Temperatures and chemical potentials at kinetic freeze-out in relativistic heavy ion collisions from coarse grained transport simulations
Inghirami, G., Hillmann, P. C., Tomášik, B., & Bleicher, M. (2020). Temperatures and chemical potentials at kinetic freeze-out in relativistic heavy ion collisions from coarse grained transport simulations. Journal of Physics G: Nuclear and Particle Physics, 47(2), Article 025104. https://doi.org/10.1088/1361-6471/ab53f4
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Journal of Physics G: Nuclear and Particle PhysicsDate
2020Copyright
© 2019 IOP Publishing Ltd.
Using the UrQMD/coarse graining approach we explore the kinetic freeze-out stage in central Au + Au collisions at various energies. These studies allow us to obtain detailed information on the thermodynamic properties (e.g. temperature and chemical potential) of the system during the kinetic decoupling stage. We explore five relevant collision energies in detail, ranging from √sNN=2.4 GeV (GSI-SIS) to √sNN=200 GeV (RHIC). By adopting a standard Hadron Resonance Gas equation of state, we determine the average temperature〈T〉and the average baryon chemical potential〈μB〉on the space-time hyper-surface of last interaction. The results highlight the nature of the kinetic freeze-out as a continuous process. This differential decoupling is an important aspect often missed when summarizing data as single points in the phase diagram as e.g. done in Blast-Wave fits. We compare the key properties of the system derived by using our approach with other models and we briefly review similarities and differences.
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Institute of PhysicsISSN Search the Publication Forum
0954-3899Keywords
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https://converis.jyu.fi/converis/portal/detail/Publication/33465781
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Academy of FinlandFunding program(s)
Academy Project, AoF
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G. Inghirami is supported by the Academy of Finland, Project no. 297058. P. Hillmann acknowledges support by the GSI in cooperation with the John von Neumann Institute for Computing; she also acknowledges support from the HGS-HIRe and FIGSS graduate schools. B. Tomasik acknowledges support by the grant No. 17-04505S from the Czech Science Foundation. The computational resources were provided by the Center for Scientic Computing (CSC) of the Goethe University Frankfurt and by the Frankfurt Institute for Advanced Studies (FIAS). This work was supported by the COST Action CA15213 (THOR).

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