Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning
Abstract
Using deep convolutional neural network (CNN), the nature of the QCD transition can be identified from the final-state pion spectra from hybrid model simulations of heavy-ion collisions that combines a viscous hydrodynamic model with a hadronic cascade “after-burner”. Two different types of equations of state (EoS) of the medium are used in the hydrodynamic evolution. The resulting spectra in transverse momentum and azimuthal angle are used as the input data to train the neural network to distinguish different EoS. Different scenarios for the input data are studied and compared in a systematic way. A clear hierarchy is observed in the prediction accuracy when using the event-by-event, cascade-coarse-grained and event-fine-averaged spectra as input for the network, which are about 80%, 90% and 99%, respectively. A comparison with the prediction performance by deep neural network (DNN) with only the normalized pion transverse momentum spectra is also made. High-level features of pion spectra captured by a carefully-trained neural network were found to be able to distinguish the nature of the QCD transition even in a simulation scenario which is close to the experiments.
- Authors:
-
[2];
- Frankfurt Inst. for Advanced Studies (FIAS), Frankfurt (Germany); Goethe Univ., Frankfurt (Germany); Nanjing Univ. (China); Univ. of Bergen (Norway)
- Frankfurt Inst. for Advanced Studies (FIAS), Frankfurt (Germany)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Central china Normal Univ., Wuhan (China)
- Frankfurt Inst. for Advanced Studies (FIAS), Frankfurt (Germany); Goethe Univ., Frankfurt (Germany)
- Nanjing Univ. (China); Nanjing Proton Source Research and Design Center (China); Anhui Normal Univ. (China)
- Frankfurt Inst. for Advanced Studies (FIAS), Frankfurt (Germany); Goethe Univ., Frankfurt (Germany); GSI-Darmstadt (Germany)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Nuclear Physics (NP); Trond Mohn Foundation; National Natural Science Foundation of China (NSFC); National Major State Basic Research of China; National Science Foundation (NSF)
- OSTI Identifier:
- 1659711
- Grant/Contract Number:
- AC02-05CH11231; BFS2018REK01; 11475085; 11535005; 11690030; 11221504; 2016Y-FE0129300; 2014CB845404; ACI-1550228
- Resource Type:
- Accepted Manuscript
- Journal Name:
- European Physical Journal. C, Particles and Fields
- Additional Journal Information:
- Journal Volume: 80; Journal Issue: 6; Journal ID: ISSN 1434-6044
- Publisher:
- Springer
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Citation Formats
Du, Yi-Lun, Zhou, Kai, Steinheimer, Jan, Pang, Long-Gang, Motornenko, Anton, Zong, Hong-Shi, Wang, Xin-Nian, and Stöcker, Horst. Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning. United States: N. p., 2020.
Web. doi:10.1140/epjc/s10052-020-8030-7.
Du, Yi-Lun, Zhou, Kai, Steinheimer, Jan, Pang, Long-Gang, Motornenko, Anton, Zong, Hong-Shi, Wang, Xin-Nian, & Stöcker, Horst. Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning. United States. https://doi.org/10.1140/epjc/s10052-020-8030-7
Du, Yi-Lun, Zhou, Kai, Steinheimer, Jan, Pang, Long-Gang, Motornenko, Anton, Zong, Hong-Shi, Wang, Xin-Nian, and Stöcker, Horst. Wed .
"Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning". United States. https://doi.org/10.1140/epjc/s10052-020-8030-7. https://www.osti.gov/servlets/purl/1659711.
