Quantum K-Means Clustering

This repository implements the K-means clustering algorithm using quantum state encoding for classical data points, and encode it to Quntum .

Functions

1. generate_random_data

Generates a NumPy array of random data with one column < Ket>

2. ground_state

Returns a NumPy array representing the ground state (|0> state).

3. initialize_centroids

Randomly initializes k centroids from the data points.

4. encode_data

Encodes classical data points into quantum states using an RXGate.

5. findClosestCentroids

Computes the centroid memberships for every encoded data point.

6. computeCentroids

Returns the new centroids by computing the means of the data points assigned to each centroid.

7. K_means_Quantum_clustering

Performs K-means clustering on classical data points using quantum state encoding.

Usage

1-Generate Random Data

2-python

3-from qiskit.circuit.library import XGate

4-import numpy as np

Installation

pip install qiskit for gates You can install the required libraries using pip: pip install qiskit matplotlib