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The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new type of acceleration strategy for RCD based on the…

Optimization and Control · Mathematics 2018-02-13 Dmitry Kovalev , Eduard Gorbunov , Elnur Gasanov , Peter Richtárik

This work proposes stochastic partial differential equations (SPDEs) as a practical tool to replicate clustering effects of more detailed particle-based dynamics. Inspired by membrane-mediated receptor dynamics on cell surfaces, we…

Quantitative Methods · Quantitative Biology 2025-01-22 Nathalie Wehlitz , Mohsen Sadeghi , Alberto Montefusco , Christof Schütte , Grigorios A. Pavliotis , Stefanie Winkelmann

The formation and subsequent growth of structural defects in an irradiated material can strongly influence the material's performance in technological and industrial applications. Predicting how the growth of defects affects material…

Deterministic simulations of the rate equations governing cluster dynamics in materials are limited by the number of equations to integrate. Stochastic simulations are limited by the high frequency of certain events. We propose a coupling…

Materials Science · Physics 2017-10-11 Pierre Terrier , Manuel Athènes , Thomas Jourdan , Gilles Adjanor , Gabriel Stoltz

Simulations of SiC crystal growth using molecular dynamics (MD) have become popular in recent years. They, however, simulate very fast deposition rates, to reduce computational costs. Therefore, they are more akin to surface sputtering,…

Materials Science · Physics 2025-12-25 Alexander Reichmann , Zahra Rajabzadeh , Sebastian Hofer , René Hammer , Lorenz Romaner

The foundations of irradiation damage theory were laid in the 1950s and 60s within the framework of chemical reaction kinetics. While helpful to analyze qualitative aspects of irradiation damage, the theory contained gaps that delayed its…

Materials Science · Physics 2026-02-16 Sicong He , Brandon Schwendeman , George Tynan , Jaime Marian

We study the inverse problem of radiative transfer equation (RTE) using stochastic gradient descent method (SGD) in this paper. Mathematically, optical tomography amounts to recovering the optical parameters in RTE using the…

Optimization and Control · Mathematics 2018-07-04 Ke Chen , Qin Li , Jian-Guo Liu

In this tutorial-style review we discuss basic concepts of coupled cluster theory and recent developments that increase its computational efficiency for calculations of molecules, solids and materials in general. We will touch upon the…

Materials Science · Physics 2020-04-15 Igor Ying Zhang , Andreas Grüneis

Coupled cluster theory is one of the most accurate electronic structure methods for predicting ground and excited state chemistry. However, the presence of numerical artifacts at electronic degeneracies, such as complex energies, has made…

Chemical Physics · Physics 2024-05-16 Eirik F. Kjønstad , Sara Angelico , Henrik Koch

We provide improved parallel approximation algorithms for the important class of packing and covering linear programs. In particular, we present new parallel $\epsilon$-approximate packing and covering solvers which run in…

Data Structures and Algorithms · Computer Science 2015-11-23 Di Wang , Michael Mahoney , Nishanth Mohan , Satish Rao

We report the formulation of a new, cost-effective approximation method in the time-dependent optimized coupled-cluster (TD-OCC) framework [T. Sato et al., J. Chem. Phys. 148, 051101 (2018)] for first-principles simulations of multielectron…

Chemical Physics · Physics 2022-08-11 Himadri Pathak , Takeshi Sato , Kenichi L. Ishikawa

In this review, we describe and analyze a mesoscale simulation method for fluid flow, which was introduced by Malevanets and Kapral in 1999, and is now called multi-particle collision dynamics (MPC) or stochastic rotation dynamics (SRD).…

Soft Condensed Matter · Physics 2009-11-13 G. Gompper , T. Ihle , D. M. Kroll , R. G. Winkler

Unitary coupled cluster (UCC), originally developed as a variational alternative to the popular traditional coupled cluster method, has seen a resurgence as a functional form for use on quantum computers. However, the number of excitors…

Chemical Physics · Physics 2021-01-07 Maria-Andreea Filip , Alex J. W. Thom

Engineering simulations are usually based on complex, grid-based, or mesh-free methods for solving partial differential equations. The results of these methods cover large fields of physical quantities at very many discrete spatial…

Fluid Dynamics · Physics 2025-08-08 Eduardo Di Costanzo , Niklas Kühl , Jean-Christophe Marongiu , Thomas Rung

A new method that accurately describes strongly correlated states and captures dynamical correlation is presented. It is derived as a modification of coupled-cluster theory with single and double excitations (CCSD) through consideration of…

Chemical Physics · Physics 2013-07-15 Daniel Kats , Frederick R. Manby

We investigate the numerical stability of time-dependent coupled-cluster theory for many-electron dynamics in intense laser pulses, comparing two coupled-cluster formulations with full configuration interaction theory. Our numerical…

The iterative sampling procedure employed by diffusion models (DMs) often leads to significant inference latency. To address this, we propose Stochastic Consistency Distillation (SCott) to enable accelerated text-to-image generation, where…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Hongjian Liu , Qingsong Xie , TianXiang Ye , Zhijie Deng , Chen Chen , Shixiang Tang , Xueyang Fu , Haonan Lu , Zheng-jun Zha

The aim of this paper is to give a short review on cluster dynamics modeling in the field of atoms and point defects clustering in materials. It is shown that this method, due to its low computer cost, can handle long term evolution that…

Materials Science · Physics 2007-09-13 Alain Barbu , Emmanuel Clouet

An improved version of the sparse multiway kernel spectral clustering (KSC) is presented in this brief. The original algorithm is derived from weighted kernel principal component (KPCA) analysis formulated within the primal-dual…

Machine Learning · Computer Science 2023-10-23 Mihaly Novak , Rocco Langone , Carlos Alzate , Johan Suykens

A cluster dynamics (CD) model has been developed to investigate the nucleation and growth of point defect clusters, i.e., interstitial prismatic loops and nanoscale and sub-nanoscale voids, in ThO2 during irradiation by energetic particles.…

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