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arXiv 2408.00537nucl-thhep-ph
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基于RHIC束能扫描数据的(3+1)维相对论核动力学的贝叶斯分析

Bayesian analysis of (3+1)D relativistic nuclear dynamics with the RHIC beam energy scan data

Wayne State University(韦恩州立大学)

Syed Afrid Jahan, Hendrik Roch, Chun Shen

AI总结:

本文基于RHIC束能扫描数据,利用贝叶斯方法分析(3+1)维相对论核动力学,探讨模型模拟器精度对后验分布和观测量预测的影响。

摘要:

本文介绍了在相对论重离子对撞机的束能扫描计划中,对相对论重离子碰撞进行贝叶斯推断研究。理论模型利用流体动力学和有核输运理论,模拟事件级的(3+1)维碰撞动力学。我们分析了通过三种不同精度的模型模拟器获得的模型20维后验分布,并展示了训练准确模型模拟器在贝叶斯分析中的关键作用。我们的分析为夸克-胶子等离子体的输运性质以及(3+1)维相对论核动力学的各个方面提供了稳健的约束。通过运行100个从后验分布中采样的参数集进行完整模型模拟,我们对$p_{\rm T}$-微分观测量进行预测,并估计其系统理论不确定性。进行了灵敏度分析,以阐明各个实验观测量如何响应不同的模型参数,为重离子碰撞的现象学模型提供了有用的物理见解。

英文摘要:

This work presents a Bayesian inference study for relativistic heavy-ion collisions in the Beam Energy Scan program at the Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)D collision dynamics using hydrodynamics and hadronic transport theory. We analyze the model's 20-dimensional posterior distributions obtained using three model emulators with different accuracy and demonstrate the essential role of training an accurate model emulator in the Bayesian analysis. Our analysis provides robust constraints on the Quark-Gluon Plasma's transport properties and various aspects of (3+1)D relativistic nuclear dynamics. By running full model simulations with 100 parameter sets sampled from the posterior distribution, we make predictions for $p_{\rm T}$-differential observables and estimate their systematic theory uncertainty. A sensitivity analysis is performed to elucidate how individual experimental observables respond to different model parameters, providing useful physics insights into the phenomenological model for heavy-ion collisions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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