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Tensor models, generalization of matrix models, are studied aiming for quantum gravity in dimensions larger than two. Among them, the canonical tensor model is formulated as a totally constrained system with first-class constraints, the…

High Energy Physics - Theory · Physics 2015-06-23 Gaurav Narain , Naoki Sasakura , Yuki Sato

A SYK--like model close to the colored tensor models has recently been proposed \cite{Witten:2016iux}. Building on results obtained in tensor models \cite{GurSch}, we discuss the complete $1/N$ expansion of the model. We detail the two and…

High Energy Physics - Theory · Physics 2017-03-08 Razvan Gurau

We present a class of models in which the top quark, by mixing with new physics at a higher energy scale, is naturally heavier than the other standard model particles. We take this new physics to be extended color. Our models contain new…

High Energy Physics - Phenomenology · Physics 2007-05-23 Oscar F. Hernandez

Random tensor models are generalizations of matrix models which also support a 1/N expansion. The dominant observables are in correspondence with some trees, namely rooted trees with vertices of degree at most $D$ and lines colored by a…

Mathematical Physics · Physics 2012-06-20 Valentin Bonzom , Razvan Gurau

We derive theorems which outline explicit mechanisms by which anomalous scaling for the probability density function of the sum of many correlated random variables asymptotically prevails. The results characterize general anomalous scaling…

Statistical Mechanics · Physics 2015-05-14 Attilio L. Stella , Fulvio Baldovin

We consider exploration algorithms of the random sequential adsorption type both for homogeneous random graphs and random geometric graphs based on spatial Poisson processes. At each step, a vertex of the graph becomes active and its…

Probability · Mathematics 2017-11-22 Paola Bermolen , Matthieu Jonckheere , Jaron Sanders

In this article, we show that the double scaling limit correlation functions of a random matrix model when two cuts merge with degeneracy $2m$ (i.e. when $y\sim x^{2m}$ for arbitrary values of the integer $m$) are the same as the…

Mathematical Physics · Physics 2013-06-06 Olivier Marchal , Mattia Cafasso

The main objects under consideration in this thesis are called maps, a certain class of graphs embedded on surfaces. Our problems have a powerful relatively recent tool in common, the so-called topological recursion (TR) introduced by…

Mathematical Physics · Physics 2020-02-04 Elba Garcia-Failde

In this paper we study two natural models of \textit{random temporal} graphs. In the first, the \textit{continuous} model, each edge $e$ is assigned $l_e$ labels, each drawn uniformly at random from $(0,1]$, where the numbers $l_e$ are…

Discrete Mathematics · Computer Science 2026-02-12 Henry Austin , George B. Mertzios , Paul G. Spirakis

We study the possible scaling limits of percolation interfaces in two dimensions on the triangular lattice. When one lets the percolation parameter p(N) vary with the size N of the box that one is considering, three possibilities arise in…

Probability · Mathematics 2017-07-19 Pierre Nolin , Wendelin Werner

The concept of universality has shaped our understanding of many-body physics, but is mostly limited to homogenous systems. Here, we present a study of universality on a non-homogeneous graph, the long-range diluted graph (LRDG). Its…

Statistical Mechanics · Physics 2024-05-21 Giacomo Bighin , Tilman Enss , Nicolò Defenu

We analyse a class of quantum field theory models illustrating some of the possibilities that have emerged in the general study of the short distance properties of superselection sectors, performed in a previous paper (together with R.…

Mathematical Physics · Physics 2010-11-11 Claudio D'Antoni , Gerardo Morsella

I study a one-matrix model of a real symmetric matrix with a potential which is a sum of two logarithmic functions and a harmonic one. This two-logarithm matrix model is the absolute square norm of a toy wave function which is obtained by…

High Energy Physics - Theory · Physics 2021-04-21 Naoki Sasakura

It is widely believed that the celebrated 2D Ising model at criticality has a universal and conformally invariant scaling limit, which is used in deriving many of its properties. However, no mathematical proof of universality and conformal…

Mathematical Physics · Physics 2011-05-17 Dmitry Chelkak , Stanislav Smirnov

Matrix models with continuous symmetry are powerful tools for studying quantum gravity and holography. Tensor models have also found applications in holographic quantum gravity. Matrix models with discrete permutation symmetry have been…

High Energy Physics - Theory · Physics 2023-12-15 George Barnes , Adrian Padellaro , Sanjaye Ramgoolam

We give a procedure to construct (quasi-)trisection diagrams for closed (pseudo-)manifolds generated by colored tensor models without restrictions on the number of simplices in the triangulation, therefore generalizing previous works in the…

Mathematical Physics · Physics 2021-11-10 Riccardo Martini , Reiko Toriumi

Two dimensional quantum gravity coupled to a conformally invariant matter field of central charge c=n/2, is represented, in a discretized version, by n independent Ising spins per cell of the triangulations of a random surface. The matrix…

High Energy Physics - Theory · Physics 2009-10-22 Shinobu Hikami , Edouard Brézin

We define in this paper a class of three indices tensor models, endowed with $O(N)^{\otimes 3}$ invariance ($N$ being the size of the tensor). This allows to generate, via the usual QFT perturbative expansion, a class of Feynman tensor…

Mathematical Physics · Physics 2016-10-11 Sylvain Carrozza , Adrian Tanasa

We introduce the scaling function associated to a graph directed Markov system, and show that it is a H\"{o}lder continuous function of the dual symbolic Cantor set. With some natural separation and regularity conditions, each such system…

Dynamical Systems · Mathematics 2019-01-15 Daniel Ingebretson

In this work, we consider an extension of graphical models to random graphs, trees, and other objects. To do this, many fundamental concepts for multivariate random variables (e.g., marginal variables, Gibbs distribution, Markov properties)…

Machine Learning · Statistics 2017-05-08 Neil Hallonquist