English

TensorTrace: an application to contract tensor networks

Quantum Physics 2019-11-07 v1 Strongly Correlated Electrons Mathematical Software

Abstract

Tensor network methods are a conceptually elegant framework for encoding complicated datasets, where high-order tensors are approximated as networks of low-order tensors. In practice, however, the numeric implementation of tensor network algorithms is often a labor-intensive and error-prone task, even for experienced researchers in this area. \emph{TensorTrace} is application designed to alleviate the burden of contracting tensor networks: it provides a graphic drawing interface specifically tailored for the construction of tensor network diagrams, from which the code for their optimal contraction can then be automatically generated (in the users choice of the MATLAB, Python or Julia languages). \emph{TensorTrace} is freely available at \url{https://www.tensortrace.com} with versions for Windows, Mac and Ubuntu.

Keywords

Cite

@article{arxiv.1911.02558,
  title  = {TensorTrace: an application to contract tensor networks},
  author = {Glen Evenbly},
  journal= {arXiv preprint arXiv:1911.02558},
  year   = {2019}
}

Comments

5 pages, 5 figures

R2 v1 2026-06-23T12:07:46.474Z