CERN Accelerating science

ATLAS Note
Report number	ATL-PHYS-PUB-2019-033
Title	Identification of hadronic tau lepton decays using neural networks in the ATLAS experiment
Corporate Author(s)	The ATLAS collaboration
Collaboration	ATLAS Collaboration
Publication	2019
Imprint	30 Aug 2019
Number of pages	15
Note	All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2019-033
Subject category	Particle Physics - Experiment
Accelerator/Facility, Experiment	CERN LHC ; ATLAS
Free keywords	ATLAS ; Tau ; Neural Network ; TAUPERF
Abstract	This note describes a novel algorithm to identify the visible decay products of hadronic tau decays ($\tau_\text{had-vis}$) used by the ATLAS experiment for Run 2 of the LHC. The algorithm is based on recurrent neural networks (RNN) employing information from reconstructed charged-particle tracks and clusters of energy in the calorimeter associated to $\tau_\text{had-vis}$ candidates as well as high-level discriminating variables. The expected performance of this algorithm is evaluated in simulated proton-proton collisions at $\sqrt{s} = 13 \, \text{TeV}$ and compared to a BDT-based approach.
Scientific contact person	Klaus Moenig, (klaus.moenig@desy.de)

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