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It was shown recently that a Langevin process can be reflected at an energy absorbing boundary. Here, we establish that the law of this reflecting process can be characterized as the unique weak solution to a certain second order stochastic…

Probability · Mathematics 2007-05-23 Jean Bertoin

Let $\{L(t),t\geq 0\}$ be a L\'{e}vy process with representative random variable $L(1)$ defined by the infinitely divisible logarithmic series distribution. We study here the transition probability and L\'{e}vy measure of this process. We…

Probability · Mathematics 2019-12-18 Penka Mayster , Assen Tchorbadjieff

We prove exponential convergence to the invariant measure, in the total variation norm, for solutions of SDEs driven by $\alpha$-stable noises in finite and in infinite dimensions. Two approaches are used. The first one is based on Harris…

Analysis of PDEs · Mathematics 2011-04-27 E. Priola , A. Shirikyan , L. Xu , J. Zabczyk

Positive dependencies have been compared in the literature under rather strong assumptions such as equality of conditional distributions, exchangeability, or stationarity. We establish supermodular ordering results for distributions that…

Statistics Theory · Mathematics 2025-11-11 Jonathan Ansari , Moritz Ritter

We prove the (generalized) principal pivot transform is matrix monotone, in the sense of the L\"owner ordering, under minimal hypotheses. This improves on the recent results of J. E. Pascoe and R. Tully-Doyle, Monotonicity of the principal…

Functional Analysis · Mathematics 2023-02-13 Kenneth Beard , Aaron Welters

We develop a notion of stochastic quantum trajectories. First, we construct a basis set of trajectories, called elementary trajectories, and go on to show that any quantum dynamical process, including those that are non-Markovian, can be…

Quantum Physics · Physics 2018-09-20 Fattah Sakuldee , Simon Milz , Felix A. Pollock , Kavan Modi

An autoregressive process with Markov regime is an autoregressive process for which the regression function at each time point is given by a nonobservable Markov chain. In this paper we consider the asymptotic properties of the maximum…

Statistics Theory · Mathematics 2007-06-13 Randal Douc , Eric Moulines , Tobias Ryden

We solve the generalized Langevin equation driven by a stochastic force with power-law autocorrelation function. A stationary Markov process has been applied as a model of the noise. However, the resulting velocity variance does not…

Statistical Mechanics · Physics 2015-07-22 T. Srokowski

In contrast to their seemingly simple and shared structure of independence and stationarity, L\'evy processes exhibit a wide variety of behaviors, from the self-similar Wiener process to piecewise-constant compound Poisson processes.…

Probability · Mathematics 2024-11-14 Julien Fageot , Alireza Fallah , Thibaut Horel

We consider equations of nonlinear transport on the circle with regular self interactions appearing in aggregation models and deterministic mean field dynamics. We introduce a random perturbation of such systems through a stochastic…

Probability · Mathematics 2026-01-07 Max-K. von Renesse , Feng-Yu Wang , Alexander Weiß

In this paper, a link between monotonicity of deterministic dynamical systems and propagation of order by Markov processes is established. The order propagation has received considerable attention in the literature, however, this notion is…

Optimization and Control · Mathematics 2015-03-10 Aivar Sootla

In this paper, the weak convergence of impulsive recurrent process with Markov switching in the scheme of Levy approximation is proved. For the relative compactness, a method proposed by R. Liptser for semimartingales is used with a…

Probability · Mathematics 2009-11-03 V. S. Koroliuk , N. Limnios , I. V. Samoilenko

A refracted L\'evy process is a L\'evy process whose dynamics change by subtracting off a fixed linear drift (of suitable size) whenever the aggregate process is above a pre-specified level. More precisely, whenever it exists, a refracted…

Probability · Mathematics 2012-05-04 Andreas E. Kyprianou , J. C. Pardo , J. L. Pérez

Strongly continuous semigroups of unital completely positive maps (i.e. quantum Markov semigroups or quantum dynamical semigroups) on compact quantum groups are studied. We show that quantum Markov semigroups on the universal or reduced…

Operator Algebras · Mathematics 2014-02-18 Fabio Cipriani , Uwe Franz , Anna Kula

We prove the well-posedness of some non-linear stochastic differential equations in the sense of McKean-Vlasov driven by non-degenerate symmetric $\alpha$-stable L\'evy processes with values in $R^d$ under some mild H{\"o}lder regularity…

Analysis of PDEs · Mathematics 2019-10-15 Noufel Frikha , Valentin Konakov , Stéphane Menozzi

The stochastic properties of a Langevin-type Markov process can be extracted from a given time series by a Markov analysis. Also processes that obey a stochastically forced second order differential equation can be analyzed this way by…

Data Analysis, Statistics and Probability · Physics 2014-12-09 Bernd Lehle , Joachim Peinke

We show that the product or convex combination of two Markov operators with equivalent stationary measures need not have a stationary measure from the same measure class. More specifically, we exhibit examples of a hitherto undescribed…

Dynamical Systems · Mathematics 2025-03-14 Behrang Forghani , Vadim Kaimanovich

This article is devoted to some time-changed stochastic models based on multivariate stable processes. The considered models have several advantages in comparison with classical time-changed Brownian motions - for instance, it turns out…

Probability · Mathematics 2018-06-12 V. Panov , E. Samarin

We introduce a model with diffusive and evaporation/condensation processes, depending on 3 parameters obeying some inequalities. The model can be solved in the sense that all correlation functions can be computed exactly without the use of…

Statistical Mechanics · Physics 2023-10-23 F. Mathieu , E. Ragoucy

We establish the functional convex order results for two scaled McKean-Vlasov processes $X=(X_{t})_{t\in[0, T]}$ and $Y=(Y_{t})_{t\in[0, T]}$ defined on a filtered probability space $(\Omega, \mathcal{F}, (\mathcal{F}_{t})_{t\geq0},…

Probability · Mathematics 2022-01-06 Yating Liu , Gilles Pagès