Probing the Majorana Nature of Neutrinos with KamLAND-Zen

中微子是电中性的，弱相互作用的亚原子粒子，是宇宙中最丰富的粒子之一。近几十年来，我们对中微子基本性质的认识有了长足的进步，但仍无法解决一些非常基本的问题。中微子的绝对质量是多少？为什么中微子的质量与其他基本粒子相比如此之小？中微子是如何获得质量的？这些问题的答案可能与中微子是它自己的反粒子（称为马约拉纳粒子）密切相关，也可能解释宇宙中没有反物质。PI将通过寻找一种称为无中微子双β衰变的假设核过程来阐明这些问题。对这个过程的观测将提供中微子是马约拉纳粒子的直接证据;然而，由于实验中不断发生大量非常相似的过程，这将非常难以观察。竞争性搜索需要大量的双β衰变同位素和对背景的精细抑制。因此，PI将升级世界领先的无中微子双β衰变实验KamLAND-Zen，采用最先进的数据采集电子设备和新颖的机器学习算法。这个令人兴奋的实验研究领域将为培养学生和博士后提供一个极好的平台，这些学生和博士后掌握在学术界，工业界和国家实验室中备受追捧的先进技术技能。去年，KamLAND-Zen（日本的一种装载有氚-136的液体闪烁体探测器）首次开始在相空间的新区域中寻找无中微子双β衰变。PI正在对KamLAND-Zen进行重大改进，同时继续收集和分析新数据。第一个增强涉及PI最近开发的最先进的深度学习算法，称为KamNET，该算法将用于搜索难以捉摸的双中微子双β衰变的π-136激发态。PI还将使用KamNET对所有现在和过去的KamLAND-Zen数据进行综合分析，以最大限度地提高其对无中微子双β衰变的敏感性。第二项改进涉及安装和调试具有在线事件标记逻辑的零死区波形数字化仪电子设备，称为MoGURA 2。MoGURA 2将用于减少KamLAND-Zen上寻找无中微子双β衰变的主要背景。该奖项反映了NSF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而被认为值得支持。

Neutrinos are electrically neutral, weakly interacting, subatomic particles and are one of the most abundant particles in the universe. Our understanding of the fundamental nature of neutrinos has rapidly progressed in recent decades, yet we are still unable to some very basic questions. What is the absolute mass of the neutrino? Why are neutrino masses so small compared to other elementary particles? How did the neutrino obtain a mass? The answers to these questions could be intimately related to the neutrino being its own antiparticle, known as a Majorana particle, and might also explain the absence of anti-matter in the universe. The PI will shed light on these questions by searching for a hypothetical nuclear process called neutrinoless double beta decay. An observation of this process would provide direct proof that neutrinos are Majorana particles; however, it will be extremely difficult to observe due to the vast number of very similar processes constantly taking place inside experiments. A competitive search requires a large quantity of double beta decay isotope and exquisite suppression of backgrounds. Therefore, the PI will upgrade the world-leading neutrinoless double beta decay experiment, KamLAND-Zen, with state-of-the-art data acquisition electronics and novel machine learning algorithms. This exciting area of experimental research will provide an excellent platform for training students and postdocs in advanced technical skills that are highly sought-after in in academia, industry, and national laboratories. In the last year, KamLAND-Zen (a liquid scintillator detector in Japan loaded with Xe-136) began searching for neutrinoless double beta decay in new regions of phase space for the first time. The PI is implementing major enhancements to KamLAND-Zen while continuing to collect and analyze new data. The first enhancement involves a state-of-the-art deep learning algorithm recently developed by the PI, called KamNET, which will be used to search for the elusive two-neutrino double beta decays of Xe-136 excited states. The PI will also use KamNET to perform a combined analysis over all present and past KamLAND-Zen data to maximize its sensitivity to neutrinoless double beta decay. The second enhancement involves the installation and commissioning of zero dead-time waveform digitizer electronics with online event tagging logic, known as MoGURA2. MoGURA2 will be used to reduce the leading backgrounds in the search for neutrinoless double beta decay on KamLAND-Zen.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.