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Linear Response theory aims to predict how added forcing alters the statistical properties of an unforced system. These kinds of questions have been studied predominantly for autonomous dynamical systems, yet many systems in the physical,…

Dynamical Systems · Mathematics 2026-04-07 Stefano Galatolo , Valerio Lucarini

Linear response theory lies at the foundation of transport phenomena, predicting that physical systems respond proportionally to weak external forces. Here we show that this principle can break down in a minimal nonequilibrium setting due…

Statistical Mechanics · Physics 2026-03-17 Yuto Takeishi , Takuma Akimoto

Synthetic augmentation is increasingly used to mitigate data scarcity in financial machine learning, yet its statistical role remains poorly understood. We formalize synthetic augmentation as a modification of the effective training…

Artificial Intelligence · Computer Science 2026-04-17 Mel Sohm , Charles Dezons , Sami Sellami , Oscar Ninou , Axel Pincon

We present a method to compute transport coefficients in molecular dynamics. Transport coefficients quantify the linear dependencies of fluxes in non-equilibrium systems subject to small external forcings. Whereas standard non-equilibrium…

Statistical Mechanics · Physics 2023-05-17 Noé Blassel , Gabriel Stoltz

Stochastic resonance (SR) is a prominent phenomenon in many natural and engineered noisy system, whereby the response to a periodic forcing is greatly amplified when the intensity of the noise is tuned to within a specific range of values.…

Statistical Mechanics · Physics 2019-12-25 Valerio Lucarini

In this work we perform rigorous small noise expansions to study the impact of stochastic forcing on the behaviour of planar travelling wave solutions to reaction-diffusion equations on cylindrical domains. In particular, we use a…

Analysis of PDEs · Mathematics 2025-02-05 Mark van den Bosch , Christian H. S. Hamster , Hermen Jan Hupkes

The question of deriving general force/flux relationships that apply out of the linear response regime is a central topic of theories for nonequilibrium statistical mechanics. This work applies an information theory perspective to compute…

Statistical Mechanics · Physics 2019-02-04 David M. Rogers

A general theory for computing information transfers in nonlinear stochastic systems driven by deterministic forcing and additive and/or multiplicative noises, is presented. It extends the Liang-Kleeman framework of causality inference to…

Chaotic Dynamics · Physics 2023-10-12 Carlos A. Pires , David Docquier , Stéphane Vannitsem

We derive simplified formulas for analyzing the stability of stochastic parametrically forced linear systems. This extends the results in [T. Blass and L.A. Romero, SIAM J. Control Optim. 51(2):1099--1127, 2013] where, assuming the…

Dynamical Systems · Mathematics 2014-02-05 Timothy Blass , L. A. Romero , J. R. Torczynski

The goal of response theory, in each of its many statistical mechanical formulations, is to predict the perturbed response of a system from the knowledge of the unperturbed state and of the applied perturbation. A new recent angle on the…

Chaotic Dynamics · Physics 2023-08-02 Umberto Maria Tomasini , Valerio Lucarini

In this Note, we describe the stationary equilibria and the asymptotic behaviour of an heterogeneous logistic reaction-diffusion equation under the influence of autonomous or time-periodic forcing terms. We show that the study of the…

Analysis of PDEs · Mathematics 2010-06-15 Mickaël D. Chekroun , Lionel Roques

Nonlinear response occurs naturally when a strong perturbation takes a system far from equilibrium. Despite of its omnipresence in nanoscale systems, it is difficult to predict in a general and efficient way. Here we introduce a way to…

Statistical Mechanics · Physics 2019-07-24 Chloe Ya Gao , David T. Limmer

The rapid advancement of generative models, such as Stable Diffusion, raises a key question: how can synthetic data from these models enhance predictive modeling? While they can generate vast amounts of datasets, only a subset meaningfully…

Machine Learning · Statistics 2025-05-09 Jialong Jiang , Wenkang Hu , Jian Huang , Yuling Jiao , Xu Liu

Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used to interpret experiments and shed light on microscopic…

Statistical Mechanics · Physics 2024-06-24 Jérémie Klinger , Grant M. Rotskoff

The transport phenomena of a nonequilibrium lattice gas system are investigated. We consider a simple system that consists of two particles interacting repulsively and the potential forces acting on these particles. Under an external…

Soft Condensed Matter · Physics 2009-11-11 Akinori Awazu

Linear response theory has developed into a formidable set of tools for studying the forced behaviour of a large variety of systems - including out of equilibrium ones. In this paper we provide a new angle on the problem, by studying under…

Statistical Mechanics · Physics 2018-10-17 Valerio Lucarini

We investigate the incremental stability properties of It\^o stochastic dynamical systems. Specifically, we derive a stochastic version of nonlinear contraction theory that provides a bound on the mean square distance between any two…

Optimization and Control · Mathematics 2011-11-09 Q. -C. Pham , N. Tabareau , J. -J. Slotine

The response of a nonlinear stochastic system driven by an external sinusoidal time dependent force is studied by a variety of numerical and analytical approximations. The validity of linear response theory is put to a critical test by…

Statistical Mechanics · Physics 2009-11-07 J. Casado-Pascual , J. Gómez-Ordóñez , M. Morillo , P. Hänggi

Synthetic data describing coherent random fluctuations have widely been used to validate numerical sim- ulations against experimental observations or to examine the reliability of extracting statistical properties of plasma turbulence via…

Plasma Physics · Physics 2016-06-22 Jaewook Kim , M. F. J. Fox , A. R. Field , Y. U. Nam , Y. -c. Ghim

This paper extends the literature on the theoretical properties of synthetic controls to the case of non-linear generative models, showing that the synthetic control estimator is generally biased in such settings. I derive a lower bound for…

Econometrics · Economics 2021-11-23 Oscar Engelbrektson
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