Max Cut Problem Solution

Solution to IonQ's challenge at MIT IQuhack 2025

Overview

This project provides a solution for the Max Cut Problem, a fundamental problem in graph theory and combinatorial optimization. The goal of the Max Cut problem is to partition the vertices of a given graph into two subsets such that the number (or total weight) of edges between the two subsets is maximized.

This repository contains a Jupyter Notebook implementing an approach to solve the IonQ's challenge, heuristic methods and quantum computing techniques.

Contents

• Implementation of the Max Cut problem solution.
• Graph representation and visualization.
• Algorithms used for solving the problem.
• Performance analysis and results.

Usage

1. Clone the repository:

   git clone https://github.com/sabrikirishwaran/max-cut-solution.git](https://github.com/Sabarikirishwaran/Max_cut_MIT_IONQr_2025.git
   cd max-cut-solution

2. Open Jupyter Notebook:

   jupyter notebook

3. Open Max_cut_solution.ipynb and run the cells.

Contributing

Feel free to submit issues, feature requests, or pull requests. Contributions are welcome!

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

Sabarikirishwaran Ponnambalam