@article{osti_1659711,
title = {Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning},
author = {Du, Yi-Lun and Zhou, Kai and Steinheimer, Jan and Pang, Long-Gang and Motornenko, Anton and Zong, Hong-Shi and Wang, Xin-Nian and Stöcker, Horst},
abstractNote = {Using deep convolutional neural network (CNN), the nature of the QCD transition can be identified from the final-state pion spectra from hybrid model simulations of heavy-ion collisions that combines a viscous hydrodynamic model with a hadronic cascade “after-burner”. Two different types of equations of state (EoS) of the medium are used in the hydrodynamic evolution. The resulting spectra in transverse momentum and azimuthal angle are used as the input data to train the neural network to distinguish different EoS. Different scenarios for the input data are studied and compared in a systematic way. A clear hierarchy is observed in the prediction accuracy when using the event-by-event, cascade-coarse-grained and event-fine-averaged spectra as input for the network, which are about 80%, 90% and 99%, respectively. A comparison with the prediction performance by deep neural network (DNN) with only the normalized pion transverse momentum spectra is also made. High-level features of pion spectra captured by a carefully-trained neural network were found to be able to distinguish the nature of the QCD transition even in a simulation scenario which is close to the experiments.},
doi = {10.1140/epjc/s10052-020-8030-7},
journal = {European Physical Journal. C, Particles and Fields},
number = 6,
volume = 80,
place = {United States},
year = {Wed Jun 10 00:00:00 EDT 2020},
month = {Wed Jun 10 00:00:00 EDT 2020}
}
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Works referenced in this record:
Possibility of Detecting Density Isomers in High-Density Nuclear Mach Shock Waves
journal, January 1976
- Hofmann, Jürgen; Stöcker, Horst; Heinz, Ulrich
- Physical Review Letters, Vol. 36, Issue 2
An equation-of-state-meter of quantum chromodynamics transition from deep learning
journal, January 2018
- Pang, Long-Gang; Zhou, Kai; Su, Nan
- Nature Communications, Vol. 9, Issue 1
First Results from Pb+Pb Collisions at the LHC
journal, November 2012
- Müller, Berndt; Schukraft, Jürgen; Wysłouch, Bolesław
- Annual Review of Nuclear and Particle Science, Vol. 62, Issue 1
Deep learning
journal, May 2015
- LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey
- Nature, Vol. 521, Issue 7553
QCD equation of state and hadron resonance gas
journal, June 2010
- Huovinen, Pasi; Petreczky, Péter
- Nuclear Physics A, Vol. 837, Issue 1-2
Quark number fluctuations in the Polyakov loop-extended quark-meson model at finite baryon density
journal, May 2011
- Skokov, V.; Friman, B.; Redlich, K.
- Physical Review C, Vol. 83, Issue 5
Microscopic models for ultrarelativistic heavy ion collisions
journal, January 1998
- Bass, S.
- Progress in Particle and Nuclear Physics, Vol. 41
flavor Polyakov–Nambu–Jona-Lasinio model at finite temperature and nonzero chemical potential
journal, January 2008
- Fu, Wei-jie; Zhang, Zhao; Liu, Yu-xin
- Physical Review D, Vol. 77, Issue 1
Determination of the polarization fractions in using a deep machine learning technique
journal, May 2016
- Searcy, Jacob; Huang, Lillian; Pleier, Marc-André
- Physical Review D, Vol. 93, Issue 9
Quarkonium Physics at a Fixed-Target Experiment using the LHC Beams
journal, May 2012
- Lansberg, J. P.; Brodsky, S. J.; Fleuret, F.
- Few-Body Systems, Vol. 53, Issue 1-2
Thermalization of Gluons with Bose-Einstein Condensation
journal, May 2015
- Xu, Zhe; Zhou, Kai; Zhuang, Pengfei
- Physical Review Letters, Vol. 114, Issue 18
Phase structure of the Polyakov-quark-meson model
journal, October 2007
- Schaefer, B. -J.; Pawlowski, J. M.; Wambach, J.
- Physical Review D, Vol. 76, Issue 7
A deep learning-based reconstruction of cosmic ray-induced air showers
journal, January 2018
- Erdmann, M.; Glombitza, J.; Walz, D.
- Astroparticle Physics, Vol. 97
Studies of heavy ion-induced high-energy density states in matter at the GSI Darmstadt SIS-18 and future FAIR facility
journal, May 2005
- Tahir, N. A.; Adonin, A.; Deutsch, C.
- Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 544, Issue 1-2
Experimental and theoretical challenges in the search for the quark–gluon plasma: The STAR Collaboration's critical assessment of the evidence from RHIC collisions
journal, August 2005
- Adams, J.; Aggarwal, M. M.; Ahammed, Z.
- Nuclear Physics A, Vol. 757, Issue 1-2
Glueballs amass at the RHIC and LHC! The early quarkless first-order phase transition at T = 270 MeV—from pure Yang–Mills glue plasma to Hagedorn glueball states
journal, December 2015
- Stoecker, Horst; Zhou, Kai; Schramm, Stefan
- Journal of Physics G: Nuclear and Particle Physics, Vol. 43, Issue 1
Influence of the hadronic phase on observables in ultrarelativistic heavy ion collisions
journal, June 2017
- Steinheimer, J.; Aichelin, J.; Bleicher, M.
