{"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/isolating-unisolated-upsilons-with-anomaly","title":"Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data","arxiv_id":"2502.14036","date":"2025-02-19","proceeding":null,"authors":["Rikab Gambhir","Radha Mastandrea","Benjamin Nachman","Jesse Thaler"],"abstract":"We present the first study of anti-isolated Upsilon decays to two muons ($\\Upsilon \\to \\mu^+ \\mu^-$) in proton-proton collisions at the Large Hadron Collider. Using a machine learning (ML)-based anomaly detection strategy, we \"rediscover\" the $\\Upsilon$ in 13 TeV CMS Open Data from 2016, despite overwhelming anti-isolated backgrounds. We elevate the signal significance to $6.4 \\sigma$ using these methods, starting from $1.6 \\sigma$ using the dimuon mass spectrum alone. Moreover, we demonstrate improved sensitivity from using an ML-based estimate of the multi-feature likelihood compared to traditional \"cut-and-count\" methods. Our work demonstrates that it is possible and practical to find real signals in experimental collider data using ML-based anomaly detection, and we distill a readily-accessible benchmark dataset from the CMS Open Data to facilitate future anomaly detection developments.","url_abs":"https://arxiv.org/abs/2502.14036v2","url_pdf":"https://arxiv.org/pdf/2502.14036v2.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":"isolating-unisolated-upsilons-with-anomaly","repo_url":"https://github.com/hep-lbdl/dimuonad","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","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}