A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. The reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from H -> gamma gamma decays. Different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events.

Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at s = 8 TeV

GABUSI, MICHELE;RATTI, SERGIO PEPPINO;RICCARDI, CRISTINA;SALVINI, PAOLA;VITULO, PAOLO
2015-01-01

Abstract

A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. The reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from H -> gamma gamma decays. Different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events.
2015
The Physics category includes resources of a broad, general nature that contain materials from all areas of physics, The category also includes resources specifically concerned with the following physics sub-fields: mathematical physics, particle and nuclear physics, physics of fluids and plasmas, quantum physics, and theoretical physics.
Esperti anonimi
Inglese
Internazionale
ELETTRONICO
10
P08010
1
61
61
calibration and fitting methods; Performance of High Energy Physics Detectors; cluster finding; Pattern recognition; Instrumentation; Mathematical Physics
http://iopscience.iop.org/1748-0221/10/08/P08010/pdf/1748-0221_10_08_P08010.pdf
5
info:eu-repo/semantics/article
262
Gabusi, Michele; Ratti, SERGIO PEPPINO; Riccardi, Cristina; Salvini, Paola; Vitulo, Paolo
1 Contributo su Rivista::1.1 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1164585
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