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This article is a presentation of specific recent results describing scaling limits of individual-based models. Thanks to them, we wish to relate the time-scales typical of demographic dynamics and natural selection to the parameters of the…

Probability · Mathematics 2023-08-01 Aurélien Velleret

Diffusion-based generative models employ stochastic differential equations (SDEs) and their equivalent probability flow ordinary differential equations (ODEs) to establish a smooth transformation between complex high-dimensional data…

Machine Learning · Computer Science 2025-12-12 Defang Chen , Zhenyu Zhou , Can Wang , Siwei Lyu

We investigate the nature of genetic drift acting at the leading edge of range expansions, building on recent results in [Hallatschek et al., Proc.\ Natl.\ Acad.\ Sci., \textbf{104}(50): 19926 - 19930 (2007)]. A well mixed population of two…

Populations and Evolution · Quantitative Biology 2010-08-16 Adnan Ali , Stefan Grosskinsky

Spatiotemporal evolution in the real Ginzburg-Landau equation is studied with space-time noise and a slowly increasing critical parameter. Analytical estimates for the characteristic size of the domains formed in a slow sweep through the…

Statistical Mechanics · Physics 2007-05-23 G. D. Lythe

Scalable spatial GPs for massive datasets can be built via sparse Directed Acyclic Graphs (DAGs) where a small number of directed edges is sufficient to flexibly characterize spatial dependence. The DAG can be used to devise fast algorithms…

Methodology · Statistics 2025-03-31 Michele Peruzzi , Sudipto Banerjee , David B. Dunson , Andrew O. Finley

We consider several one-species population dynamics model with finite and infinite carrying capacity, time dependent growth and effort rates and solve them analytically. We show that defining suitable scaling functions for a given time, one…

Disordered Systems and Neural Networks · Physics 2011-11-14 Alexandre Souto Martinez , Brenno Caetano Trocca Cabella , Fabiano Ribeiro

Diffusion with stochastic transport is investigated here when the random driving process is a very general Gaussian process, including Fractional Brownian motion. The purpose is the comparison with a deterministic PDE, which in certain…

Probability · Mathematics 2026-04-20 Franco Flandoli , Francesco Russo

For a unimodular random graph $(G,\rho)$, we consider deformations of its intrinsic path metric by a (random) weighting of its vertices. This leads to the notion of the conformal growth exponent of $(G,\rho)$, which is the best asymptotic…

Probability · Mathematics 2020-06-02 James R. Lee

This paper is concerned mainly with the macroscopic fractal behavior of various random sets that arise in modern and classical probability theory. Among other things, it is shown here that the macroscopic behavior of Boolean coverage…

Probability · Mathematics 2016-05-05 Davar Khoshnevisan , Yimin Xiao

It is shown that, by imposing reparametrization invariance, one may derive a variety of stochastic equations describing the dynamics of surface growth and identify the physical processes responsible for the various terms. This approach…

Condensed Matter · Physics 2009-10-28 M. Marsili , A. Maritan , F. Toigo , J. R. Banavar

Statistical behavior and scaling properties of iso-height lines in three different saturated two-dimensional grown surfaces with controversial universality classes are investigated using ideas from Schramm-Loewner evolution (SLE$_\kappa$).…

Statistical Mechanics · Physics 2010-08-10 A. A. Saberi , H. Dashti-Naserabadi , S. Rouhani

We establish that the static height fluctuations of a particular growth model, the PNG droplet, converges upon proper rescaling to a limit process, which we call the Airy process A(y). The Airy process is stationary, it has continuous…

Probability · Mathematics 2007-05-23 Michael Praehofer , Herbert Spohn

Matrix models are a highly successful framework for the analytic study of random two dimensional surfaces with applications to quantum gravity in two dimensions, string theory, conformal field theory, statistical physics in random geometry,…

Mathematical Physics · Physics 2012-09-17 Razvan Gurau

The computation of multifractal scaling properties associated with a critical field theory involves non-local operators and remains an open problem using conventional techniques of field theory. We propose a new description of Gaussian…

Condensed Matter · Physics 2009-10-28 Claudio de C. Chamon , Christopher Mudry , Xiao-Gang Wen

Gaussian random fields with Mat\'ern covariance functions are popular models in spatial statistics and machine learning. In this work, we develop a spatio-temporal extension of the Gaussian Mat\'ern fields formulated as solutions to a…

Methodology · Statistics 2023-04-06 Finn Lindgren , Haakon Bakka , David Bolin , Elias Krainski , Håvard Rue

Symmetries play a conspicuous role in the large-scale behavior of critical systems. While in equilibrium they allow to classify asymptotics into different universality classes, out of equilibrium they can emerge, some times unexpectedly, as…

Statistical Mechanics · Physics 2019-04-26 Enrique Rodriguez-Fernandez , Rodolfo Cuerno

We introduce particle systems in one or more dimensions in which particles perform branching Brownian motion and the population size is kept constant equal to $N > 1$, through the following selection mechanism: at all times only the $N$…

Probability · Mathematics 2013-05-02 Nathanael Berestycki , Lee Zhuo Zhao

We study Turing pattern formation in a system undergoing radial growth in two dimensions. The Lengyel-Epstein two variable model is implemented in COMSOL Multiphysics and solved on domains growing at different speeds while sweeping other…

Pattern Formation and Solitons · Physics 2019-12-10 Noah H. Somberg , Christopher Konow , Irving R. Epstein , Milos Dolnik

Stochastic dynamics of a quantum system driven by $N$ statistically independent random sudden quenches in a fixed time interval is studied. We reveal that with growing $N$ the system approaches a deterministic limit indicating…

Quantum Physics · Physics 2018-08-15 Marcin Łobejko , Jerzy Dajka , Jerzy Łuczka

We study a one-dimensional model for heavy particles in a compressible fluid. The fluid-velocity field is modelled by a persistent Gaussian random function, and the particles are assumed to be weakly inertial. Since one-dimensional…

Fluid Dynamics · Physics 2019-08-06 J. Meibohm , B. Mehlig