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arXiv 2202.05586hep-ph
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基于神经网络的$Ξ^-/\barΞ^+$分段函数

Fragmentation Functions for $Ξ^-/\barΞ^+$ Using Neural Networks

Maryam Soleymaninia, Hadi Hashamipour, Hamzeh Khanpour, Hubert Spiesberger

摘要:

本文从单重态电子正电子湮没的数据出发,确定了八重态重子$Ξ^-/\barΞ^+$的碎裂函数。我们在这个QCD分析的参数化提供了一个神经网络(NN)。我们确定了$Ξ^-/\barΞ^+$在次-首阶和首次在微扰QCD中次-首阶的碎裂函数。我们讨论了高阶QCD修正的改进,拟合的质量,以及我们的理论结果与拟合数据集的比较。作为我们新的碎裂函数SHKS 22的应用,我们给出了在LHC实验中质子-质子碰撞中产生$Ξ^- / \barΞ^+$重子的预言。

英文摘要:

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.

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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