- Physical Review C, Vol. 95, Issue 6
The QCD critical end point in the PNJL model
journal, May 2009
- Costa, P.; de Sousa, C. A.; Ruivo, M. C.
- EPL (Europhysics Letters), Vol. 86, Issue 3
Causal viscous hydrodynamics in 2 + 1 dimensions for relativistic heavy-ion collisions
journal, June 2008
- Song, Huichao; Heinz, Ulrich
- Physical Review C, Vol. 77, Issue 6
Constraining the Equation of State of Superhadronic Matter from Heavy-Ion Collisions
journal, May 2015
- Pratt, Scott; Sangaline, Evan; Sorensen, Paul
- Physical Review Letters, Vol. 114, Issue 20
Electromagnetic probes of a pure-glue initial state in nucleus-nucleus collisions at energies available at the CERN Large Hadron Collider
journal, August 2016
- Vovchenko, V.; Karpenko, Iu. A.; Gorenstein, M. I.
- Physical Review C, Vol. 94, Issue 2
Applying Bayesian parameter estimation to relativistic heavy-ion collisions: Simultaneous characterization of the initial state and quark-gluon plasma medium
journal, August 2016
- Bernhard, Jonah E.; Moreland, J. Scott; Bass, Steffen A.
- Physical Review C, Vol. 94, Issue 2
Propagators and phase structure of and QCD
journal, January 2013
- Fischer, Christian S.; Luecker, Jan
- Physics Letters B, Vol. 718, Issue 3
Antiflow of nucleons at the softest point of the equation of state
journal, January 2000
- Brachmann, J.; Soff, S.; Dumitru, A.
- Physical Review C, Vol. 61, Issue 2
Bayesian estimation of the specific shear and bulk viscosity of quark–gluon plasma
journal, August 2019
- Bernhard, Jonah E.; Moreland, J. Scott; Bass, Steffen A.
- Nature Physics, Vol. 15, Issue 11
Solving the quantum many-body problem with artificial neural networks
journal, February 2017
- Carleo, Giuseppe; Troyer, Matthias
- Science, Vol. 355, Issue 6325
The order of the quantum chromodynamics transition predicted by the standard model of particle physics
journal, October 2006
- Aoki, Y.; Endrődi, G.; Fodor, Z.
- Nature, Vol. 443, Issue 7112
Relativistic hadron-hadron collisions in the ultra-relativistic quantum molecular dynamics model
journal, September 1999
- Bleicher, M.; Zabrodin, E.; Spieles, C.
- Journal of Physics G: Nuclear and Particle Physics, Vol. 25, Issue 9
Spinodal Amplification of Density Fluctuations in Fluid-Dynamical Simulations of Relativistic Nuclear Collisions
journal, November 2012
- Steinheimer, Jan; Randrup, Jørgen
- Physical Review Letters, Vol. 109, Issue 21
Collective flow signals the quark–gluon plasma
journal, March 2005
- Stöcker, H.
- Nuclear Physics A, Vol. 750, Issue 1
Discussions on the crossover property within the Nambu–Jona-Lasinio model
journal, December 2013
- Du, Yi-lun; Cui, Zhu-fang; Xia, Yong-hui
- Physical Review D, Vol. 88, Issue 11
Onset of classical QCD dynamics in relativistic heavy ion collisions
journal, May 2005
- Kharzeev, Dmitri; Levin, Eugene; Nardi, Marzia
- Physical Review C, Vol. 71, Issue 5
Regressive and generative neural networks for scalar field theory
journal, July 2019
- Zhou, Kai; Endrődi, Gergely; Pang, Long-Gang
- Physical Review D, Vol. 100, Issue 1
Quantum Chromodynamics at High Energy
book, September 2012
- Kovchegov, Yuri V.; Levin, Eugene
- Cambridge Monographs on Particle Physics, Nuclear Physics and Cosmology
Inhomogeneous phases in the Nambu–Jona-Lasinio and quark-meson model
journal, October 2009
- Nickel, Dominik
- Physical Review D, Vol. 80, Issue 7
GLISSANDO: GLauber Initial-State Simulation AND mOre…
journal, January 2009
- Broniowski, Wojciech; Rybczyński, Maciej; Bożek, Piotr
- Computer Physics Communications, Vol. 180, Issue 1
Color glass condensate at the LHC: hadron multiplicities in pp, pA and AA collisions
journal, January 2005
- Kharzeev, Dmitri; Levin, Eugene; Nardi, Marzia
- Nuclear Physics A, Vol. 747, Issue 2-4
Challenges in QCD matter physics --The scientific programme of the Compressed Baryonic Matter experiment at FAIR
journal, March 2017
- Ablyazimov, T.; Abuhoza, A.; Adak, R. P.
