Open Access
| Issue |
EPJ Web Conf.
Volume 364, 2026
XXXI International Conference on Ultra-Relativistic Nucleus-Nucleus Collisions “Quark Matter 2025”
|
|
|---|---|---|
| Article Number | 02005 | |
| Number of page(s) | 5 | |
| Section | Awards | |
| DOI | https://doi.org/10.1051/epjconf/202636402005 | |
| Published online | 17 April 2026 | |
- M. Omana Kuttan, A. Motornenko, J. Steinheimer, H. Stoecker, Y. Nara, M. Bleicher, A chiral mean-field equation-of-state in UrQMD: effects on the heavy ion compression stage, Eur. Phys. J. C 82, 427 (2022), 2201.01622. 10.1140/epjc/s10052-022-10400-2 [CrossRef] [Google Scholar]
- J. Steinheimer, T. Reichert, Y. Nara, M. Bleicher, Momentum dependent potentials from a parity doubling CMF model in UrQMD: results on flow and particle production, J. Phys. G 52, 035103 (2025), 2410.01742. 10.1088/1361-6471/adab0b [Google Scholar]
- H. Petersen, J. Steinheimer, G. Burau, M. Bleicher, H. Stöcker, A Fully Integrated Transport Approach to Heavy Ion Reactions with an Intermediate Hydrodynamic Stage, Phys. Rev. C 78, 044901 (2008), 0806.1695. 10.1103/PhysRevC.78.044901 [Google Scholar]
- M. Omana Kuttan, J. Steinheimer, K. Zhou, H. Stoecker, QCD Equation of State of Dense Nuclear Matter from a Bayesian Analysis of Heavy-Ion Collision Data, Phys. Rev. Lett. 131, 202303 (2023), 2211.11670. 10.1103/PhysRevLett.131.202303 [Google Scholar]
- D. Oliinychenko, A. Sorensen, V. Koch, L. McLerran, Sensitivity of Au+Au collisions to the symmetric nuclear matter equation of state at 2-5 nuclear saturation densities, Phys. Rev. C 108, 034908 (2023), 2208.11996. 10.1103/PhysRevC.108.034908 [Google Scholar]
- M. Omana Kuttan, J. Steinheimer, K. Zhou, A. Redelbach, H. Stoecker, A fast centrality-meter for heavy-ion collisions at the CBM experiment, Phys. Lett. B 811, 135872 (2020), 2009.01584. 10.1016/j.physletb.2020.135872 [Google Scholar]
- M. Omana Kuttan, K. Zhou, J. Steinheimer, A. Redelbach, H. Stoecker, An equation-of-state-meter for CBM using PointNet, JHEP 21, 184 (2020), 2107.05590. 10.1007/JHEP10(2021)184 [Google Scholar]
- J.A. Sun, L. Yan, C. Gale, S. Jeon, An end-to-end generative diffusion model for heavyion collisions, arXiv (2024), 2410.13069. [Google Scholar]
- D. Torbunov, Y. Huang, M. Lin, Y. Ren, Y. Go, T. Rinn, H. Yu, B. Viren, J. Huang, Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity wholeevent simulation in high-energy heavy-ion experiments, Phys. Rev. C 110, 034912 (2024), 2406.01602. 10.1103/PhysRevC.110.034912 [Google Scholar]
- H. Huang, B. Xiao, Z. Liu, Z. Wu, Y. Mu, H. Song, Applications of deep learning to relativistic hydrodynamics, Phys. Rev. Res. 3, 023256 (2021), 1801.03334. 10.1103/Phys-RevResearch.3.023256 [Google Scholar]
- M. Omana Kuttan, K. Zhou, J. Steinheimer, H. Stöcker, Ultra fast, event-by-event heavy-ion simulations for next generation experiments, arXiv (2025), 2502.16330. [Google Scholar]
- M. Omana Kuttan, K. Zhou, J. Steinheimer, H. Stöcker, Towards a foundation model for heavy-ion collision experiments through point cloud diffusion, arXiv (2024), 2412.10352. [Google Scholar]
- S. Luo, W. Hu, Diffusion Probabilistic Models for 3D Point Cloud Generation, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021), pp. 2837–2845 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.