Study of neutrino physics in MicroBooNE

以前的中微子实验已经观察到了意外的过量事件，这可能表明了一种新型的中微子-无菌中微子。如果得到证实，这种新粒子将是超越标准模型的物理学的明确证据，寻找新的物理学一直是所有粒子物理学家的圣杯。美国费米实验室的短基线中微子（SBN）计划旨在直接解决这些异常现象，并将为这个长期存在的难题提供明确的答案。MicroBooNE是SBN计划的第一个探测器。170吨液态氩探测器于2015年秋季开始记录中微子数据，目前正在进行数据分析。MicroBooNE探测器出色的图像分辨率为中微子探测提供了极大的效率，但也带来了一些图像分析挑战。图像重建技术是目前致力于这些国家的最先进的探测器的努力的核心。MicroBooNE的物理程序是广泛的，振荡物理，相互作用研究，奇异的物理搜索.然而，主要的目标是寻找中微子振荡，可以证明所提出的无菌中微子的存在。该项目旨在用MicroBooNE研究中微子，重点是电子-中微子相互作用。电子中微子是MicroBooNE主要物理分析的关键，它们对事件重建提出了相当大的挑战。虽然最近在电子重建方面取得了重大进展，但要完成旗舰分析仍有许多工作要做。已经提出了许多尖端的重建技术来克服电子重建的挑战，学生将实施和研究其中一些技术的影响。这项工作将在学生培训的早期进行，将提供一个独特的机会来参与无菌中微子搜索，这将对物理界产生巨大的影响。除了解决之前观察到的事件过多的谜团之外，该项目还将对正在美国建造的大型DUNE项目产生相当大的影响。电子中微子将是DUNE合作分析的主要信号，该项目将为电子重建奠定一些基础，这对DUNE分析非常有价值。更详细地说，学生将熟悉MicroBooNE实验和软件，并将被要求定期“数据轮班”。在参与电子重建软件开发后，学生将进行电子中微子分析。由于MicroBooNE和DUNE都是STFC粒子物理战略计划的一部分，因此这项工作与英国的优先事项完全一致。此外，液氩探测器被用于许多不同的实验（MicroBooNE，SBND，protoDUNE和DUNE）和粒子物理学的许多其他领域，如暗物质搜索和无中微子双β衰变实验，使用类似的探测器技术。学生将学习的技能将直接转移到这些当前和未来的项目。最后，为该项目开发的计算和硬件技术也将与模式识别软件开发或医疗器械开发行业高度相关。

Previous neutrino experiments have observed an unexpected excess of events, potentially indicating a new type of neutrino - the sterile neutrino. If confirmed, this new particle would be definite proof of physics beyond the Standard Model and finding new physics has been the holy grail of all particle physicists. The Short-Baseline Neutrino (SBN) programme at Fermilab in the US has been designed to directly address these anomalies and will have a definite answer to this long-lasting puzzle. MicroBooNE is the first detector of the SBN programme. The 170t liquid argon detector started to record neutrino data in the Fall 2015 and the collaboration is now working on data analysis. The excellent image resolution of the MicroBooNE detector offers great efficiency for neutrino detection, but also poses some image analysis challenges. Image reconstruction techniques are at the heart of the current efforts dedicated to these state-of-the-art detectors. The physics programme of MicroBooNE is broad, oscillation physics, interaction studies, exotic physics searches... However, the main goal is to search for neutrino oscillations that could demonstrate the presence of the proposed sterile neutrinos. This project will aim at studying neutrinos with MicroBooNE, with a focus on the electron-neutrino interactions. Electron neutrinos are the key to MicroBooNE's main physics analysis and they represent a considerable challenge for event reconstruction. While significant progress have been recently achieved regarding electron reconstruction, a lot of work remains to be done to accomplish the flagship analysis. Many cutting-edge reconstruction techniques have been proposed to overcome the electron reconstruction challenges and the student will implement and study the impact of some of this techniques. This work, to be performed early in the student's training, will offer a unique opportunity to participate in the sterile neutrino search, which will have tremendous impact in the physics community. In addition to addressing the mystery of the previously observed excess of events, this project will have considerable impact on the large-scale DUNE project, being built in the US. Electron neutrinos will be the main signal analysed by the DUNE collaboration and this project will lay some groundwork in electron reconstruction that will be highly valuable for DUNE analyses. In more details, the student will get familiar with the MicroBooNE experiment and software and will be required to take regular "data taking shifts". After being involved in the electron reconstruction software development, the student will perform the electron-neutrino analysis. Since MicroBooNE and DUNE are both part of the STFC Particle Physics strategic plan, this work is in perfect alignment with the UK priorities. In addition, liquid argon detectors are used in many different experiments (MicroBooNE, SBND, protoDUNE and DUNE) and many other fields of particle physics, such as Dark Matter searches and Neutrinoless double-beta decay experiments, use similar detector technologies. The skills that the student will learn will be directly transferable to these current and future projects. Finally, computing and hardware techniques developed for the project will also be highly relevant to the industries doing pattern recognition software development or medical instrument development.