Multiplicity Dependence in the Non-Extensive Hadronization Model Calculated by the HIJING++ Framework

Abstract

The non-extensive statistical description of the identified final state particles measured in high energy collisions is well-known by its wide range of applicability. However, there are many open questions that need to be answered, including but not limited to, the question of the observed mass scaling of massive hadrons or the size and multiplicity dependence of the model parameters. This latter is especially relevant, since currently the amount of available experimental data with high multiplicity at small systems is very limited. This contribution has two main goals: On the one hand we provide a status report of the ongoing tuning of the soon-to-be-released HIJING++ Monte Carlo event generator. On the other hand, the role of multiplicity dependence of the parameters in the non-extensive hadronization model is investigated with HIJING++ calculations. We present cross-check comparisons of HIJING++ with existing experimental data to verify its validity in our range of interest as well as calculations at high-multiplicity regions where we have insufficient experimental data.

Entropic Divergence and Entropy Related to Nonlinear Master Equations

“…can be studied. For physical systems a good example is the hadron number distribution in high energy accelerator collision events [60].…”

Machine Learning based KNO-scaling of charged hadron multiplicities with Hijing++

“…The Hijing++ (Heavy Ion Jet INteraction Generator, C++ version) is the new generation of the popular Monte Carlo event generator for heavy-ion physics. This program code is under final tests in the development timeline, and the latest, tuned version is already performing well with data [14][15][16]. In the current study, the previously proposed and Pythia 8-trained, ML-based hadronization models were used to investigate KNO-like scaling behaviour.…”