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arXiv 2401.04065hep-exphysics.data-an
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中微子截面提取的数学方法

Mathematical methods for neutrino cross-section extraction

Steven Gardiner

AI总结:

本文综述 MINERvA、MicroBooNE 和 T2K 的中微子截面提取方法,并提出分块展开与条件协方差背景约束两种技术以改进常规流程。

摘要:

随着基于加速器的中微子振荡实验寻求有关中微子性质的开放问题的明确答案,中微子-原子核散射的精确建模正变得愈发重要。为指导所需的模型改进,越来越多的实验合作组正在开展一项覆盖广泛的 GeV 能区中微子相互作用测量计划。在大多数此类分析中,关键步骤是截面提取,即对测量到的事例计数进行背景污染和不完美探测器性能校正,以得到可直接与理论预测比较的截面结果。本文中,我利用来自 MINERvA、MicroBooNE 和 T2K 实验的代表性例子,综述文献中截面提取的主要方法。随后,我提出两种数学技术:分块展开和条件协方差背景约束,它们克服了典型截面提取流程的部分局限。

英文摘要:

Precise modeling of neutrino-nucleus scattering is becoming increasingly important as accelerator-based oscillation experiments seek definitive answers to open questions about neutrino properties. To guide the needed model refinements, a growing number of experimental collaborations are pursuing a wide-ranging program of neutrino interaction measurements at GeV energies. A key step in most such analyses is cross-section extraction, in which measured event counts are corrected for background contamination and imperfect detector performance to yield cross-section results that are directly comparable to theoretical predictions. In this paper, I review the major approaches to cross-section extraction in the literature using representative examples from the MINERvA, MicroBooNE, and T2K experiments. I then present two mathematical techniques, blockwise unfolding and the conditional covariance background constraint, which overcome some limitations of typical cross-section extraction procedures.

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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