Abstract
In the present study, we have shown the role of different clusterization algorithms on the signals of liquid–gas phase transition in the multifragmentation for the central reactions of \(^{40}\)Ar + \(^{45}\)Sc. We have used the quantum molecular dynamics (QMD) model to generate the phase space of the nucleons and clusterization algorithms based on spatial constraints and its variants, and the energy-based clusterization algorithm. We also present the correlations among fragments within the events via constructing correlation function. We find that the energy-based clusterization algorithm, i.e., simulated annealing clusterization algorithm (SACA) is the most successful among all the available clusterization algorithms. We also find that the event-by-event analysis unfolds and helps to understand reaction picture much better than the quantities constructed by averaging over events.
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