Heidelberg 2022 – wissenschaftliches Programm
Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
T: Fachverband Teilchenphysik
T 8: Higgs Boson: Decay in Fermions 1
T 8.7: Vortrag
Montag, 21. März 2022, 17:45–18:00, T-H21
Tau reconstruction exploiting machine learning techniques at CMS — •Ze Chen — DESY, Hamburg, Germany
Reconstruction of hadronically decaying tau leptons (denoted as τh ) in the CMS experiment at the Large Hadron Collider has been historically performed with the Hadron-plus-strip (HPS) algorithm. In the HPS algorithm, the τh final state signature is identified by combining information from charged hadrons, reconstructed by their associated tracks, and π0 candidates, obtained by clustering photon and electron candidates in rectangular regions, called "strips". As of the LHC Run 2, deep-learning techniques have been implemented to improve the identification of genuine τh leptons and reduce contributions from backgrounds. This talk covers a study to improve the tau decay mode reconstruction using machine learning techniques. Its efficiency is shown and compared to the one of the HPS algorithm.