Enabling real-time multi-messenger astrophysics discoveries with deep learning
Nature Reviews Physics2019Vol. 1(10), pp. 600–608
Citations Over TimeTop 10% of 2019 papers
E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier M. Antelis, E. Bachelet, G. Bruce Berriman, Federica Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, P. S. Cowperthwaite, Z. B. Etienne, M. Fishbach, F. Förster, D. George, Tom Gibbs, M. J. Graham, William Gropp, R. A. Gruendl, A. Gupta, Roland Haas, Sarah Habib, Elise Jennings, Michele Johnson, E. Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William Kramer, Xin Liu, A. Mahabal, Zsuzsa Márka, Kenton McHenry, Jonah Miller, Claudia Moreno, M. S. Neubauer, Steve Oberlin, A. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, B. F. Schutz, Alex Schwing, E. Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, L. P. Singer, Brigitta Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, J. C. Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao
Related Papers
- → Supernova neutrino burst detection with the Deep Underground Neutrino Experiment(2020)137 cited
- → Introduction to Particle and Astroparticle Physics : Multimessenger Astronomy and its Particle Physics Foundations(2018)37 cited
- → Acquiring information about neutrino parameters by detecting supernova neutrinos(2010)6 cited
- → Identifying the neutrino mass hierarchy with supernova neutrinos(2007)1 cited
- → The diffuse supernova neutrino background as a probe of late-time neutrino mass generation(2022)