This library provides quantum circuits for variational quantum algorithms, which are an approach to quantum computing that utilizes classical optimization techniques to find the optimal parameters for a quantum circuit to solve a given problem. The circuits provided in this library are used to benchmark the performance of optimizers introduced in the paper "Optimizing Variational Quantum Algorithms with qBANG: A Hybrid Approach to Tackle Flat Energy Landscapes" [[arXiv](UPDATE LINK)].
The package qflow is prepared such that it can be installed in development mode locally (such that any change in the code is instantly reflected). To install qflow locally, clone/download the repository and run the following command from the qflow folder:
pip install -e .
Then, run any of the notebooks in the example folder to play around with variational quantum circuits.
To run the quantum chemistry examples you need to install pyscf.
Feel free to reach out to me at [email protected] if you face any issues.
We welcome contributions to this project! If you'd like to contribute, please submit a pull request with your changes. If you have any questions or suggestions, please feel free to contact us at [email protected].
For testing and verification of the software run:
python -m pytest src/qflow/tests
If you want to deinstall the library use:
pip uninstall qflow
We found several very helpful codebases when building this repo, and we sincerely thank their authors:
- PennyLane Tutorials:
If you find this repo useful for your research, please consider citing our paper:
@article{opt-vqa-with-qbang,
title={Optimizing Variational Quantum Algorithms with qBang: Efficiently Interweaving Metric and Momentum to Tackle Flat Energy Landscapes},
author={Fitzek, David and Jonsson, Robert S. and Dobrautz, Werner and Schäfer, Christian},
journal={arXiv preprint arXiv:2304.13882},
year={2023},
}Initial release (v1.0): April 2023
Current maintainers:
MIT License