GPU-based computing analysis for charged-particle production in heavy ion collisions

The innovation of this paper lies in the introduction of GPU acceleration, which has greatly speeded up the projects progress. It begins by offering a brief overview of the research history on quark-gluon plasma (QGP) and the corresponding research tool, heavy ion collisions. The paper mainly focuses on data analysis of a significant process within the hadronic collisions, namely, the charged-particle production. The investigation of this process is an integral part of QGP research, as it occurs promptly after the formation of QGP. By applying the tracklet method to the datasets collected by ALICE detector, an estimate of the charged-particle multiplicity density is presented. The finding then suggests a positive correlation between the number of participating nucleons in the collision and the normalized charged-particle multiplicity density. Notably, this dependence on centrality is similar to the research conducted by the ALICE collaboration, but derived from a distinct dataset. It indicates that there should be an underlying mechanism behind the intriguing phenomenological trend waiting for further exploration. These studies have the potential to enhance the understanding of quantum chromodynamics (QCD) and provide insights into the true nature of the universe.