README_L3_05.md

L3-05: Quantum Phase Estimation Implementation

NEHAL MAHENDRA RANE

Problem Statement:

Implement Quantum Phase Estimation (QPE) to approximate eigenvalues.

Steps:

1. Install Libraries:

   • Install qiskit, numpy, and matplotlib.

   !pip install qiskit
   !pip install numpy
   !pip install matplotlib

2. Imports:

   from qiskit import QuantumCircuit
   from qiskit import transpile

3. Controlled Unitary Function: A function that creates a controlled unitary operation.

   def controlled_unitary(circuit, theta, control_qubit, target_qubit):
       # Function body here

4. Quantum Phase Estimation Function: A function that implements the QPE algorithm.

   def quantum_phase_estimation(theta, num_qubits):
       circuit = QuantumCircuit(num_qubits + 1, num_qubits)

5. Parameters: Parameters such as angle (theta) and the number of qubits.

   theta = np.pi / 4
   num_qubits = 3

6. Simulation: The circuit is transpiled and run on a Qiskit Aer simulator.

   simulator = Aer.get_backend('qasm_simulator')
   result = simulator.run(transpiled_circuit).result()
   counts = result.get_counts(circuit)
   print(counts)

7. Visualization: Plotting the results using a histogram.

   plot_histogram(counts)