Determining the temperature in heavy-ion collisions with multiplicity distribution

Abstract

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 ${}^{103}$Pd + ${}^9$Be 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 $T_{\mathrm{ap}}$ $=$ $6.4\mathrm{MeV}$, 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.

7 pages, 7 figures; Physics Letters B, in press

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Cited by in corpus (3)

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• An equation-of-state-meter for CBM using PointNet
• Finding signatures of the nuclear symmetry energy in heavy-ion collisions with deep learning