CAREER: Pivoting XENONnT to Neutrinos and Anomaly Resolution

识别暗物质，理解中微子的本质，或者发现为什么宇宙是由物质而不是物质和反物质的混合物构成的，这些都将是重大的进步。该奖项将继续XENON1T合作项目之前的测量，这些测量可能提供超出标准模型的物理证据，如中微子磁矩或太阳轴子。观察到的电子后坐力（ER）过剩是液体氙群落产生的这种类型的第一个结果。该奖项将通过利用该团队的重建工作来捕捉微物理细节，并利用他们的机器学习研发活动，提高能量分辨率及其稳健性。该奖项将提供一系列影响更广泛的活动，重点关注数据素养的社会效益，这些活动是该组织物理和计算暑期项目的延续。该项目的长期目标是增加STEM管道中的学生数量，更具体地说，增加成为数据密集型科学家和工程师的学生数量。这项工作将通过基于项目的跨学科课程为物理学家提供数据科学培训。这样的训练对于参加面向计算的研究是必不可少的。在从事各种高级分析（机器学习）项目时，PI开发了一套独特的技能，以确定这种过剩是重大发现还是微妙的实验效果。研究人员将采用两个工作包：1)重新审视ER谱分析的核心方面，并将结果应用于XENONnT （XENON1T升级版）的数据。他们将通过使用PI小组维护的更完整的Noble Element Simulation Technique (NEST) ER模型来理解ER模型的不确定性，通过使用无似然推断技术同时拟合来自其他实验的数据；2)在对下一代探测器进行现象学研究的同时，将该技术推广到更高能量的中微子双β衰变测量。受过量ER相互作用的激励，PI将通过研究这种β衰变过程来验证马约拉纳假设，这种衰变过程只有在中微子是马约拉纳粒子的情况下才能观察到。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

To identify dark matter, understand the nature of the neutrino, or discover why the Universe is made of matter instead of a mixture of matter and antimatter would all constitute major advances. This award will follow-up on previous measurements by the XENON1T collaboration that may provide evidence of physics beyond the Standard Model, such as the neutrino magnetic moment or solar axions. The observed electronic recoil (ER) excess is the first result of this type produced by the liquid-xenon community. The award will improve the energy resolution and its robustness by leveraging the group's reconstruction work to capture the microphysical details and by exploiting their machine-learning R&D activities. The award will provide a range of broader-impact activities that focus on the societal benefits of data literacy, where the activities proposed are a continuation of the group’s Physics and Computation Summer program. The long-term goal of this project is to increase the number of students in the STEM pipeline and, more specifically, to increase the number of students who become data-intensive scientists and engineers. This work would provide data-science training for physicists through a project-based interdisciplinary course. Such training is indispensable to partaking in computationally oriented research. While working on a diverse set of advanced-analysis (machine learning) projects, the PI developed a unique set of skills to determine whether this excess is a major discovery or a subtle experimental effect. The investigators will employ two work packages: 1) to revisit the core aspects of the analysis of the ER spectrum and apply the results to data from XENONnT (the XENON1T upgrade). They will understand ER-modeling uncertainties by using the more complete Noble Element Simulation Technique (NEST) ER model, which the PI’s group maintains, to fit data simultaneously from other experiments by using likelihood-free inference techniques; and 2) to generalize the techniques to higher energies to measure neutrinoless double beta decay, while performing phenomenological studies of next-generation detectors. Motivated by the excess ER interactions, the PI will test the Majorana hypothesis by studying this beta decay process, which is observable only if neutrinos are Majorana particles.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.