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The comb model is a simplified description for anomalous diffusion under geometric constraints. It represents particles spreading out in a two-dimensional space where the motions in the x-direction are allowed only when the y coordinate of…

Computational Physics · Physics 2015-07-21 H. V. Ribeiro , A. A. Tateishi , L. G. A. Alves , R. S. Zola , E. K. Lenzi

A recent experiment [Sadoon AA, Wang Y. 2018 Phys. Rev. E 98, 042411] has revealed that nucleoid associated proteins (i.e., DNA-binding proteins) exhibit highly heterogeneous diffusion processes in bacteria where not only the diffusion…

Statistical Mechanics · Physics 2021-03-09 Yuichi Itto , Christian Beck

Denoising diffusion models have become ubiquitous for generative modeling. The core idea is to transport the data distribution to a Gaussian by using a diffusion. Approximate samples from the data distribution are then obtained by…

The Laplacian $\Delta$ is the infinitesimal generator of isotropic Brownian motion, being the limit process of normal diffusion, while the fractional Laplacian $\Delta^{\beta/2}$ serves as the infinitesimal generator of the limit process of…

Analysis of PDEs · Mathematics 2020-03-20 Weihua Deng , Xudong Wang , Pingwen Zhang

The spectrum profile that emerges in molecular spectroscopy and atmospheric radiative transfer as the combined effect of Doppler and pressure broadenings is known as the Voigt profile function. Because of its convolution integral…

Mathematical Physics · Physics 2008-06-12 Gianni Pagnini , Francesco Mainardi

A population genetics model based on a multitype branching process, or equivalently a Galton-Watson branching process for multiple alleles, is pre- sented. The diffusion limit forward Kolmogorov equation is derived for the case of neutral…

Populations and Evolution · Quantitative Biology 2018-02-21 Conrad J. Burden , Yi Wei

In this paper we study finite velocity planar random motions with an infinite number of possible directions, where the number of changes of direction is randomized by means of an inhomogeneous fractional Poisson distribution. We first…

Probability · Mathematics 2014-11-25 R. Garra , E. Orsingher

We construct a recurrent diffusion process with values in the space of probability measures over an arbitrary closed Riemannian manifold of dimension $d\ge 2$. The process is associated with the Dirichlet form defined by integration of the…

Probability · Mathematics 2022-04-04 L. Dello Schiavo

Mixture models are commonly used in applications with heterogeneity and overdispersion in the population, as they allow the identification of subpopulations. In the Bayesian framework, this entails the specification of suitable prior…

Methodology · Statistics 2023-06-21 Andrea Cremaschi , Timothy M. Wertz , Maria De Iorio

We study the Brownian motion of a classical particle in one-dimensional inhomogeneous environments where the transition probabilities follow quasiperiodic or aperiodic distributions. Exploiting an exact correspondence with the…

Statistical Mechanics · Physics 2009-10-31 F. Igloi , L. Turban , H. Rieger

Duality plays an important role in population genetics. It can relate results from forwards-in-time models of allele frequency evolution with those of backwards-in-time genealogical models; a well known example is the duality between the…

Populations and Evolution · Quantitative Biology 2019-08-09 Robert C. Griffiths , Paul A. Jenkins , Sabin Lessard

We consider an indecomposable Galton-Watson branching process with countably infinitely many types. Assuming that the process is critical and allowing for infinite variance of the offspring sizes of some (or all) types of particles we…

Probability · Mathematics 2020-03-02 V. A. Topchii , V. A. Vatutin , E. E. Dyakonova

We investigate the extremal process of four-dimensional membrane models as the size of the lattice $N$ tends to infinity. We prove the cluster-like geometry of the extreme points and the existence as well as the uniqueness of the extremal…

Probability · Mathematics 2025-07-29 Hao Ge , Xinyi Li , Jiaxi Zhao

We give new and explicitly computable examples of Gibbs-non-Gibbs transitions of mean-field type, using the large deviation approach introduced in [4]. These examples include Brownian motion with small variance and related diffusion…

Probability · Mathematics 2012-12-05 Frank Redig , Feijia Wang

This article considers a class of metastable non-reversible diffusion processes whose invariant measure is a Gibbs measure associated with a Morse potential. In a companion paper [32], we proved the Eyring-Kramers formula for the…

Probability · Mathematics 2022-07-20 Jungkyoung Lee , Insuk Seo

We prove that the tagged particles of infinitely many Brownian particles in $ \Rtwo $ interacting via a logarithmic (two-dimensional Coulomb) potential with inverse temperature $ \beta = 2 $ are sub-diffusive. The associated delabeled…

Probability · Mathematics 2023-11-28 Hirofumi Osada

Gibbs type priors have been shown to be natural generalizations of Dirichlet process (DP) priors used for intricate applications of Bayesian nonparametric methods. This includes applications to mixture models and to species sampling models…

Statistics Theory · Mathematics 2023-08-29 Lancelot F. James

We consider a family of one-dimensional diffusions, in dynamical Wiener mediums, which are random perturbations of the Ornstein-Uhlenbeck diffusion process. We prove quenched and annealed convergences in distribution and under weighted…

Probability · Mathematics 2012-12-14 Yoann Offret

We scrutinize the anomalies in diffusion observed in an extended long-range system of classical rotors, the HMF model. Under suitable preparation, the system falls into long-lived quasi-stationary states presenting super-diffusion of rotor…

Statistical Mechanics · Physics 2009-11-11 Luis G. Moyano , Celia Anteneodo

In this paper we study a parametric class of stochastic processes to model both fast and slow anomalous diffusion. This class, called generalized grey Brownian motion (ggBm), is made up off self-similar with stationary increments processes…

Mathematical Physics · Physics 2009-11-13 Antonio Mura , Gianni Pagnini