# A Bayesian approach to particle identification in ALICE

- Institution: CERN
- Department: LHC Seminar
- Speaker: Pietro Antonioli
- Year: 2016
- Language: English
- Subjects: Physics
- Source: [CERN](https://videos.cern.ch/record/3005222)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Among the LHC experiments, ALICE has unique particle identification (PID) capabilities exploiting different types of detectors. During Run 1, a Bayesian approach to PID was developed and intensively tested. It facilitates the combination of information from different sub-systems. The adopted methodology and formalism as well as the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE will be reviewed. Results are presented with PID performed via measurements of specific energy loss (dE/dx) and time-of-flight using information from the TPC and TOF detectors, respectively. Methods to extract priors from data and to compare PID efficiencies and misidentification probabilities in data and Monte Carlo using high-purity samples of identified particles will be presented. Bayesian PID results were found consistent with previous measurements published by ALICE. The Bayesian PID approach gives a higher signal-to-background ratio and a similar or larger statistical significance when compared with standard PID selections, despite a reduced identification efficiency. Future potential applications of the technique will be discussed..

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## Lectures

1. [A Bayesian approach to particle identification in ALICE](https://invisiblenetwork.ai/learn/cern/3005222/c2557fa66f04), 57 min (CERN's player)