priyanshupansari / cs269q_radzihovsky_murphy_swofford_qaoa

Final Project Repository for CS 269Q, Spring 2019

A QAOA Solution to the Traveling Salesman Problem using pyQuil

CS 269Q Final Project

Matt Radzihovsky, Joey Murphy, Mason Swofford

Final Project Repository for CS 269Q, Spring 2019

QAOA TSP solution using mixers is implemented in tsp_qaoa_updated.py, based on work presented in Hadfield et. al 2017 (paper included above).

QAOA constraint hamiltonian TSP solution is implemented in quantum.py.

Classical solution implemented in classical.py. See instructions below for installation.

Installation instructions

After cloning this repository, users who already have a working installation of Anaconda can follow these steps to run the code:

1. Create a new conda environment conda create -n my_env
2. Activate the environment source activate my_env
3. Install pip conda install pip
4. Install dependencies listed in the requirements.txt file pip install —user —requirement requirements.txt
5. In another terminal window, activate the same virtual environment source activate my_env
6. Initiate a QVM connection qvm -S
7. You’re now ready to run the code in the original window. See files for command line argument documentation. python quantum.py 3 python tsp_qaoa_updated.py 3 0.75 1