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Rare events refer to qualitatively unlikely events whose realization can nevertheless have important consequences. Typically, the prediction of the kinetics of these events relies on Arrhenius laws, with exponentially distributed waiting…

Statistical Mechanics · Physics 2025-12-18 Apurba Biswas , Thomas Guérin

From numerical simulations it is known that the barrier-crossing time of a non-Markovian one-dimensional reaction coordinate with a single exponentially decaying memory function exhibits a memory-turnover: for intermediate values of the…

Statistical Mechanics · Physics 2026-01-16 Roland R. Netz

In forecasting problems it is important to know whether or not recent events represent a regime change (low long-term predictive potential), or rather a local manifestation of longer term effects (potentially higher predictive potential).…

Methodology · Statistics 2014-07-09 Timothy Graves , Robert B. Gramacy , Christian Franzke , Nicholas Watkins

The mean first-passage time (MFPT) for a Brownian particle to surmount a potential barrier of height $\Delta U$ is a fundamental quantity governing a wide array of physical and chemical processes. According to the Arrhenius Law, the MFPT…

Statistical Mechanics · Physics 2025-11-24 Vishwajeet Kumar , Ohad Shpielberg , Arnab Pal

In the face of the upcoming 30th anniversary of econophysics, we review our contributions and other related works on the modeling of the long-range memory phenomenon in physical, economic, and other social complex systems. Our group has…

Physics and Society · Physics 2021-08-31 Rytis Kazakevicius , Aleksejus Kononovicius , Bronislovas Kaulakys , Vygintas Gontis

Computing reactive trajectories and free energy (FE) landscapes associated to rare event kinetics is key to understanding the dynamics of complex systems. The analysis of the FE surface on which the underlying dynamics takes place has…

Statistical Mechanics · Physics 2018-12-05 François Sicard

We introduce an asymmetric classical Ginzburg-Landau model in a bounded interval, and study its dynamical behavior when perturbed by weak spatiotemporal noise. The Kramers escape rate from a locally stable state is computed as a function of…

Statistical Mechanics · Physics 2009-11-10 D. L. Stein

We analyse large deviations of time-averaged quantities in stochastic processes with long-range memory, where the dynamics at time t depends itself on the value q_t of the time-averaged quantity. First we consider the elephant random walk…

Statistical Mechanics · Physics 2020-08-05 Robert L. Jack , Rosemary J. Harris

Thermally activated phenomena in physics and chemistry, such as conformational changes in biomolecules, liquid film rupture, or ferromagnetic field reversal, are often associated with exponentially long transition times described by…

Statistical Mechanics · Physics 2024-09-20 Jingbang Liu , James E. Sprittles , Tobias Grafke

Analysis of non-Markovian systems and memory induced phenomena poses an everlasting challenge for physics. As a paradigmatic example we consider a classical Brownian particle of mass $M$ subjected to an external force and exposed to…

Statistical Mechanics · Physics 2024-05-21 Mateusz Wiśniewski , Jerzy Łuczka , Jakub Spiechowicz

The escape rate of a Brownian particle over a potential barrier is accurately described by the Kramers theory. A quantitative theory explicitly taking the activity of Brownian particles into account has been lacking due to the inherently…

Soft Condensed Matter · Physics 2017-02-01 A. Sharma , R. Wittmann , J. M. Brader

The efficient calculation of rare-event kinetics in complex dynamical systems, such as the rate and pathways of ligand dissociation from a protein, is a generally unsolved problem. Markov state models can systematically integrate ensembles…

Chemical Physics · Physics 2016-02-03 Benjamin Trendelkamp-Schroer , Frank Noe

The classical theory of chemical reactions can be understood in terms of diffusive barrier crossing, where the rate of a reaction is determined by the inverse of the mean first passage time (FPT) to cross a free energy barrier. Whenever a…

Statistical Mechanics · Physics 2019-11-22 David Hartich , Aljaz Godec

The mean first-passage time (MFPT) is one standard measure for the reaction time in thermally activated barrier-crossing processes. While the relationship between MFPTs and phenomenological rate coefficients is known for systems that…

Statistical Mechanics · Physics 2024-03-12 Qingyuan Zhou , Roland R. Netz , Benjamin A. Dalton

The probability per unit time for a thermally activated Brownian particle to escape over a potential well is in general well-described by Kramers theory. Kramers showed that the escape time decreases exponentially with increasing barrier…

Statistical Mechanics · Physics 2023-03-22 Iman Abdoli , Hartmut Löwen , Jens-Uwe Sommer , Abhinav Sharma

Extreme events are an important theme in various areas of science because of their typically devastating effects on society and their scientific complexities. The latter is particularly true if the underlying dynamics does not lead to…

Data Analysis, Statistics and Probability · Physics 2015-05-30 Aicko Yves Schumann , Nicholas R. Moloney , Jörn Davidsen

Exotic stochastic processes are shown to emerge in the quantum evolution of complex systems. Using influence function techniques, we consider the dynamics of a system coupled to a chaotic subsystem described through random matrix theory. We…

chao-dyn · Physics 2009-10-31 Dimitri Kusnezov , Aurel Bulgac , Giu Do Dang

Within a density matrix approach for nuclear many--body system, it is derived non--Markovian Langevin equations of motion for nuclear collective parameters, where memory effects are defined by memory time. The developed stochastic approach…

Nuclear Theory · Physics 2021-11-24 V. M. Kolomietz , S. V. Radionov

Extreme events are by nature rare and difficult to predict, yet are often much more important than frequent, typical events. An interesting counterpoint to the prediction of such events is their retrodiction -- given a process in an outlier…

Probability · Mathematics 2022-11-21 Wesley W. Erickson , Daniel A. Steck

Continual learning in artificial neural networks is fundamentally limited by the stability--plasticity dilemma: systems that retain prior knowledge tend to resist acquiring new knowledge, and vice versa. Existing approaches, most notably…

Statistical Mechanics · Physics 2026-04-07 Gunn Kim
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