Negative binomial multiplicity distribution in proton-proton collisions in limited pseudorapidity intervals at LHC up to sqrt (s) = 7 TeV and the clan model

TL;DR

This paper analyzes proton-proton collision multiplicity distributions at LHC energies using Negative Binomial Distributions, demonstrating that a two-NBD model better fits the data and reveals energy invariance in soft particle production.

Contribution

It introduces a two-NBD model to improve the description of multiplicity distributions at LHC energies and confirms energy invariance of soft component parameters.

Findings

Two-NBD model fits the data better at high energies

Energy invariance of soft component holds at LHC

Clan parameters analyzed within the two-NBD framework

Abstract

Experiments at the Large Hadron Collider (LHC) have measured multiplicity distributions in proton-proton collisions at a new domain of center-of-mass energy ($\sqrt {s}$) in limited pseudorapidity intervals. We analyze multiplicity distribution data of proton-proton collisions at LHC energies as measured by the Compact Muon Solenoid (CMS) experiment in terms of characteristic parameters of the Negative Binomial Distribution (NBD) function that has played a significant role in describing multiplicity distribution data of particle production in high energy physics experiments, in the pre-LHC energy-range, in various kinds of collisions for a wide range of collision energy and for different kinematic ranges. Beside a single NBD, we apply the formalism of weighted superposition of two NBDs to examine if the multiplicity distribution data of CMS could be better explained. The weighted superposition of two NBDs indeed explain the distribution data better at the highest available LHC energy and in large interval of phase space. The two-NBD formalism further reveals that the energy invariance of the multiplicity distribution of the "soft" component of particle production in hadronic collisions is valid at LHC also, as it is at RHIC and Tevatron. We analyze the data further in terms of clan parameters in the framework of the two-NBD model.