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Related papers: Bayesian analysis of (3+1)D relativistic nuclear d…

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We apply the Bayesian model selection method (based on the Bayes factor) to optimize $\sqrt{s_\mathrm{NN}}$-dependence in the phenomenological parameters of the (3+1)-dimensional hybrid framework for describing relativistic heavy-ion…

Nuclear Theory · Physics 2026-03-02 Syed Afrid Jahan , Hendrik Roch , Chun Shen

This work presents the first Bayesian inference study of the (3+1)D dynamics of relativistic heavy-ion collisions and Quark-Gluon Plasma (QGP) viscosities using an event-by-event (3+1)D hydrodynamics + hadronic transport theoretical…

Nuclear Theory · Physics 2023-10-18 Chun Shen , Björn Schenke , Wenbin Zhao

Recent theory progresses in (3+1)D dynamical descriptions of relativistic nuclear collisions at finite baryon density are reviewed. Heavy-ion collisions at different collision energies produce strongly coupled nuclear matter to probe the…

Nuclear Theory · Physics 2022-02-16 Chun Shen

Using a hybrid (viscous hydrodynamics + hadronic cascade) framework, we model the bulk dynamical evolution of relativistic heavy-ion collisions at Relativistic Heavy Ion Collider (RHIC) Beam Energy Scan (BES) collision energies, including…

Nuclear Theory · Physics 2018-03-14 Chun Shen , Gabriel Denicol , Charles Gale , Sangyong Jeon , Akihiko Monnai , Bjoern Schenke

Posterior distributions for physical parameters describing relativistic heavy-ion collisions, such as the viscosity of the quark-gluon plasma, are extracted through a comparison of hydrodynamic-based transport models to experimental results…

Nuclear Theory · Physics 2015-06-15 John Novak , Kevin Novak , Scott Pratt , J. Vredevoogd , Chris Coleman-Smith , Robert Wolpert

The quality of data taken at RHIC and LHC as well as the success and sophistication of computational models for the description of ultra-relativistic heavy-ion collisions have advanced to a level that allows for the quantitative extraction…

Nuclear Theory · Physics 2018-03-14 Steffen A. Bass , Jonah E. Bernhard , J. Scott Moreland

In nuclear and particle physics, reconciling sophisticated simulations with experimental data is vital for understanding complex systems like the Quark Gluon Plasma (QGP) generated in heavy-ion collisions. However, computational demands…

Nuclear Theory · Physics 2026-02-03 Hendrik Roch , Syed Afrid Jahan , Chun Shen

We present a fully three-dimensional model providing initial conditions for energy and conserved charge density distributions in heavy ion collisions at RHIC Beam Energy Scan (BES) collision energies. The model includes the dynamical…

Nuclear Theory · Physics 2019-02-20 Chun Shen , Björn Schenke

Heavy-ion collisions provide a window into the properties of many-body systems of deconfined quarks and gluons. Understanding the collective properties of quarks and gluons is possible by comparing models of heavy-ion collisions to…

Nuclear Theory · Physics 2025-02-06 Jean-François Paquet

We extend the well-studied midrapidity TRENTo initial-conditions model to three dimensions, thus facilitating (3+1)D modeling and analysis of ultrarelativistic heavy-ion collisions at RHIC and LHC energies. TRENTo-3D is a fast, parametric…

Nuclear Theory · Physics 2023-06-16 Derek Soeder , Weiyao Ke , J. -F. Paquet , Steffen A. Bass

We perform a study of electromagnetic radiation in heavy-ion collisions at Relativistic Heavy Ion Collider (RHIC) Beam Energy Scan (BES) and SPS energies using the iEBE-MUSIC framework, which includes 3D dynamical Monte Carlo Glauber…

Nuclear Theory · Physics 2025-11-13 Xiang-Yu Wu , Charles Gale , Sangyong Jeon , Jean-François Paquet , Björn Schenke , Chun Shen

We apply a 3+1D viscous hydrodynamic + cascade model to the heavy ion collision reactions with $\sqrt{s_{NN}}=6.3\dots39$ GeV. To accommodate the model for a given collision energy range, the initial conditions for hydrodynamic phase are…

Nuclear Theory · Physics 2014-09-08 Iu. Karpenko , M. Bleicher , P. Huovinen , H. Petersen

We present algorithms to solve relativistic hydrodynamics in 3+1--dimensional situations without apparent symmetry to simplify the solution. In simulations of heavy--ion collisions, these numerical schemes have to deal with the physical…

Nuclear Theory · Physics 2009-10-28 Dirk H. Rischke , Stefan Bernard , Joachim A. Maruhn

The study of heavy-ion collisions presents a challenge to both theoretical and experimental nuclear physics. Due to the extremely short lifetime and small size of the collision system, disentangling information provided by experimental…

High Energy Physics - Phenomenology · Physics 2021-08-27 Derek Everett

We provide a concise review on recent theory advancements towards full-fledged (3+1)D dynamical descriptions of relativistic nuclear collisions at finite baryon density. Heavy-ion collisions at different collision energies produce…

Nuclear Theory · Physics 2021-10-27 Shanjin Wu , Chun Shen , Huichao Song

We present calculations of bulk properties and multiparticle correlations in a large variety of collision systems within a hybrid formalism consisting of IP-Glasma initial conditions, MUSIC viscous relativistic hydrodynamics, and UrQMD…

Nuclear Theory · Physics 2020-10-21 Bjoern Schenke , Chun Shen , Prithwish Tribedy

We numerically analyze recent high energy heavy-ion collision experiments based on a hydrodynamical model with phase transition and discuss a systematic change of initial state of QGP-fluid depending on colliding-nuclei's mass. In a…

Nuclear Theory · Physics 2016-09-08 Shin Muroya , Hiroki Nakamura , Mikio Namiki

We review integrated dynamical approaches to describe heavy ion reaction as a whole at ultrarelativistic energies. Since final observables result from all the history of the reaction, it is important to describe all the stages of the…

Nuclear Theory · Physics 2015-06-04 Tetsufumi Hirano , Pasi Huovinen , Koichi Murase , Yasushi Nara

We develop a neural network model, based on the processes of high-energy heavy-ion collisions, to study and predict several experimental observables in Au+Au collisions. We present a data-driven deep learning framework for predicting…

Nuclear Theory · Physics 2026-01-06 Jun-Qi Tao , Xiang Fan , Yang Liu , Yu Sha , Kai Zhou , Hua Zheng , Ben-Wei Zhang
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