Correlated gluonic hot spots meet symmetric cumulants data at LHC energies
Abstract
We present a systematic study on the influence of spatial correlations between the proton constituents, in our case gluonic hot spots, their size and their number on the symmetric cumulant SC(2,3), at the eccentricity level, within a Monte Carlo Glauber framework [J.L. Albacete, H. Petersen, A. Soto-Ontoso, Symmetric cumulants as a probe of the proton substructure at LHC energies, Phys. Lett. B778 (2018) 128–136. arXiv:1707.05592, doi:10.1016/j.physletb.2018.01.011]. When modeling the proton as composed by 3 gluonic hot spots, the most common assumption in the literature, we find that the inclusion of spatial correlations is indispensable to reproduce the negative sign of SC(2,3) in the highest centrality bins as dictated by data. Further, the subtle interplay between the different scales of the problem is discussed. To conclude, the possibility of feeding a 2+1D viscous hydrodynamic simulation with our entropy profiles is exposed.
Main Authors
Format
Articles
Research article
Published
2019
Series
Subjects
Publication in research information system
Publisher
Elsevier BV
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201901301367Use this for linking
Review status
Peer reviewed
ISSN
0375-9474
DOI
https://doi.org/10.1016/j.nuclphysa.2018.08.013
Language
English
Published in
Nuclear Physics A
Citation
- Albacete, J. L., Niemi, H., Petersen, H., & Soto-Ontoso, A. (2019). Correlated gluonic hot spots meet symmetric cumulants data at LHC energies. Nuclear Physics A, 982, 463-466. https://doi.org/10.1016/j.nuclphysa.2018.08.013
Funder(s)
Academy of Finland
Funding program(s)
Akatemiahanke, SA
Academy Project, AoF

Additional information about funding
This work was partially supported by a Helmholtz Young Investigator Group VH-NG-822 from the Helmholtz Association and GSI, a FP7-PEOPLE-2013-CIG Grant of the European Commission, reference QCDense/631558, by Ram ́on y Cajal and MINECO projects reference RYC-2011-09010 and FPA2013-47836 and by the DFG through the grant CRC-TR 211. HN is supported by the Academy of Finland, project 297058. We acknowledge the CSCIT Center for Science in Espoo, Finland, for the allocation of the computational resources.
Copyright© 2018 Published by Elsevier B.V.