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We study a class of interacting particle systems on $\mathbb{R}$ with two types. Particles evolve by independent jumps sampled from a fixed distribution, with type-dependent jump rates $v_+$, $v_-$ and stochastic type switching driven by…

Probability · Mathematics 2026-05-14 Sayan Banerjee , Andrew Nguyen

We use analytical methods to construct the two-parameter Feller semigroup associated with a Markov process on a line with a moving membrane such that at the points on both sides of the membrane it coincides with the ordinary diffusion…

Probability · Mathematics 2020-03-10 Bohdan Kopytko , Roman Shevchuk

In this article we address the problem of the nonlinear interaction of subdiffusive particles. We introduce the random walk model in which statistical characteristics of a random walker such as escape rate and jump distribution depend on…

Statistical Mechanics · Physics 2015-06-15 Sergei Fedotov

The problem of drift estimation for the solution $X$ of a stochastic differential equation with L\'evy-type jumps is considered under discrete high-frequency observations with a growing observation window. An efficient and asymptotically…

Statistics Theory · Mathematics 2016-03-18 Arnaud Gloter , Dasha Loukianova , Hilmar Mai

We analyze a specific class of random systems that are driven by a symmetric L\'{e}vy stable noise. In view of the L\'{e}vy noise sensitivity to the confining "potential landscape" where jumps take place (in other words, to environmental…

Statistical Mechanics · Physics 2015-06-11 M. Zaba , P. Garbaczewski , V. Stephanovich

In this paper the solutions $u_{\nu}=u_{\nu}(x,t)$ to fractional diffusion equations of order $0<\nu \leq 2$ are analyzed and interpreted as densities of the composition of various types of stochastic processes. For the fractional equations…

Probability · Mathematics 2011-02-24 Enzo Orsingher , Luisa Beghin

We consider a real-valued diffusion process with a linear jump term driven by a Poisson point process and we assume that the jump amplitudes have a centered density with finite moments. We show upper and lower estimates for the density of…

Probability · Mathematics 2021-04-27 Arturo Kohatsu-Higa , Eulalia Nualart , Ngoc Khue Tran

This article studies the quasi-stationary behaviour of absorbed one-dimensional diffusions. We obtain necessary and sufficient conditions for the exponential convergence to a unique quasi-stationary distribution in total variation,…

Probability · Mathematics 2017-03-03 Nicolas Champagnat , Denis Villemonais

We study experimentally and theoretically mixing at the external boundary of a submerged turbulent jet. In the experimental study we use Particle Image Velocimetry and an Image Processing Technique based on the analysis of the intensity of…

Fluid Dynamics · Physics 2015-05-13 A. Eidelman , T. Elperin , N. Kleeorin , G. Hazak , I. Rogachevskii , O. Sadot , I. Sapir-Katiraie

We derive Wasserstein distance bounds between the probability distributions of a stochastic integral (It\^o) process with jumps $(X_t)_{t\in [0,T]}$ and a jump-diffusion process $(X^\ast_t)_{t\in [0,T]}$. Our bounds are expressed using the…

Probability · Mathematics 2022-12-12 Jean-Christophe Breton , Nicolas Privault

This paper presents some new results on the conditional joint probability distributions of phase-type under the mixture of right-continuous Markov jump processes with absorption on the same finite state space $\mathbb{S}$ moving at…

Probability · Mathematics 2018-07-24 B. A. Surya

We consider the classical Shiryaev--Roberts martingale diffusion, $(R_t)_{t\ge0}$, restricted to the interval $[0,A]$, where $A>0$ is a preset absorbing boundary. We take yet another look at the well-known phenomenon of quasi-stationarity…

Statistics Theory · Mathematics 2023-10-31 Soumik Banerjee , Aleksey S. Polunchenko

Stochastic evolution equations with compensated Poisson noise are considered in the variational approach with monotone and coercive coefficients. Here the Poisson noise is assumed to be time-homogeneous with $\sigma$-finite intensity…

Probability · Mathematics 2022-04-20 Sima Mehri , Erfan Salavati , Bijan Z. Zangeneh

In this paper, we consider the filtering problem for partially observed diffusions, which are regularly observed at discrete times. We are concerned with the case when one must resort to time-discretization of the diffusion process if the…

Numerical Analysis · Mathematics 2020-04-09 Marco Ballesio , Ajay Jasra , Erik von Schwerin , Raul Tempone

The aim of this paper is to discuss the appropriate modelling of in- and outflow boundary conditions for nonlinear drift-diffusion models for the transport of particles including size exclusion and their effect on the behaviour of…

Analysis of PDEs · Mathematics 2016-11-03 Martin Burger , Jan-Frederik Pietschmann

Diffusion of a two component fluid is studied in the framework of differential equations, but where these equations are systematically derived from a well-defined microscopic model. The model has a finite carrying capacity imposed upon it…

Statistical Mechanics · Physics 2015-06-04 D. Fanelli , A. J. McKane , G. Pompili , B. Tiribilli , M. Vassalli , T. Biancalani

The radiation (reaction, Robin) boundary condition for the continuum diffusion equation is widely used in chemical and biological applications to express reactive boundaries. The underlying trajectories of the diffusing particles are…

Mathematical Physics · Physics 2007-09-02 A. Singer , Z. Schuss , D. Holcman

We study the distribution of the unobserved states of two measure-valued diffusions of Fleming-Viot and Dawson-Watanabe type, conditional on observations from the underlying populations collected at past, present and future times. If seen…

Statistics Theory · Mathematics 2026-01-07 Filippo Ascolani , Antonio Lijoi , Matteo Ruggiero

We consider the so-called $\natural$-model. It is an one-default model which gives the conditional law of a random time with respect to a reference filtration. This model has been studied in the case where the parameters are continuous. In…

Probability · Mathematics 2013-10-01 Shiqi Song

Tuning of measurement models is challenging in real-world applications of sequential Monte Carlo methods. Recent advances in differentiable particle filters have led to various efforts to learn measurement models through neural networks.…

Artificial Intelligence · Computer Science 2022-03-17 Xiongjie Chen , Yunpeng Li