Orateur
Thomas Sainrat
(CentraleSupélec)
Description
Reconstructing gravitational wave polarizations from detector data is a challenging problem due to the low SNR and the ill-posed nature of the the problem. We leverage the so-called "Plug-and-Play" methods, commonly used in inverse problem literature to achieve state-of-the-art image reconstruction. They explicitely separate the differentiable likelihood and the regularization, which is likened to a Gaussian denoising task. This denoising tasks can be achieved in a variety of ways, typically using a neural network. We demonstrate the usage of this method on compact binary coalescences, allowing to obtain a direct measurement of relativistic precession.
Auteurs
Eric Chassande-Mottin
(APC)
Thomas Sainrat
(CentraleSupélec)