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Particle identification in ALICE: a Bayesian approach

The ALICE Collaboration, Null
•
Adam, J
•
Adamová, D.
altro
Zyzak, M.
2016
  • journal article

Periodico
THE EUROPEAN PHYSICAL JOURNAL PLUS
Abstract
We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss (dE/dx) and time of flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high-purity samples of identified particles in the decay channels K0S → π−π+, φ → K−K+, and Λ → pπ− in p-Pb collisions at √sNN = 5.02TeV. In order to thoroughly assess the validity of the Bayesian approach, this methodology was used to obtain corrected pT spectra of pions, kaons, protons, and D0 mesons in pp collisions at √s = 7TeV. In all cases, the results using Bayesian PID were found to be consistent with previous measurements performed by ALICE using a standard PID approach. For the measurement of D0 → K−π+, it was found that a Bayesian PID approach gave a higher signal-to-background ratio and a similar or larger statistical significance when compared with standard PID selections, despite a reduced identification efficiency. Finally, we present an exploratory study of the measurement of Λ+ → pK−π+ in pp collisions at √s = 7 TeV, using the Bayesian approach for the identification of its decay products.
DOI
10.1140/epjp/i2016-16168-5
WOS
WOS:000376587700004
Archivio
http://hdl.handle.net/11368/2879975
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84971408174
http://link.springer.com/article/10.1140%2Fepjp%2Fi2016-16168-5
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by/3.0/it/
FVG url
https://arts.units.it/bitstream/11368/2879975/2/art_10.1140_epjp_i2016-16168-5.pdf
Soggetti
  • Physics and Astronomy...

Scopus© citazioni
24
Data di acquisizione
Jun 15, 2022
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Web of Science© citazioni
28
Data di acquisizione
Mar 27, 2024
Visualizzazioni
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Data di acquisizione
Jun 8, 2022
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