Negative Binomial Distribution and the multiplicity moments at the LHC

TL;DR

This paper demonstrates that LHC multiplicity moments are accurately modeled by a two-step convolution of Poisson and Negative Binomial Distributions, providing predictions for future higher-energy collisions.

Contribution

It introduces a two-step convolution model using Negative Binomial Distribution for the source function to describe LHC multiplicity moments.

Findings

LHC data on multiplicity moments fit well with the model

No unexpected behavior of the Negative Binomial parameter k observed

Predictions provided for 10 and 14 TeV energies

Abstract

In this work we show that the latest LHC data on multiplicity moments $C_2-C_5$ are well described by a two-step model in the form of a convolution of the Poisson distribution with energy-dependent source function. For the source function we take $\Gamma$ Negative Binomial Distribution. No unexpected behavior of Negative Binomial Distribution parameter $k$ is found. We give also predictions for the higher energies of 10 and 14 TeV.