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The Cytnx library for tensor networks

Year: 2025
Type: article
Abstract: We introduce a tensor network library designed for classical and quantum physics simulations called Cytnx (pronounced as sci-tens). This library provides an almost identical interface and syntax for both C++ and Python, allowing users to effortlessly switch between the two languages. Aiming at a quick learning process for new users of tensor network algorithms, the interfaces resemble the popular Python scientific libraries like NumPy, Scipy, and PyTorch. Not only multiple global Abelian symmetries can be easily defined and implemented, Cytnx also provides a new tool called Network that allows users to store large tensor networks and perform tensor network contractions in an optimal order automatically. With the integration of cuQuantum, tensor calculations can also be executed efficiently on GPUs. We present benchmark results for tensor operations on both devices, CPU and GPU. We also discuss features and higher-level interfaces to be added in the future.
DOI: 10.21468/scipostphyscodeb.53
Authors: Kai-Hsin Wu, Chang-Teng Lin, Ke Hsu, Hao-Ti Hung, Manuel Schneider, Chia-Min Chung, Ying-Jer Kao, Pochung Chen
Institutions: Boston University, National Taiwan University, National Yang Ming Chiao Tung University, National Sun Yat-sen University, National Center for Theoretical Sciences, Physics Division, National Tsing Hua University
Language: English
Open Access status: diamond
OpenAlex ID: W4408413844
FWCI: 1.107
Cites: 65
Cited by: 3
Related to: 10