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Improved coarse-graining methods for two dimensional tensor networks including fermions

Journal Article · · Journal of High Energy Physics (Online)
 [1];  [2];  [3];  [2];  [2]
  1. Syracuse Univ., NY (United States); Univ. of Iowa, Iowa City, IA (United States); Syracuse University
  2. Syracuse Univ., NY (United States)
  3. Univ. of Iowa, Iowa City, IA (United States)
+ Show Author Affiliations
We show how to apply renormalization group algorithms incorporating entanglement filtering methods and a loop optimization to a tensor network which includes Grassmann variables which represent fermions in an underlying lattice field theory. As a numerical test a variety of quantities are calculated for two dimensional Wilson-Majorana fermions and for the two flavor Gross-Neveu model. The improved algorithms show much better accuracy for quantities such as the free energy and the determination of Fisher’s zeros.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Syracuse Univ., NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
AC02-05CH11231; SC0009998; SC0019139
OSTI ID:
2242474
Journal Information:
Journal of High Energy Physics (Online), Journal Name: Journal of High Energy Physics (Online) Journal Issue: 1 Vol. 2023; ISSN 1029-8479
Publisher:
Springer NatureCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

Phase transitions
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
Algorithms and theoretical developments
Field theories in lower dimensions