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The simple L\'evy Poisson process and scaled forms are explicitly constructed from partial sums of independent and identically distributed random variables and from sums of non-stationary independent random variables. For the latter, the…

Probability · Mathematics 2022-05-31 Aladji Babacar Niang , Gane Samb Lo , Chérif Mamadou Moctar Traoré , Amadou Ball

Percolation plays an important role in fields and phenomena as diverse as the study of social networks, the dynamics of epidemics, the robustness of electricity grids, conduction in disordered media, and geometric properties in statistical…

Statistical Mechanics · Physics 2015-06-10 Mykola Maksymenko , Roderich Moessner , Kirill Shtengel

The space-fractional and the time-fractional Poisson processes are two well-known models of fractional evolution. They can be constructed as standard Poisson processes with the time variable replaced by a stable subordinator and its…

Probability · Mathematics 2016-08-09 Luisa Beghin , Costantino Ricciuti

We are dealing in this work with such formal and conceptual extensions of nonrelativistic quantum mechanics (QM) which contain QM with its standard formalism and interpretation as a subtheory. QM is here primarily equivalently reformulated…

Mathematical Physics · Physics 2020-07-25 Pavel Bóna

We prove phase transitions for continuum percolation in a Boolean model based on a Cox point process with nonstabilizing directing measure. The directing measure, which can be seen as a stationary random environment for the classical…

Probability · Mathematics 2023-05-10 Benedikt Jahnel , Sanjoy Kumar Jhawar , Anh Duc Vu

We propose a random matrix modeling for the parametric evolution of eigenstates. The model is inspired by a large class of quantized chaotic systems. Its unique feature is having parametric invariance while still possessing the…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 J. A. Mendez-Bermudez , Tsampikos Kottos , Doron Cohen

In this paper we consider a random walk of a particle in $\mathbb{R}^d$. Convergence of different transformations of trajectories of random flights with Poisson switching moments has been obtained by Davydov and Konakov, as well as…

Probability · Mathematics 2019-10-10 Alexander Falaleev , Valentin Konakov

We develop a Perron-Frobenius type theory for products of random quantum channels acting on finite-dimensional matrix algebras sampled from a stationary and ergodic stochastic process, which, in keeping with the literature, we call ergodic…

Quantum Physics · Physics 2026-04-13 Owen Ekblad , Jeffrey Schenker

These notes describe several loop soup models and their {\it universal behaviour} in dimensions greater or equal to 3. These loop models represent certain classical or quantum statistical mechanical systems. These systems undergo phase…

Statistical Mechanics · Physics 2022-04-28 Daniel Ueltschi

Analyzing point patterns with linear structures has recently been of interest in e.g. neuroscience and geography. To detect anisotropy in such cases, we introduce a functional summary statistic, called the cylindrical $K$-function, since it…

Statistics Theory · Mathematics 2016-08-29 Jesper Møller , Farzaneh Safavimanesh , Jakob G. Rasmussen

The Poisson-Nernst-Planck system of equations used to model ionic transport is interpreted as a gradient flow for the Wasserstein distance and a free energy in the space of probability measures with finite second moment. A variational…

Analysis of PDEs · Mathematics 2015-09-08 David Kinderlehrer , Léonard Monsaingeon , Xiang Xu

We develop correlated random measures, random measures where the atom weights can exhibit a flexible pattern of dependence, and use them to develop powerful hierarchical Bayesian nonparametric models. Hierarchical Bayesian nonparametric…

Machine Learning · Statistics 2016-11-10 Rajesh Ranganath , David Blei

Linear fractional Galton-Watson branching processes in i.i.d.~random environment are, on the quenched level, intimately connected to random difference equations by the evolution of the random parameters of their linear fractional marginals.…

Probability · Mathematics 2021-10-01 Gerold Alsmeyer

The result provided in this paper helps complete a unified picture of the scaling behavior in heavy-tailed stochastic models for transmission of packet traffic on high-speed communication links. Popular models include infinite source…

Probability · Mathematics 2010-08-17 Clément Dombry , Ingemar Kaj

The class of random-cluster models is a unification of a variety of stochastic processes of significance for probability and statistical physics, including percolation, Ising, and Potts models; in addition, their study has impact on the…

Probability · Mathematics 2007-05-23 Geoffrey Grimmett

Non-linear Hawkes processes with memory kernels given by the sum of Erlang kernels are considered. It is shown that their stability properties can be studied in terms of an associated class of piecewise deterministic Markov processes,…

Probability · Mathematics 2018-11-27 Aline Duarte , Eva Löcherbach , Guilherme Ost

In this paper we prove a version of the Berman-Konsowa principle for reversible Markov jump processes on Polish spaces. The Berman-Konsowa principle provides a variational formula for the capacity of a pair of disjoint measurable sets.…

Probability · Mathematics 2016-11-08 F. den Hollander , S. Jansen

We investigate the statistical properties of one-dimensional Burgers dynamics evolving from stochastic initial conditions defined by a Poisson point process for the velocity potential, with a power-law intensity. Thanks to the geometrical…

Statistical Mechanics · Physics 2025-11-06 Patrick Valageas

Kingman derived the Ewens sampling formula for random partitions describing the genetic variation in a neutral mutation model defined by a Poisson process of mutations along lines of descent governed by a simple coalescent process, and…

Probability · Mathematics 2007-05-23 Rui Dong , Alexander Gnedin , Jim Pitman

Diffusion models are loosely modelled based on non-equilibrium thermodynamics, where \textit{diffusion} refers to particles flowing from high-concentration regions towards low-concentration regions. In statistics, the meaning is quite…

Machine Learning · Computer Science 2023-12-19 Inga Strümke , Helge Langseth