Minimally-modeled search of higher multipole gravitational-wave radiation in compact binary coalescences. (24th January 2022)

• Record Type: Journal Article
• Authors: Vedovato, G; Milotti, E; Prodi, G A; Bini, S; Drago, M; Gayathri, V; Halim, O; Lazzaro, C; Lopez, D; Miani, A; O'Brien, B; Salemi, F; Szczepanczyk, M; Tiwari, S; Virtuoso, A; Klimenko, S
• Is Part Of: Classical and quantum gravity. Volume 39:Number 4(2022)
• Publication Date: 2022-01-24
• Subjects: minimally-modeled -- higher order mode -- gravitational waves -- binary compact coalescences; Quantum gravity -- Periodicals; Gravitation -- Periodicals; Relativity (Physics) -- Periodicals; Space and time -- Periodicals; Periodicals; 521.1
• DOI: 10.1088/1361-6382/ac45da
• Languages: English
• ISSNs: 0264-9381

Abstract

Abstract: As the Advanced LIGO and Advanced Virgo interferometers, soon to be joined by the KAGRA interferometer, increase their sensitivity, they detect an ever-larger number of gravitational waves with a significant presence of higher multipoles (HMs) in addition to the dominant (2, 2) multipole. These HMs can be detected with different approaches, such as the minimally-modeled burst search methods, and here we discuss one such approach based on the coherent WaveBurst (cWB) pipeline. During the inspiral phase the HMs produce chirps whose instantaneous frequency is a multiple of the dominant (2, 2) multipole, and here we describe how cWB can be used to detect these spectral features. The search is performed within suitable regions of the time-frequency representation; their shape is determined by optimizing the receiver operating characteristics. This novel method has already been used in the GW190814 discovery paper (Abbott et al 2020 Astrophys. J. Lett. 896 L44) and is very fast and flexible. Here we describe in full detail the procedure used to detect the (3, 3) multipole in GW190814 as well as searches for other HMs during the inspiral phase, and apply it to another event that displays HMs, GW190412, replicating the results obtained with different methods. The procedure described here can be used for the fast analysis of HMs and to support the findings obtained with the model-based Bayesian parameter estimates.