Create quantum_simulation_algorithms.py

quantum/algorithms/quantum_simulation_algorithms.py

@@ -0,0 +1,95 @@
+# quantum_simulation_algorithms.py
+import numpy as np
+from qiskit import QuantumCircuit, Aer, transpile, assemble, execute
+from qiskit.visualization import plot_histogram
+from qiskit.quantum_info import Statevector
+
+class QuantumPhaseEstimation:
+    def __init__(self, unitary, num_qubits):
+        """
+        Initialize the Quantum Phase Estimation algorithm.
+
+        Parameters:
+        - unitary: The unitary operator (as a quantum circuit) whose eigenvalue is to be estimated.
+        - num_qubits: Number of qubits for the phase estimation.
+        """
+        self.unitary = unitary
+        self.num_qubits = num_qubits
+
+    def create_circuit(self):
+        """
+        Create the quantum circuit for the Quantum Phase Estimation algorithm.
+
+        Returns:
+        - QuantumCircuit: The constructed QPE circuit.
+        """
+        # Create a quantum circuit with additional qubits for the phase estimation
+        circuit = QuantumCircuit(self.num_qubits + 1, self.num_qubits)
+
+        # Initialize the counting qubits to |+>
+        for i in range(self.num_qubits):
+            circuit.h(i)
+
+        # Apply controlled unitary operations
+        for i in range(self.num_qubits):
+            circuit.append(self.unitary.control(), [i] + [self.num_qubits])
+
+        # Apply inverse QFT
+        circuit.append(self.inverse_qft(self.num_qubits), range(self.num_qubits))
+
+        # Measure the counting qubits
+        circuit.measure(range(self.num_qubits), range(self.num_qubits))
+
+        return circuit
+
+    def inverse_qft(self, n):
+        """
+        Create the inverse Quantum Fourier Transform circuit.
+
+        Parameters:
+        - n: Number of qubits.
+
+        Returns:
+        - QuantumCircuit: The inverse QFT circuit.
+        """
+        circuit = QuantumCircuit(n)
+        for j in range(n):
+            circuit.h(j)
+            for k in range(j):
+                circuit.cp(-np.pi / (2 ** (j - k)), k, j)
+        return circuit
+
+    def estimate_phase(self):
+        """
+        Estimate the phase using the Quantum Phase Estimation algorithm.
+
+        Returns:
+        - result: The measurement result of the phase estimation.
+        """
+        # Create the QPE circuit
+        circuit = self.create_circuit()
+
+        # Execute the circuit
+        backend = Aer.get_backend('qasm_simulator')
+        transpiled_circuit = transpile(circuit, backend)
+        qobj = assemble(transpiled_circuit)
+        result = execute(qobj, backend, shots=1024).result()
+
+        return result.get_counts()
+
+if __name__ == "__main__":
+    # Example usage
+    # Define a unitary operator (e.g., a rotation operator)
+    theta = np.pi / 4  # Example angle
+    unitary = QuantumCircuit(1)
+    unitary.rz(theta, 0)  # Apply a rotation around the Z-axis
+
+    # Initialize the Quantum Phase Estimation algorithm
+    qpe = QuantumPhaseEstimation(unitary, num_qubits=3)
+
+    # Estimate the phase
+    counts = qpe.estimate_phase()
+    print("Measurement Results:", counts)
+
+    # Plot the results
+    plot_histogram(counts)