QCompress is an implementation of the quantum autoencoder using Forest and OpenFermion.
This was our project for Rigetti Computing's first quantum computing hackathon. Our goal was to create a flexible framework for the quantum autoencoder (QAE) that can be used to compress quantum data. This autoencoder implementation is based on the work by Romero et al.
We've included a demonstration of the quantum autoencoder code in qae_h2_demo.ipynb, in which we
compress the ground states of molecular hydrogen.
- Python 3.5
- pyQuil 2.0.0
- OpenFermion 0.6
- forestopenfermion 0.0.3
- Grove 1.6.0
Sukin Sim (Hannah), Evan Anderson, Eric Brown, Jonathan Romero
We note that there is a lot of room for improvement and fixes. Please feel free to submit pull requests!