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Using the Feynman-Kac and Cameron-Martin-Girsanov formulas, we obtain a generalized integral fluctuation theorem (GIFT) for discrete jump processes by constructing a time-invariable inner product. The existing discrete IFTs can be derived…

Statistical Mechanics · Physics 2009-06-11 Fei Liu , Yu-Pin Luo , Ming-Chang Huang , Zhong-can Ou-Yang

Modeling transformations between arbitrary data distributions is a fundamental scientific challenge, arising in applications like drug discovery and evolutionary simulation. While flow matching offers a natural framework for this task, its…

Machine Learning · Computer Science 2025-10-09 Shiye Su , Yuhui Zhang , Linqi Zhou , Rajesh Ranganath , Serena Yeung-Levy

We calculate the time-evolution of a discrete-time fragmentation process in which clusters of particles break up and reassemble and move stochastically with size-dependent rates. In the continuous-time limit the process turns into the…

Statistical Mechanics · Physics 2007-05-23 A. Rákos , G. M. Schütz

The stochastic interpolant framework offers a powerful approach for constructing generative models based on ordinary differential equations (ODEs) or stochastic differential equations (SDEs) to transform arbitrary data distributions.…

Machine Learning · Computer Science 2025-07-29 Yuhao Liu , Yu Chen , Rui Hu , Longbo Huang

This paper is concerned with classes of models of stochastic reaction dynamics with time-scales separation. We demonstrate that the existence of the time-scale separation naturally leads to the application of the averaging principle and…

Computational Physics · Physics 2007-05-23 Sergey Plyasunov

We develop an inertial coupling method for modeling the dynamics of point-like 'blob' particles immersed in an incompressible fluid, generalizing previous work for compressible fluids. The coupling consistently includes excess (positive or…

Soft Condensed Matter · Physics 2015-08-06 F. Balboa Usabiaga , R. Delgado-Buscalioni , B. E. Griffith , A. Donev

In this work, we present a new approach to disordered, periodically driven (Floquet) quantum many-body systems based on flow equations. Specifically, we introduce a continuous unitary flow of Floquet operators in an extended Hilbert space,…

Disordered Systems and Neural Networks · Physics 2021-08-11 S. J. Thomson , D. Magano , M. Schiró

Analyzing and controlling system entropy is a powerful tool for regulating predictability of control systems. Applications benefiting from such approaches range from reinforcement learning and data security to human-robot collaboration. In…

Systems and Control · Electrical Eng. & Systems 2026-03-06 Menno van Zutphen , Giannis Delimpaltadakis , Duarte J. Antunes

In order to study the stochastic Markov processes conditioned on a specific value of a time-integrated observable, the concept of ensembles of trajectories has been recently used extensively. In this paper, we consider a generic…

Statistical Mechanics · Physics 2019-02-15 Sara Kaviani , Farhad H. Jafarpour

Stochastic thermodynamics provides the framework to analyze thermodynamic laws and quantities along individual trajectories of small but fully observable systems. If the observable level fails to capture all relevant degrees of freedom,…

Statistical Mechanics · Physics 2024-07-01 Julius Degünther , Jann van der Meer , Udo Seifert

We consider the task of generating discrete-time realisations of a nonlinear multivariate diffusion process satisfying an It\^o stochastic differential equation conditional on an observation taken at a fixed future time-point. Such…

Computation · Statistics 2016-04-26 Gavin A. Whitaker , Andrew Golightly , Richard J. Boys , Chris Sherlock

We introduce an efficient discretization of a novel fractional-order adaptive exponential (FrAdEx) integrate-and-fire model, which is used to study the fractional-order dynamics of neuronal activities. The discretization is based on…

Biological Physics · Physics 2025-11-13 Alexandru Fikl , Aman Jhinga , Eva Kaslik , Argha Mondal

We construct flexible spatio-temporal models through stochastic partial differential equations (SPDEs) where both diffusion and advection can be spatially varying. Computations are done through a Gaussian Markov random field approximation…

Methodology · Statistics 2024-10-29 Martin Outzen Berild , Geir-Arne Fuglstad

Particle smoothing methods are used for inference of stochastic processes based on noisy observations. Typically, the estimation of the marginal posterior distribution given all observations is cumbersome and computational intensive. In…

Machine Learning · Computer Science 2017-05-24 H. -Ch. Ruiz , H. J. Kappen

The generalized totally asymmetric exclusion process (TASEP) [J. Stat. Mech. P05014 (2012)] is an integrable generalization of the TASEP equipped with an interaction, which enhances the clustering of particles. The process interpolates…

Mathematical Physics · Physics 2015-02-24 A. E. Derbyshev , A. M. Povolotsky , V. B. Priezzhev

This paper is concerned with a compositional approach for constructing finite Markov decision processes of interconnected discrete-time stochastic control systems. The proposed approach leverages the interconnection topology and a notion of…

Systems and Control · Computer Science 2017-12-22 Abolfazl Lavaei , Sadegh Soudjani , Majid Zamani

Open quantum systems can display periodic dynamics at the classical level either due to external periodic modulations or to self-pulsing phenomena typically following a Hopf bifurcation. In both cases, the quantum fluctuations around…

Quantum Physics · Physics 2021-02-24 C. Navarrete-Benlloch , R. Garcés , N. Mohseni , G. J. de Valcárcel

"Floquet engineering" - designing band structures "on-demand" through the application of coherent time-periodic drives - has recently emerged as a powerful tool for creating new topological and anomalous phases of matter. In this…

Strongly Correlated Electrons · Physics 2021-09-16 Iliya Esin , Gaurav Kumar Gupta , Erez Berg , Mark S. Rudner , Netanel H. Lindner

The TASEP (totally asymmetric simple exclusion process) is a basic model for an one-dimensional interacting particle system with non-reversible dynamics. Despite the simplicity of the model it shows a very rich and interesting behaviour. In…

Probability · Mathematics 2010-03-30 James Martin , Philipp Schmidt

The computer-assisted modeling of re-entrant production lines, and, in particular, simulation scalability, is attracting a lot of attention due to the importance of such lines in semiconductor manufacturing. Re-entrant flows lead to…

Dynamical Systems · Mathematics 2009-11-11 Y. Zou , I. G. Kevrekidis , D. Armbruster