English
Related papers

Related papers: Comparison of free energy methods for molecular sy…

200 papers

Finding optimal solutions to combinatorial optimization problems is pivotal in both scientific and technological domains, within academic research and industrial applications. A considerable amount of effort has been invested in the…

Statistical Mechanics · Physics 2024-12-13 Zi-Song Shen , Feng Pan , Yao Wang , Yi-Ding Men , Wen-Biao Xu , Man-Hong Yung , Pan Zhang

One reason that free energy difference calculations are notoriously difficult in molecular systems is due to insufficient conformational overlap, or similarity, between the two states or systems of interest. The degree of overlap is…

Biological Physics · Physics 2009-11-11 F. Marty Ytreberg , Daniel M. Zuckerman

This article is concerned with the mathematical analysis of a family of adaptive importance sampling algorithms applied to diffusion processes. These methods, referred to as Adaptive Biasing Potential methods, are designed to efficiently…

Probability · Mathematics 2018-05-10 Michel Benaïm , Charles-Edouard Bréhier

Variational inference in probabilistic graphical models aims to approximate fundamental quantities such as marginal distributions and the partition function. Popular approaches are the Bethe approximation, tree-reweighted, and other types…

Machine Learning · Statistics 2025-02-06 Harald Leisenberger , Franz Pernkopf

Sets of free energy differences are useful for finding the equilibria of chemical reactions, while absolute free energies have little physical meaning. However finding the relative free energy between two macrostates by subtraction of their…

Statistical Mechanics · Physics 2012-11-26 Joshua T. Berryman , Tanja Schilling

Interacting defect systems are ubiquitous in materials under realistic scenarios, yet gaining an atomic-level understanding of these systems from a computational perspective is challenging - it often demands substantial resources due to the…

Materials Science · Physics 2024-03-21 Hao Yu

Sampling a target probability distribution with an unknown normalization constant is a fundamental challenge in computational science and engineering. Recent work shows that algorithms derived by considering gradient flows in the space of…

Machine Learning · Statistics 2024-03-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M Stuart

Excess contributions to the free energy due to interfaces occur for many problems encountered in the statistical physics of condensed matter when coexistence between different phases is possible (e.g. wetting phenomena, nucleation, crystal…

Statistical Mechanics · Physics 2015-05-27 Kurt Binder , Benjamin Block , Subir K. Das , Peter Virnau , David Winter

Flat histogram methods, such as Wang--Landau sampling, provide a means for high-throughput calculation of phase diagrams of atomistic/lattice model systems. Many parallelisation schemes with varying degrees of complexity have been proposed…

Computational Physics · Physics 2026-03-11 Hubert J. Naguszewski , Christopher D. Woodgate , David Quigley

In recent years, the power system research community has seen an explosion of novel methods for formulating and solving power network optimization problems. These emerging methods range from new power flow approximations, which go beyond…

Optimization and Control · Mathematics 2018-03-14 Carleton Coffrin , Russell Bent , Kaarthik Sundar , Yeesian Ng , Miles Lubin

Sampling molecular conformations from the Boltzmann distribution is essential for computational chemistry, but iterative diffusion methods are prohibitively slow. Drifting Models offer one-step generation, yet their equilibrium matches the…

Chemical Physics · Physics 2026-03-09 Pipi Hu

Due to the time scale problem, rare events are not accessible by straight forward molecular dynamics. The presence of multiple reaction channels complicates the problem even further. The feasibility of the standard free energy based methods…

Statistical Mechanics · Physics 2009-11-13 Titus S. van Erp

Wang-Landau sampling (WLS) of large systems requires dividing the energy range into "windows" and joining the results of simulations in each window. The resulting density of states (and associated thermodynamic functions) are shown to…

Statistical Mechanics · Physics 2009-11-13 A. G. Cunha-Netto , A. A. Caparica , Shan-Ho Tsai , Ronald Dickman , D. P. Landau

The biological functions of proteins often depend on dynamic structural ensembles. In this work, we develop a flow-based generative modeling approach for learning and sampling the conformational landscapes of proteins. We repurpose highly…

Biomolecules · Quantitative Biology 2024-09-04 Bowen Jing , Bonnie Berger , Tommi Jaakkola

Target-oriented discovery under limited evaluation budgets requires making reliable progress in high-dimensional, heterogeneous design spaces where each new measurement is costly, whether experimental or high-fidelity simulation. We present…

Machine Learning · Computer Science 2026-02-04 Yixuan Zhang , Zhiyuan Li , Weijia He , Mian Dai , Chen Shen , Teng Long , Hongbin Zhang

We propose using an adaptive sampling method to detect changes for a system with multiple lines. The adaptive sampling utilizes the information in responses to learn on which line is more likely to have a change thus allocating more units…

Applications · Statistics 2025-12-18 Yanqing Yi , Su-Fen Yang

In this study, we carried out equilibrium molecular dynamics (EMD) simulations of the liquid-liquid interface between two different Lennard-Jones components with varying miscibility, where we examined the relation between the interfacial…

Soft Condensed Matter · Physics 2025-12-29 Rei Ogawa , Hiroki Kusudo , Takeshi Omori , Edward R. Smith , Laurent Joly , Samy Merabia , Yasutaka Yamaguchi

We consider within a finite element approach the usage of different adaptively refined meshes for different variables in systems of nonlinear, time-depended PDEs. To resolve different solution behaviours of these variables, the meshes can…

Numerical Analysis · Mathematics 2010-05-27 Thomas Witkowski , Axel Voigt

With more energy networks being interconnected to form integrated energy systems (IESs), the optimal energy flow (OEF) problem has drawn increasing attention. Extant studies on OEF models mostly utilize the finite difference method (FDM) to…

Systems and Control · Electrical Eng. & Systems 2022-09-07 Binbin Chen , Wenchuan Wu , Qinglai Guo , Hongbin Sun

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions.…

Optimization and Control · Mathematics 2020-09-16 David Biagioni , Peter Graf , Xiangyu Zhang , Ahmed Zamzam , Kyri Baker , Jennifer King