Artifact of Accelerating Quantum Algorithms With Machine Learning

This artifact contains the code and data related to our efforts to tackle the Quantum Algorithm Grand Challenge (QAGC2024)--putting together a team of quantum physics and computer scientists--to accelerate the Variational Quantum Eigensolver (VQE) algorithms and eigensolvers in general.

Submission to the QAGC2024: We submitted two solutions for the challenge QCELS Implementation at GitHub and QAGC with ML Implementation at GitHub plus shared extra code here to combine these ideas, in general. This artifact contains snapshots of the solutions as zip files (QAGC_submission-main.zip and QCELS_for_QAGC-main.zip).

The Original Challenge: See [here](https://github.com/Connorpl/KCL_QAGC/blob/main/GQGC_Presentation.pdf) for details. Web page: https://qunasys.com/en/technology/, and its GitHub [quantum-algorithm-grand-challenge-2024](https://github.com/QunaSys/quantum-algorithm-grand-challenge-2024). 

Note: Some code and data used during the development and testing from the original challenge and is required to run our solutions.