Speaker
Dr
Nikolaos Karnesis
(AUTh)
Description
EMRIs are long-lived signals with a frequency profile which may occupy the complete LISA band. On top of that, LISA is going to be signal dominated, with many different signatures overlapping in time and in frequency, while at the same time the instrumental noise which will not be completely known a-priori. In this talk, I will describe the usage of heavier-tailed likelihoods for the detection and characterization of signals in noise with unknown spectral properties. This analysis framework is based on the hyperbolic likelihood, which allows us to probe the spectral properties of the given signal and simultaneously account for any departures from Gaussianity.
