The reviewed record of science sign in
Pith

arxiv: 2408.02010 · v3 · pith:4EQLNVV2 · submitted 2024-08-04 · cond-mat.str-el

Tensor Network Python (TeNPy) version 1

Johannes Hauschild , Jakob Unfried , Sajant Anand , Bartholomew Andrews , Marcus Bintz , Umberto Borla , Stefan Divic , Markus Drescher
show 22 more authors
Jan Geiger Martin Hefel K\'evin H\'emery Wilhelm Kadow Jack Kemp Nico Kirchner Vincent S. Liu Gunnar M\"oller Daniel Parker Michael Rader Anton Romen Samuel Scalet Leon Schoonderwoerd Maximilian Schulz Tomohiro Soejima Philipp Thoma Yantao Wu Philip Zechmann Ludwig Zweng Roger S. K. Mong Michael P. Zaletel Frank Pollmann
This is my paper

Reviewed by Pithpith:4EQLNVV2open to challenge →

classification cond-mat.str-el
keywords pythontenpytensoralgorithmslibrarynetworkversionachieve
0
0 comments X
read the original abstract

TeNPy (short for 'Tensor Network Python') is a python library for the simulation of strongly correlated quantum systems with tensor networks. The philosophy of this library is to achieve a balance of readability and usability for new-comers, while at the same time providing powerful algorithms for experts. The focus is on MPS algorithms for 1D and 2D lattices, such as DMRG ground state search, as well as dynamics using TEBD, TDVP, or MPO evolution. This article is a companion to the recent version 1.0 release of TeNPy and gives a brief overview of the package.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Mapping twist fields to local operators via tensor networks

    quant-ph 2026-05 unverdicted novelty 7.0

    Constructs explicit physical local operators whose expectation values match twist field actions in MPS, exact in the injectivity limit and at the center of orthogonality, with numerical tests in the transverse-field I...