{"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/jet-flavour-tagging-at-fcc-ee-with-a","title":"Tagging more quark jet flavours at FCC-ee at 91 GeV with a transformer-based neural network","arxiv_id":"2406.08590","date":"2024-06-12","proceeding":null,"authors":["Freya Blekman","Florencia Canelli","Alexandre De Moor","Kunal Gautam","Armin Ilg","Anna Macchiolo","Eduardo Ploerer"],"abstract":"Jet flavour tagging is crucial in experimental high-energy physics. A tagging algorithm, DeepJetTransformer, is presented, which exploits a transformer-based neural network that is substantially faster to train than state-of-the-art graph neural networks. The DeepJetTransformer algorithm uses information from particle flow-style objects and secondary vertex reconstruction for $b$- and $c$-jet identification, supplemented by additional information that is not always included in tagging algorithms at the LHC, such as reconstructed $K_{S}^{0}$ and $\\Lambda^{0}$ and $K^{\\pm}/\\pi^{\\pm}$ discrimination. The model is trained as a multiclassifier to identify all quark flavours separately and performs excellently in identifying $b$- and $c$-jets. An $s$-tagging efficiency of $40\\%$ can be achieved with a $10\\%$ $ud$-jet background efficiency. The performance improvement achieved by including $K_{S}^{0}$ and $\\Lambda^{0}$ reconstruction and $K^{\\pm}/\\pi^{\\pm}$ discrimination is presented. The algorithm is applied on exclusive $Z \\to q\\bar{q}$ samples to examine the physics potential and is shown to isolate $Z \\to s\\bar{s}$ events. Assuming all non-$Z \\to q\\bar{q}$ backgrounds can be efficiently rejected, a $5\\sigma$ discovery significance for $Z \\to s\\bar{s}$ can be achieved with an integrated luminosity of $60~\\text{nb}^{-1}$ of $e^{+}e^{-}$ collisions at $\\sqrt{s}=91.2~\\mathrm{GeV}$, corresponding to less than a second of the FCC-ee run plan at the $Z$ boson resonance.","url_abs":"https://arxiv.org/abs/2406.08590v4","url_pdf":"https://arxiv.org/pdf/2406.08590v4.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":"jet-flavour-tagging-at-fcc-ee-with-a","repo_url":"https://github.com/Edler1/DeepJetFCC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"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}