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We first study crossing statistics in random connection models (RCM) built on marked Poisson point processes on $\mathbb R^d$. Under general assumptions, we show exponential tail bounds for the number of crossings of a box contained in the…

Probability · Mathematics 2025-10-29 Alessandra Faggionato , Ivailo Hartarsky

This work reviews deterministic and diffusion approximations of the stochastic chemical reaction networks and explains their applications. We discuss the added value the diffusion approximation provides for systems with different phenomena,…

Probability · Mathematics 2018-01-15 Pavel Mozgunov , Marco Beccuti , Andras Horvath , Thomas Jaki , Roberta Sirovich , Enrico Bibbona

We investigate the observables of the one-dimensional model for anomalous transport in semiconductor devices where diffusion arises from scattering at dislocations at fixed random positions, known as L\'evy-Lorentz gas. To gain insight into…

Statistical Mechanics · Physics 2024-08-15 Muhammad Tayyab

Stochastic processes offer a fundamentally different paradigm of dynamics than deterministic processes, the most prominent example of the latter being Newton's laws of motion. Here, we discuss in a pedagogical manner a simple and…

Statistical Mechanics · Physics 2022-04-15 Shamik Gupta , Arun M. Jayannavar

This thesis develops exact analytical tools to study strongly correlated stochastic systems, with a focus on extreme value statistics, gap statistics, and full counting statistics in multi-particle processes. A central contribution is the…

Statistical Mechanics · Physics 2025-08-19 Marco Biroli

Different theoretical methods used for the description of diffractive processes in small-x deep inelastic scattering are reviewed. The semiclassical approach, where a partonic fluctuation of the incoming virtual photon scatters off a…

High Energy Physics - Phenomenology · Physics 2009-02-20 A. Hebecker

A general system of particles (of one or several species) on a one dimensional lattice with boundaries is considered. Two general behaviors of such systems are investigated. The stationary behavior of the system, and the dominant way of the…

Statistical Mechanics · Physics 2015-06-24 Mohammad Khorrami , Amir Aghamohammadi

Diffusions are a successful technique to sample from high-dimensional distributions. The target distribution can be either explicitly given or learnt from a collection of samples. They implement a diffusion process whose endpoint is a…

Machine Learning · Computer Science 2025-09-03 Andrea Montanari

Anisotropic diffusion processes with a diffusion tensor are important in image analysis, physics, and engineering. However, their numerical approximation has a strong impact on dissipative artefacts and deviations from rotation invariance.…

Numerical Analysis · Mathematics 2024-04-09 Karl Schrader , Joachim Weickert , Michael Krause

In [Schuhmacher, Electron. J. Probab. 10 (2005), 165--201] estimates of the Barbour-Brown distance d_2 between the distribution of a thinned point process and the distribution of a Poisson process were derived by combining discretization…

Probability · Mathematics 2007-05-23 Dominic Schuhmacher

This study deals with continuous limits of interacting one-dimensional diffusive systems, arising from stochastic distortions of discrete curves with various kinds of coding representations. These systems are essentially of a…

Statistical Mechanics · Physics 2011-09-09 Guy Fayolle , Cyril Furtlehner

Motivated by the recent contribution \cite{BB17} we study the scaling limit behavior of a class of one-dimensional stochastic differential equations which has a unique attracting point subject to a small additional repulsive perturbation.…

Mathematical Physics · Physics 2019-06-26 Martin Kolb , Matthias Liesenfeld

We study the adsorption and desorption kinetics of interacting particles moving on a one-dimensional lattice. Confinement is introduced by limiting the number of particles on a lattice site. Adsorption and desorption are found to proceed at…

Statistical Mechanics · Physics 2014-12-16 T. Becker , K. Nelissen , B. Cleuren , B. Partoens , C. Van den Broeck

Resetting a stochastic process is an important problem describing the evolution of physical, biological and other systems which are continually returned to their certain fixed point. We consider the motion of a subdiffusive particle with a…

Statistical Mechanics · Physics 2024-01-18 Aleksander A. Stanislavsky

Positional reasoning is the process of ordering unsorted parts contained in a set into a consistent structure. We present Positional Diffusion, a plug-and-play graph formulation with Diffusion Probabilistic Models to address positional…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Francesco Giuliari , Gianluca Scarpellini , Stuart James , Yiming Wang , Alessio Del Bue

In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between global stationarity and nonstationarity for both parametric…

Statistics Theory · Mathematics 2020-05-04 Sucharita Roy , Sourabh Bhattacharya

The well-known plastic number substitution gives rise to a ternary inflation tiling of the real line whose inflation factor is the smallest Pisot-Vijayaraghavan number. The corresponding dynamical system has pure point spectrum, and the…

Dynamical Systems · Mathematics 2020-05-20 Michael Baake , Uwe Grimm

We introduce a continuum percolation model defined on the points of a d-dimensional homogeneous Poisson process. Each Poisson point is connected to all points within its connection range, which depends on the distances to the other Poisson…

Probability · Mathematics 2007-05-23 A. Gillett , M. Nuyens

We analyze two models of subdiffusion with stochastic resetting. Each of them consists of two parts: subdiffusion based on the continuous-time random walk (CTRW) scheme and independent resetting events generated uniformly in time according…

Statistical Mechanics · Physics 2019-05-22 Łukasz Kuśmierz , Ewa Gudowska-Nowak

A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from…

Applications · Statistics 2020-06-25 Rose Baker