Speaker
Costantino Pacilio
(Istituto Nazionale di Fisica Nucleare)
Description
Gravitational waves provide a powerful means to perform tests of strong-gravity physics. Statistical methods based on hierarchical inference, adapted from population studies, have been developed to confidently identify potential signatures of new physics. While these methods are well-suited for detection, they provide limited insight into how exotic physics depends on standard degrees of freedom, such as the mass and spin of an observed black hole. In this talk, we present an extension of hierarchical tests that enables the modeling of such dependencies in a flexible and theory-agnostic manner. The method adopts an optimization strategy based on (a queer use of) Gaussian Process Regression.