Enabling real-time multi-messenger astrophysics discoveries with deep learning

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 neutri...

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Veröffentlicht in:arXiv.org 2019-11
Hauptverfasser: Huerta, E A, Allen, Gabrielle, Andreoni, Igor, Antelis, Javier M, Bachelet, Etienne, Berriman, Bruce, Bianco, Federica, Biswas, Rahul, Carrasco, Matias, Chard, Kyle, Cho, Minsik, Cowperthwaite, Philip S, Etienne, Zachariah B, Fishbach, Maya, ster, Francisco, George, Daniel, Gibbs, Tom, Graham, Matthew, Gropp, William, Gruendl, Robert, Gupta, Anushri, Haas, Roland, Habib, Sarah, Jennings, Elise, Johnson, Margaret W G, Katsavounidis, Erik, Katz, Daniel S, Khan, Asad, Kindratenko, Volodymyr, Kramer, William T C, Liu, Xin, Mahabal, Ashish, Marka, Zsuzsa, McHenry, Kenton, Miller, Jonah, Moreno, Claudia, Neubauer, Mark, Oberlin, Steve, Olivas, Alexander R, Petravick, Donald, Rebei, Adam, Rosofsky, Shawn, Ruiz, Milton, Saxton, Aaron, Schutz, Bernard F, Schwing, Alex, Seidel, Ed, Shapiro, Stuart L, Shen, Hongyu, Shen, Yue, Singer, Leo, Sipőcz, Brigitta M, Sun, Lunan, Towns, John, Tsokaros, Antonios, Wei, Wei, Wells, Jack, Williams, Timothy J, Xiong, Jinjun, Zhao, Zhizhen
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