Entanglement filtering and improved coarse-graining on two dimensional tensor networks including fermions

Ryo Sakai, Muhammad Asaduzzaman, Simon Catterall, Yannick Meurice, Goksu Can Toga

Research output: Contribution to journalConference Articlepeer-review

Abstract

Tensor renormalization group (TRG) has attractive features like the absence of sign problems and the accessibility to the thermodynamic limit, and many applications to lattice field theories have been reported so far. However it is known that the TRG has a fictitious fixed point that is called the CDL tensor and that causes less accurate numerical results. There are improved coarse-graining methods that attempt to remove the CDL structure from tensor networks. Such approaches have been shown to be beneficial on two dimensional spin systems. We discuss how to adapt the removal of the CDL structure to tensor networks including fermions, and numerical results that contain some comparisons to the plain TRG, where significant differences are found, will be shown. The detailed discussion of this work is given in ref. [1].

Original languageEnglish (US)
Article number034
JournalProceedings of Science
Volume430
StatePublished - Apr 6 2023
Event39th International Symposium on Lattice Field Theory, LATTICE 2022 - Bonn, Germany
Duration: Aug 8 2022Aug 13 2022

ASJC Scopus subject areas

  • General

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