The algorithm developed by the CMS Collaboration to reconstruct and identify τ leptons produced in proton-proton collisions at s=7 and 8 TeV, via their decays to hadrons and a neutrino, has been significantly improved. The changes include a revised reconstruction of π0 candidates, and improvements in multivariate discriminants to separate τ leptons from jets and electrons. The algorithm is extended to reconstruct τ 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 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 τ lepton to pass the identification criteria and of the probabilities for jets, electrons, and muons to be misidentified as τ leptons. The results are found to be very close to those expected from Monte Carlo simulation.

Performance of reconstruction and identification of τ leptons decaying to hadrons and vτ in pp collisions at s=13 TeV

Cavallo, N.;Fabozzi, F.;
2018-01-01

Abstract

The algorithm developed by the CMS Collaboration to reconstruct and identify τ leptons produced in proton-proton collisions at s=7 and 8 TeV, via their decays to hadrons and a neutrino, has been significantly improved. The changes include a revised reconstruction of π0 candidates, and improvements in multivariate discriminants to separate τ leptons from jets and electrons. The algorithm is extended to reconstruct τ 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 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 τ lepton to pass the identification criteria and of the probabilities for jets, electrons, and muons to be misidentified as τ leptons. The results are found to be very close to those expected from Monte Carlo simulation.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/135502
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