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

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Abstract

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.

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Asaduzzaman, M., Catterall, S., Meurice, Y., Sakai, R., & Toga, G. C. (2023). Improved coarse-graining methods for two dimensional tensor networks including fermions. Journal of High Energy Physics, 2023(1). https://doi.org/10.1007/JHEP01(2023)024

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