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The maximum mean discrepancy (MMD) is a recently proposed test statistic for two-sample test. Its quadratic time complexity, however, greatly hampers its availability to large-scale applications. To accelerate the MMD calculation, in this…

Artificial Intelligence · Computer Science 2015-06-19 Ji Zhao , Deyu Meng

We develop an efficient parallel multiscale method that bridges the atomistic and mesoscale regimes, from nanometer to micron and beyond, via concurrent coupling of atomistic simulation and mesoscopic dynamics. In particular, we combine an…

Computational Physics · Physics 2020-12-23 Yuying Wang , Zhen Li , Junbo Xu , Chao Yang , George Em Karniadakis

The dynamic mode decomposition (DMD) is a broadly applicable dimensionality reduction algorithm that approximates a matrix containing time-series data by the outer product of a matrix of exponentials, representing Fourier-like time…

Optimization and Control · Mathematics 2017-12-07 Travis Askham , Peng Zheng , Aleksandr Aravkin , J. Nathan Kutz

We review a molecular dynamics method for nucleon many-body systems called the quantum molecular dynamics (QMD) and our studies using this method. These studies address the structure and the dynamics of nuclear matter relevant to the…

Nuclear Theory · Physics 2014-01-31 Toshiki Maruyama , Gentaro Watanabe , Satoshi Chiba

Kernel mean embeddings are a popular tool that consists in representing probability measures by their infinite-dimensional mean embeddings in a reproducing kernel Hilbert space. When the kernel is characteristic, mean embeddings can be used…

Machine Learning · Computer Science 2021-06-29 Boris Muzellec , Francis Bach , Alessandro Rudi

Diffusive molecular dynamics is a novel model for materials with atomistic resolution that can reach diffusive time scales. The main ideas of diffusive molecular dynamics are to first minimize an approximate variational Gaussian free energy…

Numerical Analysis · Mathematics 2015-06-09 Gideon Simpson , Mitchell Luskin , David J. Srolovitz

Simulations of macromolecular diffusion and adsorption in confined environments can offer valuable mechanistic insights into numerous biophysical processes. In order to model solutes at atomic detail on relevant time scales, Brownian…

Soft Condensed Matter · Physics 2021-03-16 Martin Reinhardt , Neil J. Bruce , Daria B. Kokh , Rebecca C. Wade

We propose a continuous-time formulation of persistent contrastive divergence (PCD) for maximum likelihood estimation (MLE) of unnormalised densities. Our approach expresses PCD as a coupled, multiscale system of stochastic differential…

Machine Learning · Statistics 2025-10-03 Paul Felix Valsecchi Oliva , O. Deniz Akyildiz , Andrew Duncan

Due to particle conservation, Canonical Molecular Dynamics (MD) simulations fail in the description of surface phase transitions involving coverage or lateral density changes. However, a step on the surface can act effectively as a source…

Materials Science · Physics 2016-08-31 D. Passerone , U. Tartaglino , F. Ercolessi , E. Tosatti

We present extensive molecular dynamics simulations of the motion of a single linear rigid molecule in a two-dimensional random array of fixed obstacles. The diffusion constant for the center of mass translation, $D_{\rm CM}$, and for…

Soft Condensed Matter · Physics 2009-11-10 Angel J. Moreno , Walter Kob

Only a small fraction of the data generated in state-of-the-art all-atom multi-microsecond molecular dynamics (MD) simulations is typically analyzed. With femtosecond integration steps, microsecond simulations generate billions of time…

We consider the dynamics of a linear stochastic approximation algorithm driven by Markovian noise, and derive finite-time bounds on the moments of the error, i.e., deviation of the output of the algorithm from the equilibrium point of an…

Machine Learning · Computer Science 2019-03-11 R. Srikant , Lei Ying

The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of…

Diffusion in a multidimensional energy surface with minima and barriers is a problem of importance in statistical mechanics and also has wide applications, such as protein folding. To understand it in such a system, we carry out theory and…

Statistical Mechanics · Physics 2022-06-29 Subhajit Acharya , Biman Bagchi

In recent years, machine learning interatomic potentials (MLIPs) have attracted significant attention as a method that enables large-scale, long-time atomistic simulations while maintaining accuracy comparable to electronic structure…

Materials Science · Physics 2025-03-27 Yuta Yoshimoto , Naoki Matsumura , Yuto Iwasaki , Hiroshi Nakao , Yasufumi Sakai

A dynamical atomistic chain to simulate mechanical properties of a one-dimensional material with zero temperature may be modelled by the molecular dynamics (MD) model. Because the number of particles (atoms) is huge for a MD model, in…

Numerical Analysis · Mathematics 2019-02-22 Mingjie Liao , Ping Lin

The (asymptotic) behaviour of the second moment of solutions to stochastic differential equations is treated in mean-square stability analysis. This property is discussed for approximations of infinite-dimensional stochastic differential…

Numerical Analysis · Mathematics 2023-12-06 Annika Lang , Andreas Petersson , Andreas Thalhammer

We present a study of single-mode Rayleigh-Taylor instabilities (smRTI) with a modified Direct Simulation Monte Carlo (mDSMC) code in two dimensions. The mDSMC code is aimed to capture the dynamics of matter for a large range of Knudsen…

Fluid Dynamics · Physics 2016-11-15 Irina Sagert , Jim Howell , Alec Staber , Terrance Strother , Dirk Colbry , Wolfgang Bauer

We consider the problem of detecting change-points in univariate time series by fitting a continuous piecewise linear signal using the residual sum of squares. Values of the inferred signal at slope breaks are restricted to a finite set of…

Computation · Statistics 2022-04-08 Vincent Runge , Marco Pascucci , Nicolas Deschamps de Boishebert

The use of molecular dynamics (MD) simulations has led to promising results to unravel the atomistic origins of adhesive wear, and in particular for the onset of wear at nanoscale surface asperities. However, MD simulations come with a high…

Soft Condensed Matter · Physics 2022-06-29 Son Pham-Ba , Jean-François Molinari
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