Probing the shape of the quark-gluon plasma droplet via event-by-event quark-gluon plasma tomography
Abstract
This study investigates quark-gluon plasma in heavy-ion collisions through two avenues: high-đâ„ frameworks and hydrodynamic modeling. Using the TRâąENTo model, we find that the đ=0 value aligns well with high-đâ„ data, in agreement with Bayesian analysis of the low-đâ„ regime. While adjusting đ values may improve a fit to a particular high-đâ„ observable, it does not permit an earlier onset of transverse expansion.
Main Authors
Format
Articles
Research article
Published
2024
Series
Subjects
Publication in research information system
Publisher
American Physical Society (APS)
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202410216408KÀytÀ tÀtÀ linkitykseen.
Review status
Peer reviewed
ISSN
2469-9985
DOI
https://doi.org/10.1103/physrevc.110.044906
Language
English
Published in
Physical Review C
Citation
- Karmakar, B., Zigic, D., Djordjevic, M., Huovinen, P., Djordjevic, M., & Auvinen, J. (2024). Probing the shape of the quark-gluon plasma droplet via event-by-event quark-gluon plasma tomography. Physical Review C, 110, Article 044906. https://doi.org/10.1103/physrevc.110.044906
Funder(s)
Research Council of Finland
European Commission
Funding program(s)
Academy Project, AoF
ERC Advanced Grant
Akatemiahanke, SA
ERC Advanced Grant
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Additional information about funding
This work is supported by the European Research Council, Grant No. ERC-2016-COG: 725741, and by the Ministry of Science and Technological Development of the Republic of Serbia. P.H. and B.K. were also supported by the program Excellence InitiativeâResearch University of the University of Wroclaw of the Ministry of Education and Science. J.A. acknowledges the financial support from the Academy of Finland Project No. 330448. J.A.'s research was also funded as a part of the Center of Excellence in Quark Matter of the Academy of Finland (Project No. 330448). This research is part of the European Research Council Project No. ERC-2018-ADG-835105 YoctoLHC.
Copyright© Authors 2024