{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/long-time-persistence-of-hydrodynamic-memory","title":"Long-time persistence of hydrodynamic memory boosts microparticle transport","arxiv_id":"1906.04957","date":"2019-06-12","proceeding":null,"authors":["Sean L Seyler","Steve Pressé"],"abstract":"In a viscous fluid, the past motion of an accelerating particle is retained as an imprint on the vorticity field, which decays slowly as $t^{-3/2}$. At low Reynolds number, the Basset-Boussinesq-Oseen (BBO) equation correctly describes nonuniform particle motion, capturing hydrodynamic memory effects associated with this slow algebraic decay. Using the BBO equation, we numerically simulate driven single-particle transport to show that memory effects persist indefinitely under rather general driving conditions. In particular, when driving forces do not vary smoothly, hydrodynamic memory substantially lowers the effective transport friction. Remarkably, this enables coasting over a spatially uneven potential that otherwise traps particles modeled with pure Stokes drag. Our results provide direct physical insight into role of particle-fluid coupling in nonequilibrium microparticle transport.","url_abs":"http://arxiv.org/abs/1906.04957v2","url_pdf":"http://arxiv.org/pdf/1906.04957v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"long-time-persistence-of-hydrodynamic-memory","repo_url":"https://bitbucket.org/sseyler/glsimulator","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}