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A stochastic method is introduced for geometric modeling aerosol surface roughness with random field and discrete differential geometry theory. Optical scattering properties are computed for randomly oriented spheroidal particles with…

Atmospheric and Oceanic Physics · Physics 2017-10-24 Jianing Zhang

Scattering of electromagnetic waves in billiard-like systems has become a standard experimental tool of studying properties associated with Quantum Chaos. Random Matrix Theory (RMT) describing statistics of eigenfrequencies and associated…

Disordered Systems and Neural Networks · Physics 2021-05-11 Yan V Fyodorov

We consider a composite medium, which consists of a homogeneous matrix containing a statistically homogeneous set of multimodal spherical inclusions. This model is used to represent the morphology of heterogeneous solid propellants (HSP)…

Materials Science · Physics 2015-03-20 V. A. Buryachenko , T. L. Jackson , G. Amadio

We review models of random geometries based on the dynamical lattice approach. We discuss one dimensional model of simplicial complexes (branched polymers), two dimensional model of dynamical triangulations and four dimensional model of…

High Energy Physics - Lattice · Physics 2007-05-23 Z. Burda

While matrix variate regression models have been studied in many existing works, classical statistical and computational methods for the analysis of the regression coefficient estimation are highly affected by high dimensional and noisy…

Machine Learning · Statistics 2022-05-17 Hsin-Hsiung Huang , Feng Yu , Xing Fan , Teng Zhang

We consider the efficiency of multiplexing spatially encoded information across random configurations of a metasurface-programmable chaotic cavity in the microwave domain. The distribution of the effective rank of the channel matrix is…

Applied Physics · Physics 2020-08-05 Philipp del Hougne , Dmitry V. Savin , Olivier Legrand , Ulrich Kuhl

Matrix normal models have an associated 4-tensor for their covariance representation. The covariance array associated with a matrix normal model is naturally represented as a Kronecker-product structured covariance associated with the…

Computation · Statistics 2025-01-10 Quinn Simonis , Martin T. Wells

We define a message-passing algorithm for computing magnetizations in Restricted Boltzmann machines, which are Ising models on bipartite graphs introduced as neural network models for probability distributions over spin configurations. To…

Machine Learning · Computer Science 2020-12-02 Burak Çakmak , Manfred Opper

In this article, we study microscopic properties of a two-dimensional eigenvalue ensemble near a conical singularity arising from insertion of a point charge in the bulk of the support of eigenvalues. In particular, we characterize all…

Mathematical Physics · Physics 2021-09-01 Yacin Ameur , Nam-Gyu Kang , Seong-Mi Seo

A model for diffusion on a cubic lattice with a random distribution of traps is developed. The traps are redistributed at certain time intervals. Such models are useful for describing systems showing dynamic disorder, such as ion-conducting…

Condensed Matter · Physics 2009-10-31 S. Mandal , R. Dasgupta

In the last few years several new Random Matrix Models have been proposed and studied. They have found application in various different contexts, ranging from the physics of mesoscopic systems to the chiral transition in lattice gauge…

Statistical Mechanics · Physics 2008-02-03 M. Caselle

We introduce and analyze a model for the transport of particles or energy in extended lattice systems. The dynamics of the model acts on a discrete phase space at discrete times but has nonetheless some of the characteristic properties of…

Mathematical Physics · Physics 2015-06-12 Raphael Lefevere

We study the matrix ansatz in the quantum group framework, applying integrable systems techniques to statistical physics models. We start by reviewing the two approaches, and then show how one can use the former to get new insight on the…

Mathematical Physics · Physics 2015-10-02 N. Crampe , E. Ragoucy , M. Vanicat

We study the entanglement spectrum of a translationally-invariant lattice system under a random partition, implemented by choosing each site to be in one subsystem with probability $p\in[0, 1]$. We apply this random partitioning to a…

Strongly Correlated Electrons · Physics 2015-06-23 Sagar Vijay , Liang Fu

We study properties of Hamiltonian integrable systems with random initial data by considering their Lax representation. Specifically, we investigate the spectral behaviour of the corresponding Lax matrices when the number $N$ of degrees of…

Mathematical Physics · Physics 2023-09-12 Massimo Gisonni , Tamara Grava , Giorgio Gubbiotti , Guido Mazzuca

We introduce a concept for random tilings which, comprising the conventional one, is also applicable to tiling ensembles without height representation. In particular, we focus on the random tiling entropy as a function of the tile…

Statistical Mechanics · Physics 2008-08-28 Christoph Richard , Moritz Hoeffe , Joachim Hermisson , Michael Baake

We introduce a numerical method that enables efficient modelling of light scattering by large, disordered ensembles of non-spherical particles incorporated in stratified media, including when the particles are in close vicinity to each…

This paper aims at presenting a few models of quantum dynamics whose description involves the analysis of random unitary matrices for which dynamical localization has been proven to hold. Some models come from physical approximations…

Mathematical Physics · Physics 2011-05-03 Alain Joye

The partition function of the 2d Ising model with random nearest neighbor coupling is expressed in the dual lattice made of square plaquettes. The dual model is solved in the the mean field and in different types of Bethe-Peierls…

Condensed Matter · Physics 2009-10-28 G. Paladin , M. Serva

A restricted Boltzmann machine (RBM) is an undirected graphical model constructed for discrete or continuous random variables, with two layers, one hidden and one visible, and no conditional dependency within a layer. In recent years, RBMs…

Machine Learning · Statistics 2019-09-12 Andee Kaplan , Daniel Nordman , Stephen Vardeman