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Tensor Network Python (TeNPy) version 1

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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
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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
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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.

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    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...