{"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/performance-of-reconstruction-and","title":"Performance of reconstruction and identification of $τ$ leptons decaying to hadrons and $ν_τ$ in pp collisions at $\\sqrt{s}=$ 13 TeV","arxiv_id":"1809.02816","date":"2018-09-08","proceeding":null,"authors":["CMS Collaboration"],"abstract":"The algorithm developed by the CMS Collaboration to reconstruct and identify $\\tau$ leptons produced in proton-proton collisions at $\\sqrt{s}=$ 7 and 8 TeV, via their decays to hadrons and a neutrino, has been significantly improved. The changes include a revised reconstruction of $\\pi^0$ candidates, and improvements in multivariate discriminants to separate $\\tau$ leptons from jets and electrons. The algorithm is extended to reconstruct $\\tau$ leptons in highly Lorentz-boosted pair production, and in the high-level trigger. The performance of the algorithm is studied using proton-proton collisions recorded during 2016 at $\\sqrt{s}=$ 13 TeV, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The performance is evaluated in terms of the efficiency for a genuine $\\tau$ lepton to pass the identification criteria and of the probabilities for jets, electrons, and muons to be misidentified as $\\tau$ leptons. The results are found to be very close to those expected from Monte Carlo simulation.","url_abs":"https://arxiv.org/abs/1809.02816v3","url_pdf":"https://arxiv.org/pdf/1809.02816v3.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":"performance-of-reconstruction-and","repo_url":"https://github.com/fojensen/TauTraining","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"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}