Deep-learning quasi-particle masses from QCD equation of state
The interactions of quarks and gluons are strong in the non-perturbative regime. The equation of state (EoS) of a strongly-interacting quantum chromodynamics (QCD) medium can only be studied using the first-principle lattice QCD calculations. However, the complicated QCD EoS can be reproduced using...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
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| Series: | Physics Letters B |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0370269323004227 |
| _version_ | 1797736879625338880 |
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| author | Fu-Peng Li Hong-Liang Lü Long-Gang Pang Guang-You Qin |
| author_facet | Fu-Peng Li Hong-Liang Lü Long-Gang Pang Guang-You Qin |
| author_sort | Fu-Peng Li |
| collection | DOAJ |
| description | The interactions of quarks and gluons are strong in the non-perturbative regime. The equation of state (EoS) of a strongly-interacting quantum chromodynamics (QCD) medium can only be studied using the first-principle lattice QCD calculations. However, the complicated QCD EoS can be reproduced using simple statistical formula by treating the medium as a free parton gas whose fundamental degrees of freedom are dressed quarks and gluons called quasi-particles, with temperature-dependent masses. We use deep neural networks and auto differentiation to solve this variational problem in which the masses of quasi gluons, up/down and strange quarks are three unknown functions, whose forms are represented by deep neural network. We reproduce the QCD EoS at zero net baryon chemical potential using these machine learned quasi-particle masses, and calculate the shear viscosity over the entropy density (η/s) as a function of temperature of the hot QCD matter. |
| first_indexed | 2024-03-12T13:20:32Z |
| format | Article |
| id | doaj.art-88f7ede745574ee69dcad2675af2b683 |
| institution | Directory Open Access Journal |
| issn | 0370-2693 |
| language | English |
| last_indexed | 2024-03-12T13:20:32Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Physics Letters B |
| spelling | doaj.art-88f7ede745574ee69dcad2675af2b6832023-08-26T04:42:32ZengElsevierPhysics Letters B0370-26932023-09-01844138088Deep-learning quasi-particle masses from QCD equation of stateFu-Peng Li0Hong-Liang Lü1Long-Gang Pang2Guang-You Qin3Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079, ChinaHiSilicon Research Department, Huawei Technologies Co., Ltd., Shenzhen 518000, ChinaKey Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079, China; Corresponding authors.Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079, China; Corresponding authors.The interactions of quarks and gluons are strong in the non-perturbative regime. The equation of state (EoS) of a strongly-interacting quantum chromodynamics (QCD) medium can only be studied using the first-principle lattice QCD calculations. However, the complicated QCD EoS can be reproduced using simple statistical formula by treating the medium as a free parton gas whose fundamental degrees of freedom are dressed quarks and gluons called quasi-particles, with temperature-dependent masses. We use deep neural networks and auto differentiation to solve this variational problem in which the masses of quasi gluons, up/down and strange quarks are three unknown functions, whose forms are represented by deep neural network. We reproduce the QCD EoS at zero net baryon chemical potential using these machine learned quasi-particle masses, and calculate the shear viscosity over the entropy density (η/s) as a function of temperature of the hot QCD matter.http://www.sciencedirect.com/science/article/pii/S0370269323004227 |
| spellingShingle | Fu-Peng Li Hong-Liang Lü Long-Gang Pang Guang-You Qin Deep-learning quasi-particle masses from QCD equation of state Physics Letters B |
| title | Deep-learning quasi-particle masses from QCD equation of state |
| title_full | Deep-learning quasi-particle masses from QCD equation of state |
| title_fullStr | Deep-learning quasi-particle masses from QCD equation of state |
| title_full_unstemmed | Deep-learning quasi-particle masses from QCD equation of state |
| title_short | Deep-learning quasi-particle masses from QCD equation of state |
| title_sort | deep learning quasi particle masses from qcd equation of state |
| url | http://www.sciencedirect.com/science/article/pii/S0370269323004227 |
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