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This paper deals with ergodic theorems for particular time-inhomogeneous Markov processes, whose the time-inhomogeneity is asymptotically periodic. Under a Lyapunov/minorization condition, it is shown that, for any measurable bounded…

Probability · Mathematics 2022-04-06 William Oçafrain

Diffusion with stochastic resetting has recently emerged as a powerful modeling tool with a myriad of potential applications. Here, we study local time in this model, covering situations of free and biased diffusion with, and without, the…

Statistical Mechanics · Physics 2019-06-06 Arnab Pal , Rakesh Chatterjee , Shlomi Reuveni , Anupam Kundu

In this article we study a homogeneous transient diffusion process $X$. We combine the theories of differential equations and of stochastic processes to obtain new results for homogeneous diffusion processes, generalizing the results of…

Probability · Mathematics 2013-06-07 Mykola Perestyuk , Yuliya Mishura , Georgiy Shevchenko

Materials with unusual optical properties are central to advanced control of light. Yet, in nature, such materials may be exceedingly rare and often difficult to obtain. To overcome this limitation, here we introduce the concept of temporal…

Optics · Physics 2026-05-19 Grigorii Ptitcyn , Diego M. Solís , M. S. Mirmoosa , Nader Engheta

We prove a sequence of limiting results about weakly dependent stationary and regularly varying stochastic processes in discrete time. After deducing the limiting distribution for individual clusters of extremes, we present a new type of…

Probability · Mathematics 2017-12-05 Bojan Basrak , Hrvoje Planinic , Philippe Soulier

We study some regularity properties in locally stationary Markov models which are fundamental for controlling the bias of nonparametric kernel estimators. In particular, we provide an alternative to the standard notion of derivative process…

Statistics Theory · Mathematics 2018-12-07 Lionel Truquet

We study a continuous-time random walk, $X$, on $\mathbb{Z}^d$ in an environment of dynamic random conductances taking values in $(0, \infty)$. We assume that the law of the conductances is ergodic with respect to space-time shifts. We…

Probability · Mathematics 2019-05-31 Sebastian Andres , Alberto Chiarini , Jean-Dominique Deuschel , Martin Slowik

We consider triangular arrays of Markov chains that converge weakly to a diffusion process. Local limit theorems for transition densities are proved. The observation time [0,T] may be fixed or lim n T = 0, where nh = T and h is a mesh…

Probability · Mathematics 2007-06-13 Valentin Konakov

We consider a general discrete-time branching random walk on a countable set X. We relate local, strong local and global survival with suitable inequalities involving the first-moment matrix M of the process. In particular we prove that,…

Probability · Mathematics 2015-05-18 Fabio Zucca

We obtain a strong invariance principle for nonconventional sums and applying this result we derive for them a version of the law of iterated logarithm, as well as an almost sure central limit theorem. Among motivations for such results are…

Probability · Mathematics 2012-09-11 Yuri Kifer

We give a complete expansion, at any accuracy order, for the iterated convolution of a complex valued integrable sequence in one space dimension. The remainders are estimated sharply with generalized Gaussian bounds. The result applies in…

Numerical Analysis · Mathematics 2024-11-14 Jean-François Coulombel , Grégory Faye

We give sufficient Gordin-type criteria for the iterated (enhanced) weak invariance principle to hold for deterministic dynamical systems. Such an invariance principle is intrinsically related to the interpretation of stochastic integrals.…

Dynamical Systems · Mathematics 2022-05-30 Matt Galton , Ian Melbourne

The basic characteristics of the classical many-particle (''macroscopic'') systems are notoriously hard to reproduce in quantum theory. In this paper we show that this is not the case for certain many-particle systems within the recently…

Quantum Physics · Physics 2025-03-03 J. Jeknic-Dugic , M. Arsenijevic , M. Dugic

We consider random walks in dynamic random environments, with an environment generated by the time-reversal of a Markov process from the oriented percolation universality class. If the influence of the random medium on the walk is small in…

Probability · Mathematics 2016-06-02 Matthias Birkner , Jiří Černý , Andrej Depperschmidt

In this paper we study the convergence in distribution and the local limit theorem for the partial sums of linear random fields with i.i.d. innovations that have infinite second moment and belong to the domain of attraction of a stable law…

Probability · Mathematics 2022-05-10 Magda Peligrad , Hailin Sang , Yimin Xiao , Guangyu Yang

In this paper, we establish a local limit theorem for linear fields of random variables constructed from independent and identically distributed innovations each with finite second moment. When the coefficients are absolutely summable we do…

Probability · Mathematics 2020-08-06 Timothy Fortune , Magda Peligrad , Hailin Sang

Consider a non-local (i.e., involving a convolution term) conservation law: when the convolution term converges to a Dirac delta, in the limit we formally recover a classical (or "local") conservation law. In this note we overview recent…

Analysis of PDEs · Mathematics 2023-11-27 Maria Colombo , Gianluca Crippa , Elio Marconi , Laura V. Spinolo

We prove an invariance principle for continuous-time random walks in a dynamically averaging environment on $\mathbb Z$. In the beginning, the conductances may fluctuate substantially, but we assume that as time proceeds, the fluctuations…

Probability · Mathematics 2020-09-24 Stein Andreas Bethuelsen , Christian Hirsch , Christian Mönch

We establish almost sure invariance principles, a strong form of approximation by Brownian motion, for non-stationary time-series arising as observations on dynamical systems. Our examples include observations on sequential expanding maps,…

Dynamical Systems · Mathematics 2014-06-18 N. Haydn , M. Nicol , A. Tôrôk , S. Vaienti

We use the abstract method of (local) martingale problems in order to give criteria for convergence of stochastic processes. Extending previous notions, the formulation we use is neither restricted to Markov processes (or semimartingales),…

Probability · Mathematics 2021-08-27 David Criens , Peter Pfaffelhuber , Thorsten Schmidt