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Parallel tempering (PT), also known as replica exchange, is the go-to workhorse for simulations of multi-modal distributions. The key to the success of PT is to adopt efficient swap schemes. The popular deterministic even-odd (DEO) scheme…

Machine Learning · Computer Science 2022-11-22 Wei Deng , Qian Zhang , Qi Feng , Faming Liang , Guang Lin

In particle-in-cell simulations, excessive or even unfeasible computational demands can be caused by the growth of the number of particles in the course of prolific ionization or cascaded pair production due to the effects of quantum…

Computational Physics · Physics 2021-01-25 A. Muraviev , A. Bashinov , E. Efimenko , V. Volokitin , I. Meyerov , A. Gonoskov

Mechanistic mathematical models of biological systems usually contain a number of unknown parameters whose values need to be estimated from available experimental data in order for the models to be validated and used to make quantitative…

Quantitative Methods · Quantitative Biology 2025-06-16 Yue Liu , Philip K. Maini , Ruth E. Baker

This article proposes a new way to construct computationally efficient `wrappers' around fine scale, microscopic, detailed descriptions of dynamical systems, such as molecular dynamics, to make predictions at the macroscale `continuum'…

Dynamical Systems · Mathematics 2017-03-06 Hammad Alotaibi , Barry Cox , A. J. Roberts

We describe the results obtained from an improved model for protein folding. We find that a good agreement with the native structure of a 46 residue long, five-letter protein segment is obtained by carefully tuning the parameters of the…

Biomolecules · Quantitative Biology 2009-11-11 Andrea Nobile , Federico Rapuano

Sampling complex potential energies is one of the most pressing challenges of contemporary computational science. Inspired by recent efforts that use quantum effects and discretized Feynman's path integrals to overcome large barriers we…

Statistical Mechanics · Physics 2016-07-19 Marco Nava , Ferruccio Palazzesi , Claudio Perego , Michele Parrinello

A common problem to all applications of linear finite dynamical systems is analyzing the dynamics without enumerating every possible state transition. Of particular interest is the long term dynamical behaviour. In this paper, we study the…

Dynamical Systems · Mathematics 2019-04-01 Björn Lindenberg

Computational methods in drug repositioning can help to conserve resources. In particular, methods based on biological networks are showing promise. Considering only the network topology and knowledge on drug target genes is not sufficient…

Molecular Networks · Quantitative Biology 2025-04-02 Atte Aalto , La Mi , Diego A. Blanco-Mora , Jorge Goncalves

The method of tempered transitions was proposed by Neal (1996) for tackling the difficulties arising when using Markov chain Monte Carlo to sample from multimodal distributions. In common with methods such as simulated tempering and…

Computation · Statistics 2012-09-11 Gundula Behrens , Nial Friel , Merrilee Hurn

Controlling the evolution of nonequilibrium systems to minimize dissipated heat or work is a key goal for designing nanodevices, both in nanotechnology and biology. Progress in computing optimal protocols has thus far been limited to either…

Computational Physics · Physics 2022-01-04 Megan C. Engel , Jamie A. Smith , Michael P. Brenner

We have introduced a variational method to improve the computation of integrated correlation times in the Parallel Tempering Dynamics, obtaining a better estimate (a lower bound, at least) of the exponential correlation time. Using this…

Disordered Systems and Neural Networks · Physics 2018-03-08 A. Billoire , L. A. Fernandez , A. Maiorano , E. Marinari , V. Martin-Mayor , J. Moreno-Gordo , G. Parisi , F. Ricci-Tersenghi , J. J. Ruiz-Lorenzo

This letter compares the performance of four different, popular simulation environments for robotics and reinforcement learning (RL) through a series of benchmarks. The benchmarked scenarios are designed carefully with current industrial…

Robotics · Computer Science 2021-03-09 Marian Körber , Johann Lange , Stephan Rediske , Simon Steinmann , Roland Glück

The process of calibrating computer models of natural phenomena is essential for applications in the physical sciences, where plenty of domain knowledge can be embedded into simulations and then calibrated against real observations. Current…

Machine Learning · Computer Science 2025-01-20 Rafael Oliveira , Dino Sejdinovic , David Howard , Edwin V. Bonilla

Optimization plays a significant role in many areas of science and technology. Most of the industrial optimization problems have inordinately complex structures that render finding their global minima a daunting task. Therefore, designing…

Disordered Systems and Neural Networks · Physics 2021-09-09 Amin Barzegar , Anuj Kankani , Salvatore Mandrà , Helmut G. Katzgraber

Several methods for density matrix propagation in distributed computing environments, such as clusters and graphics processing units, are proposed and evaluated. It is demonstrated that the large communication overhead associated with each…

Chemical Physics · Physics 2014-07-16 Luke J. Edwards , Ilya Kuprov

We propose a novel method for fast and scalable evaluation of periodic solutions of systems of ordinary differential equations for a given set of parameter values and initial conditions. The equations governing the system dynamics are…

Dynamical Systems · Mathematics 2016-05-30 I. Yu. Tyukin , A. N. Gorban , T. A. Tyukina , J. Al Ameri , Yu. A. Korablev

Reactive molecular dynamics simulations are computationally demanding. Reaching spatial and temporal scales where interesting scientific phenomena can be observed requires efficient and scalable implementations on modern hardware. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-26 Hasan Metin Aktulga , Christopher Knight , Paul Coffman , Kurt A. O'Hearn , Tzu-Ray Shan , Wei Jiang

The large demand for simulated data has made the reality gap a problem on the forefront of robotics. We propose a method to traverse the gap by tuning available simulation parameters. Through the optimisation of physics engine parameters,…

Robotics · Computer Science 2020-03-04 Jack Collins , Ross Brown , Jurgen Leitner , David Howard

The sampling problem lies at the heart of atomistic simulations and over the years many different enhanced sampling methods have been suggested towards its solution. These methods are often grouped into two broad families. On the one hand…

Computational Physics · Physics 2020-11-25 Michele Invernizzi , Pablo Miguel Piaggi , Michele Parrinello

The constant increase in parallelism available on large-scale distributed computers poses major scalability challenges to many scientific applications. A common strategy to improve scalability is to express the algorithm in terms of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-23 Andrew Garmon , Vinay Ramakrishnaiah , Danny Perez
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