English
Related papers

Related papers: Escorted Free Energy Simulations: Improving Conver…

200 papers

For systems in equilibrium at a temperature $T$, thermal noise and energy damping are related to $T$ through the fluctuation-dissipation theorem (FDT). We study here an extension of the FDT to an out of equilibrium steady state: a…

Statistical Mechanics · Physics 2023-03-23 Alex Fontana , Ludovic Bellon

Many enhanced sampling techniques rely on the identification of a number of collective variables that describe all the slow modes of the system. By constructing a bias potential in this reduced space one is then able to sample efficiently…

Computational Physics · Physics 2019-03-05 Michele Invernizzi , Michele Parrinello

Sampling the free energy surface, namely, the distribution of collective variables (CVs), is a crucial problem in statistical physics, as it underpins a better understanding of chemical reactions and conformational transitions. Traditional…

Machine Learning · Computer Science 2026-05-04 Zichen Liu , Tiejun Li

A fluid in a non-equilibrium state exhibits long-ranged correlations of its hydrodynamic fluctuations. In this article, we examine the effect of a transpiration interface on these correlations -- specifically, we consider a dilute gas in a…

Statistical Mechanics · Physics 2020-05-11 Daniel R. Ladiges , Andrew J. Nonaka , John B. Bell , Alejandro L. Garcia

Complex systems can convert energy imparted by nonequilibrium forces to regulate how quickly they transition between long lived states. While such behavior is ubiquitous in natural and synthetic systems, currently there is no general…

Statistical Mechanics · Physics 2021-04-28 Benjamin Kuznets-Speck , David T. Limmer

Sampling the Boltzmann distribution using forces that violate detailed balance can be faster than with the equilibrium evolution, but the acceleration depends on the nature of the nonequilibrium drive and the physical situation. Here, we…

Soft Condensed Matter · Physics 2023-12-20 Federico Ghimenti , Ludovic Berthier , Grzegorz Szamel , Frédéric van Wijland

Scene flow estimation is an essential ingredient for a variety of real-world applications, especially for autonomous agents, such as self-driving cars and robots. While recent scene flow estimation approaches achieve a reasonable accuracy,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-07 Yushan Zhang , Bastian Wandt , Maria Magnusson , Michael Felsberg

Drift-diffusion plasma fluid models are commonly used to simulate electric discharges. Such models can computationally be very efficient if they are combined with explicit time integration. This paper deals with two issues that often arise…

Computational Physics · Physics 2020-02-19 Jannis Teunissen

The problem of transient hysteresis cycles induced by the pre-sliding kinetic friction is relevant for analyzing the system dynamics e.g. of micro- and nano-positioning instruments and devices and their controlled operation. The associated…

Systems and Control · Electrical Eng. & Systems 2023-10-03 Michael Ruderman

In real-time applications involving power flow equations, measuring of voltage phase angle difference of the connected buses is essential. However, it needs special techniques to measure voltage angle difference, which may enlarge the…

Signal Processing · Electrical Eng. & Systems 2018-06-21 Irfan Khan , Vikram Bhattacharjee

The excess work required to drive a stochastic system out of thermodynamic equilibrium through a time-dependent external perturbation is directly related to the amount of entropy produced during the driving process, allowing excess work and…

Statistical Mechanics · Physics 2021-03-15 Steven J Large , Jannik Ehrich , David A Sivak

We present a methodology for accelerating the estimation of the free energy from path integral Monte Carlo simulations by considering an intermediate artificial reference system where interactions are inexpensive to evaluate numerically.…

In small systems where relevant energies are comparable to thermal agitation, fluctuations are of the order of average values. In systems in thermodynamical equilibrium, the variance of these fluctuations can be related to the dissipation…

Statistical Mechanics · Physics 2007-05-23 Nicolas Garnier , Ciliberto Sergio

Data assimilation (DA) estimates a dynamical system's state from noisy observations. Recent generative models like the ensemble score filter (EnSF) improve DA in high-dimensional nonlinear settings but are computationally expensive. We…

Machine Learning · Statistics 2025-09-30 Taos Transue , Bohan Chen , So Takao , Bao Wang

Consider a polynomial optimisation problem, whose instances vary continuously over time. We propose to use a coordinate-descent algorithm for solving such time-varying optimisation problems. In particular, we focus on relaxations of…

Optimization and Control · Mathematics 2019-09-24 Jie Liu , Jakub Marecek , Andrea Simonetto , Martin Takac

Standard diffuse approximations of the Willmore flow often lead to intersecting phase boundaries that in many cases do not correspond to the intended sharp interface evolution. Here we introduce a new two-variable diffuse approximation that…

Analysis of PDEs · Mathematics 2019-11-01 Andreas Rätz , Matthias Röger

Jarzynski's identity for the free energy difference between two equilibrium states can be viewed as a special case of a more general procedure based on phase space mappings. Solving a system's equation of motion by approximate means…

Statistical Mechanics · Physics 2009-11-11 Wolfgang Lechner , Harald Oberhofer , Christoph Dellago , Phillip L. Geissler

In recent years, the dissipating energy flow (DEF) method has emerged as a promising tool for online localization of oscillation sources. In literature, the mathematical foundations of this method are well-studied for networks with…

Systems and Control · Electrical Eng. & Systems 2021-11-23 Kaustav Chatterjee , Sayan Samanta , Nilanjan Ray Chaudhuri

Consistency models imitate the multi-step sampling of score-based diffusion in a single forward pass of a neural network. They can be learned in two ways: consistency distillation and consistency training. The former relies on the true…

Machine Learning · Computer Science 2025-07-03 Thibaut Issenhuth , Sangchul Lee , Ludovic Dos Santos , Jean-Yves Franceschi , Chansoo Kim , Alain Rakotomamonjy

Systematic inaccuracy is inherent in any computational estimate of a non-linear average, such as the free energy difference (Delta-F) between two states or systems, because of the availability of only a finite number of data values, N. In…

Computational Physics · Physics 2007-05-23 Daniel M. Zuckerman , Thomas B. Woolf