no code implementations • 25 Feb 2021 • Josiah N. Purdum, Zhong-Yi Lin, Bryce T. Bolin, Kritti Sharma, Phillip I. Choi, Varun Bhalerao, Harsh Kumar, Robert Quimby, Joannes C. Van Roestel, Chengxing Zhai, Yanga R. Fernandez, Josef Hanuš, Carey M. Lisse, Dennis Bodewits, Christoffer Fremling, Nathan Ryan Golovich, Chen-Yen Hsu, Wing-Huen Ip, Chow-Choong Ngeow, Navtej S. Saini, Michael Shao, Yuhan Yao, Tomás Ahumada, Shreya Anand, Igor Andreoni, Kevin B. Burdge, Rick Burruss, Chan-Kao Chang, Chris M. Copperwheat, Michael Coughlin, Kishalay De, Richard Dekany, Alexandre Delacroix, Andrew Drake, Dmitry Duev, Matthew Graham, David Hale, Erik C. Kool, Mansi M. Kasliwal, Iva S. Kostadinova, Shrinivas R. Kulkarni, Russ R. Laher, Ashish Mahabal, Frank J. Masci, Przemyslaw J. Mróz, James D. Neill, Reed Riddle, Hector Rodriguez, Roger M. Smith, Richard Walters, Lin Yan, Jeffry Zolkower
We observed Episodically Active Asteroid (6478) Gault in 2020 with multiple telescopes in Asia and North America and have found that it is no longer active after its recent outbursts at the end of 2018 and start of 2019.
Time Series Analysis Earth and Planetary Astrophysics
1 code implementation • 11 Aug 2020 • Sara Webb, Michelle Lochner, Daniel Muthukrishna, Jeff Cooke, Chris Flynn, Ashish Mahabal, Simon Goode, Igor Andreoni, Tyler Pritchard, Timothy M. C. Abbott
We present an unsupervised method for transient discovery using a clustering technique and the Astronomaly package.
Instrumentation and Methods for Astrophysics
no code implementations • 26 Nov 2019 • E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier M. Antelis, Etienne Bachelet, Bruce Berriman, Federica Bianco, Rahul Biswas, Matias Carrasco, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, 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, Jonah Miller, Claudia Moreno, Mark Neubauer, Steve Oberlin, Alexander R. Olivas, 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 Singer, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, JinJun Xiong, Zhizhen Zhao
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.
no code implementations • 1 Feb 2019 • Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, JinJun Xiong, Zhizhen Zhao
We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics; (ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data; (iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups; (iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era; (v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics.