{"title":"Study and Optimization of N-Particle Numerical Statistical Algorithm for Solving the Boltzmann Equation","authors":"G. Z. Lotova, G. A. Mikhailov, S. V. Rogasinsky","doi":"10.1134/s0965542524700246","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The main goal of this work is to check the hypothesis that the well-known <i>N</i>-particle statistical algorithm yields a solution estimate for the nonlinear Boltzmann equation with an <span>\\(O(1{\\text{/}}N)\\)</span> error. For this purpose, practically important optimal relations between <span>\\(N\\)</span> and the number <span>\\(n\\)</span> of sample estimate values are determined. Numerical results for a problem with a known solution confirm that the formulated estimates and conclusions are satisfactory.</p>","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1134/s0965542524700246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The main goal of this work is to check the hypothesis that the well-known N-particle statistical algorithm yields a solution estimate for the nonlinear Boltzmann equation with an \(O(1{\text{/}}N)\) error. For this purpose, practically important optimal relations between \(N\) and the number \(n\) of sample estimate values are determined. Numerical results for a problem with a known solution confirm that the formulated estimates and conclusions are satisfactory.