AI 中文总结
本研究利用改进的CCAKE代码和MUSES状态方程，在相对论粘性流体动力学框架下动态搜寻QCD临界点，量化束流能量、临界点位置与快度范围的关联。
AI 中文摘要
随着STAR的束流能量扫描二期（BES II），已有大量数据可用于搜寻QCD临界点。然而，一个核心挑战在于临界点无法直接从数据中提取，而是在一个膨胀、冷却且可能远离平衡的系统中被动态探测。在本次报告中，我们展示了由MUSES合作组生成、具有可移动临界点的状态方程在3+1维相对论粘性流体动力学代码CCAKE中的最新运行结果。我们讨论了CCAKE的数值改进，包括“玻璃”初始条件和自适应光滑粒子流体动力学，从而能够快速且准确地获得流体动力学运动方程的数值解。我们能够量化束流能量、临界点位置和快度范围之间的相互作用。
英文摘要
With the STAR's Beam Energy Scan II, a rich amount of data exists to search for the QCD critical point. However, a central challenge is that the critical point cannot be directly extracted from data but rather is probed dynamically in an expanding, cooling system that may be far-from-equilibrium. In this talk, we show the latest results from equations of state with a movable critical point generated by the MUSES collaboration, run in the 3+1D relativistic viscous hydrodynamics code CCAKE. We discuss numerical improvements to CCAKE that include ``glass'' initial conditions and adaptive smoothed particle hydrodynamics, allowing us to rapidly and accurately obtain numerical solutions to the hydrodynamic equations of motion. We can quantify the interplay between beam energy, location of the critical point, and rapidity range.
Comments6 pages, 3 figures
