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PLUMED is an open-source software package that is widely used for analyzing and enhancing molecular dynamics simulations that works in conjunction with most available molecular dynamics softwares. While the computational cost of PLUMED…

Computational Physics · Physics 2025-11-05 Daniele Rapetti , Massimiliano Bonomi , Carlo Camilloni , Giovanni Bussi , Gareth A. Tribello

We present new algorithms and fast implementations to find efficient approximations for modelling stochastic processes. For many numerical computations it is essential to develop finite approximations for stochastic processes. While the…

Optimization and Control · Mathematics 2020-12-03 Kipngeno Benard Kirui , Georg Ch. Pflug , Alois Pichler

In recent years, simulation methods based on the scaling of atomic potential functions, such as quasi-coarse-grained dynamics and coarse-grained dynamics, have shown promising results for modeling crystalline systems at multiple scales.…

Mesoscale and Nanoscale Physics · Physics 2024-09-11 Dong-Dong Jiang , Jian-Li Shao

When addressing spatial biological questions using mathematical models, symmetries within the system are often exploited to simplify the problem by reducing its physical dimension. In a reduced-dimension model molecular movement is…

Quantitative Methods · Quantitative Biology 2025-02-17 Natasha S. Savage

Quantum chemical calculations on quantum computers have been focused mostly on simulating molecules in gas-phase. Molecules in liquid solution are however most relevant for Chemistry. Continuum solvation models represent a good compromise…

Quantum Physics · Physics 2022-11-14 Davide Castaldo , Soran Jahangiri , Alain Delgado , Stefano Corni

We establish, through coarse-grained computation, a connection between traditional, continuum numerical algorithms (initial value problems as well as fixed point algorithms) and atomistic simulations of the Larson model of micelle…

Soft Condensed Matter · Physics 2009-11-10 Dmitry I. Kopelevich , Athanassios Z. Panagiotopoulos , Ioannis G. Kevrekidis

Molecular simulations produce very high-dimensional data-sets with millions of data points. As analysis methods are often unable to cope with so many dimensions, it is common to use dimensionality reduction and clustering methods to reach a…

Machine Learning · Statistics 2017-11-03 Stefan Doerr , Igor Ariz-Extreme , Matthew J. Harvey , Gianni De Fabritiis

Computational methods are the most effective tools we have besides scientific experiments to explore the properties of complex biological systems. Progress is slowing because digital silicon computers have reached their limits in terms of…

Quantum Physics · Physics 2020-04-03 Viv Kendon

The present level of development of molecular force field methods is assessed from the point of view of simulation-based engineering, outlining the immediate perspective for further development and highlighting the newly emerging discipline…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-05-22 Martin Horsch , Christoph Niethammer , Jadran Vrabec , Hans Hasse

The complexities of today's materials simulations demand computer codes which are both powerful and highly flexible. A researcher should be able to readily choose different geometries, different materials and different algorithms without…

We review a family of local algorithms that permit the simulation of charged particles with purely local dynamics. Molecular dynamics formulations lead to discretizations similar to those of ``particle in cell'' methods in plasma physics.…

Statistical Mechanics · Physics 2009-11-10 A. C. Maggs , J. Rottler

Quantum computing, an innovative computing system carrying prominent processing rate, is meant to be the solutions to problems in many fields. Among these realms, the most intuitive application is to help chemical researchers correctly…

Quantum Physics · Physics 2022-12-29 Qingchun Wang , Huan-Yu Liu , Qing-Song Li , Jianyu Zhao , Qiankun Gong , Ye Li , Yu-Chun Wu , Guo-Ping Guo

The complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. Quantum mechanics/molecular mechanics (QM/MM) molecular…

Material properties are fundamentally dictated by multiscale phenomena, which often reach mesoscale in size. The {\mu}m mesoscale is also the size which can be observed directly under an optical microscope, bridging the atomistic…

We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of…

Materials Science · Physics 2026-02-17 Artem Chuprov , Egor E. Nuzhin , Alexey A. Tsukanov , Nikolay V. Brilliantov

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims…

The most difficult aspect of the realistic modeling of granular materials is how to capture the real shape of the particles. Here we present a method to simulate granular materials with complex-shaped particles. The particle shape is…

Materials Science · Physics 2008-04-18 F. Alonso-Marroquin , Yucang Wang

Quantum computing has the potential to revolutionize multiple fields by solving complex problems that can not be solved in reasonable time with current classical computers. Nevertheless, the development of quantum computers is still in its…

We report new statistical time-series analysis tools providing significant improvements in the rapid, precision extraction of discrete state dynamics from large databases of experimental observations of molecular machines. By building…

Quantitative Methods · Quantitative Biology 2019-10-23 Max A. Little , Bradley C. Steel , Fan Bai , Yoshiyuki Sowa , Thomas Bilyard , David M. Mueller , Richard M. Berry , Nick S. Jones

Real-world experiments involve batched & delayed feedback, non-stationarity, multiple objectives & constraints, and (often some) personalization. Tailoring adaptive methods to address these challenges on a per-problem basis is infeasible,…

Machine Learning · Computer Science 2024-11-11 Ethan Che , Daniel R. Jiang , Hongseok Namkoong , Jimmy Wang
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