Investigating all-sky Frequency Hough performances for neutron stars
Authors
Martina Di Cesare
Pia Astone
Rosario De Rosa
David Keitel
Cristiano Palomba
Marco Serra
Abstract
Between the estimated population of Neutron Stars (NSs) and the actual number present in the catalogs, there is a huge gap: O(10$^{8-9}$) vs O(10$^3$). Among the different search techniques for Continuous gravitational waves (CWs), the all-sky could help to reduce the discrepancy. We focus on the all-sky CW pipeline Frequency Hough (FH), which operates without prior knowledge of the source parameters ($f,\dot{f}, λ, β$). Here, we present a Machine Learning strategy, diverging from the standard follow-up(FU) of the FH pipeline. We study the performance with real interferometer data, until reaching $h$ value subthreshold for the standard FU procedure ($CR_{thr}=5$), with encouraging classification results.
