Studying the performance of the DUNE LAr neutrino detector

中微子是非常有趣的粒子，并揭示了意想不到的特性。中微子振荡的发现，证明了中微子具有非零质量，挑战了粒子物理学中公认的标准模型。此外，中微子可能是解决许多其他重大物理学问题的关键，比如为什么宇宙是由物质（而不是反物质）主导的。如果中微子和反中微子的行为不同，这个长期存在的重要物理学问题就可以得到回答，这是下一代中微子实验的主要目标。下一代中微子实验的主要项目是深地下中微子实验（DUNE）。这个非常大规模的实验，高达4万吨液态氩的中微子探测器，目前正在由有史以来最大的中微子合作（全球超过800人）设计和优化。DUNE将使用来自美国费米国家实验室的全新的，更强大的中微子束，并将中微子发送到1300公里外位于南达科他州矿井地下深处的四个10kt液态氩探测器。DUNE是一个前所未有的实验，它将解决该领域的几个重大问题，如宇宙中物质和反物质之间的不平衡，中微子质量的排序以及超越标准模型的潜在对称性的信息。然而，在我们为DUNE建造前所未有的大规模液态氩探测器之前，一些中等规模的探测器必须证明它可以实现，这就是为什么DUNE合作目前正在建造DUNE原型（protoDUNE）。protoDUNE液氩时间投影室位于CERN的粒子束中，为研究液氩探测器中单个粒子的相互作用提供了独特的数据集，并验证了最终DUNE探测器的主要性能特征。该项目将允许学生参与欧洲核子研究中心探测器的调试和操作。此外，该学生还将帮助开发protoDUNE的重建和分析软件，以便对来自光束和宇宙射线的选定粒子进行完整的数据分析。他将使用这些数据来完善模拟和重建算法和分析技术，一旦DUNE实验从2026年开始采集中微子数据，这些算法和分析技术将用于数据分析。由于protoDUNE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，并将作为国际DUNE合作的一部分进行。此外，液态氩探测器用于许多不同的实验（MicroBooNE， SBND， protoDUNE和DUNE），许多其他粒子物理领域，如暗物质搜索和中微子双β衰变实验，都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中。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的行业高度相关。

Neutrinos are very intriguing particles and have revealed unexpected properties. The discovery of neutrino oscillation, demonstrating that neutrinos have a non-zero mass, has challenged the well-established Standard Model of Particle Physics. Furthermore, neutrinos may hold the key to many other great question of physics such as why is the Universe dominated by matter (over anti-matter). This long-lasting important question of Physics could be answered if neutrinos and anti-neutrinos behave differently and this is the main goal of the next generation of neutrino experiments. The main project for the next generation of neutrino experiments is the Deep Underground Neutrino Experiment (DUNE). This very-large scale experiment, neutrino detector of up to 40 kiloton of liquid argon, is currently being designed and optimised by the largest neutrino collaboration ever seen (over 800 people worldwide). DUNE will use a brand-new, much more powerful, neutrino beam from the Fermilab National Laboratory in the US and will send neutrinos 1300km away to four 10kt liquid argon detectors located deep underground in a mine in South Dakota. DUNE is an unprecedented experiment that will address several great questions of the field such as the imbalance between matter and anti-matter in the Universe, the ordering of the neutrino masses and information on potential underlying symmetries beyond the Standard Model. However, before we can build the unprecedentedly large-scale liquid argon detector for DUNE, some intermediate scale detectors have to demonstrate that it can be achieved and this is why the DUNE collaboration is currently constructing a DUNE prototype (protoDUNE). The protoDUNE liquid argon time projection chamber is located in a particle beam at CERN, offering a unique dataset to study the interactions of individual particles in liquid argon detectors and verify the main performance characteristics of the eventual DUNE detector. This project will allow the student to participate in the commissioning and operation of the detector at CERN. In addition the student would help develop the reconstruction and analysis software for protoDUNE in the goal of performing the full data analysis with selected particles from beam and cosmic rays. He will use this data to refine the simulation and reconstruction algorithms and analysis techniques that will be used for the data analysis once the DUNE experiment starts taking neutrino data from 2026. Since protoDUNE and DUNE are both part of the STFC Particle Physics strategic plan, this work is in perfect alignment with the UK priorities and will be performed as part of the international DUNE collaboration. 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.