CAREER: Pivoting XENONnT to Neutrinos and Anomaly Resolution

识别暗物质，理解中微子的性质，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，这些都将构成重大进展。该奖项将跟踪XENON 1 T合作项目之前的测量结果，这些测量结果可能提供标准模型之外的物理学证据，例如中微子磁矩或太阳轴子。观察到的电子反冲（ER）过剩是这种类型的液体氙社区产生的第一个结果。该奖项将通过利用该小组的重建工作来捕获微物理细节并利用其机器学习研发活动来提高能量分辨率及其鲁棒性。该奖项将提供一系列具有更广泛影响力的活动，重点关注数据素养的社会效益，其中提出的活动是该组织物理和计算夏季计划的延续。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。这种培训对于参与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）项目的同时，PI开发了一套独特的技能，以确定这种过度是一个重大发现还是一个微妙的实验效果。研究人员将采用两个工作包：1）重新审视ER光谱分析的核心方面，并将结果应用于XENONnT（XENON 1 T升级版）的数据。他们将通过使用PI小组维护的更完整的贵元素模拟技术（NEST）ER模型来理解ER建模的不确定性，以通过使用无可能性推理技术同时拟合来自其他实验的数据; 2）将技术推广到更高的能量以测量无中微子双β衰变，同时对下一代探测器进行唯象学研究。受多余的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β衰变过程只有在中微子是马约拉纳粒子时才能观察到。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

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.