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Starting from a master equation in a quantum Hamiltonian form and a coupling to a heat bath we derive an evolution equation for a collective hopping process under the influence of a stochastic energy landscape. There results different…

Statistical Mechanics · Physics 2009-10-31 Michael Schulz , Steffen Trimper

We describe the processes obtained by time reversal of a class of stationary jump-diffusion processes that model the dynamics of genetic variation in populations subject to repeated bottlenecks. Assuming that only one lineage survives each…

Probability · Mathematics 2020-11-25 Martin Hutzenthaler , Jesse E. Taylor

We introduce the mathematical theory of the particle systems that interact via permutations, where the transition rates are assigned not to the jumps from a site to a site, but to the permutations themselves. This permutation processes can…

Probability · Mathematics 2007-05-23 Yevgeniy Kovchegov

We study the optimal financing and dividend distribution problem with restricted dividend rates in a diffusion type surplus model where the drift and volatility coefficients are general functions of the level of surplus and the external…

Optimization and Control · Mathematics 2015-06-30 Jinxia Zhu , Hailiang Yang

In this paper, we study the asymptotic of exit problem for controlled Markov diffusion processes with random jumps and vanishing diffusion terms, where the random jumps are introduced in order to modify the evolution of the controlled…

Dynamical Systems · Mathematics 2018-02-08 Getachew K. Befekadu

This paper is concerned with the optimal control of hysteresis-reaction-diffusion systems. We study a control problem with two sorts of controls, namely distributed control functions, or controls which act on a part of the boundary of the…

Optimization and Control · Mathematics 2017-06-01 Christian Münch

In this paper, we proved moderate deviation principles for a fully coupled two-time-scale stochastic systems, where the slow process is given by stochastic differential equations with small noise, while the fast process is a rapidly…

Probability · Mathematics 2025-12-02 Hongjiang Qian

We report the results of calculation of diffusion coefficients for Lennard-Jones liquids, based on the idea of time-scale invariance of relaxation processes in liquids. The results were compared with the molecular dynamics data for…

Disordered Systems and Neural Networks · Physics 2007-05-23 Renat M. Yulmetyev , Anatolii V. Mokshin , Peter Hänggi

We study the existence theory for parabolic variational inequalities in weighted $L^2$ spaces with respect to excessive measures associated with a transition semigroup. We characterize the value function of optimal stopping problems for…

Analysis of PDEs · Mathematics 2011-11-09 Viorel Barbu , Carlo Marinelli

The article presents a novel variational calculus to analyze the stability and the propagation of chaos properties of nonlinear and interacting diffusions. This differential methodology combines gradient flow estimates with backward…

Probability · Mathematics 2019-01-30 Marc Arnaudon , Pierre Del Moral

Demixing of binary fluids subjected to slow temperature ramps shows repeated waves of nucleation which arise as a consequence of the competition between generation of supersaturation by the temperature ramp and relaxation of supersaturation…

Statistical Mechanics · Physics 2012-10-16 Izabella J. Benczik , Jürgen Vollmer

Reaction-diffusion processes are the foundational model for a diverse range of complex systems, ranging from biochemical reactions to social agent-based phenomena. The underlying dynamics of these systems occur at the individual…

Statistical Mechanics · Physics 2025-10-15 Mauricio J. del Razo , Margarita Kostré

A novel principle is presented which allows for the proof of bounded weak solutions to a class of physically relevant, strongly coupled parabolic systems exhibiting a formal gradient-flow structure. The main feature of these systems is that…

Analysis of PDEs · Mathematics 2015-06-11 Ansgar Jüngel

We give an account of matter and (basically) a solution of a new class of problems synthesizing percolation theory and branching diffusion processes. They led us to realizing a novel type of stochastic processes, namely branching processes…

Condensed Matter · Physics 2011-12-08 A. Mezhlumian , S. A. Molchanov

The log-Harnack inequality and Harnack inequality with powers for semigroups associated to SDEs with non-degenerate diffusion coefficient and non-regular time-dependent drift coefficient are established, based on the recent papers…

Probability · Mathematics 2014-04-15 Huaiqian Li , Dejun Luo , Jian Wang

In this paper, we study optimal stochastic control problems for stochastic systems driven by non-Markov sub-diffusion $B_{L_t}$, which have the mixed features of deterministic and stochastic controls. Here $B_t$ is the standard Brownian…

Probability · Mathematics 2023-11-28 Shuaiqi Zhang , Zhen-Qing Chen

Stochastic differential equations (SDEs) using jump-diffusion processes describe many natural phenomena at the microscopic level. Since they are commonly used to model economic and financial evolutions, the calibration and optimal control…

Optimization and Control · Mathematics 2025-05-08 Jan Bartsch , Alfio Borzi , Gabriele Ciaramella , Jan Reichle

We prove convergence of the proximal policy gradient method for a class of constrained stochastic control problems with control in both the drift and diffusion of the state process. The problem requires either the running or terminal cost…

Optimization and Control · Mathematics 2025-05-27 Ashley Davey , Harry Zheng

In this paper, we study a stochastically driven non-equilibrium quantum system where the driving protocols consist of hopping and waiting processes. The waiting times between two hopping processes satisfy a heavy-tailed distribution. By…

Strongly Correlated Electrons · Physics 2025-01-13 Chenyue Guo , Yuchen Bi

Point processes model the distribution of random point sets in mathematical spaces, such as spatial and temporal domains, with applications in fields like seismology, neuroscience, and economics. Existing statistical and machine learning…

Machine Learning · Computer Science 2024-10-31 David Lüdke , Enric Rabasseda Raventós , Marcel Kollovieh , Stephan Günnemann