Yetkin, Elif Aslı2022-10-172022-10-172022-07-011748-0221https://hdl.handle.net/11411/4581https://doi.org/10.1088/1748-0221/17/07/P07023Abstract: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (? h) that originate from genuine tau leptons in the CMS detector against ? h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a ? h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine ? h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient ? h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved ? h reconstruction method are validated with LHC proton-proton collision data at s = 13 TeV. © 2022 CERN.eninfo:eu-repo/semantics/openAccesscalibration and fitting methodscluster findingLarge detector systems for particle and astroparticle physicsParticle identification methodsArticle2-s2.0-8513591874410.1088/1748-0221/17/07/P07023Q2WOS:000867442500009