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

通过在测试光束实验中应用机器学习技术来增强水切伦科夫探测器技术

• 批准号: EP/X027368/1
• 负责人: Mark Scott
• 金额: $ 24.26万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX027368%2F1
• 关键词: Enhancing; water; Cherenkov; detector; technology

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.

中微子振荡实验已经进入了精确测量的新时代。随着正在进行的实验检测到轻子中CP对称性破坏的第一个证据，现在未来的实验，如日本正在建设的超级神冈实验，旨在通过中微子混合CP相位的第一次测量来确定neturino振荡中的CP破坏。为了实现这一目标，升级的硬件和新的检测器功能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CERN运行，将作为新型探测器技术和水基粒子探测器分析技术的测试平台。该奖学金将涉及开发基于机器学习的事件重建软件，用于WCTE中复杂的多环事件，在探测器的调试和操作中发挥主导作用，收集带电π介子测试束中的实验数据，用于验证和进一步开发重建软件，并将这些进展应用于新型探测器校准方法。