Tau Neutrino Appearance in the Flux of Atmospheric Neutrinos at the Super-Kamiokande Experiment
Tau Neutrino Appearance in the Flux of Atmospheric Neutrinos at the Super-Kamiokande Experiment
复制标题
超级神冈实验中大气中微子通量中 Tau 中微子的出现
DOI：
10.22323/1.414.1074
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Maitrayee Mandal
中科院分区：
文献类型：
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作者：
Maitrayee Mandal
超级神冈实验（英语：Super-Kamiokande experiment，简称Super-K）是一个水切伦科夫探测器，以发现大气中微子振荡而闻名。μ中微子在大气中振荡的主要效应是τ中微子的出现。直接探测大气中中微子中微子的ν τ将提供中微子振荡的明确证实。在Super-K上研究了次主导的ν μ振荡模式，即ν μ变为ν e，以确定质量有序。目前，在Super-K分析中，ν τ相互作用形成质量有序信号的最大背景。超级K使用神经网络的机器学习技术，将ν τ带电电流相互作用与大气μ介子和电子中微子的相互作用分离。通过扩大探测器的基准体积，可以将10%以上的事件添加到分析中。对2008年至2018年的超级K运行期间的蒙特-卡罗模拟的研究表明，我们可以期待在寻找τ中微子和抑制质量排序背景方面的改进。
The Super-Kamiokande experiment (Super-K) is a water Cherenkov detector noted for its discovery of the oscillation of atmospheric neutrinos. The dominant effect of the oscillation of muon neutrinos in the atmosphere is the appearance of tau neutrinos. Direct detection of ν τ in the atmospheric neutrino flux would provide a clear confirmation of neutrino oscillations. The sub-dominant ν µ oscillation mode, of ν µ changing to ν e , is studied at Super-K to determine mass ordering. Currently, ν τ interactions form the biggest background to the mass ordering signal in the Super-K analysis. Machine learning techniques of neural networks are used at Super-K to segregate ν τ charged-current interactions from the interactions of the atmospheric muon and electron neutrinos. 10% more events can be added to the analysis by expanding the fiducial volume of the detector. Studies on the Monte-Carlo simulations for a Super-K run period, between 2008 to 2018, suggest that we can expect improvements in the search for tau neutrinos and the suppression of mass-ordering backgrounds.
影响因子：
5
作者：
Z. Li;K. Abe;C. Bronner;Y. Hayato;M. Ikeda;K. Iyogi;J. Kameda;Y. Kato;Y. Kishimoto;L. Marti
通讯作者：
Z. Li;K. Abe;C. Bronner;Y. Hayato;M. Ikeda;K. Iyogi;J. Kameda;Y. Kato;Y. Kishimoto;L. Marti