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A physical model for the simulation ink/paper interaction at the mesoscopic scale is developed. It is based on the modified Ising model, and is generalized to consider the restriction of the finite-volume of ink and also its dynamic…

Computational Engineering, Finance, and Science · Computer Science 2013-07-11 Reza Farrahi Moghaddam , Fereydoun Farrahi Moghaddam , Mohamed Cheriet

Generative policies based on diffusion and flow matching achieve strong performance in robotic manipulation by modeling multi-modal human demonstrations. However, their reliance on iterative Ordinary Differential Equation (ODE) integration…

Diffusion models have shown remarkable empirical success in sampling from rich multi-modal distributions. Their inference relies on numerically solving a certain differential equation. This differential equation cannot be solved in closed…

Machine Learning · Computer Science 2026-01-16 Khashayar Gatmiry , Sitan Chen , Adil Salim

Large scale atomistic simulations with suitable interatomic potentials are widely employed by scientists or engineers of different areas. Quick generation of high-quality interatomic potentials is of urgent need under present circumstances,…

Materials Science · Physics 2016-11-23 Kun Wang , Wenjun Zhu , Shifang Xiao , Jun Chen , Wangyu Hu

The emergence and understanding of new design paradigms that exploit flow induced mechanical instabilities for propulsion or energy harvesting demands robust and accurate flow structure interaction numerical models. In this context, we…

Fluid Dynamics · Physics 2019-05-22 Caroline Bernier , Mattia Gazzola , Renaud Ronsse , Philippe Chatelain

We provide a robust and general algorithm for computing distribution functions associated to induced orthogonal polynomial measures. We leverage several tools for orthogonal polynomials to provide a spectrally-accurate method for a broad…

Numerical Analysis · Mathematics 2017-04-28 Akil Narayan

We demonstrate that an inverse Monte Carlo approach allows to reconstruct effective interaction potentials from real-space images. The method is exemplified on monomolecular ethanol-water films imaged with scanning force microscopy (SFM),…

Statistical Mechanics · Physics 2016-04-13 Jonas Gienger , Nikolai Severin , Jürgen P. Rabe , Igor M. Sokolov

We propose a two-body spherically symmetric (isotropic) potential such that particles interacting by the potential self assemble into linear semiflexible polymeric chains without branching. By suitable control of the potential parameters we…

Soft Condensed Matter · Physics 2018-05-09 Alex Abraham , Apratim Chatterji

The synthesis of complex materials through the self-assembly of particles at the nanoscale provides opportunities for the realization of novel material properties. However, the inverse design process to create experimentally feasible…

Soft Condensed Matter · Physics 2022-03-01 Carl S. Adorf , James Antonaglia , Julia Dshemuchadse , Sharon C. Glotzer

The osmotic pressure $P$ in equilibrium polymers (EP) in good solvent is investigated by means of a three dimensional off-lattice Monte Carlo simulation. Our results compare well with real space renormalisation group theory and the osmotic…

Statistical Mechanics · Physics 2009-10-31 A. Milchev , J. P. Wittmer , P. van der Schoot , D. Landau

Probabilistic graphical models are a key tool in machine learning applications. Computing the partition function, i.e., normalizing constant, is a fundamental task of statistical inference but it is generally computationally intractable,…

Machine Learning · Statistics 2020-01-29 Sungsoo Ahn , Michael Chertkov , Adrian Weller , Jinwoo Shin

In this paper an iterated function system on the space of distribution functions is built. The inverse problem is introduced and studied by convex optimization problems. Some applications of this method to approximation of distribution…

Statistics Theory · Mathematics 2007-06-13 Stefano M. Iacus , Davide La Torre

We compare three model-free numerical methods for inverting structural data to obtain interaction potentials, namely iterative Boltzmann inversion (IBI), test-particle insertion (TPI), and a machine-learning (ML) approach called ActiveNet.…

A first-principle multiscale modeling approach is presented, which is derived from the solution of the Ornstein-Zernike equation for the coarse-grained representation of polymer liquids. The approach is analytical, and for this reason is…

Soft Condensed Matter · Physics 2009-09-09 J. McCarty , I. Y. Lyubimov , M. G. Guenza

Multi-component polymer mixtures are ubiquitous in biological self-organization but are notoriously difficult to study computationally. Plagued by both slow single molecule relaxation times and slow equilibration within dense mixtures,…

Soft Condensed Matter · Physics 2024-12-19 Emmit K. Pert , Clay H. Batton , Sherry Li , Steven Dunne , Grant M. Rotskoff

Probabilistic power flow (PPF) is essential for quantifying operational uncertainty in modern distribution systems with high penetration of renewable generation and flexible loads. Conventional PPF methods primarily rely on Monte Carlo (MC)…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Weijie Xia , James Ciyu Qin , Edgar Mauricio Salazar Duque , Hongjin Du , Peter Palensky , Giovanni Sansavini , Pedro P. Vergara

We present a detailed derivation and testing of our approach to rescale the dynamics of mesoscale simulations of coarse-grained polymer melts (I. Y. Lyubimov et al. J. Chem. Phys. \textbf{132}, 11876, 2010). Starting from the…

Soft Condensed Matter · Physics 2015-05-27 I. Y. Lyubimov , M. G. Guenza

Polymer flooding is a mature enhanced oil recovery technique that has been successfully applied in many field projects. By injecting polymer into a reservoir, the viscosity of water is increased, and the efficiency of water flooding is…

Computational Engineering, Finance, and Science · Computer Science 2018-12-19 He Zhong , Hui Liu , Tao Cui , Lihua Shen , Bo Yang , Ruijian He , Zhangxin Chen

Interatomic potentials approximate the potential energy of atoms as a function of their coordinates. Their main application is the effective simulation of many-atom systems. Here, we review empirical interatomic potentials designed to…

Materials Science · Physics 2022-11-11 Martin H. Muser , Sergey V. Sukhomlinov , Lars Pastewka

Monte Carlo methods represent the "de facto" standard for approximating complicated integrals involving multidimensional target distributions. In order to generate random realizations from the target distribution, Monte Carlo techniques use…

Computation · Statistics 2022-01-21 L. Martino , V. Elvira , D. Luengo , J. Corander