PUBLICATION: PHYSICS LETTERS B

AUTHORS: Song, YD; Wang, R; Ma, YG; Deng, XG; Liu, HL

By relating the charge multiplicity distribution and the temperature of a de-exciting nucleus through a deep neural network, we propose that the charge multiplicity distribution can be used as a thermometer of heavy-ion collisions. Based on an isospin-dependent quantum molecular dynamics model, we study the caloric curve of reaction Pd-103 + Be-9 with the apparent temperature determined through the charge multiplicity distribution. The caloric curve shows a characteristic signature of nuclear liquid-gas phase transition around the apparent temperature T-ap = 6.4 MeV, which is consistent with that through a traditional heavy-ion collision thermometer, and indicates the viability of determining the temperature in heavy-ion collisions with multiplicity distribution. (C) 2021 The Authors. Published by Elsevier B.V.

LINKS: http://dx.doi.org/10.1016/j.physletb.2021.136084