Bulletin of the American Physical Society
APS April Meeting 2019
Volume 64, Number 3
Saturday–Tuesday, April 13–16, 2019; Denver, Colorado
Session D17: Binary Black Hole Mergers and Core-Collapse Supernovae: Modeling in the Multimessenger Era
3:30 PM–5:18 PM,
Saturday, April 13, 2019
Sheraton
Room: Grand Ballroom II
Sponsoring
Units:
DAP DGRAV
Chair: Zach Etienne, West Virginia University
Abstract: D17.00009 : Frontiers at the interface of deep learning and large scale computing for Multi-Messenger Astrophysics
5:06 PM–5:18 PM
View Presentation Abstract
Presenter:
Eliu Antonio Huerta
(University of Illinois at Urbana-Champaign)
Author:
Eliu Antonio Huerta
(University of Illinois at Urbana-Champaign)
We discuss recent developments at the interface of deep learning and large scale computing for the design and use of deep neural network models for the detection of gravitational waves in non-Gaussian and non-stationary noise, and the characterization of the binary components and the remnant of black hole mergers. We discuss the generality of these methodologies for the analysis of telescope image datasets, and showcase its application with the construction of large scale galaxy catalogs with the Dark Energy Survey. We also present neural network models, endowed with a statistical backbone, for gravitational wave parameter estimation analyses.
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