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We propose a Markov chain simulation method to generate simple connected random graphs with a specified degree sequence and level of clustering. The networks generated by our algorithm are random in all other respects and can thus serve as…

Discrete Mathematics · Computer Science 2010-02-09 Shweta Bansal , Shashank Khandelwal , Lauren Ancel Meyers

Inspired by striking advances in language modeling, there has recently been much interest in developing autogressive sequence models that are amenable to analytical study. In this short note, we consider extensions of simple disordered…

Disordered Systems and Neural Networks · Physics 2025-12-18 Jacob A. Zavatone-Veth , Cengiz Pehlevan

We investigate the geometry of a critical system undergoing a second order thermal phase transition. Using a local description for the dynamics characterizing the system at the critical point T=Tc, we reveal the formation of clusters with…

High Energy Physics - Phenomenology · Physics 2009-10-31 N. G. Antoniou , Y. F. Contoyiannis , F. K. Diakonos

Using the maximum entropy method, we derive the "adaptive cluster expansion" (ACE), which can be trained to estimate probability density functions in high dimensional spaces. The main advantage of ACE over other Bayesian networks is its…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Stephen Luttrell

Usual formulations of the clustering coefficient can be shown to be insufficient in the task of describing the local topology of very simple networks. Motivated by this, we review some alternatives in order to present an extension, the…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Alexandre H. Abdo , A. P. S. de Moura

It is well known that the imposition of a constraint can transform the properties of critical systems. Early work on this phenomenon by Essam and Garelick, Fisher, and others, focused on the effects of constraints on the leading critical…

Statistical Mechanics · Physics 2014-06-17 Nickolay Izmailian , Ralph Kenna

Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering is a semi-supervised extension to this process that can be…

Machine Learning · Computer Science 2023-03-02 Germán González-Almagro , Daniel Peralta , Eli De Poorter , José-Ramón Cano , Salvador García

The linked-cluster expansion technique for the high-temperature expansion of spin model is reviewed. A new algorithm for the computation of three-point and higher Green's functions is presented. Series are computed for all components of…

Statistical Mechanics · Physics 2008-11-26 Massimo Campostrini

We propose a hypergraph expansion which facilitates the direct treatment of quantum spin models with many-site interactions via perturbative linked cluster expansions. The main idea is to generate all relevant subclusters and sort them into…

Strongly Correlated Electrons · Physics 2022-06-22 M. Mühlhauser , K. P. Schmidt

We have studied the kinetics of cluster formation for dynamical systems of dimensions up to $n=8$ interacting through elastic collisions or coalescence. These systems could serve as possible models for gas kinetics, polymerization and…

Statistical Mechanics · Physics 2013-01-15 Carson McFadden , Louis-S. Bouchard

We consider a partially ionized gas at thermal equilibrium, in the Saha regime. The system is described in terms of a quantum plasma of nuclei and electrons. In this framework, the Coulomb interaction is the source of a large variety of…

Statistical Mechanics · Physics 2007-05-23 A. Alastuey , V. Ballenegger , F. Cornu , Ph. A. Martin

Two dimensional condensed matter is realised in increasingly diverse forms that are accessible to experiment and of potential technological value. The properties of these systems are influenced by many length scales and reflect both generic…

Statistical Mechanics · Physics 2011-07-15 Andrea Taroni , Steven T. Bramwell , Peter C. W. Holdsworth

By the early 1960's advances in statistical physics had established the existence of universality classes for systems with second-order phase transitions and characterized these by critical exponents which are different to the classical…

Statistical Mechanics · Physics 2017-08-23 Ralph Kenna

Many complex systems are representable as macroscopic set of elements which interact by simple rules. The complex macroscopically relevant phenomena are then the result of the generic emergence of a space-time multi-scale dynamics. Critical…

High Energy Physics - Lattice · Physics 2016-11-03 Sorin Solomon

Complex networks structures have been extensively used for describing complex natural and technological systems, like the Internet or social networks. More recently complex network theory has been applied to quantum systems, where complex…

Quantum Physics · Physics 2020-01-22 Francesca Sansavini , Valentina Parigi

We present an analytical approach to determining the expected cascade size in a broad range of dynamical models on the class of random networks with arbitrary degree distribution and nonzero clustering introduced in [M.E.J. Newman, Phys.…

Physics and Society · Physics 2013-06-06 Adam Hackett , Sergey Melnik , James P. Gleeson

We use two high resolution CDM simulations to show that (i) when clusters of galaxies form the infall pattern of matter is not random but shows clear features which are correlated in time; (ii) in addition, the infall patterns are…

Astrophysics · Physics 2007-05-23 J. M. Colberg , S. D. M. White , A. Jenkins , F. R. Pearce

In this tutorial-style review we discuss basic concepts of coupled cluster theory and recent developments that increase its computational efficiency for calculations of molecules, solids and materials in general. We will touch upon the…

Materials Science · Physics 2020-04-15 Igor Ying Zhang , Andreas Grüneis

Grids - the collection of heterogeneous computers spread across the globe - present a new paradigm for the large scale problems in variety of fields. We discuss two representative cases in the area of condensed matter physics outlining the…

Mesoscale and Nanoscale Physics · Physics 2010-02-12 Bhalchandra S. Pujari

A useful property of a network that can be used to characterize many systems is the degree distribution. However, many complex networks exhibit higher--order degree correlations that must be studied through other means, such as clustering…

Physics and Society · Physics 2010-07-06 Murray E. Alexander , Randy Kobes
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