Enhancing water Cherenkov detector technology with machine learning techniques applied at a test beam experiment

中微子振荡实验进入了精密测量的新时代。随着正在进行的实验发现轻子CP对称性破缺的第一个证据，现在未来的实验，如日本正在建设的Hyper-Kamiokande实验，旨在通过首次测量中微子混合CP相来确定Neturino振荡中的CP破缺。为了实现这一目标，升级的硬件和新的检测器能力必须与分析技术的进步相匹配。水切伦科夫测试实验(WCTE)将于2023年年中在欧洲核子研究中心运行，将作为水基颗粒探测器的新探测器技术和分析技术的试验台。这项奖学金将涉及为WCTE中的复杂多环事件开发基于机器学习的事件重建软件，在探测器的调试和操作中发挥主导作用，在带电的pion测试束中收集实验数据以用于验证和进一步开发重建软件，并将这些进展应用于新的探测器校准方法。

Neutrino oscillation experiments have entered a new era of precision measurements. With ongoing experiments detecting the first evidence of CP symmetry violation in leptons, now future experiments, such as the Hyper-Kamiokande experiment under construction in Japan, aim to establish CP violation in neturino oscillations through the first measurement of the neutrino mixing CP phase. To achieve this goal, upgraded hardware and new detector capabilities must be matched by advances in analysis techniques. The Water Cherenkov Test Experiment (WCTE), due to be operated at CERN in mid 2023, will act as a test-bed for novel detector technologies and analysis techniques for water-based particle detectors. This fellowship will involve developing machine learning based event reconstruction software for complex multi-ring events in the WCTE, taking a leading role in the commissioning and operation of the detector, collecting experimental data in a charged pion test beam to use in validating and further developing the reconstruction software, and applying these advances to novel detector calibration methods.