Geometric Poisson distribution of photons produced in the ultrarelativistic hadronic collisions

TL;DR

This paper demonstrates that the geometric Poisson distribution accurately models photon multiplicity in high-energy proton-proton collisions, outperforming the negative binomial distribution in capturing void probabilities and distribution shapes.

Contribution

It introduces the geometric Poisson distribution as a better fit for photon multiplicity data, challenging the conventional negative binomial approach in high-energy collision modeling.

Findings

Geometric Poisson distribution fits photon multiplicity data well.

Negative binomial distribution fails to reproduce void probabilities.

Enhanced void probability observed in LHC photon data.

Abstract

We show that the multiplicity distribution of photons produced with enhanced void probability in inelastic proton-proton collisions at $\sqrt{s} =$ 900 GeV, 2.76 TeV, and 7 TeV, measured at forward rapidities by the ALICE experiment at LHC, can be described by the geometric Poisson distribution. The traditionally used negative binomial distribution fails to reproduce the enhanced void probability and the shape of the modified combinants simultaneously. Our findings are relevant for the theoretical modeling of photon production processes in high-energy hadronic collisions.