Rare Event Searches at MIT

暗物质的性质是物理学中最大的谜团之一。仅次于此的是宇宙中观测到的物质-反物质不对称性的奥秘。轴子和马约拉纳中微子分别是迄今尚未发现的粒子，它们可能参与提供答案。轴子是一个动机良好的暗物质候选者，而Majorana中微子可以通过一种称为细微发生的过程产生物质反物质的宇宙不对称性。罕见事件搜索是探索这些模型的唯一可行技术。出于这个原因，实验类型分别是粒子物理和核物理的最高优先级。该奖项将支持两项工作：寻找具有Araadabra和DMRadio的微型EV轴子，以及无中微子双β衰变(0νββ)搜索Kamland-Zen。这些努力建立在麻省理工学院团队内部的专业知识基础上，这两项实验努力都使用了从深度学习到量子感知的新的多学科技术。更广泛的影响是双重的：为低温实验开发坚固的隔振技术，以及培训下一代科学家。该奖项将把从引力波探测到0νββ的不同社区聚集在一起，举办一个关于隔振的研讨会。本科生研究是PI的优先事项，因为它对招收和留住物理专业的学生至关重要。该奖项将资助麻省理工学院的一项本科生研究和开发最佳实践，以吸引不同群体的学生参与STEM领域。弦和QCD轴子模型激发了对质量低于10^−6 eV的轴子暗物质的研究。Abracadabra和暗物质无线电实验已经联合起来，作为DMRadio实验来探测这个质量范围。这是一个阶段性计划，建立在ABRA-10厘米的成功基础上，扩展到DMRadio-50L以测试共振读数，然后移动到m^3尺度的更高频率以向下搜索QCD轴子。无中微子双β衰变是在Kamland-Zen实验中寻找的。深度学习技术将用于对搜索算法进行训练和基准测试。KLZ探测器的调谐不是平凡的，因为许多蒙特卡罗(MC)输入具有相同的总体效应，并且实验是在不同维度的光曲线的微小偏差上调谐的。该组织正在探索生成性对抗网络(GAN)作为解决这一问题的一种方式。GANS的主要用途是生成人造图像。对抗性网络善于提取许多小特征，以提高分类器对候选罕见事件的准确性。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The nature of dark matter is one of the great mysteries of physics. Second only to this is the mystery of the universe’s observed matter-antimatter asymmetry. Axions and Majorana neutrinos, respectively, are as-yet undiscovered particles which may participate in providing the answers. Axions are a well-motivated dark matter candidate while Majorana neutrinos can produce the matter antimatter asymmetry of the universe through a process called leptogenesis. Rare-event searches are the only feasible techniques to explore these models. For this reason, the types of experiments are the highest priority for particle and nuclear physics, respectively. This award will support two efforts: the search for micro-eV axions with ABRACADABRA and DMRadio, and the neutrinoless double-beta decay (0νββ) search KamLAND-Zen. These efforts build on the expertise within the MIT group, and both experimental efforts use novel multidisciplinary techniques from deep learning to quantum sensing.The broader impacts are two-fold: the development of robust vibration isolation for cryogenic experiments and the training of the next generation of scientists. This award will bring together disparate communities from gravitational wave detection to 0νββ for a workshop on vibration isolation. Undergraduate research is a priority for the PI since it is critical for recruiting and retaining physics students. This award will sponsor a study of undergraduate research at MIT and the development of best practices to engage a diverse group of students in STEM fields.The string and QCD axion models motivate a search for Axion dark matter with masses below 10^−6 eV. The ABRACADABRA and Dark Matter Radio experiments have joined forces to probe this mass-range as the DMRadio experiment. This is a staged program that builds on the success of ABRA-10 cm, expands to DMRadio-50L to test the resonant readout, then moves to higher frequencies at the m^3-scale to search down to the QCD axion. Neutrinoless double beta decay is sought in the KamLAND-Zen experiment. Deep learning techniques will be used for training and benchmarking the search algorithm. The tuning of the KLZ detector is non-trivial because many of the Monte Carlo (MC) inputs have the same gross effect and the experiments are tuning on minor deviations of the light curves in various dimensions. The group is exploring generative adversarial networks (GAN) as a way to tackle this problem. The main use of GANs is the generation of artificial images. The adversarial network is good at picking up many small features to increase the accuracy of the classifier for candidate rare events.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.