Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2023)
Series Vol. 5
, 25 May 2023
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Tracklet Method Analysis on Particle Production Based on Centrality Dependence
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Theoretical and Natural Science, Vol. 5,
Published 25 May 2023. © 2023 The Author(s). Published by EWA
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Citation Nicole Chik, Brian Wen Cheng, Xinyu Cheng, Weihao Jin. Tracklet Method Analysis on Particle Production Based on Centrality Dependence. TNS (2023) Vol. 5: 113-118. DOI: 10.54254/2753-8818/5/20230319.
This paper presents an analysis on a parametrization of ALICE open data on the Pb-Pb collisions at √sNN = 2.76TeV created by the Large Hadron Collider (LHC). We will use the tracklet method to calculate the differences in pseudorapidity values (∆η), generate ∆η distributions for different centrality ranges, and investigate the centrality dependence of the number of particles produced. This document presents findings of a negative correlation between centrality classes and the number of particles produced.
Large Hadron Collider, ALICE, tracklet method, centrality dependence, Pb-Pb collisions.
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The datasets used and/or analyzed during the current study will be available
from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2023)
- ISBN (Print)
- ISBN (Online)
- Published Date
- 25 May 2023
- Theoretical and Natural Science
- ISSN (Print)
- ISSN (Online)
- © 2023 The Author(s)
- Open Access
- This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license, which
permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited