论文标题
通过缩放性能在重离子碰撞中探测Parton能量损失的路径长度依赖性
Probing the path-length dependence of parton energy loss via scaling properties in heavy ion collisions
论文作者
论文摘要
The scaling property of large-$p_\perp$ hadron suppression, $R_{\rm{AA}}(p_\perp)$, measured in heavy ion collisions at RHIC and LHC leads to the determination of the average parton energy loss $\langle ε\rangle$ in quark-gluon plasma produced in a variety of collision systems and centrality classes.将$ \ langle的ε\ rangle $与粒子多重性和碰撞几何形状相关联,可以探测Parton能量损失对路径长度$ L $的依赖性。我们发现,$ \langleε\ rangle \ propto l^β$带有$β= 1.02^{+0.09} _ { - 0.06} $,与PQCD期望在纵向扩展的Quark-Gluon Plasma中对Parton Energy损失的期望一致。然后,我们证明了方位角各向异性系数除以碰撞偏心度,$ v_2/\ textrm {e} $遵循与$ r _ {\ rm {aa}} $相同的缩放属性。在数据中观察到此缩放,该数据由大型$ p_ \ perp $以模型复制。最后,在数据中找到并确认了$ v_2/\ textrm {e} $与$ r _ {\ rm {aa}} $的对数导数之间的线性关系,并在数据中确认并确认,提供另一种方法来探测$ l $ lhc sumely of Parton Energe损失的$ l $ lhc依赖性。
The scaling property of large-$p_\perp$ hadron suppression, $R_{\rm{AA}}(p_\perp)$, measured in heavy ion collisions at RHIC and LHC leads to the determination of the average parton energy loss $\langle ε\rangle$ in quark-gluon plasma produced in a variety of collision systems and centrality classes. Relating $\langle ε\rangle$ to the particle multiplicity and collision geometry allows for probing the dependence of parton energy loss on the path-length $L$. We find that $\langle ε\rangle \propto L^β$ with $β=1.02^{+0.09}_{-0.06}$, consistent with the pQCD expectation of parton energy loss in a longitudinally expanding quark-gluon plasma. We then demonstrate that the azimuthal anisotropy coefficient divided by the collision eccentricity, $v_2/\textrm{e}$, follows the same scaling property as $R_{\rm{AA}}$. This scaling is observed in data, which are reproduced by the model at large $p_\perp$. Finally, a linear relationship between $v_2/\textrm{e}$ and the logarithmic derivative of $R_{\rm{AA}}$ is found and confirmed in data, offering an additional way to probe the $L$ dependence of parton energy loss using coming measurements from LHC Run 3.