lanl/pyQBTNs

pyQBTNs is a Python library for boolean matrix and tensor factorization using D-Wave quantum annealers. The library includes five different boolean tensor decomposition methods making up three distinct types of tensor networks. pyQBTNs is developed as part of the R&D 100 award wining SmartTensors project.

BibTeX:

@MISC{Pelofske2021_pyQBTNs,
    author = {E. {Pelofske} and H. {Djidjev} and D. {O'Malley} and M. E. {Eren} and G. {Hahn} and B. S. {Alexandrov}},
    title = {pyQBTNs},
    year = {2021},
    publisher = {GitHub},
    journal = {GitHub repository},
    doi = {10.5281/zenodo.4876527},
    howpublished = {\url{https://github.com/lanl/pyQBTNs}}
}

@misc{pelofske2021boolean,
    title={Boolean Hierarchical Tucker Networks on Quantum Annealers}, 
    author={Elijah Pelofske and Georg Hahn and Daniel O'Malley and Hristo N. Djidjev and Boian S. Alexandrov},
    year={2021},
    eprint={2103.07399},
    archivePrefix={arXiv},
    primaryClass={quant-ph}
}
Maksim E. Eren
Maksim E. Eren
Computer Science Student

My research interests lie at the intersection of the machine learning and cybersecurity disciplines, with a concentration in tensor decomposition.