论文标题
使用神经网络的$ξ^ - /\barξ^+$的碎片功能
Fragmentation Functions for $Ξ^-/\barΞ^+$ Using Neural Networks
论文作者
论文摘要
我们从单个包容性电子静脉歼灭的数据中介绍了八位位baryon $ξ^ - /\barξ^+$的片段化函数（FFS）的确定。我们在此QCD分析中的参数化是根据神经网络（NN）提供的。我们在近代领先顺序下确定$ξ^ - /\ bar配$ $的片段函数，在扰动QCD中首次在近隔到领先的顺序上。我们讨论了高阶QCD校正的改进，拟合质量以及我们的理论结果与拟合数据集的比较。作为名为SHKS22的新型片段化函数集的应用，我们介绍了$ξ^ - / \barξ^+$ baryon在proton-proton碰撞中的预测。
We present a determination of fragmentation functions (FFs) for the octet baryon $Ξ^-/\barΞ^+$ from data for single inclusive electron-positron annihilation. Our parametrization in this QCD analysis is provided in terms of a Neural Network (NN). We determine fragmentation functions for $Ξ^-/\barΞ^+$ at next-to-leading order and for the first time at next-to-next-to-leading order in perturbative QCD. We discuss the improvement of higher-order QCD corrections, the quality of fit, and the comparison of our theoretical results with the fitted datasets. As an application of our new set of fragmentation functions, named SHKS22, we present predictions for $Ξ^- / \barΞ^+$ baryon production in proton-proton collisions at the LHC experiments.
