English
Related papers

Related papers: Dissipative timescales from coarse-graining irreve…

200 papers

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

We examine an analytic variational inference scheme for the Gaussian Process State Space Model (GPSSM) - a probabilistic model for system identification and time-series modelling. Our approach performs variational inference over both the…

Machine Learning · Statistics 2018-12-11 Alessandro Davide Ialongo , Mark van der Wilk , Carl Edward Rasmussen

We derive a variational expression for the correlation time of physical observables in steady-state diffusive systems. As a consequence of this variational expression, we obtain lower bounds on the correlation time, which provide speed…

Statistical Mechanics · Physics 2023-03-24 Andreas Dechant , Jerome Garnier-Brun , Shin-ichi Sasa

Near equilibrium, the symmetric part of the time-integrated steady-state covariance, i.e., the time integral of correlation functions, is governed by the fluctuation-dissipation theorem, while the antisymmetric part vanishes due to Onsager…

Statistical Mechanics · Physics 2026-03-10 Timur Aslyamov , Massimiliano Esposito

We introduce a scalable approach to Gaussian process inference that combines spatio-temporal filtering with natural gradient variational inference, resulting in a non-conjugate GP method for multivariate data that scales linearly with…

Machine Learning · Computer Science 2021-11-03 Oliver Hamelijnck , William J. Wilkinson , Niki A. Loppi , Arno Solin , Theodoros Damoulas

A scheme is developed for estimating state-dependent drift and diffusion coefficients in a stochastic differential equation from time-series data. The scheme does not require to specify parametric forms for the drift and diffusion…

Biological Physics · Physics 2012-09-28 Jun Ohkubo

It is known that a finite-size homogeneous granular fluid develops an hydrodynamic-like instability when dissipation crosses a threshold value. This instability is analyzed in terms of modified hydrodynamic equations: first, a source term…

Statistical Mechanics · Physics 2009-10-31 R. Soto , M. Mareschal , M. Malek Mansour

We introduce a single generative mechanism with which it is able to describe diverse non-stationary diffusions. A non-stationary Markovian replication process for steps is considered, for which we analytically derive time-evolution of the…

Statistical Mechanics · Physics 2017-10-25 Yichul Choi , Hyun-Joo Kim

Fluctuation theorems show how coarse graining transforms microscopic symmetry into observable irreversibility. Here we ask whether an analogous symmetrybased diagnostic can be constructed for financial markets. At the microscopic level,…

Statistical Mechanics · Physics 2026-04-17 Jian Gao , Lufeng Zhang , Ping Fang , Pu Ke , Jin Wu , Yue Liu , Haijun Zhou

Energy dissipation is highly intermittent in turbulent plasmas, being localized in coherent structures such as current sheets. The statistical analysis of spatial dissipative structures is an effective approach to studying turbulence. In…

High Energy Astrophysical Phenomena · Physics 2015-09-16 Vladimir Zhdankin , Dmitri A. Uzdensky , Stanislav Boldyrev

A directed dissipative sandpile model is studied in the two-dimension. Numerical results indicate that the long time steady states of this model are critical when grains are dropped only at the top or, everywhere. The critical behaviour is…

Soft Condensed Matter · Physics 2009-10-31 S. S. Manna , A. D. Chakrabarti , R. Cafiero

A fundamental question in nonequilibrium statistical physics is whether effective equilibrium behavior can emerge at coarse-grained scales in strongly driven systems. Here, we investigate this question in the context of human mobility by…

Physics and Society · Physics 2026-03-24 Lei Dong

This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend…

Econometrics · Economics 2022-11-23 Francesco Giancaterini , Alain Hecq , Claudio Morana

We investigate non-equilibrium behavior of driven dissipative systems, using the model presented in [Phys. Rev. Lett. 93, 240601 (2004)]. We solve the non-Boltzmann steady state energy distribution and the temporal evolution to it, and find…

Statistical Mechanics · Physics 2007-05-23 Yair Shokef , Dov Levine

Lumping a Markov process introduces a coarser level of description that is useful in many contexts and applications. The dynamics on the coarse grained states is often approximated by its Markovian component. In this letter we derive…

Statistical Mechanics · Physics 2012-07-31 David Andrieux

In the copula-based approach to univariate time series modeling, the finite dimensional temporal dependence of a stationary time series is captured by a copula. Recent studies investigate how copula-based time series models can be…

Methodology · Statistics 2026-04-03 Sven Pappert , Harry Joe

Time crystals are a nonequilibrium phase of matter that extend fundamental spontaneous symmetry breaking into the temporal dimension, typically requiring external driving for their realization. Here, we explore the nonequilibrium phase…

Quantum Physics · Physics 2025-05-13 Shu Yang , Zeqing Wang , Libin Fu , Jianwen Jie

Thermodynamic irreversibility is a crucial property of living matter. Irreversible processes maintain spatiotemporally complex structures and functions characteristic of living systems. In high-dimensional biological dynamics, robust and…

Statistical Mechanics · Physics 2023-09-20 Junang Li , Chih-Wei Joshua Liu , Michal Szurek , Nikta Fakhri

This work extends the results of the recently developed theory of a rather complete thermodynamic formalism for discrete-state, continuous-time Markov processes with and without detailed balance. We aim at investigating the question that…

Statistical Mechanics · Physics 2011-05-30 Moises Santillan , Hong Qian

We study statistical inferences for a class of modulated stationary processes with time-dependent variances. Due to non-stationarity and the large number of unknown parameters, existing methods for stationary, or locally stationary, time…

Statistics Theory · Mathematics 2013-02-04 Zhibiao Zhao , Xiaoye Li