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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Acknowledgements
This work is funded by Council of Scientific and Industrial Research (CSIR), Govt. of India, vide Grant No. 03(1388)/16/EMR-II.
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Sood, S., Kumar, R., Sharma, A., Puri, R.K. (2021). On the Fragment Production and Phase Transition Using QMD + SACA Model. In: Puri, R.K., Aichelin, J., Gautam, S., Kumar, R. (eds) Advances in Nuclear Physics. Springer Proceedings in Physics, vol 257. Springer, Singapore. https://doi.org/10.1007/978-981-15-9062-7_6
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