{"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/encoding-and-selecting-coarse-grain-mapping","title":"Encoding and Selecting Coarse-Grain Mapping Operators with Hierarchical Graphs","arxiv_id":"1804.04997","date":"2018-04-13","proceeding":null,"authors":["Maghesree Chakraborty","Chenliang Xu","Andrew D. White"],"abstract":"Coarse grain (CG) molecular dynamics (MD) can simulate systems inaccessible to fine grain (FG) MD simulations. A CG simulation decreases the degrees of freedom by mapping atoms from an FG representation into agglomerate CG particles. The FG to CG mapping is not unique. Research into systematic selection of these mappings is challenging due to their combinatorial growth with respect to the number of atoms in a molecule. Here we present a method of reducing the total count of mappings by imposing molecular topology and symmetry constraints. The count reduction is illustrated by considering all mappings for nearly 49,889 molecules. The resulting number of mapping operators is still large, so we introduce hierarchical graphs which encode multiple CG mapping operators. The encoding method is demonstrated for methanol and a 14-mer peptide. This encoding provides a foundation to perform automated mapping selection.","url_abs":"http://arxiv.org/abs/1804.04997v1","url_pdf":"http://arxiv.org/pdf/1804.04997v1.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":"encoding-and-selecting-coarse-grain-mapping","repo_url":"https://github.com/ur-whitelab/mapping-graph","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}