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Related papers: Monitoring L\'evy-Process Crossovers

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We consider a situation commonly encountered in microfluidics: two streams of miscible liquids are brought at a junction to flow side by side within a microchannel, allowing solutes to diffuse from one stream to the other and possibly…

Soft Condensed Matter · Physics 2007-05-23 Jean-Baptiste Salmon , Armand Ajdari

The crossover between dispersion patterns has been frequently observed in various systems. Inspired by the pathway-based kinetic model for E. coli chemotaxis that accounts for the intracellular adaptation process and noise, we propose a…

Analysis of PDEs · Mathematics 2025-01-07 Zhe Xue , Weiran Sun , Zhennan Zhou , Min Tang

In this paper, we introduce branching processes in a L\'evy random environment. In order to define this class of processes, we study a particular class of non-negative stochastic differential equations driven by Brownian motions and Poisson…

Probability · Mathematics 2016-07-13 S. Palau , J. C. Pardo

We study the evolution of a system of free fermions in one dimension under the simultaneous effects of coherent tunneling and stochastic Markovian noise. We identify a class of noise terms where a hierarchy of decoupled equations for the…

Statistical Mechanics · Physics 2015-05-27 Viktor Eisler

We examine characteristic properties of deterministic and stochastic diffusion in low-dimensional chaotic dynamical systems. As an example, we consider a periodic array of scatterers defined by a simple chaotic map on the line. Adding…

Chaotic Dynamics · Physics 2009-11-07 R. Klages

This paper introduces a novel framework for causal inference in spatial economics that explicitly models the stochastic transition from partial to general equilibrium effects. We develop a Denoising Diffusion Probabilistic Model (DDPM)…

General Economics · Economics 2025-10-28 Tatsuru Kikuchi

We introduce diffusions on a space of interval partitions of the unit interval that are stationary with the Poisson-Dirichlet laws with parameters $(\alpha,0)$ and $(\alpha,\alpha)$. The construction has two steps. The first is a general…

Probability · Mathematics 2019-10-18 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

Diffusion models have recently shown considerable potential in solving Bayesian inverse problems when used as priors. However, sampling from the resulting denoising posterior distributions remains a challenge as it involves intractable…

Machine Learning · Statistics 2024-12-25 Badr Moufad , Yazid Janati , Lisa Bedin , Alain Durmus , Randal Douc , Eric Moulines , Jimmy Olsson

The dispersion of solute in porous media shows a non-linear increase in the transition from diffusion to advection dominated dispersion as the flow velocity is raised. In the past, the behavior in this intermediate regime has been explained…

Fluid Dynamics · Physics 2014-09-23 B. Ph. van Milligen , P. D. Bons

Discrete diffusion models have gained increasing attention for their ability to model complex distributions with tractable sampling and inference. However, the error analysis for discrete diffusion models remains less well-understood. In…

Machine Learning · Computer Science 2025-03-04 Yinuo Ren , Haoxuan Chen , Grant M. Rotskoff , Lexing Ying

This study makes the first attempt to use the 2/3-order fractional Laplacian modeling of enhanced diffusing movements of random turbulent particle resulting from nonlinear inertial interactions. A combined effect of the inertial…

Chaotic Dynamics · Physics 2007-05-23 Wen Chen

In heterogeneous environments, the diffusivity is not constant but changes with time. It is important to detect changes in the diffusivity from single-particle-tracking trajectories in experiments. Here, we devise a novel method for…

Statistical Mechanics · Physics 2017-12-06 Takuma Akimoto , Eiji Yamamoto

Among Markovian processes, the hallmark of L\'evy flights is superdiffusion, or faster-than-Brownian dynamics. Here we show that L\'evy laws, as well as Gaussians, can also be the limit distributions of processes with long range memory that…

Statistical Mechanics · Physics 2016-02-10 Denis Boyer , Inti Pineda

We study diffusion in a one-dimensional periodic array of scatterers modeled by a simple map. The chaotic scattering process for this map can be changed by a control parameter and exhibits the dynamics of a crisis in chaotic scattering. We…

chao-dyn · Physics 2008-02-03 R. Klages , J. R. Dorfman

This paper is a preliminary work to address the problem of dynamical systems with parameters varying in time. An idea to predict their behaviour is proposed. These systems are called \emph{transient systems}, and are distinguished from…

Dynamical Systems · Mathematics 2014-11-04 Ugo Galvanetto , Luca Magri

We consider the problem of simulating diffusion bridges, which are diffusion processes that are conditioned to initialize and terminate at two given states. The simulation of diffusion bridges has applications in diverse scientific fields…

Computation · Statistics 2025-06-19 Jeremy Heng , Valentin De Bortoli , Arnaud Doucet , James Thornton

Cognitive processes undergo various fluctuations and transient states across different temporal scales. Superstatistics are emerging as a flexible framework for incorporating such non-stationary dynamics into existing cognitive model…

Neurons and Cognition · Quantitative Biology 2024-10-02 Lukas Schumacher , Martin Schnuerch , Andreas Voss , Stefan T. Radev

In this paper, we consider the composition of two independent processes : one process corresponds to position and the other one to time. Such processes will be called iterated processes. We first propose an algorithm based on the Euler…

Probability · Mathematics 2017-05-03 Michèle Thieullen , Alexis Vigot

Convergence of stochastic processes with jumps to diffusion processes is investigated in the case when the limit process has discontinuous coefficients. An example is given in which the diffusion approximation of a queueing model yields a…

Probability · Mathematics 2016-09-07 N. V. Krylov , R. Liptser

Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When equipped with a guidance mechanism, these models can also…

Machine Learning · Computer Science 2026-05-04 Saeed Mohseni-Sehdeh , Walid Saad , Kei Sakaguchi , Tao Yu
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