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We apply the higher order tensor renormalization group to two and three dimensional relativistic fermion systems on the lattice. In order to perform a coarse-graining of tensor networks including Grassmann variables, we introduce Grassmann…

High Energy Physics - Lattice · Physics 2017-08-07 Ryo Sakai , Shinji Takeda , Yusuke Yoshimura

The exact renormalization group is used to study the RG flow of quantities in field theories. The basic idea is to write an evolution operator for the flow and evaluate it in perturbation theory. This is easier than directly solving the…

High Energy Physics - Theory · Physics 2022-05-18 Prafulla Oak , B. Sathiapalan

We compare different versions of a bosonic description for systems of interacting fermions, with particular emphasis on the free energy functional. The bosonic effective action makes the issue of symmetries particularly transparent and we…

Strongly Correlated Electrons · Physics 2013-05-29 Christof Wetterich

We use a perturbative momentum shell renormalization group (RG) approach to study the properties of a driven quantum system at zero temperature. To illustrate the technique, we consider a bosonic $\phi^4$ theory with an arbitrary time…

Strongly Correlated Electrons · Physics 2015-06-17 Sangita De Sarkar , Rajdeep Sensarma , K. Sengupta

We show that the Tensor Renormalization Group (TRG) method can be applied to O(N) spin models, principal chiral models and pure gauge theories (Z2, U(1) and SU(2)) on (hyper) cubic lattices. We explain that contrarily to some common belief,…

High Energy Physics - Lattice · Physics 2014-12-02 Yannick Meurice , Alan Denbleyker , Yuzhi Liu , Tao Xiang , Zhiyuan Xie , Ji-Feng Yu , Judah Unmuth-Yockey , Haiyuan Zou

The Wilsonian renormalisation group is applied to a system of two nonrelativistic particles interacting via short-range forces and coupled to an external EM field. By demanding that a fully off-shell one-particle-irreducible 5-point…

Nuclear Theory · Physics 2019-01-30 A. N. Kvinikhidze , M. C. Birse

We treat random rank-$D$ tensor models as $D$-dimensional quantum field theories---tensor field theories (TFT)---and review some of their non-perturbative methods. We classify the correlation functions of complex tensor field theories by…

High Energy Physics - Theory · Physics 2018-08-28 Carlos I. Perez-Sanchez

We study the two-dimensional square lattice Ising ferromagnet and antiferromagnet with a magnetic field by using tensor network method. Focusing on the role of guage fixing, we present the partition function in terms of a tensor network.…

Statistical Mechanics · Physics 2025-01-03 Myung-Hoon Chung

In the context of tensor network states, we for the first time reformulate the corner transfer matrix renormalization group (CTMRG) method into a variational bilevel optimization algorithm. The solution of the optimization problem…

Strongly Correlated Electrons · Physics 2022-05-20 X. F. Liu , Y. F. Fu , W. Q. Yu , J. F. Yu , Z. Y. Xie

We study the noncommutative \phi^4_4-quantum field theory at the self-duality point. This model is renormalisable to all orders as shown in earlier work of us and does not have a Landau ghost problem. Using the Ward identity of Disertori,…

High Energy Physics - Theory · Physics 2009-09-09 Harald Grosse , Raimar Wulkenhaar

We present our progress on a study of the $O(3)$ model in two-dimensions using the Tensor Renormalization Group method. We first construct the theory in terms of tensors, and show how to construct $n$-point correlation functions. We then…

High Energy Physics - Lattice · Physics 2014-11-18 Judah Unmuth-Yockey , Yannick Meurice , James Osborn , Haiyuan Zou

We present a new theoretical approach for the study of the phase diagram of interacting quantum particles: bosons, fermions or spins. In the neighborhood of a phase transition, the expected renormalization group structure is recovered both…

Strongly Correlated Electrons · Physics 2009-10-31 Pietro Gianinetti , Alberto Parola

We demonstrate the efficiency of the bond weighting method for the Grassmann tensor renormalization group (TRG). Benchmarking with the two-dimensional Gross-Neveu model with the Wilson fermion at finite density, we show that the bond…

High Energy Physics - Lattice · Physics 2023-11-30 Shinichiro Akiyama

Tensor completion estimates missing components by exploiting the low-rank structure of multi-way data. The recently proposed methods based on tensor train (TT) and tensor ring (TR) show better performance in image recovery than classical…

Machine Learning · Computer Science 2020-04-24 Huyan Huang , Yipeng Liu , Ce Zhu

The Density Matrix Renormalization Group (DMRG) algorithm is a powerful tool for solving eigenvalue problems to model quantum systems. DMRG relies on tensor contractions and dense linear algebra to compute properties of condensed matter…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-26 Ryan Levy , Edgar Solomonik , Bryan K. Clark

We study the renormalization of the Fermi surface coupled to a massless boson near three spatial dimensions. For this, we set up a Wilsonian RG with independent decimation procedures for bosons and fermions, where the four-fermion…

Strongly Correlated Electrons · Physics 2015-06-03 A. Liam Fitzpatrick , Gonzalo Torroba , Huajia Wang

This thesis focuses on renormalization of quantum field theories. Its first part considers three tensor models in three dimensions, a Fermionic quartic with tensors of rank-3 and two Bosonic sextic, of ranks 3 and 5. We rely upon the…

High Energy Physics - Theory · Physics 2020-10-16 Nicolas Delporte

The functional renormalization group (fRG) is acknowledged as a powerful tool in quantum many-body physics and beyond. On the technical side, conventional implementations of the fRG rely on regulators for bare propagators only. Starting…

Strongly Correlated Electrons · Physics 2026-04-09 Aiman Al-Eryani , Marcel Gievers , Kilian Fraboulet

One of the most well known relativistic field theory models is the Thirring model (TM). Its realization can demonstrate the famous prediction for the renormalization of mass due to interactions. However, experimental verification of the…

Quantum Physics · Physics 2013-03-22 Dimitris G. Angelakis , MingXia Huo , Darrick Chang , Leong Chuan Kwek , Vladimir Korepin

Variational tensor network optimization has become a powerful tool for studying classical statistical models in two dimensions. However, its application to three-dimensional systems remains limited, primarily due to the high computational…

Statistical Mechanics · Physics 2025-10-14 Xia-Ze Xu , Tong-Yu Lin , Guang-Ming Zhang