = execute(circuit, self.backend, shots=1024).result() |
| counts = result.get_counts() |
| return counts |
|
|
| # Variational Quantum Eigensolver (VQE) |
| def vqe_solver(self, hamiltonian): |
| ansatz = EfficientSU2(num_qubits=2, entanglement="linear") |
| optimizer = COBYLA(maxiter=200) |
| vqe = VQE(ansatz, optimizer, quantum_instance=self.quantum_instance) |
| result = vqe.compute_minimum_eigenvalue(operator=hamiltonian) |
| return result |
|
|
| # Riemann Zeta Function Oscillation Simulation |
| def riemann_oscillation(self, t_span, zeta_func): |
| def oscillatory_rhs(t, y): |
| return [np.sin(y[0]) - zeta_func(t)] |
| solution = solve_ivp(oscillatory_rhs, t_span, [0], t_eval=np.linspace(t_span[0], t_span[1], 500)) |
| return solution.t, solution.y[0] |
|
|
| # PennyLane Quantum Circuit Simulation |
| def pennylane_simulation(self, params): |
| dev = qml.device("default.qubit", wires=2) |
|
|
| @qml.qnode(dev) |
| def circuit(params): |
| qml.RX(params[0], wires=0) |
| qml.RY(params[1], wires=1) |
| qml.CNOT(wires=[0, 1]) |
| return qml.expval(qml.PauliZ(0)) |
|
|
| return circuit(params) |
|
|
| # Visualization Utility |
| def plot_results(self, x, y, title, xlabel, ylabel): |
| plt.figure(figsize=(8, 6)) |
| plt.plot(x, y, label="Simulation Data") |
| plt.title(title) |
| plt.xlabel(xlabel) |
| plt.ylabel(ylabel) |
| plt.legend() |
| plt.grid(True) |
| plt.show() |
|
|
| # Unified Agent in Action |
| if __name__ == "__main__": |
| agent = UnifiedQuantumAgent() |
|
|
| # Example 1: Grover's Search |
| oracle = "1010" |
| counts = agent.grover_search(oracle) |
| print(f"Grover's Search Results: {counts}") |
|
|
| # Example 2: VQE Solver |
| from qiskit.opflow import I, Z |
| hamiltonian = (Z ^ I) + (I ^ Z) |
| vqe_result = agent.vqe_solver(hamiltonian) |
| print(f"VQE Optimal Value: {vqe_result.eigenvalue.real}") |
|
|
| # Example 3: Riemann Zeta Function Oscillation |
| t, y = agent.riemann_oscillation((0, 10), lambda t: np.cos(t)) |
| agent.plot_results(t, y, "Riemann Zeta Oscillation", "Time", "Amplitude") |
|
|
| # Example 4: PennyLane Simulation |
| params = [np.pi / 4, np.pi / 3] |
| expectation = agent.pennylane_simulation(params) |
| print(f"PennyLane Simulation Expectation Value: {expectation}") |
