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We study the random walk of a particle in a compartmentalized environment, as realized in biological samples or solid state compounds. Each compartment is characterized by its length $L$ and the boundaries transmittance $T$. We identify two…

Statistical Mechanics · Physics 2019-03-12 Gorka Muñoz-Gil , Miguel Angel García-March , Carlo Manzo , Alessio Celi , Maciej Lewenstein

Deterministic diffusion in temporally oscillating convection is studied for particles with finite mass. The particles are assumed to obey a simple dissipative dynamical system and the particle diffusion is induced by the strange attractor.…

Chaotic Dynamics · Physics 2009-11-07 Hidetsugu Sakaguchi

We study the convergence of $N-$particle systems described by SDEs driven by Brownian motion and Poisson random measure, where the coefficients depend on the empirical measure of the system. Every particle jumps with a jump rate depending…

Probability · Mathematics 2021-03-09 Xavier Erny , Eva Löcherbach , Dasha Loukianova

The probability density is a fundamental quantity for characterizing diffusion processes. However, it is seldom known except in a few renowned cases, including Brownian motion and the Ornstein-Uhlenbeck process and their bridges, geometric…

Mathematical Physics · Physics 2024-03-05 Alain Mazzolo

In this paper, we are concerned with centered Markov Additive Processes $\{(X_t,Y_t)\}_{t\in\T}$ where the driving Markov process $\{X_t\}_{t\in\T}$ has a finite state space. Under suitable conditions, we provide a local limit theorem for…

Probability · Mathematics 2013-06-25 Loïc Hervé , James Ledoux

We consider a reaction--diffusion equation perturbed by noise (not necessarily white). We prove existence of the Fomin derivative of the corresponding transition semigroup $P_t$. The main tool is a new estimate for $P_tD\varphi$ in terms of…

Probability · Mathematics 2015-02-27 Giuseppe Da Prato , Arnaud Debussche

The Large Deviations Principle (LDP) is verified for a homogeneous diffusion process with respect to a Brownian motion $B_t$, $$ X^\eps_t=x_0+\int_0^tb(X^\eps_s)ds+ \eps\int_0^t\sigma(X^\eps_s)dB_s, $$ where $b(x)$ and $\sigma(x)$ are are…

Probability · Mathematics 2011-08-24 P. Chigansky , R. Liptser

Flow Matching, a promising approach in generative modeling, has recently gained popularity. Relying on ordinary differential equations, it offers a simple and flexible alternative to diffusion models, which are currently the…

Machine Learning · Statistics 2026-03-13 Lea Kunkel

We discuss the combined effects of overdamped motion in a quenched random potential and diffusion, in one dimension, in the limit where the diffusion coefficient is small. Our analysis considers the statistics of the mean first-passage time…

Statistical Mechanics · Physics 2020-08-19 Michael Wilkinson , Marc Pradas , Gerhard Kling

This paper concerns the use of the expectation-maximisation (EM) algorithm for inference in partially observed diffusion processes. In this context, a well known problem is that all except a few diffusion processes lack closed-form…

Statistics Theory · Mathematics 2010-08-18 Jimmy Olsson , Jonas Ströjby

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

We consider systems of particles hopping stochastically on $d$-dimensional lattices with space-dependent probabilities. We map the master equation onto an evolution equation in a Fock space where the dynamics are given by a quantum…

Condensed Matter · Physics 2007-05-23 Gunter Schuetz , Sven Sandow

In this paper we investigate deterministic diffusion in systems which are spatially extended in certain directions but are restricted in size and open in other directions, consequently particles can escape. We introduce besides the…

chao-dyn · Physics 2016-08-31 Z. Kaufmann , H. Lustfeld , A. Nemeth , P. Szepfalusy

In this article, we consider a jump diffusion process (X_t), with drift function b, diffusion coefficient sigma and jump coefficient xi^{2}. This process is observed at discrete times t=0,Delta,...,nDelta. The sampling interval Delta tends…

Statistics Theory · Mathematics 2013-11-27 Emeline Schmisser

The filtering of a Markov diffusion process on a manifold from counting process observations leads to `large' changes in the conditional distribution upon an observed event, corresponding to a multiplication of the density by the intensity…

Optimization and Control · Mathematics 2019-11-01 Simone Carlo Surace , Anna Kutschireiter , Jean-Pascal Pfister

We consider the problem of estimating the density of the process associated with the small jumps of a pure jump L\'evy process, possibly of infinite variation, from discrete observations of one trajectory. The interest of such a question…

Statistics Theory · Mathematics 2024-12-10 Céline Duval , Taher Jalal , Ester Mariucci

In this paper we consider one-dimensional diffusions with constant coefficients in a finite interval with jump boundary and a certain deterministic jump distribution. We use coupling methods in order to identify the spectral gap in the case…

Probability · Mathematics 2011-01-17 Martin Kolb , Achim Wübker

We consider a fractional counting process with jumps of amplitude $1,2,\ldots,k$, with $k\in \mathbb{N}$, whose probabilities satisfy a suitable system of fractional difference-differential equations. We obtain the moment generating…

Probability · Mathematics 2016-03-10 Antonio Di Crescenzo , Barbara Martinucci , Alessandra Meoli

If $X,Y,Z$ denote sets of random variables, two different data sources may contain samples from $P_{X,Y}$ and $P_{Y,Z}$, respectively. We argue that causal inference can help inferring properties of the 'unobserved joint distributions'…

Statistics Theory · Mathematics 2018-05-18 Dominik Janzing

In this paper we consider non convex control problems of stochastic differential equations driven by relaxed controls. We present existence of optimal controls and then develop necessary conditions of optimality. We cover both continuous…

Optimization and Control · Mathematics 2013-02-15 Nasir U. Ahmed , Charalambos D. Charalambous