New search pipeline for gravitational waves with higher-order modes using mode-by-mode filtering
arXiv:2405.17400 · doi:10.1103/PhysRevD.110.044063
Abstract
Nearly all template-based gravitational wave (GW) searches only include the quasi-circular quadrupolar modes of the signals in their templates. Including additional degrees of freedom in the GW templates corresponding to higher-order harmonics, orbital precession, or eccentricity is challenging because: () the size of template banks and the matched-filtering cost increases significantly with the number of degrees of freedom, if these additional degrees are not included properly, the search can lose sensitivity overall (due to an increase in the rate of background triggers). Here, we focus on including aligned-spin higher harmonics in GW search templates. We use a new mode-by-mode filtering approach, where we separately filter GW strain data with three harmonics [namely , and ]. This results in an increase in the matched-filtering cost by only a factor of compared to that of a -only search. We develop computationally cheap trigger-ranking statistics to optimally combine the different signal-to-noise ratios (SNR) timeseries from different harmonics, which ensure only physically-allowed combinations of the different harmonics are triggered on. We use an empirical template-dependent background model in our ranking statistic to account for non-Gaussian transients. In addition, we develop a tool called band eraser which specifically excises narrow time-varying noisy bands in time-frequency space (without having to excise entire time chunks in the data). New GW candidate events that we detect using our search pipeline and the details of our template banks are discussed in accompanying papers: Wadekar et al. [1] and [2] respectively. Apart from higher harmonics, we expect our methodology to also be useful for cheap and optimal searches including orbital precession and eccentricity in GW waveforms.
arXiv comment11+4 pages, 5 figures. Version appearing in PRD. The IAS-HM pipeline is available at https://github.com/JayWadekar/gwIAS-HM
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