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TensorNetwork: A Library for Physics and Machine Learning

Chase Roberts, Ashley Milsted, Martin Ganahl, Adam Zalcman, Bruce Fontaine, Yijian Zou, Jack Hidary, Guifre Vidal, Stefan Leichenauer
Alphabet (Google) X, Mountain View, CA 94043, USA
arXiv:1905.01330 [physics.comp-ph], (3 May 2019)

@misc{roberts2019tensornetwork,

   title={TensorNetwork: A Library for Physics and Machine Learning},

   author={Roberts, Chase and Milsted, Ashley and Ganahl, Martin and Zalcman, Adam and Fontaine, Bruce and Zou, Yijian and Hidary, Jack and Vidal, Guifre and Leichenauer, Stefan},

   year={2019},

   eprint={1905.01330},

   archivePrefix={arXiv},

   primaryClass={physics.comp-ph}

}

TensorNetwork is an open source library for implementing tensor network algorithms. Tensor networks are sparse data structures originally designed for simulating quantum many-body physics, but are currently also applied in a number of other research areas, including machine learning. We demonstrate the use of the API with applications both physics and machine learning, with details appearing in companion papers.
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