{"ID":2846650,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.01464","arxiv_id":"2511.01464","title":"Split-Flows: Measure Transport and Information Loss Across Molecular Resolutions","abstract":"By reducing resolution, coarse-grained models greatly accelerate molecular simulations, unlocking access to long-timescale phenomena, though at the expense of microscopic information. Recovering this fine-grained detail is essential for tasks that depend on atomistic accuracy, making backmapping a central challenge in molecular modeling. We introduce split-flows, a novel flow-based approach that reinterprets backmapping as a continuous-time measure transport across resolutions. Unlike existing generative strategies, split-flows establish a direct probabilistic link between resolutions, enabling expressive conditional sampling of atomistic structures and -- for the first time -- a tractable route to computing mapping entropies, an information-theoretic measure of the irreducible detail lost in coarse-graining. We demonstrate these capabilities on diverse molecular systems, including chignolin, a lipid bilayer, and alanine dipeptide, highlighting split-flows as a principled framework for accurate backmapping and systematic evaluation of coarse-grained models.","short_abstract":"By reducing resolution, coarse-grained models greatly accelerate molecular simulations, unlocking access to long-timescale phenomena, though at the expense of microscopic information. Recovering this fine-grained detail is essential for tasks that depend on atomistic accuracy, making backmapping a central challenge in...","url_abs":"https://arxiv.org/abs/2511.01464","url_pdf":"https://arxiv.org/pdf/2511.01464v2","authors":"[\"Sander Hummerich\",\"Tristan Bereau\",\"Ullrich Köthe\"]","published":"2025-11-03T11:23:13Z","proceeding":"physics.chem-ph","tasks":"[\"physics.chem-ph\",\"cs.LG\",\"physics.comp-ph\"]","methods":"[]","has_code":false}