Please use this identifier to cite or link to this item: https://doi.org/10.1142/S0217732311037339
Title: Extraction of clan model parameters from multiplicity distributions measured in pp collisions at LHC energies
Authors: Dutta, S.
Jasvantlal, J.K.
Dewanto, A. 
Chan, A.H. 
Oh, C.H. 
Keywords: ALICE
clan model, void probability
CMS
LHC
multiplicity distribution
negative binomial distribution (NBD)
Issue Date: 21-Dec-2011
Citation: Dutta, S., Jasvantlal, J.K., Dewanto, A., Chan, A.H., Oh, C.H. (2011-12-21). Extraction of clan model parameters from multiplicity distributions measured in pp collisions at LHC energies. Modern Physics Letters A 26 (39) : 2951-2961. ScholarBank@NUS Repository. https://doi.org/10.1142/S0217732311037339
Abstract: This paper presents the variation of clan model parameters nc and N̄ with energy for p-p collisions at √s = 900 and 2360 GeV using ALICE and CMS as the detectors. The data for multiplicity distribution was reported by the ALICE and CMS collaborations. The values of n̄c and N̄ are evaluated from the NBD fit parameters n̄ and k. Hegyi [Phys. Lett. B 274, 214 (1992)] suggested an alternative method for determination of clan model parameters from void probability. A comparison of values obtained from the two methods is also done. A close agreement of values obtained from the two methods was observed for 546 GeV p-p̄ collisions. However for LHC data the agreement is not very well. Void probability overestimates the value of n̄c and underestimates the value of N̄ compared to that obtained from NBD. n̄c is found to increase with energy for both ALICE and CMS data. Contrary to the observation at lower energies that N̄ does not depend on energy, it is found to vary with energy. The variation of N̄ with energy is more prominent for CMS data. The results are discussed in detail. For CMS data, comparison of the results with the 7000 GeV data is also shown. © 2011 World Scientific Publishing Company.
Source Title: Modern Physics Letters A
URI: http://scholarbank.nus.edu.sg/handle/10635/96581
ISSN: 02177323
DOI: 10.1142/S0217732311037339
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