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We analyze classical dimer models on the square and triangular lattice using a tensor network representation of the dimers. The correlation functions are numerically calculated using the recently developed "Tensor renormalization group"…

Strongly Correlated Electrons · Physics 2015-05-20 Krishanu Roychowdhury , Ching-Yu Huang

We describe a simple real space renormalization group technique for two dimensional classical lattice models. The approach is similar in spirit to block spin methods, but at the same time it is fundamentally based on the theory of quantum…

Statistical Mechanics · Physics 2009-11-11 Michael Levin , Cody P. Nave

In the tensor network approach to statistical physics, properties of the critical point of a 2D lattice model are encoded by a four-legged tensor which is a fixed point of an RG map. The traditional way to find the fixed point tensor…

Statistical Mechanics · Physics 2025-10-31 Nikolay Ebel , Tom Kennedy , Slava Rychkov

Symmetric tensor decomposition is an important problem with applications in several areas for example signal processing, statistics, data analysis and computational neuroscience. It is equivalent to Waring's problem for homogeneous…

Symbolic Computation · Computer Science 2019-09-12 Matías Bender , Jean-Charles Faugère , Ludovic Perret , Elias Tsigaridas

This paper derives the CS decomposition for orthogonal tensors (T-CSD) and the generalized singular value decomposition for two tensors (T-GSVD) via the T-product. The structures of the two decompositions are analyzed in detail and are…

Numerical Analysis · Mathematics 2021-07-01 Yating Zhang , Xiaoxia Guo , Pengpeng Xie , Zhengbang Cao

An efficient, accurate and reliable approximation of a matrix by one of lower rank is a fundamental task in numerical linear algebra and signal processing applications. In this paper, we introduce a new matrix decomposition approach termed…

Numerical Analysis · Computer Science 2018-08-15 Maboud F. Kaloorazi , Rodrigo C. de Lamare

An effective formalism for white noise analysis, conceptually equivalent to Wilsonian renormalization theory, is introduced. Space-time gets represented by a boolean lattice of coarse regions, energy scales become space-time partitions by…

Mathematical Physics · Physics 2018-03-02 Horst Thaler , Rodrigo Vargas Le-Bert

Recently, the tensor network description with bond weights on its edges has been proposed as a novel improvement for the tensor renormalization group algorithm. The bond weight is controlled by a single hyperparameter, whose optimal value…

High Energy Physics - Lattice · Physics 2022-11-09 Shinichiro Akiyama

We present a comprehensive analysis and extraction of the unpolarized transverse momentum dependent (TMD) parton distribution functions, which are fundamental constituents of the TMD factorization theorem. We provide a general review of the…

High Energy Physics - Phenomenology · Physics 2018-03-14 Ignazio Scimemi , Alexey Vladimirov

The $(1+1)$-dimensional two-color lattice QCD is studied with the Grassmann tensor renormalization group. We construct tensor network representations of theories with the staggered fermion and the Wilson fermion and show that Grassmann…

High Energy Physics - Lattice · Physics 2025-02-03 Kwok Ho Pai , Shinichiro Akiyama , Synge Todo

We have discussed the tensor-network representation of classical statistical or interacting quantum lattice models, and given a comprehensive introduction to the numerical methods we recently proposed for studying the tensor-network…

Strongly Correlated Electrons · Physics 2013-05-29 H. H. Zhao , Z. Y. Xie , Q. N. Chen , Z. C. Wei , J. W. Cai , T. Xiang

Classes of renormalizable models in the Tensorial Group Field Theory framework are investigated. The rank $d$ tensor fields are defined over $d$ copies of a group manifold $G_D=U(1)^D$ or $G_D= SU(2)^D$ with no symmetry and no gauge…

High Energy Physics - Theory · Physics 2013-06-06 Joseph Ben Geloun

We introduce the tubal tensor train (TTT) decomposition, a tensor-network model that combines the t-product algebra of the tensor singular value decomposition (T-SVD) with the low-order core structure of the tensor train (TT) format. For an…

Numerical Analysis · Mathematics 2026-03-12 Salman Ahmadi-Asl , Valentin Leplat , Anh-Huy Phan , Andrzej Cichocki

We classify and compute, by means of the six-dimensional embedding formalism in twistor space, all possible three-point functions in four dimensional conformal field theories involving bosonic or fermionic operators in irreducible…

High Energy Physics - Theory · Physics 2016-01-26 Emtinan Elkhidir , Denis Karateev , Marco Serone

We propose an entanglement-based algorithm of the tensor-network strong-disorder renormalization group (tSDRG) method for quantum spin systems with quenched randomness. In contrast to the previous tSDRG algorithm based on the energy…

Strongly Correlated Electrons · Physics 2021-10-19 Kouichi Seki , Toshiya Hikihara , Kouichi Okunishi

We investigate the unfolded formulation of bosonic Lorentz tensor fields of arbitrary spin in $AdS_3$ containing a parity breaking mass parameter. They include deformations of the linearisations of the Prokushkin--Vasiliev higher spin…

High Energy Physics - Theory · Physics 2016-02-01 Nicolas Boulanger , Dmitry Ponomarev , Ergin Sezgin , Per Sundell

Recently, a rank four tensor group field theory has been proved renormalizable. We provide here the key points on the renormalizability of this model and its UV asymptotic freedom.

High Energy Physics - Theory · Physics 2012-10-22 Joseph Ben Geloun

We construct the manifestly Lorentz-invariant twistorial formulation of N=1 D=4 superparticle with tensorial central charges which describes massive and massless cases in a uniform manner. The tensorial central charges are realized in terms…

High Energy Physics - Theory · Physics 2014-11-18 S. Fedoruk , V. G. Zima

A discretized massless wave equation in two dimensions, on an appropriately chosen square lattice, exactly reproduces the solutions of the corresponding continuous equations. We show that the reason for this exact solution property is the…

High Energy Physics - Theory · Physics 2016-08-24 Serge Winitzki

Tensors are ubiquitous in science and engineering and tensor factorization approaches have become important tools for the characterization of higher order structure. Factorizations includes the outer-product rank Canonical Polyadic…

Machine Learning · Statistics 2023-10-05 Jesper Løve Hinrich , Morten Mørup
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