1. Enabling Real-time Multi-messenger Astrophysics Discoveries with Deep Learning
- Author
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E A Huerta, Gabrielle Allen, Igor Andreoni, Javier M Antelis, Etienne Bachelet, G Bruce Berriman, Federica B Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S Cowperthwaite, Zacariah B Etienne, Maya Fishbach, Francisco Forster, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Robert Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W G Johnson, Erik Katsavounidis, Daniel S Katz, Asad Khan, Volodymyr Kindratenko, William T C Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Marka, Kenton McHenry, J M Miller, Claudia Moreno, M S Neubauer, Steve Oberlin, Alexander Rolivas Jr, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F Schutz, Alex Schwing, Ed Seidel, Stuart L Shapiro, Hongyu Shen, Yue Shen, Leo P Singer, Brigitta M Sipocz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J Williams, Jinjun Xiong, and Zhizhen Zhao
- Subjects
Astrophysics - Abstract
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics.
- Published
- 2019
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