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We propose a novel coarse graining tensor renormalization group method based on the higher-order singular value decomposition. This method provides an accurate but low computational cost technique for studying both classical and quantum…

Statistical Mechanics · Physics 2015-03-19 Z. Y. Xie , J. Chen , M. P. Qin , J. W. Zhu , L. P. Yang , T. Xiang

The tensor renormalization group is a promising complementary approach to traditional Monte Carlo methods for lattice systems, as it is inherently free from the sign problem. We discuss recent developments crucial for its application to…

High Energy Physics - Lattice · Physics 2025-01-27 Atis Yosprakob

We propose a general framework for finding the ground state of many-body fermionic systems by using feed-forward neural networks. The anticommutation relation for fermions is usually implemented to a variational wave function by the Slater…

Strongly Correlated Electrons · Physics 2021-12-21 Koji Inui , Yasuyuki Kato , Yukitoshi Motome

We discuss the lattice formulation of gauge theories with fermions in arbitrary representations of the color group, and present the implementation of the RHMC algorithm for simulating dynamical Wilson fermions. A first dataset is presented…

High Energy Physics - Lattice · Physics 2010-01-21 Luigi Del Debbio , Agostino Patella , Claudio Pica

Tensor network methods have progressed from variational techniques based on matrix-product states able to compute properties of one-dimensional condensed-matter lattice models into methods rooted in more elaborate states such as projected…

Strongly Correlated Electrons · Physics 2021-08-23 C. Krumnow , L. Veis , J. Eisert , Ö. Legeza

We present a method for formulating gauge theories of chiral fermions in lattice field theory. The method makes use of a Wilson mass to remove doublers. Gauge invariance is then restored by modifying the theory in two ways: the magnitude of…

High Energy Physics - Lattice · Physics 2009-10-28 Geoffrey T. Bodwin

We show how fermionic statistics can be naturally incorporated in tensor networks on arbitrary graphs through the use of graded Hilbert spaces. This formalism allows to use tensor network methods for fermionic lattice systems in a local…

This paper is the first in a series devoted to the development of a rigorous renormalisation group method for lattice field theories involving boson fields, fermion fields, or both. Our immediate motivation is a specific model, involving…

Mathematical Physics · Physics 2015-06-19 David C. Brydges , Gordon Slade

We study the chiral Gross-Neveu model with Wilson fermions. In the framework of the Schroedinger functional we show that in general not only the bare mass has to be tuned to achieve chiral symmetry in the continuum, but also coupling…

High Energy Physics - Lattice · Physics 2016-09-01 Bjorn Leder , Tomasz Korzec

We present results for the renormalization of gauge invariant nonlocal fermion operators which contain a Wilson line, to one loop level in lattice perturbation theory. Our calculations have been performed for Wilson/clover fermions and a…

High Energy Physics - Lattice · Physics 2018-04-18 M. Constantinou , H. Panagopoulos

We have proposed a novel numerical method to calculate accurately the physical quantities of the ground state with the tensor-network wave function in two dimensions. We determine the tensor network wavefunction by a projection approach…

Strongly Correlated Electrons · Physics 2009-11-13 H. C. Jiang , Z. Y. Weng , T. Xiang

We discuss techniques of the density matrix renormalization group and their application to interacting fermion systems in more than one dimension. We show numerical results for equal--time spin--spin and singlet pair field correlation…

Condensed Matter · Physics 2007-05-23 R. M. Noack , S. R. White , D. J. Scalapino

We find a geometrical description from a field theoretical setup based on Wilson's renormalization group in real space. We show that renormalization group equations of coupling parameters encode the metric structure of an emergent curved…

High Energy Physics - Theory · Physics 2016-06-29 Ki-Seok Kim , Chanyong Park

We review recent developments in tensor network approaches, focusing on renormalization group methods. Since they are free from the negative sign and complex action problems, there is growing interest in their application to lattice field…

High Energy Physics - Lattice · Physics 2026-03-04 Shinichiro Akiyama

We undertake first steps in making a class of discrete models of quantum gravity, spin foams, accessible to a large scale analysis by numerical and computational methods. In particular, we apply Migdal-Kadanoff and Tensor Network…

General Relativity and Quantum Cosmology · Physics 2015-10-19 Bianca Dittrich , Frank C. Eckert , Mercedes Martin-Benito

We propose that Kreimer's method of Feynman diagram renormalization via a Hopf algebra of rooted trees can be fruitfully employed in the analysis of block spin renormalization or coarse graining of inhomogeneous statistical systems.…

High Energy Physics - Theory · Physics 2007-05-23 Fotini Markopoulou

A novel method for nonperturbative renormalization of lattice operators is introduced, which lends itself to the calculation of renormalization factors for nonsinglet as well as singlet operators. The method is based on the Feynman-Hellmann…

High Energy Physics - Lattice · Physics 2015-06-23 A. J. Chambers , R. Horsley , Y. Nakamura , H. Perlt , P. E. L. Rakow , G. Schierholz , A. Schiller , J. M. Zanotti

Making a combined use of bosonization and fermionization techniques, we build nonlocal transformations between dual fermion operators, describing junctions of strongly interacting spinful one-dimensional quantum wires. Our approach allows…

Strongly Correlated Electrons · Physics 2015-09-30 Domenico Giuliano , Andrea Nava

We describe the use of tensor networks to numerically determine wave functions of interacting two-dimensional fermionic models in the continuum limit. We use two different tensor network states: one based on the numerical continuum limit of…

Strongly Correlated Electrons · Physics 2021-04-28 Reza Haghshenas , Zhi-Hao Cui , Garnet Kin-Lic Chan

We study the recovery of the underlying graphs or permutations for tensors in the tensor ring or tensor train format. Our proposed algorithms compare the matricization ranks after down-sampling, whose complexity is $O(d\log d)$ for $d$-th…

Numerical Analysis · Mathematics 2024-04-04 Ziang Chen , Jianfeng Lu , Anru R. Zhang