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Free energy profiles serve as a fundamental bridge between microscopic atomic fluctuations and macroscopic thermodynamic observables. Estimating the free energy profile along a reaction coordinate, referred to as the potential of mean force…

Free energy perturbation (FEP) was proposed by Zwanzig more than six decades ago as a method to estimate free energy differences, and has since inspired a huge body of related methods that use it as an integral building block. Being an…

A myriad of applications ranging from engineering and scientific simulations, image and signal processing as well as high-sensitive data retrieval demand high processing power reaching up to teraflops for their efficient execution. While a…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-02 Patrick Mukala

We derive the optimal estimates of the free energies of an arbitrary number of thermodynamic states from nonequilibrium work measurements; the work data are collected from forward and reverse switching processes and obey a fluctuation…

Statistical Mechanics · Physics 2009-11-11 Paul Maragakis , Martin Spichty , Martin Karplus

This paper considers multiple binary hypothesis tests with adaptive allocation of sensing resources from a shared budget over a small number of stages. A Bayesian formulation is provided for the multistage allocation problem of minimizing…

Methodology · Statistics 2014-11-05 Dennis Wei

Starting from a classical Budyko-Sellers-Ghil energy balance model for the average surface temperature of the Earth, a nonautonomous version is designed by allowing the solar irradiance and the cloud cover coefficients to vary with time in…

Atmospheric and Oceanic Physics · Physics 2025-11-25 Iacopo P. Longo , Rafael Obaya , Ana M. Sanz

Calibrating simulation models that take large quantities of multi-dimensional data as input is a hard simulation optimization problem. Existing adaptive sampling strategies offer a methodological solution. However, they may not sufficiently…

Methodology · Statistics 2024-07-17 Pranav Jain , Sara Shashaani , Eunshin Byon

Estimating free energy differences, an important problem in computational drug discovery and in a wide range of other application areas, commonly involves a computationally intensive process of sampling a family of high-dimensional…

In this article, we propose a data-driven methodology for combining the solutions of a set of competing turbulence models. The individual model predictions are linearly combined for providing an ensemble solution accompanied by estimates of…

Fluid Dynamics · Physics 2023-01-24 Maximilien de Zordo-Banliat , Grégory Dergham , Xavier Merle , Paola Cinnella

We devise automated workflows for the calculation of Helmholtz and Gibbs free energies and their temperature and pressure dependence and provide the corresponding computational tools. We employ non-equilibrium thermodynamics for evaluating…

Materials Science · Physics 2021-10-13 Sarath Menon , Yury Lysogorskiy , Jutta Rogal , Ralf Drautz

This article describes nonequilibrium techniques for the calculation of free energies of solids using molecular dynamics (MD) simulations. These methods provide an alternative to standard equilibrium thermodynamic integration methods and…

Materials Science · Physics 2022-01-13 Rodrigo Freitas , Mark Asta , Maurice de Koning

Adaptive precision molecular dynamics simulations have developed along energy- and force-coupling approaches, which allow for a continuous transition between different particle descriptions or interaction potentials. Most approaches…

Computational Physics · Physics 2025-12-09 David Immel , Ralf Drautz , Godehard Sutmann

The growing number of wireless edge devices has magnified challenges concerning energy, bandwidth, latency, and data heterogeneity. These challenges have become bottlenecks for distributed learning. To address these issues, this paper…

Machine Learning · Computer Science 2023-12-25 Mohamed Badi , Chaouki Ben Issaid , Anis Elgabli , Mehdi Bennis

Federated learning (FL) enables multiple clients to collaboratively train a machine learning model without sharing their raw data. However, the limited computation resources of the clients may result in a high delay and energy consumption…

Machine Learning · Computer Science 2026-03-06 Chuiyang Meng , Ming Tang , Vincent W. S. Wong

Adaptation is used by biological sensory systems to respond to a wide range of environmental signals, by adapting their response properties to the statistics of the stimulus in order to maximize information transmission. We derive rules of…

Neurons and Cognition · Quantitative Biology 2021-04-14 Daniele Conti , Thierry Mora

Algorithms which compute locally optimal continuous designs often rely on a finite design space or on repeatedly solving a complex non-linear program. Both methods require extensive evaluations of the Jacobian Df of the underlying model.…

Methodology · Statistics 2021-01-18 Philipp Seufert , Jan Schwientek , Michael Bortz

Data centers play an increasingly critical role in societal digitalization, yet their rapidly growing energy demand poses significant challenges for sustainable operation. To enhance the energy efficiency of geographically distributed data…

Systems and Control · Electrical Eng. & Systems 2025-12-16 Junhong Liu , Lanxin Du , Yujia Li , Rong-Peng Liu , Yunfeng Li , Fei Teng , Francis Yunhe Hou

Performing alchemical transformations, in which one molecular system is nonphysically changed to another system, is a popular approach adopted in performing free energy calculations associated with various biophysical processes, such as…

Statistical Mechanics · Physics 2023-12-15 Wei-Tse Hsu , Valerio Piomponi , Pascal T. Merz , Giovanni Bussi , Michael R. Shirts

We review a selection of methods for performing enhanced sampling in molecular dynamics simulations. We consider methods based on collective variable biasing and on tempering, and offer both historical and contemporary perspectives. In…

Statistical Mechanics · Physics 2014-01-03 Cameron Abrams , Giovanni Bussi

In conventional well-known derivation methods for the adaptive Thouless-Anderson-Palmer (TAP) free energy, special assumptions that are difficult to mathematically justify except in some mean-field models, must be made. Here, we present a…

Disordered Systems and Neural Networks · Physics 2018-05-14 Muneki Yasuda , Chako Takahashi , Kazuyuki Tanaka
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