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Sci. Comput."],"published-print":{"date-parts":[[2023,10,31]]},"abstract":"<jats:p>Abstract.<\/jats:p>\n                  <jats:p>We develop an accurate, highly efficient, and scalable random batch sum-of-Gaussians (RBSOG) method for molecular dynamics simulations of systems with Coulomb interactions. The idea of the RBSOG method is based on a sum-of-Gaussians decomposition of the Coulomb kernel, and then a random batch importance sampling on the Fourier space is employed for approximating the Fourier expansion of the Gaussians with large bandwidths (the far components). The importance sampling significantly reduces the computational cost, resulting in a scalable algorithm by avoiding the use of communication-intensive fast Fourier transform. Theoretical analysis is presented to demonstrate the unbiasedness of the approximate force, the controllability of variance, and the convergence of the algorithm. The resultant method has [Formula: see text] complexity with low communication latency. Accurate simulation results on both dynamical and equilibrium properties of benchmark problems are reported to illustrate the attractive performance of the method. Simulations on parallel computing are, also performed to show the high parallel efficiency. The RBSOG method can be straightforwardly extended to more general interactions with long-ranged kernels and thus is promising for constructing fast algorithms for molecular dynamics simulations of various systems.<\/jats:p>","DOI":"10.1137\/22m1497201","type":"journal-article","created":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T04:08:54Z","timestamp":1696392534000},"page":"B591-B617","source":"Crossref","is-referenced-by-count":23,"title":["Random Batch Sum-of-Gaussians Method for Molecular Dynamics Simulations of Particle Systems"],"prefix":"10.1137","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0247-4149","authenticated-orcid":true,"given":"Jiuyang","family":"Liang","sequence":"first","affiliation":[{"name":"School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, 200240, People\u2019s Republic of China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7645-4998","authenticated-orcid":true,"given":"Zhenli","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Institute of Natural Sciences, and MOE-LSC, Shanghai Jiao Tong University, Shanghai, 200240, People\u2019s Republic of China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4894-2198","authenticated-orcid":true,"given":"Qi","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, 200240, People\u2019s Republic of China."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"351","published-online":{"date-parts":[[2023,10,4]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.softx.2015.06.001"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780198803195.001.0001"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1063\/1.446373"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.88.063308"},{"key":"ref5","doi-asserted-by":"crossref","unstructured":"A. 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