TY  - JOUR
A1  - Pang, Long-Gang
A1  - Zhou, Kai
A1  - Su, Nan
A1  - Petersen, Hannah
A1  - Stöcker, Horst
A1  - Wang, Xin-Nian
T1  - An equation-of-state-meter of quantum chromodynamics transition from deep learning
T2  - Nature Communications
N2  - A primordial state of matter consisting of free quarks and gluons that existed in the early universe a few microseconds after the Big Bang is also expected to form in high-energy heavy-ion collisions. Determining the equation of state (EoS) of such a primordial matter is the ultimate goal of high-energy heavy-ion experiments. Here we use supervised learning with a deep convolutional neural network to identify the EoS employed in the relativistic hydrodynamic simulations of heavy ion collisions. High-level correlations of particle spectra in transverse momentum and azimuthal angle learned by the network act as an effective EoS-meter in deciphering the nature of the phase transition in quantum chromodynamics. Such EoS-meter is model-independent and insensitive to other simulation inputs including the initial conditions for hydrodynamic simulations.
KW  - Fluid dynamics
KW  - Information theory and computation
KW  - Theoretical nuclear physics
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/45649
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-456491
SN  - 2041-1723
N1  - Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
VL  - 9
IS  - 1, Art. 210
SP  - 1
EP  - 6
PB  - Nature Publishing Group UK
CY  - [London]
ER  -