Davide Gerosa

University of Birmingham

Machine-learning interpolation of population-synthesis simulations to interpret gravitational-wave observations: a case study

Gravitational-wave astronomy is, seems obvious to say, about doing astronomy with gravitational waves. One has gravitational-wave observations (thanks LIGO and Virgo!) on hand and astrophysical models on the other hand. The more closely these two sides interact, the more we can hope to use gravitational-wave data to learn about the astrophysics of the sources. Today’s paper with JHU student Kaze Wong tries to further stimulate this dialog. And, well, one needs to throw some artificial intelligence in the game. There are three players now (astrophysics, gravitational waves, and machine learning) and things get even more interesting.

Kaze W.K. Wong, Davide Gerosa.
arXiv:1909.06373 [astro-ph.HE].

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