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Related papers: Infinite-Scale Percolation in a New Type of Branch…

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Every realistic instance of a percolation problem is faced with some degree of polydispersity, e.g., the pore-size distribution of an inhomogeneous medium, the size distribution of filler particles in composite materials, or the vertex…

Statistical Mechanics · Physics 2025-06-16 Fabian Coupette , Tanja Schilling

We construct a class of discontinuous superprocesses with dependent spatial motion and general branching mechanism. The process arises as the weak limit of critical interacting-branching particle systems where the spatial motions of the…

Probability · Mathematics 2008-07-02 Hui He

This paper is a survey of various results and techniques in first passage percolation, a random process modeling a spreading fluid on an infinite graph. The latter half of the paper focuses on the connection between first passage…

Probability · Mathematics 2010-05-06 Nathaniel D. Blair-Stahn

The diffusion of finite-size hard-core interacting particles in two- or three-dimensional confined domains is considered in the limit that the confinement dimensions become comparable to the particle's dimensions. The result is a nonlinear…

Mathematical Physics · Physics 2017-03-23 Maria Bruna , S. Jonathan Chapman

The work continues the author's many-year research in theory of maximal branching processes, which are obtained from classical branching processes by replacing the summation of descendant numbers with taking the maximum. One can say that in…

Probability · Mathematics 2021-04-20 Alexey V. Lebedev

Many biological processes and objects can be described by fractals. The paper uses a new type of objects - blinking fractals - that are not covered by traditional theories considering dynamics of self-similarity processes. It is shown that…

Chaotic Dynamics · Physics 2012-03-15 Yaroslav D. Sergeyev

In many physical situations involving diverse length scales, waves or rays representing them travel through media characterized by spatially smooth, random, modest refactive index variations. "Primary" diffraction (by individual…

Classical Physics · Physics 2021-12-14 Eric J Heller , Ragnar Fleischmann , Tobias Kramer

We present a new algorithm to optimize distributions defined implicitly by parameterized stochastic diffusions. Doing so allows us to modify the outcome distribution of sampling processes by optimizing over their parameters. We introduce a…

How finite-sized material lines stretch in chaotic (mono-scale) and turbulent (multi-scale) flows remains a central but unresolved problem that governs mixing, transport and reaction. We show elongation is controlled by a finite-sampling…

Fluid Dynamics · Physics 2026-04-21 Daniel Lester , Marco Dentz

A continuous-state polynomial branching process is constructed as the pathwise unique solution of a stochastic integral equation with absorbing boundary condition. The extinction and explosion probabilities and the mean extinction and…

Probability · Mathematics 2018-10-09 Pei-Sen Li

We propose a particle system of diffusion processes coupled through a chain-like network structure described by an infinite-dimensional, nonlinear stochastic differential equation of McKean-Vlasov type. It has both (i) a local chain…

Probability · Mathematics 2019-07-18 Nils Detering , Jean-Pierre Fouque , Tomoyuki Ichiba

Drawing from the theory of stochastic differential equations, we introduce a novel sampling method for known distributions and a new algorithm for diffusion generative models with unknown distributions. Our approach is inspired by the…

Statistics Theory · Mathematics 2024-07-12 Xicheng Zhang

After collecting data from observations or experiments, the next step is to build an appropriate mathematical or stochastic model to describe the data so that further studies can be done with the help of the models. In this article, the…

Data Analysis, Statistics and Probability · Physics 2023-07-19 A. M. Mathai , H. J. Haubold

We address the now classical problem of a diffusion process that crosses over from a ballistic behavior at short times to a fractional diffusion (sub- or super-diffusion) at longer times. Using the standard non-Markovian diffusion equation…

Statistical Mechanics · Physics 2015-05-14 Valery Ilyin , Itamar Procaccia , Anatoly Zagorodny

Percolation is a concept widely used in many fields of research and refers to the propagation of substances through porous media (e.g., coffee filtering), or the behaviour of complex networks (e.g., spreading of diseases). Percolation…

Soft Condensed Matter · Physics 2015-12-02 Wolf B. Dapp , Martin H. Müser

We consider the inference problem for parameters in stochastic differential equation models from discrete time observations (e.g. experimental or simulation data). Specifically, we study the case where one does not have access to…

Numerical Analysis · Mathematics 2018-04-10 Sebastian Krumscheid

We prove a maximum principle for the problem of optimal control for a fractional diffusion with infinite horizon. Further, we show existence of fractional backward stochastic differential equations on infinite horizon. We illustrate our…

Optimization and Control · Mathematics 2012-06-29 Sven Haadem

We construct a class of superprocesses by taking the high density limit of a sequence of interacting-branching particle systems. The spatial motion of the superprocess is determined by a system of interacting diffusions, the branching…

Probability · Mathematics 2011-02-19 Donald A. Dawson , Zenghu Li , Hao Wang

We show that the size distributions of fragments created by high energy nuclear collisions are remarkably well reproduced within the framework of a parameter free percolation model. We discuss two possible scenarios to explain this…

Statistical Mechanics · Physics 2009-10-31 X. Campi , H. Krivine , E. Plagnol , N. Sator

The properties of the similarity transformation in percolation theory in the complex plane of the percolation probability are studied. It is shown that the percolation problem on a two-dimensional square lattice reduces to the Mandelbrot…

Disordered Systems and Neural Networks · Physics 2008-02-03 M. V. Entin , G. M. Entin