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SUMMARY:Determination of the quark-gluon string parameters from the data o
n pp\, pA and AA collisions at wide energy range using Bayesian Gaussian P
rocess Optimization
DTSTART;VALUE=DATE-TIME:20180801T160000Z
DTEND;VALUE=DATE-TIME:20180801T162000Z
DTSTAMP;VALUE=DATE-TIME:20191120T174340Z
UID:indico-contribution-3032024@indico.cern.ch
DESCRIPTION:Speakers: Vladimir Kovalenko (St Petersburg State University)\
nBayesian Gaussian Process Optimization [1\,2\,3] can be considered as a m
ethod of the determination of the model parameters\, based on the experime
ntal data. In the range of soft QCD physics\, the processes of hadron and
nuclear interactions require using phenomenological models containing many
parameters. In order to minimize the computation time\, the model predict
ions can be parameterized using Gaussian Process regression\, and then pro
vide the input to the Bayesian Optimization.\n In this paper the Bayesian
Gaussian Process Optimization has been applied to the Monte Carlo model w
ith string fusion [4\,5\,6]. The parameters of the model are determined us
ing experimental data on multiplicity and cross section of pp\, pA and AA
collisions at wide energy range (from SPS to LHC). Principal Component Ana
lysis has been applied to the data and model predictions. The results prov
ide important constrains on the transverse radius of the quark-gluon strin
g ($r_{str}$) and the mean multiplicity per rapidity from one string ($\\m
u_0$).\nThe research was supported by Russian Science Foundation under gra
nt 17-72-20045.\n\n References\n[1] C. E. Rasmussen\, C. K. I. Williams\,
Gaussian Processes for Machine Learning. The MIT Press\, 2006\n[2] Jonah
E. Bernhard\, et al\, Phys. Rev. C 94\, 024907 (2016)\n[3] Jonah E. Bernha
rd\, arXiv:1804.06469 [nucl-th] (2018)\n[4] V. N. Kovalenko. Phys. Atom. N
ucl. 76\, 1189 (2013)\, arXiv:1211.6209 [hep-ph]\n[5] V. Kovalenko\, V. Ve
chernin.\, PoS (Baldin ISHEPP XXI) 077\, arXiv:1212.2590 [nucl-th]\, 2012\
n[6] V. Kovalenko\, Kovalenko\, PoS QFTHEP2013 (2013) 052.\n\nhttps://indi
co.cern.ch/event/648004/contributions/3032024/
LOCATION:Arts Bldg. Hall C
URL:https://indico.cern.ch/event/648004/contributions/3032024/
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