RUI: Neutrino Oscillation Studies with MINOS and Super-K

这项提案请求支持明尼苏达大学德卢斯分校(UMD)的研究，在NSF本科生机构研究(RUI)计划下，使用费米拉和索丹的MINOS(主注入中微子振荡搜索)探测器以及日本的Super-Kamiokande探测器来研究中微子振荡。Super-K最近的结果使用了宇宙射线与高层大气相互作用产生的中微子，有力地表明，能量从几百MeV到几百GeV的Muon中微子在穿过地球数万公里到达探测器时会振荡为tau中微子。这意味着中微子携带的质量不为零。目前正在建造MINOS实验，以明确证实这一结果，并使用费米实验室产生的经过良好校准的人造中微子束精确测量振荡参数。这些中微子将被类似的探测器观测到，这些中微子位于费米实验室的发源地附近，并在穿越730公里到达明尼苏达州北部的苏丹矿后被观测到。这两个探测器信号的差异将提供迄今为止对中微子振荡参数的最佳测量。这里提议的工作是让一名物理学家PI和两名本科生参与MINOS FAR探测器的建造，并开发探测器控制系统的一部分。此外，研究人员将继续参与Super-K探测器的操作，收集更多数据以提高其统计意义，同时改进分析技术。

This proposal requests support for research at the University of Minnesota Duluth (UMD) to study neutrino oscillations using the MINOS (Main Injector Neutrino Oscillation Search) detectors at Fermilab and Soudan, and the Super-Kamiokande detector in Japan, under the NSF Research at Undergraduate Institutions (RUI) program. Recent results from Super-K have used neutrinos produced in cosmic ray interactions with the upper atmosphere to strongly suggest that muon neutrinos of energies from a few hundred MeV to a few hundred GeV oscillate to tau neutrinos as they travel the tens of thousands of kilometers through the earth to the detector. This would imply that neutrinos carry non-zero mass. The MINOS experiment is currently being constructed both to unambiguously confirm this result and to measure precisely the oscillation parameters using an intense well-calibrated man-made beam of neutrinos generated at Fermilab. The neutrinos will be observed by similar detectors near their origin in Fermilab and after travelling the 730-km to the Soudan mine in northern Minnesota. The differences in the signals at the two detectors will provide the best measurement yet of neutrino oscillation parameters. The work being proposed here is for one physicist PI and two undergraduate students to participate in the construction of the MINOS far detector and to develop part of the Detector Control System. Additionally, the researchers will continue to participate in the operation of the Super-K detector, gathering more data to improve its statistical significance while improving the analysis techniques.