Uploaded July 2022 | Updated September 2026, 4 hours ago
Merging Massive Black Hole Binaries (MBHBs) are the loudest gravitational wave (GW) sources in the LISA band. Since the MBHB signals are also broadband, they corrupt the estimation of the power spectral density and make it challenging to uncover other sources. We propose a scheme to detect and to subtract the MBHB signals from the data to the noise level using a fast and approximate model of inspiral-merger-ringdown. The detection and parameter estimation is based on the computation of the likelihood maximised over the extrinsic parameters and the time of coalescence (F-statistic) combined with a mesh-refinement algorithm (Vegas). The data with the subtracted signals will be further analysed with faithful MBHB models and for searching Galactic binaries. This method is demonstrated on the LDC2a (Sangria) dataset.
Author: Senwen Deng, Stanislav Babak, Antoine Petiteau
Presenter: Senwen Deng
Merging Massive Black Hole Binaries (MBHBs) are the loudest gravitational wave (GW) sources in the LISA band. Since the MBHB signals are also broadband, they corrupt the estimation of the power spectral density and make it challenging to uncover other sources. We propose a scheme to detect and to subtract the MBHB signals from the data to the noise level using a fast and approximate model of inspiral-merger-ringdown. The detection and parameter estimation is based on the computation of the likelihood maximised over the extrinsic parameters and the time of coalescence (F-statistic) combined with a mesh-refinement algorithm (Vegas). The data with the subtracted signals will be further analysed with faithful MBHB models and for searching Galactic binaries. This method is demonstrated on the LDC2a (Sangria) dataset.
Author: Senwen Deng, Stanislav Babak, Antoine Petiteau
Presenter: Senwen Deng
