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We propose a novel stochastic method to exactly generate Brownian paths conditioned to start at an initial point and end at a given final point during a fixed time $t_{f}$. These paths are weighted with a probability given by the overdamped…

Statistical Mechanics · Physics 2015-05-14 Satya N. Majumdar , Henri Orland

We investigate learning the eigenfunctions of evolution operators for time-reversal invariant stochastic processes, a prime example being the Langevin equation used in molecular dynamics. Many physical or chemical processes described by…

Machine Learning · Computer Science 2024-12-11 Timothée Devergne , Vladimir Kostic , Michele Parrinello , Massimiliano Pontil

Motivated by L\'{e}vy's characterization of Brownian motion on the line, we propose an analogue of Brownian motion that has as its state space an arbitrary closed subset of the line that is unbounded above and below: such a process will be…

Probability · Mathematics 2009-09-29 Shankar Bhamidi , Steven N. Evans , Ron Peled , Peter Ralph

We define and study the multiparameter fractional Brownian motion. This process is a generalization of both the classical fractional Brownian motion and the multiparameter Brownian motion, when the condition of independence is relaxed.…

Probability · Mathematics 2007-05-23 Erick Herbin , Ely Merzbach

A classification for Brownian motions on metric graphs, that is, right continuous strong Markov processes which behave like a one-dimensional Brownian motion on the edges and feature effects like Walsh skewness, stickiness and jumps at the…

Probability · Mathematics 2018-05-18 Florian Werner

We study the asymptotic behaviour of a properly normalized time-changed multidimensional Wiener process; the time change is given by an additive functional of the Wiener process itself. At the level of generators, the time change means that…

Probability · Mathematics 2025-01-22 Yuliia Mishura , René L. Schilling

Motivated by quantum information theory, we introduce a dynamical random state built out of the sum of $k \geq 2$ independent unitary Brownian motions. In the large size limit, its spectral distribution equals, up to a normalising factor,…

Probability · Mathematics 2023-07-26 Nizar Demni , Tarek Hamdi

Our first result concerns a characterisation by means of a functional equation of Poisson point processes conditioned by the value of their first moment. It leads to a generalised version of Mecke's formula. En passant, it also allows to…

Probability · Mathematics 2018-09-25 Giovanni Conforti , Tetiana Kosenkova , Sylvie Roelly

We study growth lemmas and questions of regularity for generators of Markov processes. The generators are allowed to have an arbitrary order of differentiability less than 2. In general, this order is represented by a function and not by a…

Analysis of PDEs · Mathematics 2013-11-21 Moritz Kassmann , Ante Mimica

We study the existence of densities for distributions of piecewise deterministic Markov processes. We also obtain relationships between invariant densities of the continuous time process and that of the process observed at jump times. In…

Probability · Mathematics 2020-06-03 Piotr Gwiżdż , Marta Tyran-Kamińska

We consider the Markov process defined by some pseudo-differential operator of the order $1<\alpha<2$ as the process generator. Using a pseudo-gradient operator, that is, the operator defined by the symbol $i\lambda|\lambda|^{\beta-1}$ with…

Probability · Mathematics 2024-02-06 Mykola Boiko , Mykhailo Osypchuk

In \cite{Bia97} Biane proposed a new statistic on set partitions which he called \emph{restricted crossings}. In a series of papers \cite{Ans01,Ans04,Ans04b,Ans05} Anshelevich showed that this statistic is an essential tool to investigate…

Functional Analysis · Mathematics 2020-08-06 Wiktor Ejsmont

We construct a stochastic process, called the Liouville Brownian motion, which is the Brownian motion associated to the metric $e^{\gamma X(z)}\,dz^2$, $\gamma<\gamma_c=2$ and $X$ is a Gaussian Free Field. Such a process is conjectured to…

Probability · Mathematics 2016-09-05 Christophe Garban , Rémi Rhodes , Vincent Vargas

Different change-point type models encountered in statistical inference for stochastic processes give rise to different limiting likelihood ratio processes. In this paper we consider two such likelihood ratios. The first one is an…

Statistics Theory · Mathematics 2010-04-05 Serguei Dachian

We construct stationary max-infinitely divisible (max-id) processes from systems of randomly time-changed L\'evy particles. Classical examples without time change, such as the Brown-Resnick process, are, up to marginal transformations,…

Probability · Mathematics 2026-04-14 Ioan Scheffel

The first passage time process of a L\'evy subordinator with heavy-tailed L\'evy measure has long-range dependent paths. The random fluctuations that appear under two natural schemes of summation and time scaling of such stochastic…

Probability · Mathematics 2012-04-02 Ingemar Kaj , Anders Martin-Löf

In the context of Markov processes, we show a new scheme to derive dual processes and a duality function based on a boson representation. This scheme is applicable to a case in which a generator is expressed by boson creation and…

Statistical Mechanics · Physics 2015-05-14 Jun Ohkubo

We address diffusion processes in a bounded domain, while focusing on somewhat unexplored affinities between the presence of absorbing and/or inaccessible boundaries. For the Brownian motion (L\'{e}vy-stable cases are briefly mentioned)…

Statistical Mechanics · Physics 2017-10-24 Piotr Garbaczewski

Several finite difference methods are proposed for the infinitesimal generator of 1D asymmetric $\alpha$-stable L\'{e}vy motions, based on the fact that the operator becomes a multiplier in the spectral space. These methods take the general…

Numerical Analysis · Mathematics 2017-08-21 Yanghong Huang , Xiao Wang

We are studying stationary random processes with conditional polynomial moments that allow a continuous path modification. Processes with continuous path modification, are important because they are relatively easy to simulate. One does not…

Probability · Mathematics 2024-11-21 Paweł J. Szabłowski
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