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An equation-of-state-meter of quantum chromodynamics transition from deep learning

Nature communications, 2018-01, Vol.9 (1), p.210-6, Article 210

2018

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Pseudorapidity distribution and decorrelation of anisotropic flow within the open-computing-language implementation CLVisc hydrodynamics

Physical review. C, 2018-06, Vol.97 (6), Article 064918

2018

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A machine learning study to identify spinodal clumping in high energy nuclear collisions

The journal of high energy physics, 2019-12, Vol.2019 (12), p.1-26, Article 122

2019

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Exploring QCD matter in extreme conditions with Machine Learning

Progress in particle and nuclear physics, 2024-02, Vol.135, p.104084, Article 104084

2024

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Effects of jet-induced medium excitation in γ-hadron correlation in A+A collisions

Physics letters. B, 2018-02, Vol.777 (C), p.86-90

2018

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Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning

The European physical journal. C, Particles and fields, 2020-06, Vol.80 (6), p.1-17, Article 516

2020

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Polarization of massive fermions in a vortical fluid

Physical review. C, 2016-08, Vol.94 (2), Article 024904

2016

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Interplaying mechanisms behind single inclusive jet suppression in heavy-ion collisions

Physical review. C, 2019-05, Vol.99 (5), Article 054911

2019

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Medium modification of γ-jet fragmentation functions in Pb+Pb collisions at LHC

Physics letters. B, 2020-11, Vol.810 (C), p.135783, Article 135783

2020

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Longitudinal fluctuations and decorrelations of anisotropic flows at energies available at the CERN Large Hadron Collider and at the BNL Relativistic Heavy Ion Collider

Physical review. C, 2018-08, Vol.98 (2), Article 024913

2018

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Probing criticality with deep learning in relativistic heavy-ion collisions

Physics letters. B, 2022-04, Vol.827, p.137001, Article 137001

2022

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High-energy nuclear physics meets machine learning

Nuclear science and techniques, 2023-06, Vol.34 (6), p.82-114, Article 88

2023

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Local spin polarization in high energy heavy ion collisions

Physical review research, 2019-10, Vol.1 (3), Article 033058

2019

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Decorrelation of anisotropic flow along the longitudinal direction

The European physical journal. A, Hadrons and nuclei, 2016-04, Vol.52 (4), Article 97

2016

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Deep-learning quasi-particle masses from QCD equation of state

Physics letters. B, 2023-09, Vol.844, p.138088, Article 138088

2023

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Longitudinal decorrelation of anisotropic flows in heavy-ion collisions at the CERN Large Hadron Collider

Physical review. C, Nuclear physics, 2015-04, Vol.91 (4), Article 044904

2015

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Deep learning assisted jet tomography for the study of Mach cones in QGP

The European physical journal. C, Particles and fields, 2023-07, Vol.83 (7), p.652-14, Article 652

2023

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Global Λ polarization in heavy-ion collisions from a transport model

Physical review. C, 2017-11, Vol.96 (5), Article 054908

2017

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Vortical Fluid and Λ Spin Correlations in High-Energy Heavy-Ion Collisions

Physical review letters, 2016-11, Vol.117 (19), p.192301-192301, Article 192301

2016

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Phase Transition Study Meets Machine Learning

Chinese physics letters, 2023-12, Vol.40 (12), p.122101

2023

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Classify QCD phase transition with deep learning

Nuclear physics. A, 2019-02, Vol.982 (C), p.867-870

2019

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Microscopic study of deuteron production in PbPb collisions at s = 2.76 TeV via hydrodynamics and a hadronic afterburner

Physical review. C, 2019-04, Vol.99 (4), Article 044907

2019

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Local and global Λ polarization in a vortical fluid

Nuclear physics. A, 2017-11, Vol.967 (C), p.772-775

2017

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Machine learning for high energy heavy ion collisions

Nuclear physics. A, 2021-01, Vol.1005, p.121972, Article 121972

Pang, Long-Gang

2021

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Gradient Tomography of Jet Quenching in Heavy-Ion Collisions

Physical review letters, 2020-09, Vol.125 (12), p.1-122301, Article 122301

2020

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An equation-of-state-meter of quantum chromodynamics transition from deep learning

Pseudorapidity distribution and decorrelation of anisotropic flow within the open-computing-language implementation CLVisc hydrodynamics

A machine learning study to identify spinodal clumping in high energy nuclear collisions

Exploring QCD matter in extreme conditions with Machine Learning

Effects of jet-induced medium excitation in γ-hadron correlation in A+A collisions

Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning

Polarization of massive fermions in a vortical fluid

Interplaying mechanisms behind single inclusive jet suppression in heavy-ion collisions

Medium modification of γ-jet fragmentation functions in Pb+Pb collisions at LHC

Longitudinal fluctuations and decorrelations of anisotropic flows at energies available at the CERN Large Hadron Collider and at the BNL Relativistic Heavy Ion Collider

Probing criticality with deep learning in relativistic heavy-ion collisions

High-energy nuclear physics meets machine learning

Local spin polarization in high energy heavy ion collisions

Decorrelation of anisotropic flow along the longitudinal direction

Deep-learning quasi-particle masses from QCD equation of state

Longitudinal decorrelation of anisotropic flows in heavy-ion collisions at the CERN Large Hadron Collider

Deep learning assisted jet tomography for the study of Mach cones in QGP

Global Λ polarization in heavy-ion collisions from a transport model

Vortical Fluid and Λ Spin Correlations in High-Energy Heavy-Ion Collisions

Phase Transition Study Meets Machine Learning

Classify QCD phase transition with deep learning

Microscopic study of deuteron production in PbPb collisions at s = 2.76 TeV via hydrodynamics and a hadronic afterburner

Local and global Λ polarization in a vortical fluid

Machine learning for high energy heavy ion collisions

Gradient Tomography of Jet Quenching in Heavy-Ion Collisions

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