Create Quantayomama

Self-destruct sequence

Quantayomama

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+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}")