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In the spherical Poisson Boolean model, one takes the union of random balls centred on the points of a Poisson process in Euclidean $d$-space with $d \geq 2$. We prove that whenever the radius distribution has a finite $d$-th moment, there…

Probability · Mathematics 2018-07-24 Mathew D. Penrose

Suppose some random resource (energy, mass or space) $\chi \geq 0$ is to be shared at random between (possibly infinitely many) species (atoms or fragments). Assume ${\Bbb E}\chi =\theta <\infty $ and suppose the amount of the individual…

Disordered Systems and Neural Networks · Physics 2007-05-23 Thierry Huillet

We investigate thermodynamics of a single classical particle placed in a spherical box of a finite radius $R$ and subject to a superposition of a $N-$dimensional Gaussian random potential and the parabolic potential with the curvature…

Disordered Systems and Neural Networks · Physics 2009-11-11 Yan V. Fyodorov , H. -J. Sommers

We prove that the probability that a sum of independent random variables in $\mathbb{R}^d$ with bounded densities lies in a ball is maximized by taking uniform distributions on balls. This in turn generalizes a result by Rogozin on the…

Probability · Mathematics 2015-04-03 T. Juškevičius , J. D. Lee

Level-spacing distributions of the Gaussian Unitary Ensemble (GUE) of random matrix theory are expressed in terms of solutions of coupled differential equations. Series solutions up to order 50 in the level spacing are obtained, thus…

Disordered Systems and Neural Networks · Physics 2007-05-23 Uwe Grimm

Consider a stationary Poisson process of horospheres in a $d$-dimensional hyperbolic space. In the focus of this note is the total surface area these random horospheres induce in a sequence of balls of growing radius $R$. The main result is…

Probability · Mathematics 2024-03-08 Zakhar Kabluchko , Daniel Rosen , Christoph Thäle

Volume-fraction expressions are obtained for the systems of an infinite number of parallel planes arranged both regularly and randomly. As a special case of random arrangement, a non-Poissonian point process (the second-order Erlang…

Materials Science · Physics 2021-06-10 Nikolay V. Alekseechkin

We study the space-time scaling limits of solitons in the box-ball system with random initial distribution. In particular, we show that any recentered tagged soliton converges to a Brownian motion in the diffusive space-time scale, and also…

Probability · Mathematics 2025-05-07 Stefano Olla , Makiko Sasada , Hayate Suda

We obtain quenched hitting distributions to be compound Poissonian for a certain class of random dynamical systems. The theory is general and designed to accommodate non-uniformly expanding behavior and targets that do not overlap much with…

Dynamical Systems · Mathematics 2024-02-06 Lucas Amorim , Nicolai Haydn , Sandro Vaienti

The aim of this paper is to analyze a class of random motions which models the motion of a particle on the real line with random velocity and subject to the action of the friction. The speed randomly changes when a Poissonian event occurs.…

Probability · Mathematics 2009-12-31 Alessandro De Gregorio

In this work we establish a link between two different phenomena that were studied in a large and growing number of biological, composite and soft media: the diffusion in compartmentalized environment and the Brownian yet non-Gaussian…

Statistical Mechanics · Physics 2020-08-05 Jakub Ślęzak , Stanislav Burov

A formalism is presented for analytically obtaining the probability density function, (P_{n}(s)), for the random distance (s) between two random points in an (n)-dimensional spherical object of radius (R). Our formalism allows (P_{n}(s)) to…

Mathematical Physics · Physics 2009-11-07 Shu-Ju Tu , Ephraim Fischbach

The velocity of a passive particle in a one-dimensional wave field is shown to converge in law to a Wiener process, in the limit of a dense wave spectrum with independent complex amplitudes, where the random phases distribution is invariant…

Mathematical Physics · Physics 2012-07-12 Yves Elskens

Boundary constraints in physical, environmental and engineering models restrict smooth states such as temperature to follow known physical laws at the edges of their spatio-temporal domain. Examples include fixed-state or fixed-derivative…

Methodology · Statistics 2025-12-05 Yue Ma , Oksana A. Chkrebtii , Stephen R. Niezgoda

Balls-in-bins models describe a random sequential allocation of infinitely many balls into a finite number of bins. In these models a ball is placed into a bin with probability proportional to a given function (feedback function), which…

Probability · Mathematics 2022-04-13 Mikhail Menshikov , Vadim Shcherbakov

We calculate the density of stationary points and minima of a $N\gg 1$ dimensional Gaussian energy landscape. We use it to show that the point of zero-temperature replica symmetry breaking in the equilibrium statistical mechanics of a…

Disordered Systems and Neural Networks · Physics 2009-11-11 Yan V Fyodorov , H-J Sommers , Ian Williams

\textit{Parastichies} are spiral patterns observed in plants and numerical patterns generated using golden angle method. We generalize this method by using Markoff theory and the theory of product of linear forms, to obtain a theory for…

Number Theory · Mathematics 2024-09-27 S. E. Graiff Zurita , B. Kane , R. Oishi-Tomiyasu

We prove empirical central limit theorems for the distribution of levels of various random fields defined on high-dimensional discrete structures as the dimension of the structure goes to $\infty$. The random fields considered include costs…

Probability · Mathematics 2012-03-08 Zakhar Kabluchko

Random matrix ensembles are introduced that respect the local tensor structure of Hamiltonians describing a chain of $n$ distinguishable spin-half particles with nearest-neighbour interactions. We prove a central limit theorem for the…

Mathematical Physics · Physics 2017-06-19 J. P. Keating , N. Linden , H. J. Wells

We introduce stochastic variational inference for Gaussian process models. This enables the application of Gaussian process (GP) models to data sets containing millions of data points. We show how GPs can be vari- ationally decomposed to…

Machine Learning · Computer Science 2013-09-27 James Hensman , Nicolo Fusi , Neil D. Lawrence
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