- The European Physical Journal A, Vol. 53, Issue 3
Kinetic description of Bose-Einstein condensation with test particle simulations
journal, July 2017
- Zhou, Kai; Xu, Zhe; Zhuang, Pengfei
- Physical Review D, Vol. 96, Issue 1
Under-saturation of quarks at early stages of relativistic nuclear collisions: The hot glue initial scenario and its observable signatures: Under-saturation of quarks at early stages of relativistic nuclear collisions: The hot glue initial scenario and its observable signatures
journal, November 2015
- Stöcker, H.; Beitel, M.; Biró, T. S.
- Astronomische Nachrichten, Vol. 336, Issue 8-9
High energy heavy ion collisions—probing the equation of state of highly excited hardronic matter
journal, May 1986
- Stöcker, Horst; Greiner, Walter
- Physics Reports, Vol. 137, Issue 5-6
The nuclotron-based ion collider facility (NICA) at JINR: new prospects for heavy ion collisions and spin physics
journal, May 2009
- Sissakian, A. N.; Sorin, A. S.
- Journal of Physics G: Nuclear and Particle Physics, Vol. 36, Issue 6
Machine learning action parameters in lattice quantum chromodynamics
journal, May 2018
- Shanahan, Phiala E.; Trewartha, Daniel; Detmold, William
- Physical Review D, Vol. 97, Issue 9
Hydrodynamical description of 200 A GeV/ c S+Au collisions: Hadron and electromagnetic spectra
journal, January 1997
- Sollfrank, Josef; Huovinen, Pasi; Kataja, Markku
- Physical Review C, Vol. 55, Issue 1
Enhanced Higgs Boson to Search with Deep Learning
journal, March 2015
- Baldi, P.; Sadowski, P.; Whiteson, D.
- Physical Review Letters, Vol. 114, Issue 11
New angles on energy correlation functions
journal, December 2016
- Moult, Ian; Necib, Lina; Thaler, Jesse
- Journal of High Energy Physics, Vol. 2016, Issue 12
Improved version of the PHOBOS Glauber Monte Carlo
journal, September 2015
- Loizides, C.; Nagle, J.; Steinberg, P.
- SoftwareX, Vol. 1-2
Locate QCD critical end point in a continuum model study
journal, July 2014
- Shi, Chao; Wang, Yong-long; Jiang, Yu
- Journal of High Energy Physics, Vol. 2014, Issue 7
Phase diagrams in the three-flavor Nambu–Jona-Lasinio model with the Polyakov loop
journal, June 2008
- Fukushima, Kenji
- Physical Review D, Vol. 77, Issue 11
Nuclear charge radii: density functional theory meets Bayesian neural networks
journal, October 2016
- Utama, R.; Chen, Wei-Chia; Piekarewicz, J.
- Journal of Physics G: Nuclear and Particle Physics, Vol. 43, Issue 11
Effects of initial flow velocity fluctuation in event-by-event (3+1)D hydrodynamics
journal, August 2012
- Pang, Longgang; Wang, Qun; Wang, Xin-Nian
- Physical Review C, Vol. 86, Issue 2
On Information and Sufficiency
journal, March 1951
- Kullback, S.; Leibler, R. A.
- The Annals of Mathematical Statistics, Vol. 22, Issue 1
New Developments in Relativistic Viscous Hydrodynamics
journal, January 2010
- Romatschke, Paul
- International Journal of Modern Physics E, Vol. 19, Issue 01
Elliptic and Triangular Flow in Event-by-Event Viscous Hydrodynamics
journal, January 2011
- Schenke, Björn; Jeon, Sangyong; Gale, Charles
- Physical Review Letters, Vol. 106, Issue 4
Phase Diagram and Critical End Point for Strongly Interacting Quarks
journal, April 2011
- Qin, Si-xue; Chang, Lei; Chen, Huan
- Physical Review Letters, Vol. 106, Issue 17
Learning thermodynamics with Boltzmann machines
journal, October 2016
- Torlai, Giacomo; Melko, Roger G.
