Investigation of particle production in $h{\text -}A$ collisions using statistical distributions

TL;DR

This paper compares various statistical models like Negative Binomial, Gompertz, Weibull, and Krasznovszky-Wagner distributions to analyze charged particle production in high-energy hadron-nucleus collisions, assessing their effectiveness.

Contribution

It provides a comparative analysis of multiple statistical distributions to model particle production in h-A collisions, highlighting their relative success and applicability.

Findings

Negative Binomial distribution effectively models particle multiplicities.

Gompertz and Weibull distributions show promising fits to data.

Models based on different dynamics offer varied insights into particle production.

Abstract

Study of the characteristic properties of charged particle production in hadron-nucleus collisions at high energies, by utilising the approaches from different statistical models is performed.~Predictions from different approaches using the Negative Binomial distribution, shifted Gompertz distribution, Weibull distribution and the Krasznovszky-Wagner distribution are utilised for a comparative study of the relative successes of these models.~These distributions derived from a variety of functional forms are based on either phenomenological parameterizations or some model of the underlying dynamics.~Some of these have have also been used to study the data at the LHC for both proton-proton and nucleus-nucleus collisions.~Various physical and derived observables have been used for the analysis.