arXiv · 2401.00402
3D Multi-system Bayesian Calibration with Energy Conservation to Study Rapidity-dependent Dynamics of Nuclear Collisions
Abstract
Considerable information about the early-stage dynamics of heavy-ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems -- large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late- time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.
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Andi Mankolli, Aaron Angerami, Ritu Arora, Steffen Bass, Shanshan Cao, Yi Chen, Lipei Du, Raymond Ehlers, Hannah Elfner, Wenkai Fan, Rainer J. Fries, Charles Gale, Yayun He, Ulrich Heinz, Barbara Jacak, Peter Jacobs, Sangyong Jeon, Yi Ji, Lauren Kasper, Michael Kordell II, Amit Kumar, R. Kunnawalkam-Elayavalli, Joseph Latessa, Sook H. Lee, Yen-Jie Lee, Dananjaya Liyanage, Matt Luzum, Abhijit Majumder, Simon Mak, Christal Martin, Haydar Mehryar, Tanner Mengel, James Mulligan, Christine Nattrass, Jean-Francois Paquet, Cameron Parker, Joern H. Putschke, Gunther Roland, Bjoern Schenke, Loren Schwiebert, Arjun Sengupta, Chun Shen, Chathuranga Sirimanna, Ron A. Soltz, Ismail Soudi, Michael Strickland, Yasuki Tachibana, Julia Velkovska, Gojko Vujanovic, Xin-Nian Wang, Wenbin Zhao. 2023-12-31. 3D Multi-system Bayesian Calibration with Energy Conservation to Study Rapidity-dependent Dynamics of Nuclear Collisions. https://arxiv.org/abs/2401.00402
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