Modifications in clusterization procedures for heavy-ion collisions: minimum spanning tree, simulated annealing, coalescence

TL;DR

This paper introduces the Common Clusterization Library (CCL) for heavy-ion collision analysis, compares it with existing methods, and proposes improvements in algorithms like simulated annealing and coalescence to enhance accuracy and computational efficiency.

Contribution

The paper presents a new open-source cluster finding library and novel modifications to clustering algorithms for better performance and accuracy in heavy-ion collision simulations.

Findings

CCL performs comparably to established MST and SACA methods.

Proposed algorithm improvements reduce computational time.

Differences between Helium-3 identified by different clustering methods.

Abstract

A new open-source cluster finding library ''Common Clusterization Library'' (CCL) is proposed to describe the clusters production when applied to the transport codes. The new library was applied to the Parton-Hadron-Quantum-Molecular Dynamics approach to be comparable with the established and well known MST and SACA implementations on the exactly same set of the events. The presented procedures were tested with rapidity density distributions and complex observables like $\langle M_{imf} \rangle$ and $\langle Z_{\text{max}} \rangle$ vs $Z_{bound}2$ at the energies of ALADiN and NA49 experiments. An improvement to the simulated annealing chain is proposed to reduce the computational time. The new stable clusters tracking algorithm for the ''lost'' cluster recovering is presented. The results of the ''box-like'' coalescence procedure and a mixed method which incorporates the coalescence algorithm steps and the negative binding energy criteria are presented. The difference between the Helium-3 found by the MST-based cluster finding procedure and the coalescence algorithm applied on the exactly same set of events and baryons is shown for the first time.