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arXiv 0907.0274nucl-th
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用关联多项式分析K介子光生的微分截面

Differential cross section analysis in kaon photoproduction using associated legendre polynomials

P. T. P. Hutauruk, D. G. Ireland, G. Rosner

摘要:

本文利用最新的CLAS数据集\cite{bradford},对反应$γ+p {\to} K^{+} + Λ$的微分截面角分布进行了分析。这一分析是基于参考文献\cite{fasano}中的理论计算,其中K介子光生过程中的所有16个观测量可分为4个勒让德类。每一个可观测的可以通过相关联的勒让德多项式函数的展开来描述。要解决的问题之一是需要多少相关的勒让德多项式来描述数据。在这个初步分析中,我们使用了具有不同数量的相关勒让德多项式的数据模型。然后,我们通过计算模型的后验概率来比较这些模型。我们发现,CLAS数据集只需要不超过四个相关的勒让德多项式来描述微分截面数据。此外,我们还展示了最佳模型的提取系数。

英文摘要:

Angular distributions of differential cross sections from the latest CLAS data sets \cite{bradford}, for the reaction $γ+p {\to} K^{+} + Λ$ have been analyzed using associated Legendre polynomials. This analysis is based upon theoretical calculations in Ref. \cite{fasano} where all sixteen observables in kaon photoproduction can be classified into four Legendre classes. Each observable can be described by an expansion of associated Legendre polynomial functions. One of the questions to be addressed is how many associated Legendre polynomials are required to describe the data. In this preliminary analysis, we used data models with different numbers of associated Legendre polynomials. We then compared these models by calculating posterior probabilities of the models. We found that the CLAS data set needs no more than four associated Legendre polynomials to describe the differential cross section data. In addition, we also show the extracted coefficients of the best model.

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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