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There has been enormous progress in the last few years in designing neural networks that respect the fundamental symmetries and coordinate freedoms of physical law. Some of these frameworks make use of irreducible representations, some make…

Machine Learning · Computer Science 2023-02-09 Soledad Villar , David W. Hogg , Kate Storey-Fisher , Weichi Yao , Ben Blum-Smith

Complex systems that consist of different kinds of entities that interact in different ways can be modeled by multilayer networks. This paper uses the tensor formalism with the Einstein tensor product to model this type of networks. Several…

Numerical Analysis · Mathematics 2023-08-03 Smahane El-Halouy , Silvia Noschese , Lothar Reichel

Group algebras of permutations have proved highly useful in solving a number of problems in large N gauge theories. I review the use of permutations in classifying gauge invariants in one-matrix and multi-matrix models and computing their…

High Energy Physics - Theory · Physics 2016-05-04 Sanjaye Ramgoolam

We prove two universality results for random tensors of arbitrary rank D. We first prove that a random tensor whose entries are N^D independent, identically distributed, complex random variables converges in distribution in the large N…

Probability · Mathematics 2013-05-07 Razvan Gurau

We discuss how to construct models of interacting anyons by generalizing quantum spin Hamiltonians to anyonic degrees of freedom. The simplest interactions energetically favor pairs of anyons to fuse into the trivial ("identity") channel,…

Statistical Mechanics · Physics 2009-02-20 Simon Trebst , Matthias Troyer , Zhenghan Wang , Andreas W. W. Ludwig

We develop a mesoscopic approach to model the non-equilibrium behavior of membranes at the cellular scale. Relying on lattice Boltzmann methods, we develop a solution procedure to recover the Nernst-Planck equations and Gauss's law. A…

Mesoscale and Nanoscale Physics · Physics 2023-02-22 James E. McClure , Zhe Li

Real-world signals typically span across multiple dimensions, that is, they naturally reside on multi-way data structures referred to as tensors. In contrast to standard ``flat-view'' multivariate matrix models which are agnostic to data…

Signal Processing · Electrical Eng. & Systems 2019-12-04 Bruno Scalzo Dees , Anh-Huy Phan , Danilo P. Mandic

Following the procedures by which O(N)-invariant real vector models and their large-N behavior have previously been solved, we extend similar techniques to the study of real symmetric N x N-matrix models with O(N)-invariant interactions.…

High Energy Physics - Theory · Physics 2015-06-18 John R. Klauder

Real-world networks, e.g. the social relations or world-wide-web graphs, exhibit both small-world and scale-free behaviour. We interpret lattice triangulations as planar graphs by identifying triangulation vertices with graph nodes and…

Disordered Systems and Neural Networks · Physics 2015-02-06 Benedikt Krüger , Ella M. Schmidt , Klaus Mecke

Neutrino-electron scattering is a purely leptonic fundamental interaction and therefore provides an important channel to test the Standard Model, especially at the low energy-momentum transfer regime. We derived constraints on neutrino…

High Energy Physics - Experiment · Physics 2017-03-08 M. Deniz , B. Sevda , S. Kerman , A. Ajjaq , L. Singh , H. T. Wong , M. Zeyrek

We study invariants of bosonic and fermionic (Grassmann-valued) matrices under the adjoint action of $U(N)$, weighted by the fermion number. Such models naturally appear as the supersymmetric indices of supersymmetric gauge theories and are…

High Energy Physics - Theory · Physics 2026-05-11 Giorgos Eleftheriou , Ziming Ji , Sameer Murthy

We investigate numerically and analytically Potts models on ``thin'' random graphs -- generic Feynman diagrams, using the idea that such models may be expressed as the N --> 1 limit of a matrix model. The thin random graphs in this limit…

High Energy Physics - Lattice · Physics 2008-11-26 D. A. Johnston , P. Plechac

This paper provides a unified framework for analyzing tensor estimation problems that allow for nonlinear observations, heteroskedastic noise, and covariate information. We study a general class of high-dimensional models where each…

Information Theory · Computer Science 2025-06-10 Riccardo Rossetti , Galen Reeves

We introduce a taxonomy of interaction types and show that graphs are focal hypergraphs: every graph is canonically a focal hypergraph via its closed neighbourhood structure, and every graph dynamical model is a special case of the general…

Physics and Society · Physics 2026-03-05 Elkaïoum M. Moutuou

Nonrenormalizable scalar fields, such as \varphi^4_n, n\ge5, require infinitely many distinct counter terms when perturbed about the free theory, and lead to free theories when defined as the continuum limit of a lattice regularized theory…

High Energy Physics - Theory · Physics 2011-08-04 John R. Klauder

The meander problem is a combinatorial problem which provides a toy model of the compact folding of polymer chains. In this paper we study various questions relating to the enumeration of meander diagrams, using diagrammatical methods. By…

High Energy Physics - Theory · Physics 2007-05-23 M. G. Harris

I review the formalism, Feynman rules, and combinatorics that constrain a field to propagate ``classically", strictly in tree diagrams, either by itself, or interacting with other, purely quantum fields. The perturbation theory is…

High Energy Physics - Theory · Physics 2026-02-03 Dimitrios Metaxas

Group field theories have recently been shown to admit a 1/N expansion dominated by so-called `melonic graphs', dual to triangulated spheres. In this note, we deepen the analysis of this melonic sector. We obtain a combinatorial formula for…

High Energy Physics - Theory · Physics 2015-06-16 Aristide Baratin , Sylvain Carrozza , Daniele Oriti , James P. Ryan , Matteo Smerlak

Tree-level Feynman diagrams in a cubic scalar theory can be given a metric such that each edge has a length. The space of metric trees is made out of orthants joined where a tree degenerates. Here we restrict to planar trees since each…

High Energy Physics - Theory · Physics 2020-12-30 Francisco Borges , Freddy Cachazo

A network representation is useful for describing the structure of a large variety of complex systems. However, most real and engineered systems have multiple subsystems and layers of connectivity, and the data produced by such systems is…