1999
DOI: 10.1103/physrevd.59.094008
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Multiplicity distributions at high energies as a sum of Poissonian-like distributions

Abstract: It is shown that at collider energies experimental distributions in the multiplicity n of negatively charged particles in inelastic and non-single diffractive pp collisions are well parameterized by a sum of so-called Gupta-Sarma distributions having the Poisson distribution as a particular case. This extends the earlier description of the multiplicity distributions in hadron-hadron collisions at c.m. energies below 65 GeV by the two parameter sum of Poissonians. Implications of the proposed parametrization fo… Show more

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Cited by 2 publications
(2 citation statements)
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References 53 publications
(56 reference statements)
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“…In high energy positron-electron (e + e − ), proton-proton (pp), proton-antiproton (pp), positron-proton (e + p), proton-nucleus (pA), and nucleus-nucleus (AA) collisions, many particles are usually produced in the final state [1][2][3][4][5]. In the investigation of high energy collisions, multiplicity distributions of final-state particles may be measured in experiments.…”
Section: Introductionmentioning
confidence: 99%
“…In high energy positron-electron (e + e − ), proton-proton (pp), proton-antiproton (pp), positron-proton (e + p), proton-nucleus (pA), and nucleus-nucleus (AA) collisions, many particles are usually produced in the final state [1][2][3][4][5]. In the investigation of high energy collisions, multiplicity distributions of final-state particles may be measured in experiments.…”
Section: Introductionmentioning
confidence: 99%
“…where the number of clusters N h and the number of galaxies N i in each cluster are chosen randomly and at first we take the cluster occupation numbers N i to be independent and identically distributed. A similar sum over clusters arises in situations ranging from the distribution of particle multiplicities in hadron collisions at highenergy accelerators (Finkelstein 1988;Hegyi 1994;Tchikilev 1999) to the distribution of rainfall totals (Rodriguez-Iturbe, Cox & Isham 1987;Cowpertwait 1994;Evin & Favre 2008). We can characterize the net count distribution directly for small counts and in general using the generating function G(z).…”
Section: E L L C O U N T S O N L a R G E S C A L E S : T H E P O I mentioning
confidence: 96%