Fast Gravitational-wave Parameter Estimation without Compromises

We present a lightweight, flexible, and high-performance framework for inferring the properties of gravitational-wave events. By combining likelihood heterodyning, automatically differentiable, and accelerator-compatible waveforms, and gradient-based Markov Chain Monte Carlo sampling enhanced by nor...

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Veröffentlicht in:	The Astrophysical journal 2023-12, Vol.958 (2), p.129
Hauptverfasser:	Wong, Kaze W. K., Isi, Maximiliano, Edwards, Thomas D. P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Astronomical methods Astrophysics Computational methods GPU computing Gravitational waves Heterodyning Markov chain Monte Carlo Markov chains Neural networks Normalizing (statistics) Parameter estimation Sampling Waveforms
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