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A physical-mathematical approach to anomalous diffusion may be based on fractional diffusion equations and related random walk models. The fundamental solutions of these equations can be interpreted as probability densities evolving in time…

Statistical Mechanics · Physics 2008-05-27 Rudolf Gorenflo , Francesco Mainardi

We obtain large deviation results for a two time-scale model of jump-diffusion processes. The processes on the two time scales are fully inter-dependent, the slow process has small perturbative noise and the fast process is ergodic. Our…

Probability · Mathematics 2016-09-19 Rohini Kumar , Lea Popovic

We study two one-parameter families of point processes connected to random matrices: the Sine_beta and Sch_tau processes. The first one is the bulk point process limit for the Gaussian beta-ensemble. For beta=1, 2 and 4 it gives the limit…

Probability · Mathematics 2013-11-19 Diane Holcomb , Benedek Valkó

In this Letter we show that the analysis of Lyapunov-exponents fluctuations contributes to deepen our understanding of high-dimensional chaos. This is achieved by introducing a Gaussian approximation for the large deviation function that…

Chaotic Dynamics · Physics 2012-03-28 Pavel V. Kuptsov , Antonio Politi

We study generalised anomalous diffusion processes whose diffusion coefficient $D(x,t)\sim D_0|x|^{\alpha}t^{\beta}$ depends on both the position $x$ of the test particle and the process time $t$. This process thus combines the features of…

Statistical Mechanics · Physics 2015-02-06 Andrey G. Cherstvy , Ralf Metzler

Drift diffusion models (DDMs) have found widespread use in computational neuroscience and other fields. They model evidence accumulation in simple decision tasks as a stochastic process drifting towards a decision barrier. In models where…

Methodology · Statistics 2025-12-12 Sicheng Liu , Alexander Fengler , Michael J. Frank , Matthew T. Harrison

There have been increasing reports that the diffusion coefficient of macromolecules depends on time and fluctuates randomly. Here, a novel method to elucidate the fluctuating diffusivity from trajectory data is developed. The time-averaged…

Statistical Mechanics · Physics 2017-10-25 Tomoshige Miyaguchi

Last year in [Phys. Rev. E 102, 042121 (2020)] the authors studied an overdamped dynamics of nonequilibrium noise driven Brownian particle dwelling in a spatially periodic potential and discovered a novel class of Brownian, yet non-Gaussian…

Statistical Mechanics · Physics 2021-12-22 Karol Białas , Jakub Spiechowicz

The non-Markovian continuous-time random walk model, featuring fat-tailed waiting times and narrow distributed displacements with a non-zero mean, is a well studied model for anomalous diffusion. Using an analytical approach, we recently…

Statistical Mechanics · Physics 2023-09-18 Wanli Wang , Eli Barkai

We analyse mobile-immobile transport of particles that switch between the mobile and immobile phases with finite rates. Despite this seemingly simple assumption of Poissonian switching we unveil a rich transport dynamics including…

Statistical Mechanics · Physics 2022-03-28 T. Doerries , A. V. Chechkin , R. Metzler

A physical-mathematical approach to anomalous diffusion may be based on generalized diffusion equations (containing derivatives of fractional order in space or/and time) and related random walk models. The fundamental solution (for the…

Statistical Mechanics · Physics 2007-09-25 Rudolf Gorenflo , Francesco Mainardi , Daniele Moretti , Gianni Pagnini , Paolo Paradisi

We present a class of diffusion-based algorithms to draw samples from high-dimensional probability distributions given their unnormalized densities. Ideally, our methods can transport samples from a Gaussian distribution to a specified…

Machine Learning · Computer Science 2025-02-04 Anand Jerry George , Nicolas Macris

Recent works have shown that high probability metrics with stochastic gradient descent (SGD) exhibit informativeness and in some cases advantage over the commonly adopted mean-square error-based ones. In this work we provide a formal…

Machine Learning · Computer Science 2022-11-03 Dragana Bajovic , Dusan Jakovetic , Soummya Kar

A stochastic theory for the toppling activity in sandpile models is developed, based on a simple mean-field assumption about the toppling process. The theory describes the process as an anti-persistent Gaussian walk, where the diffusion…

Statistical Finance · Quantitative Finance 2009-11-13 Martin Rypdal , Kristoffer Rypdal

The aim of the present paper is to extend the large deviation with discontinuous statistics studied in \cite{BDE} to the diffusion $d\mathbf{x}^\varepsilon = -\{\mathbf{A}^\top (\mathbf{A} \mathbf{x}^\varepsilon - \mathbf{y}) + \mu…

Probability · Mathematics 2016-10-04 Azzouz Dermoune , Khalifa Es-Sebaiy , Youssef Ouknine

Large deviations for fat tailed distributions, i.e. those that decay slower than exponential, are not only relatively likely, but they also occur in a rather peculiar way where a finite fraction of the whole sample deviation is concentrated…

Statistical Mechanics · Physics 2015-06-03 Mario Filiasi , Giacomo Livan , Matteo Marsili , Maria Peressi , Erik Vesselli , Elia Zarinelli

Linear diffusions are used to model a large number of stochastic processes in physics, including small mechanical and electrical systems perturbed by thermal noise, as well as Brownian particles controlled by electrical and optical forces.…

Statistical Mechanics · Physics 2023-05-10 Johan du Buisson , Hugo Touchette

Fractional Brownian motion, a stochastic process with long-time correlations between its increments, is a prototypical model for anomalous diffusion. We analyze fractional Brownian motion in the presence of a reflecting wall by means of…

Statistical Mechanics · Physics 2018-02-21 Alexander H. O. Wada , Thomas Vojta

We study large deviation principles for Gaussian processes lifted to the free nilpotent group of step N. We apply this to a large class of Gaussian processes lifted to geometric rough paths. A large deviation principle for enhanced…

Probability · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

Recent advances in light microscopy have spawned new research frontiers in microbiology by working around the diffraction barrier and allowing for the observation of nanometric biological structures. Microrheology is the study of the…

Probability · Mathematics 2016-07-27 Gustavo Didier , Kui Zhang