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.

Project Start
Project End
Budget Start
2020-09-01
Budget End
2024-08-31
Support Year
Fiscal Year
2020
Total Cost
$3,000,000
Indirect Cost
Name
South Dakota School of Mines and Technology
Department
Type
DUNS #
City
Rapid City
State
SD
Country
United States
Zip Code
57701