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We investigate the renormalization group flows and fixed point structure of many coupled minimal models. The models are coupled two by two by energy-energy couplings. We take the general approach where the bare couplings are all taken to be…

Statistical Mechanics · Physics 2011-07-19 M. -A. Lewis , P. Simon

Given a set of variables and the correlations among them, we develop a method for finding clustering among the variables. The method takes advantage of information implicit in higher-order (not just pairwise) correlations. The idea is to…

Statistical Mechanics · Physics 2015-05-13 L. S. Schulman

For the Potts model on Cayley trees, a very wide class of new Gibbs measures is given. We give a review of all known Gibbs measures of the Potts model on trees and compare them with our new measures.

Mathematical Physics · Physics 2022-11-23 Muzaffar M. Rahmatullaev , Dekhkonov D. Jasur

When approximating the joint distribution of the component counts of a decomposable combinatorial structure that is `almost' in the logarithmic class, but nonetheless has irregular structure, it is useful to be able first to establish that…

Probability · Mathematics 2010-11-02 A. D. Barbour , Anna Pósfai

Information Retrieval systems can be improved by exploiting context information such as user and document features. This article presents a model based on overlapping probabilistic or fuzzy clusters for such features. The model is applied…

Human-Computer Interaction · Computer Science 2011-02-21 Thomas Mandl , Christa Womser-Hacker

The fundamental non-Hermitian nature of the forms of coupled-cluster (CC) theory widely used in quantum chemistry has usually been viewed as a negative, but the present letter shows how this can be used to advantage. Specifically, the…

For the $q-$state Potts model new order parameters projecting on a group of spins instead of a single spin are introduced. On a Cayley tree this allows the physical interpretation of the Potts model at noninteger values q of the number of…

Statistical Mechanics · Physics 2009-11-07 F. Wagner , D. Grensing , J. Heide

We study the topology of a random cubical complex associated to Bernoulli site percolation on a cubical grid. We begin by establishing a limit law for homotopy types. More precisely, looking within an expanding window, we define a sequence…

Probability · Mathematics 2021-09-14 Kenneth Dowling , Erik Lundberg

We introduce and study systems of randomly coupled maps (RCM) where the relevant parameter is the degree of connectivity in the system. Global (almost-) synchronized states are found (equivalent to the synchronization observed in globally…

Condensed Matter · Physics 2009-10-31 Susanna C. Manrubia , Alexander S. Mikhailov

We conjecture an exact form for an universal ratio of four-point cluster connectivities in the critical two-dimensional $Q$-color Potts model. We also provide analogous results for the limit $Q\rightarrow 1$ that corresponds to percolation…

Statistical Mechanics · Physics 2018-12-24 Giacomo Gori , Jacopo Viti

In this paper we address a series of open questions about the construction of spatially coupled measurement matrices in compressed sensing. For hardware implementations one is forced to depart from the limiting regime of parameters in which…

Information Theory · Computer Science 2014-01-27 Francesco Caltagirone , Lenka Zdeborová

Clustering is a widely used unsupervised learning method for finding structure in the data. However, the resulting clusters are typically presented without any guarantees on their robustness; slightly changing the used data sample or…

Machine Learning · Statistics 2017-01-02 Andreas Henelius , Kai Puolamäki , Henrik Boström , Panagiotis Papapetrou

A major challenge for molecular modeling consists in optimizing the unlike interaction potentials. In many cases, combination rules are generally suboptimal when accurate predictions of properties like the mixture vapor pressure are needed.…

Computational Physics · Physics 2010-01-13 Martin Horsch , Martina Heitzig , Thorsten Merker , Thorsten Schnabel , Yow-Lin Huang , Hans Hasse , Jadran Vrabec

In a freely cooling granular material fluctuations in density and temperature cause position dependent energy loss. Due to strong local dissipation, pressure and energy drop rapidly and material moves from `hot' to `cold' regions, leading…

Statistical Mechanics · Physics 2007-05-23 Stefan Luding

We consider the problem of clustering grouped data with possibly non-exchangeable groups whose dependencies can be characterized by a known directed acyclic graph. To allow the sharing of clusters among the non-exchangeable groups, we…

The principle of similarity, or homophily, is often used to explain patterns observed in complex networks such as transitivity and the abundance of triangles (3-cycles). However, many phenomena from division of labor to protein-protein…

Physics and Society · Physics 2022-10-12 Szymon Talaga , Andrzej Nowak

We study the thermodynamic properties of a system of two-level dipoles that are coupled ultrastrongly to a single cavity mode. By using exact numerical and approximate analytical methods, we evaluate the free energy of this system at…

Quantum Physics · Physics 2020-09-30 Philipp Pilar , Daniele De Bernardis , Peter Rabl

In a standard cluster analysis, such as k-means, in addition to clusters locations and distances between them, it's important to know if they are connected or well separated from each other. The main focus of this paper is discovering the…

Machine Learning · Statistics 2017-05-22 Evgeny Bauman , Konstantin Bauman

We give an example of a long range Bernoulli percolation process on a group non-quasi-isometric with $\mathbb{Z}$, in which clusters are almost surely finite for all values of the parameter. This random graph admits diverse equivalent…

Probability · Mathematics 2020-08-12 Agelos Georgakopoulos , John Haslegrave

An approach to improve neural network interpretability is via clusterability, i.e., splitting a model into disjoint clusters that can be studied independently. We define a measure for clusterability and show that pre-trained models form…

Machine Learning · Computer Science 2025-07-28 Satvik Golechha , Maheep Chaudhary , Joan Velja , Alessandro Abate , Nandi Schoots