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A central limit theorem is established for a sum of random variables belonging to a sequence of random fields. The fields are assumed to have zero mean conditional on the past history and to satisfy certain conditional $\alpha$-mixing…

Probability · Mathematics 2024-09-17 Abdollah Jalilian , Arnaud Poinas , Ganggang Xu , Rasmus Waagepetersen

We consider random rectangles in $\mathbb{R}^2$ that are distributed according to a Poisson random measure, i.e., independently and uniformly scattered in the plane. The distributions of the length and the width of the rectangles are…

Probability · Mathematics 2018-06-29 Frank Aurzada , Sebastian Schwinn

We study the percolation properties of the growing clusters model. In this model, a number of seeds placed on random locations on a lattice are allowed to grow with a constant velocity to form clusters. When two or more clusters eventually…

Statistical Mechanics · Physics 2015-05-18 Nikolaos Tsakiris , Michail Maragakis , Kosmas Kosmidis , Panos Argyrakis

Stochastic models, based on random processes, may lead to power law distributions, which provide long range correlations. The observation of power law behavior and the presence of long range correlations in biological systems has been…

Statistical Mechanics · Physics 2008-03-26 Thomas Oikonomou

Given any regularly varying dislocation measure, we identify a natural self-similar fragmentation tree as scaling limit of discrete fragmentation trees with unit edge lengths. As an application, we obtain continuum random tree limits of…

Probability · Mathematics 2009-09-29 Bénédicte Haas , Grégory Miermont , Jim Pitman , Matthias Winkel

For various species of biological cells, experimental observations indicate the existence of universal distributions of the cellular size, scaling relations between the cell-size moments and simple rules for the cell-size control. We…

Soft Condensed Matter · Physics 2017-01-12 David A. Kessler , Stanislav Burov

We give a general existence result for interacting particle systems with local interactions and bounded jump rates but noncompact state space at each site. We allow for jump events at a site that affect the state of its neighbours. We give…

Probability · Mathematics 2008-04-04 Mathew D. Penrose

Using population data of high spatial resolution for a region in the south of Europe, we define cities by aggregating individuals to form connected clusters. The resulting cluster-population distributions show a smooth decreasing behavior…

Physics and Society · Physics 2020-11-10 Alvaro Corral , Frederic Udina , Elsa Arcaute

Many popular random partition models, such as the Chinese restaurant process and its two-parameter extension, fall in the class of exchangeable random partitions, and have found wide applicability in model-based clustering, population…

Methodology · Statistics 2017-11-21 Giuseppe Di Benedetto , François Caron , Yee Whye Teh

We consider a noninteracting disordered system designed to model particle diffusion, relaxation in glasses, and impurity bands of semiconductors. Disorder originates in the random spatial distribution of sites. We find strong numerical…

Disordered Systems and Neural Networks · Physics 2015-03-17 Jacob J. Krich , Alán Aspuru-Guzik

A finite range interacting particle system on a transitive graph is considered. Assuming that the dynamics and the initial measure are invariant, the normalized empirical distribution process converges in distribution to a centered…

Mathematical Physics · Physics 2007-05-23 Paul Doukhan , Gabriel Lang , Sana Louhichi , Bernard Ycart

We present a preferential attachment growth model to obtain the distribution $P(K)$ of number of units $K$ in the classes which may represent business firms or other socio-economic entities. We found that $P(K)$ is described in its central…

Physics and Society · Physics 2009-11-13 S. V. Buldyrev , F. Pammolli , M. Riccaboni , K. Yamasaki , D. Fu , K. Matia , H. E. Stanley

Deep neural networks exhibit empirical neural scaling laws, with error decreasing as a power law with increasing model or data size, across a wide variety of architectures, tasks, and datasets. This universality suggests that scaling laws…

Machine Learning · Computer Science 2024-12-12 Ari Brill

Surface growth in random media is usually governed by both the surface tension and the random local forces. Simulations on lattices mimic the former by imposing a maximum gradient $m$ on the surface heights, and the latter by site-dependent…

Statistical Mechanics · Physics 2009-11-07 Amnon Aharony , Dietrich Stauffer

Large language models with a huge number of parameters, when trained on near internet-sized number of tokens, have been empirically shown to obey neural scaling laws: specifically, their performance behaves predictably as a power law in…

Machine Learning · Computer Science 2022-11-01 Alexander Maloney , Daniel A. Roberts , James Sully

We consider a class of growing random graphs obtained by creating vertices sequentially one by one: at each step, we choose uniformly the neighbours of the newly created vertex; its degree is a random variable with a fixed but arbitrary…

Combinatorics · Mathematics 2013-11-13 Svante Janson , Simone Severini

In this article, we discuss the continuous version of the generalized exchange-driven growth model which is a variant of the coagulation model in which a smaller size particle is detached from a bigger one and merges with another particle.…

Analysis of PDEs · Mathematics 2025-09-03 Prasanta K. Barik , Fernando P. da Costa , João T. Pinto , Rafael Sasportes

We propose a stochastic model of a fragmentation process, developed by taking into account fragment lifetime as a function of their size based on the Gibrat process. If lifetime is determined by a power function of fragment size, numerical…

Statistical Mechanics · Physics 2015-06-22 Shin-ichi Ito , Satoshi Yukawa

We consider diffusion processes on power-law small-world networks in different dimensions. In one dimension, we find a rich phase diagram, with different transient and recurrent phases, including a critical line with continuously varying…

Statistical Mechanics · Physics 2007-05-23 Balázs Kozma , Matthew B. Hastings , G. Korniss

The Generalized Central Limit Theorem is a remarkable generalization of the Central Limit Theorem, showing that the sum of a large number of independent, identically-distributed (i.i.d) random variables with infinite variance may converge…

Statistical Mechanics · Physics 2020-02-19 Ariel Amir