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This work focuses on recurrence and ergodicity of switching diffusions consisting of continuous and discrete components, in which the discrete component takes values in a countably infinite set and the rates of switching at current time…

Probability · Mathematics 2017-06-27 Dang H. Nguyen , George Yin

A semi-martingale reflecting Brownian motion is a popular process for diffusion approximations of queueing models including their networks. In this paper, we are concerned with the case that it lives on the nonnegative half-line, but the…

Probability · Mathematics 2024-08-13 Masakiyo Miyazawa

We study a class of Markov processes with finite state space and continuous time that have product form stationary distributions. We obtain a number of examples that can generate conjectures for diffusions with inert drift.

Probability · Mathematics 2008-10-19 Krzysztof Burdzy , David White

We present a study on the dynamics of a system consisting of a pair of hardcore particles diffusing with different rates. We solved the drift-diffusion equation for this model in the case when one particle, labeled F, drifts and diffuses…

Statistical Mechanics · Physics 2010-12-14 S. L. Narasimhan , A. Baumgaertner

Considering the example of interacting Brownian particles we present a linear response derivation of the boundary condition for the corresponding hydrodynamic description (the diffusion equation). This requires us to identify a non-analytic…

Statistical Mechanics · Physics 2009-11-07 M. Fuchs , K. Kroy

We study an interacting particle system whose dynamics depends on an interacting random environment. As the number of particles grows large, the transition rate of the particles slows down (perhaps because they share a common resource of…

Probability · Mathematics 2009-02-16 Charles Bordenave , David McDonald , Alexandre Proutiere

In this paper, we focus on the problem of stable prediction across unknown test data, where the test distribution is agnostic and might be totally different from the training one. In such a case, previous machine learning methods might…

Machine Learning · Computer Science 2020-06-11 Kun Kuang , Bo Li , Peng Cui , Yue Liu , Jianrong Tao , Yueting Zhuang , Fei Wu

We propose a conditional stochastic interpolation (CSI) method for learning conditional distributions. CSI is based on estimating probability flow equations or stochastic differential equations that transport a reference distribution to the…

Machine Learning · Statistics 2025-08-26 Ding Huang , Jian Huang , Ting Li , Guohao Shen

We review generalized Fluctuation-Dissipation Relations which are valid under general conditions even in ``non-standard systems'', e.g. out of equilibrium and/or without a Hamiltonian structure. The response functions can be expressed in…

Statistical Mechanics · Physics 2019-09-10 A. Sarracino , A. Vulpiani

When the unconditioned process is a diffusion submitted to a space-dependent killing rate $k(\vec x)$, various conditioning constraints can be imposed for a finite time horizon $T$. We first analyze the conditioned process when one imposes…

Statistical Mechanics · Physics 2022-09-01 Alain Mazzolo , Cécile Monthus

Risk assessment for rare events is essential for understanding systemic stability in complex systems. As rare events are typically highly correlated, it is important to study heavy-tailed multivariate distributions of the relevant…

Statistical Finance · Quantitative Finance 2025-12-02 Efstratios Manolakis , Anton J. Heckens , Benjamin Köhler , Thomas Guhr

We derive the stationary probability distribution for a non-equilibrium system composed by an arbitrary number of degrees of freedom that are subject to Gaussian colored noise and a conservative potential. This is based on a…

Statistical Mechanics · Physics 2015-06-01 Claudio Maggi , Umberto Marini Bettolo Marconi , Nicoletta Gnan , Roberto Di Leonardo

Frequency-dependent selection reflects the interaction between different species as they battle for limited resources in their environment. In a stochastic evolutionary game the species relative fitnesses guides the evolutionary dynamics…

Probability · Mathematics 2020-12-29 Lea Popovic , Liam Peuckert

We study dioecious (i.e., two-sex) branching particle system models, where there are two types of particles, modeling the male and female populations, and where birth of new particles requires the presence of both male and female particles.…

Probability · Mathematics 2009-09-29 Feng Yu

This article deals with transport properties of one dimensional Brownian diffusion under the influence of a correlated quenched random force, distributed as a two-level Poisson process. We find in particular that large time scaling laws of…

Condensed Matter · Physics 2009-10-28 Cecile MONTHUS

There has been a lot of work fitting Ising models to multivariate binary data in order to understand the conditional dependency relationships between the variables. However, additional covariates are frequently recorded together with the…

Machine Learning · Statistics 2012-09-28 Jie Cheng , Elizaveta Levina , Pei Wang , Ji Zhu

Density-dependent diffusion is a widespread phenomenon in nature. We have examined the density-dependent diffusion behavior of some biological processes such as tumor growth and invasion [23]. Here, we extend our previous work by developing…

Statistical Mechanics · Physics 2022-02-14 Ahmed M. Fouad , Marwa M. Fouad

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

Boundary driven diffusive systems describe a broad range of transport phenomena. We study large deviations of the density profile in these systems, using numerical and analytical methods. We find that the large deviation may be…

Statistical Mechanics · Physics 2015-10-07 Guy Bunin , Yariv Kafri , Daniel Podolsky

We analyze a simple model of deterministic diffusion. The model consists of a one-dimensional periodic array of scatterers in which point particles move from cell to cell as defined by a piecewise linear map. The microscopic chaotic…

chao-dyn · Physics 2009-10-31 R. Klages , J. R. Dorfman
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