A study of event-by-event fluctuations in relativistic heavy-ion collisions

TL;DR

This paper introduces a method to identify and analyze events with high particle density fluctuations in relativistic heavy-ion collisions, revealing potential dynamical fluctuations and jet-like structures that could aid event classification.

Contribution

It presents a new event selection method based on density spikes and demonstrates its effectiveness in identifying events with significant fluctuations and jet-like features.

Findings

Identification of events with dense particle spikes.

Evidence of clustering or jet-like structures in selected events.

Potential use of clustering algorithms for event triggering.

Abstract

A method for selecting events with densely populated narrow regions or spikes in a given data sample is discussed. Applying this method to 200 A GeV/c 32S-AgBr and 32S-Gold collision data, a few events having "hot regions" are chosen for further analysis. The finding reveals that a systematic study of particle density fluctuations, if carried out in terms of scaled factorial moments, and the results are compared with those for the analysis of correlation free Monte Carlo events, would be useful in identifying events with large dynamical fluctuations. Formation of clusters or jet-like structure in multihadronic final states in the selected spiky events is also looked into and compared with the predictions of AMPT and independent emission hypothesis models by carrying out Monte Carlo simulation. The findings suggest that clustering or jet-like algorithm adopted in the present study may also serve as an important tool for triggering different classes of events.