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A concise and self-contained derivation of hybrid quantum-classical dynamics is given in terms of Markovian master equations. Many previously known results are re-derived, revised, some of them completed or corrected. Using as simple method…

Quantum Physics · Physics 2024-10-23 Lajos Diósi

We analyze a specific class of random systems that are driven by a symmetric L\'{e}vy stable noise. In view of the L\'{e}vy noise sensitivity to the confining "potential landscape" where jumps take place (in other words, to environmental…

Statistical Mechanics · Physics 2015-06-11 M. Zaba , P. Garbaczewski , V. Stephanovich

A biological competition model where the individuals of the same species perform a two-dimensional Markovian continuous-time random walk and undergo reproduction and death is studied. The competition is introduced through the assumption…

Biological Physics · Physics 2011-08-31 E. Heinsalu , E. Hernandez-Garcia , C. Lopez

We solve exactly the non-equilibrium dynamics of two discrete random walkers moving in channels with transition rates $p \neq q$ that swap positions at a rate $s$. We compute exactly the joint probability distribution $P_{n,m}(t)$ for the…

Statistical Mechanics · Physics 2025-09-12 José Julian Díaz-Pérez , R. Mulet

The escape probability is a deterministic concept that quantifies some aspects of stochastic dynamics. This issue has been investigated previously for dynamical systems driven by Gaussian Brownian motions. The present work considers escape…

Dynamical Systems · Mathematics 2012-05-15 Huijie Qiao , Xingye Kan , Jinqiao Duan

We study three classes of continuous time Markov processes (inclusion process, exclusion process, independent walkers) and a family of interacting diffusions (Brownian energy process). For each model we define a boundary driven process…

Mathematical Physics · Physics 2015-06-12 Gioia Carinci , Cristian Giardina' , Claudio Giberti , Frank Redig

Quantum trajectories of a Markovian open quantum system arise from the back-action of measurements performed in the environment with which the system interacts. In this work, we consider counting measurements of quantum jumps, corresponding…

Quantum Physics · Physics 2025-07-23 Calum A. Brown , Katarzyna Macieszczak , Robert L. Jack

It is shown that non-Markovian master equations for an open system which are local in time can be unravelled through a piecewise deterministic quantum jump process in its Hilbert space. We derive a stochastic Schr\"odinger equation that…

Quantum Physics · Physics 2009-11-13 Heinz-Peter Breuer , Jyrki Piilo

Diffusive approximations of Markov jump processes often fail to accurately capture large fluctuations. This is confounding, as the rare events triggered by these large fluctuations, such as the failure of electronic memories, are often the…

Mesoscale and Nanoscale Physics · Physics 2025-12-17 David Roberts , Trevor McCourt , Geremia Massarelli , Jeremy Rothschild , Nahuel Freitas

In complex systems, the interplay between nonlinear and stochastic dynamics, e.g., J. Monod's necessity and chance, gives rise to an evolutionary process in Darwinian sense, in terms of discrete jumps among attractors, with punctuated…

Adaptation and Self-Organizing Systems · Physics 2013-03-18 Hong Qian

Spatial birth-and-death processes with a finite number of particles are obtained as unique solutions to certain stochastic equations. Conditions are given for existence and uniqueness of such solutions, as well as for continuous dependence…

Probability · Mathematics 2015-02-25 Viktor Bezborodov

In this paper, we consider a stochastic differential equation driven by a fractional Brownian motion (fBm) and a Wiener process and having jumps. We prove that this equation has a unique solution and show that all its moments are finite.

Probability · Mathematics 2013-04-02 Georgiy Shevchenko

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability…

Statistical Mechanics · Physics 2018-11-26 V. Sposini , A. V. Chechkin , F. Seno , G. Pagnini , R. Metzler

In this paper, we propose a novel stochastic process that serves as a natural discrete-time counterpart to the continuous-time model known as the ``Poisson hyperbolic staircase'' proposed by Levikson et al. (1999), and clarify its…

Probability · Mathematics 2026-04-27 Naohiro Yoshida

This paper is concerned with one kind of partially observed progressive optimal control problems of coupled forward-backward stochastic systems driven by both Brownian motion and Poisson random measure with risk-sensitive criteria. The…

Optimization and Control · Mathematics 2025-04-08 Jingtao Lin , Jingtao Shi

Einstein-Smoluchowski diffusion, damped harmonic oscillations, and spatial decoherence are special cases of an elegant class of Markovian quantum Brownian motion models that is invariant under linear symplectic transformations. Here we…

Quantum Physics · Physics 2016-02-04 C. Jess Riedel

We consider Markovian dynamics of a finitely dimensional open quantum system featuring a weak unitary symmetry, i.e., when the action of a unitary symmetry on the space of density matrices commutes with the master operator governing the…

Quantum Physics · Physics 2021-04-08 Katarzyna Macieszczak , Dominic C. Rose

In this paper we give general criteria on tightness and weak convergence of discrete Markov chains to symmetric jump processes on metric measure spaces under mild conditions. As an application, we investigate discrete approximation for a…

Probability · Mathematics 2010-09-01 Zhen-Qing Chen , Panki Kim , Takashi Kumagai

We study a system of $N$ interacting particles on $\bf{Z}$. The stochastic dynamics consists of two components: a free motion of each particle (independent random walks) and a pair-wise interaction between particles. The interaction belongs…

Probability · Mathematics 2011-10-25 A. Manita , V. Shcherbakov

Existing theory of momentum assumes that gradients arrive at every parameter at a roughly constant rate, an assumption violated in practice by heavy-tailed data distributions and modern architectures. We theoretically analyze the dynamics…

Machine Learning · Statistics 2026-05-29 Katie Everett , Elliot Paquette