Collaborative Research: WoU-MMA: Development of an Advanced Data Selection System for the DUNE Far Detector

合作研究：WoU-MMA：为 DUNE 远距离探测器开发先进的数据选择系统

• 批准号: 1914065
• 负责人: Georgia Karagiorgi
• 金额: $ 44.99万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1914065&HistoricalAwards=false
• 关键词: Collaborative; Research; WoU; MMA; Development

One of the major intellectual achievements of the 20th century was the development of the Standard Model (SM) of particle physics. This model succeeded in classifying all of the elementary particles known at the time into a hierarchy of groups having similar quantum properties. The validity of this model to date was confirmed by the discovery of the Higgs boson at the Large Hadron Collider at CERN. However, the Standard Model as it currently exists leaves open many questions about the universe, including such fundamental questions as to why the Higgs mass has the value it has and why there is no antimatter in the universe. One of the primary areas to search for answers to these and other open questions about the universe, how it came to be, and why it is the way it is, is to focus on a study of the properties of neutrinos and to use what we know and can learn about neutrinos as probes of science Beyond the Standard Model (BSM). Detailed measurements of the interactions of these unusual particles are one of the most promising ways to probe for new physics beyond the Standard Model.Neutrinos can be produced from ground-based facilities, such as the accelerator complex at Fermilab, and can also come from astrophysical origin. The interactions of these neutrinos will be recorded and studied in the Deep Underground Neutrino Experiment (DUNE) located at the Sanford Underground Research Facility located in South Dakota. DUNE, with its large liquid Argon Time Projection Chambers, will study the oscillations of the accelerator-based neutrino beam from Fermilab, and additionally is sensitive to extra-terrestrial neutrinos, including those from supernova explosions, solar neutrinos, and other sources. The challenge for the experimenters is the vastly different energies of the neutrinos produced by Fermilab and those from many interesting astrophysical sources. Through this award, which includes support from the NSF Windows on the Universe Program, the Columbia group will initiate the development of trigger and data acquisition strategies that can provide a guide for DUNE detection of low energy electron neutrino interactions in Liquid Argon. This includes the use of machine learning techniques for triggering, an approach which has recently been demonstrated to be a disruptive technology for event selection and reconstruction in liquid Argon. The broader impact of this triggering approach is significant. It has the potential to allow the DUNE experiment to make direct and significant contributions to the international scientific effort in Multi-Messenger Astrophysics and time-domain astrophysics, through access to solar and supernova neutrinos and as well as to searches for proton decay.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.

世纪的主要学术成就之一是粒子物理学标准模型（SM）的发展。该模型成功地将当时已知的所有基本粒子分类为具有相似量子特性的组的层次结构。到目前为止，这个模型的有效性被欧洲核子研究中心大型强子对撞机上发现的希格斯玻色子所证实。然而，目前存在的标准模型留下了许多关于宇宙的问题，包括为什么希格斯质量具有它的价值以及为什么宇宙中没有反物质等基本问题。对于这些和其他关于宇宙的开放性问题，它是如何形成的，以及为什么它是这样的，寻找答案的主要领域之一是专注于中微子性质的研究，并利用我们所知道的和可以了解的关于中微子的知识作为超越标准模型（BSM）的科学探针。 详细测量这些不寻常粒子的相互作用是探索标准模型之外的新物理学最有希望的方法之一。中微子可以从地面设施产生，例如费米实验室的加速器复合体，也可以来自天体物理学。 这些中微子的相互作用将在位于南达科他州的桑福德地下研究设施的深地下中微子实验（DUNE）中记录和研究。 DUNE拥有大型液态氩时间投影室，将研究费米实验室基于加速器的中微子束的振荡，此外还对地外中微子敏感，包括来自超新星爆炸、太阳中微子和其他来源的中微子。 实验者面临的挑战是费米实验室产生的中微子和许多有趣的天体物理来源产生的中微子的能量截然不同。通过这个奖项，其中包括从美国国家科学基金会的宇宙窗口计划的支持，哥伦比亚集团将启动触发器和数据采集策略，可以提供一个指导DUNE探测液态氩中的低能电子中微子相互作用的发展。 这包括使用机器学习技术进行触发，这种方法最近被证明是一种用于液态氩中事件选择和重建的颠覆性技术。 这种触发方法的广泛影响是重大的。 它有可能使DUNE实验通过获得太阳和超新星中微子以及寻找质子衰变，对多信使天体物理学和时域天体物理学的国际科学努力做出直接和重大的贡献。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，被认为值得支持。

项目成果

Accelerating Deep Neural Networks for Real-time Data Selection for High-resolution Imaging Particle Detectors

• DOI: 10.1109/nysds.2019.8909784
• 发表时间: 2019-06
• 期刊: 2019 New York Scientific Data Summit (NYSDS)
• 作者: Y. Jwa;G. Di Guglielmo;L. Carloni;G. Karagiorgi

Machine learning in the search for new fundamental physics

• DOI: 10.1038/s42254-022-00455-1
• 发表时间: 2021-12
• 期刊: Nature Reviews Physics
• 影响因子: 38.5
• 作者: G. Karagiorgi;G. Kasieczka;S. Kravitz;B. Nachman;D. Shih