RII Track-2 FEC: The IceCube EPSCoR Initiative (IEI) - IceCube and the Data Revolution

这个研究基础设施改进轨道-2聚焦EPSCoR合作（RII轨道-2 FEC）奖汇集了来自亚拉巴马，阿拉斯加，特拉华州，堪萨斯，内布拉斯加州和南达科他州的科学家，以探索数据革命如何为宇宙及其极端现象提供新的见解：宇宙在哪里以及如何产生携带宏观能量的微观粒子？ 传统的天文学已经从可见光望远镜发展到包括从无线电到伽马射线的全部电磁光谱。宇宙射线在世纪前就被发现了，但这些来自外太空的高能粒子的来源仍然是个谜。LIGO、Virgo和IceCube最近的发现，通过来自深空的引力波和高能中微子打开了宇宙的新窗口。对这些宇宙信使的观测将我们带入了多信使天文学（MMA）的时代。可以想象，使用各种探测器网络进行多信使观测会产生大量复杂的数据。管理和分析数据对科学界，特别是那些分布在EPSCoR州的群体构成了巨大的挑战。该项目将在六个EPSCoR司法管辖区增强大数据能力，以应对挑战。具有互补技能的科学家将合作在MMA方面取得进展，超越在单一管辖范围内可以做的事情。该项目支持五名早期职业教师，并培训博士后学者和大学生。它还让来自代表性不足群体的中学生了解IceCube及其大数据挑战，这将有助于招募年轻人进入STEM领域，并促进多样性和包容性。该项目的愿景是建立一个强大的EPSCoR团队，促进新的科学思想和创新的大数据技术，使MMA时代的发现，同时准备一个高科技的劳动力有利于所有六个参与EPSCoR国家。 IceCube是世界上最大的中微子天文台，为多信使天体物理学（MMA）服务。在南极冰川冰层2公里深处的5000多个光学传感器的立方公里阵列和表面上的探测器阵列以大约1 TB/天的速度产生数据。虽然绝大多数数据是宇宙射线事件，但其中每年有10-100个中微子，能量在10 TeV和10 PeV之间。这些事件构成了IceCube MMA计划的核心，旨在回答一些基本问题，例如极其强大的宇宙加速器位于何处，它们如何产生粒子和光，以及它们是由什么组成的。下一代IceCube-Gen 2将把数据量提高一个数量级，并将运行到2050年，以更高的精度超越当前的能源限制。EPSCoR集团在IceCube和未来MMA中的全面参与取决于克服单一管辖区内有限的基础设施或人力资本所带来的障碍。该项目支持六个EPSCoR司法管辖区之间的合作努力，以在IceCube MMA计划的三个关键主题中创造新知识。(1)宇宙射线和伽马射线物理学，重点是将粒子从银河系和河外起源中分离出来;（2）利用来自Askaryan射电阵列的数据，应对在开发作为IceCube-Gen 2一部分的射电仪器方面的技术挑战;（3）利用光学和射电传感器，为IceCube-Gen 2探测介质冰制定校准和建模战略。所有这些任务都将由通过数据吞吐量、校准、模拟、分析、建模和假设检验方面的先进数据科学技术管理大数据的能力驱动。该项目还致力于加强六个EPSCoR司法管辖区的STEM劳动力。劳动力发展计划主要包括（i）指导五名早期职业教师，（ii）实施一系列计划，通过博士后研究加强中学年轻科学家的招聘，保留和发展，以及（iii）使用IceCube数据和研究示例开发数据科学课程。该项目的成功将建立一个多元化、有竞争力和可持续发展的EPSCoR团队，并提高研究能力，以确保EPSCoR在IceCube未来计划和NSF的宇宙窗口主题中发挥突出作用。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。

This Research Infrastructure Improvement Track-2 Focused EPSCoR Collaborations (RII Track-2 FEC) award brings together scientists from Alabama, Alaska, Delaware, Kansas, Nebraska and South Dakota to explore how Data Revolution can provide new insight into the Universe and its extreme phenomena: Where and how is the Universe producing microscopic particles that carry macroscopic energies? Traditional astronomy has progressed from telescopes for visible light to include the full electromagnetic spectrum from radio to gamma-rays. Cosmic rays were discovered over a century ago, but the sources of these high energy particles from outer space remain mysterious. Recent discoveries by LIGO, Virgo, and IceCube have opened new windows on the Universe through gravitational waves and high energy neutrinos from deep space. Observations of these cosmic messengers have brought us into the era of Multi Messenger Astronomy (MMA). As one can imagine, multi-messenger observations with a network of a variety of detectors produce huge amounts of data with enormous complexity. Managing and analyzing the data pose a tremendous challenge to the science community, particularly those groups spread in EPSCoR states. This project will grow Big Data capability across six EPSCoR jurisdictions to address the challenge. Scientists with complementary skill sets will cooperate to make advances in MMA, beyond what could be done within a single jurisdiction. The project supports five early career faculty and trains postdoctoral scholars and college students. It also exposes secondary school students from underrepresented groups to IceCube and its Big Data challenges, which will help recruit young people into STEM fields and promote diversity and inclusion. The project’s vision is to establish a strong EPSCoR team that promotes new scientific ideas and innovates Big Data techniques to make discoveries in the era of MMA while preparing a high-tech workforce beneficial to all six participating EPSCoR states. IceCube is the world’s largest neutrino observatory serving Multi-Messenger Astrophysics (MMA). The cubic kilometer array of over 5000 optical sensors 2 km deep in the glacial ice at the South Pole and the detector array on the surface produce data at a rate of about 1 Terabyte/day. While the vast majority of the data are cosmic-ray events, among them are 10-100 neutrinos per year with energies between 10 TeV and 10 PeV. These events constitute the core of IceCube’s MMA program aiming to answer fundamental questions such as where extremely powerful cosmic accelerators reside, how they generate particles and light, and what they are made of. The next generation IceCube-Gen2 will increase the data volume by an order of magnitude and operate through 2050, to go beyond current energy limits with a much better accuracy. A full scale engagement of EPSCoR groups in IceCube and future MMA relies on overcoming impediments posed by limited infrastructure or human capital within a single jurisdiction. This project supports collaborative efforts among six EPSCoR jurisdictions to create new knowledge in three themes pivotal for IceCube’s MMA program. (1) Cosmic ray and gamma ray physics, with emphasis on separating particles from Galactic and extragalactic origins; (2) Address technical challenges in the development of radio instrumentation as part of IceCube-Gen2 by using data from the Askaryan Radio Array; (3) Develop a calibration and modeling strategy for the detection medium ice for IceCube-Gen2 by utilizing both optical and radio sensors. All these tasks will be driven by the ability to manage Big Data through advanced data science techniques in data throughput, calibration, simulation, analysis, modeling and hypothesis testing. The project is also committed to strengthen the STEM workforce across six EPSCoR jurisdictions. The workforce development plan mainly includes (i) mentoring five early career faculty, (ii) implementing a suite of programs to enhance the recruitment, retention and development of young scientists from secondary school through post-doctoral research, and (iii) developing a data science curriculum using IceCube data and research examples. The success of this project will establish a diverse, competitive, and sustainable EPSCoR team with increased research capacity to ensure that EPSCoR leverages a prominent role in IceCube’s future program and NSF's Windows on the Universe theme.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.