- Physical Review B, Vol. 94, Issue 16
Methodology study of machine learning for the neutron star equation of state
journal, July 2018
- Fujimoto, Yuki; Fukushima, Kenji; Murase, Koichi
- Physical Review D, Vol. 98, Issue 2
Conformal relativistic viscous hydrodynamics: Applications to RHIC results at GeV
journal, September 2008
- Luzum, Matthew; Romatschke, Paul
- Physical Review C, Vol. 78, Issue 3
Searching for exotic particles in high-energy physics with deep learning
journal, July 2014
- Baldi, P.; Sadowski, P.; Whiteson, D.
- Nature Communications, Vol. 5, Issue 1
Machine learning spatial geometry from entanglement features
journal, January 2018
- You, Yi-Zhuang; Yang, Zhao; Qi, Xiao-Liang
- Physical Review B, Vol. 97, Issue 4
Anisotropic hydrodynamics for rapidly expanding systems
journal, October 2013
- Florkowski, Wojciech; Ryblewski, Radoslaw; Strickland, Michael
- Nuclear Physics A, Vol. 916
Analytical and numerical Gubser solutions of the second-order hydrodynamics
journal, April 2015
- Pang, Long-Gang; Hatta, Yoshitaka; Wang, Xin-Nian
- Physical Review D, Vol. 91, Issue 7
Deep learning in neural networks: An overview
journal, January 2015
- Schmidhuber, Jürgen
- Neural Networks, Vol. 61
Non-Gaussian Fluctuations near the QCD Critical Point
journal, January 2009
- Stephanov, M. A.
- Physical Review Letters, Vol. 102, Issue 3
Multiphase transport model for relativistic heavy ion collisions
journal, December 2005
- Lin, Zi-Wei; Ko, Che Ming; Li, Bao-An
- Physical Review C, Vol. 72, Issue 6
Influence of Shear Viscosity of Quark-Gluon Plasma on Elliptic Flow in Ultrarelativistic Heavy-Ion Collisions
journal, May 2011
- Niemi, H.; Denicol, G. S.; Huovinen, P.
- Physical Review Letters, Vol. 106, Issue 21
The QCD transition temperature: Results with physical masses in the continuum limit
journal, November 2006
- Aoki, Y.; Fodor, Z.; Katz, S. D.
- Physics Letters B, Vol. 643, Issue 1
Results from the experiment E895 at the BNL AGS
journal, December 1999
- Rai, G.; Ajitanand, N. N.; Alexander, J.
- Nuclear Physics A, Vol. 661, Issue 1-4
Application of a neural network to the sign problem via the path optimization method
journal, February 2018
- Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira
- Progress of Theoretical and Experimental Physics, Vol. 2018, Issue 2
Parton shower uncertainties in jet substructure analyses with deep neural networks
journal, January 2017
- Barnard, James; Dawe, Edmund Noel; Dolan, Matthew J.
- Physical Review D, Vol. 95, Issue 1
Thermodynamics and critical behavior in the Nambu–Jona-Lasinio model of QCD
journal, May 2008
- Costa, P.; Ruivo, M. C.; de Sousa, C. A.
- Physical Review D, Vol. 77, Issue 9
Hydrodynamics near the QCD Phase Transition: Looking for the Longest-Lived Fireball
journal, November 1995
- Hung, C. M.; Shuryak, E. V.
- Physical Review Letters, Vol. 75, Issue 22
The iEBE-VISHNU code package for relativistic heavy-ion collisions
journal, February 2016
- Shen, Chun; Qiu, Zhi; Song, Huichao
- Computer Physics Communications, Vol. 199
Signatures of the Tricritical Point in QCD
journal, November 1998
- Stephanov, M.; Rajagopal, K.; Shuryak, E.
- Physical Review Letters, Vol. 81, Issue 22
The phase transition to the quark-gluon plasma and its effect on hydrodynamic flow
journal, June 1995
- Rischke, Dirk H.; Pürsün, Yariş; Maruhn, Joachim A.
- Acta Physica Hungarica A) Heavy Ion Physics, Vol. 1, Issue 3-4
Works referencing / citing this record:
E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once
text, January 2021
- Nachman, Benjamin; Thaler, Jesse
- arXiv