A Deep Learning Based Estimator for Light Flavour Elliptic Flow in Heavy Ion Collisions at LHC Energies
We developed a deep learning feed-forward network for estimating elliptic flow (v2) coefficients in heavy-ion collisions from RHIC to LHC energies. The success of our model is mainly the estimation of v2 from final state particle kinematic information and learning the centrality and the transverse m...
Saved in:
Main Authors: | Barnaföldi Gergely Gábor, Mallick Neelkamal, Prasad Suraj, Sahoo Raghunath, Mishra Aditya Nath |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2025-01-01
|
Series: | EPJ Web of Conferences |
Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2025/01/epjconf_sqm2024_03004.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Statistical production of Bc mesons in heavy-ion collisions at the LHC energy
by: Shouxing Zhao, et al.
Published: (2025-02-01) -
Lévy walk of pions in heavy-ion collisions
by: Dániel Kincses, et al.
Published: (2025-02-01) -
Disoriented isospin condensates in heavy-ion collisions
by: Kapusta Joseph, et al.
Published: (2025-01-01) -
Quarkonium production in pp and heavy-ion collisions
by: Song Taesoo, et al.
Published: (2025-01-01) -
Multimessenger study of baryon-charged QCD matter in heavy-ion collisions
by: Lipei Du
Published: (2025-02-01)