An equation-of-state-meter of quantum chromodynamics transition from deep learning
- 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.
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| Author: | Long-Gang PangORCiD, Kai ZhouORCiD, Nan SuORCiDGND, Hannah PetersenORCiDGND, Horst StöckerORCiDGND, Xin-Nian WangORCiDGND |
|---|---|
| URN: | urn:nbn:de:hebis:30:3-456491 |
| DOI: | https://doi.org/10.1038/s41467-017-02726-3 |
| ISSN: | 2041-1723 |
| Pubmed Id: | https://pubmed.ncbi.nlm.nih.gov/29335457 |
| Parent Title (English): | Nature Communications |
| Publisher: | Nature Publishing Group UK |
| Place of publication: | [London] |
| Document Type: | Article |
| Language: | English |
| Year of Completion: | 2018 |
| Date of first Publication: | 2018/01/15 |
| Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
| Release Date: | 2018/02/13 |
| Tag: | Fluid dynamics; Information theory and computation; Theoretical nuclear physics |
| Volume: | 9 |
| Issue: | 1, Art. 210 |
| Page Number: | 6 |
| First Page: | 1 |
| Last Page: | 6 |
| Note: | 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/. |
| HeBIS-PPN: | 426624106 |
| Institutes: | Geowissenschaften / Geographie / Geowissenschaften |
| Physik / Physik | |
| Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS) | |
| Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik |
| Sammlungen: | Universitätspublikationen |
| Licence (German): |  Creative Commons - Namensnennung 4.0 |
