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arXiv 2202.10779hep-phhep-ex
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SIDIS数据下带电强子碎裂函数的神经网络QCD分析

Neural Network QCD analysis of charged hadron Fragmentation Functions in the presence of SIDIS data

Maryam Soleymaninia, Hadi Hashamipour, Hamzeh Khanpour

摘要:

本文利用QCD方法从高能轻子-轻子湮灭和轻子-强子散射数据中提取了一个未知轻荷强子SHK22.h的碎裂函数。该分析包括所有可用的单包容性电子正电子湮没(SIA)过程和半包容性深非弹性散射(SIDIS)测量的数据为不明的轻带电强子生产。通过COMPASS实验测量的SIDIS数据可以很好地约束FF的风味依赖性。我们利用神经网络(NN)的解析导数拟合的FF在下一个引导阶(NLO)的精度在微扰QCD(pQCD)。Monte Carlo方法适用于所有实验不确定性来源和部分子分布函数(PDF)。SHK22.h FF集与文献中最新的QCD拟合,即JAM 20和NNFF 1.1h之间实现了非常好的一致性。此外,我们讨论了所产生的影响,包括SIDIS数据上提取的轻荷强子FF。在非线性光学条件下得到的带电强子FFS的整体QCD结果为带电强子末态过程的高能测量提供了有价值的应用。

英文摘要:

In this paper, we present a QCD analysis to extract the Fragmentation Functions (FFs) of unidentified light charged hadron entitled as SHK22.h from high-energy lepton-lepton annihilation and lepton-hadron scattering data sets. This analysis includes the data from all available single inclusive electron-positron annihilation (SIA) processes and semi-inclusive deep-inelastic scattering (SIDIS) measurements for the unidentified light charged hadron productions. The SIDIS data which has been measured by the COMPASS experiment could allow the flavor dependence of the FFs to be well constrained. We exploit the analytic derivative of the Neural Network (NN) for fitting of FFs at next-to-leading-order (NLO) accuracy in the perturbative QCD (pQCD). The Monte Carlo method is implied for all sources of experimental uncertainties and the Parton distribution functions (PDFs) as well. Very good agreements are achieved between the SHK22.h FFs set and the most recent QCD fits available in literature, namely JAM20 and NNFF1.1h. In addition, we discuss the impact arising from the inclusion of SIDIS data on the extracted light-charged hadron FFs. The global QCD resulting at NLO for charged hadron FFs provides valuable insights for applications in present and future high-energy measurement of charged hadron final state processes.

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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