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First place, CWRU Quantum Computing Club Hackathon, Fall 2022

Python 100.00%
hackathon-winner laser-cutting qiskit quantum-computing quantum-optimization traveling-salesman-problem

qiskit-gcode-path-optimization's Introduction

qiskit-gcode-path-optimization

First place, CWRU Quantum Computing Club Hackathon, Fall 2022.

Objective

Use a combination of quantum and classical optimization techniques to produce optimal G-Code paths for modern laser cutters.

Methodology

  1. Use an off-the-shelf library to generate G-Code from the SVG
  2. Replace the one small part of the library that approximates a solution to TSP with something that interfaces with a quantum computer
    • Generate a complete weighted graph with NetworkX
    • Use Qiskit's algorithms module to convert the graph to a quadratic unconstrained binary optimization problem
    • Use a variational quantum eigensolver to solve the QUBO
  3. Use the result of the optimization problem to construct faster G-Code paths.

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