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Landscape of stellar-mass black-hole spectroscopy with third-generation gravitational-wave detectors

S. BhagwatInstitute for Gravitational Wave Astronomy and School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT, United KingdomCostantino PacilioDipartimento di Fisica “G. Occhialini,” Università degli Studi di Milano-Bicocca, Piazza della Scienza 3, 20126 Milano, ItalyPaolo PaniDipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185, Roma, ItalyMichela MapelliINAF—Osservatorio Astronomico di Padova, Vicolo dell’Osservatorio 5, I-35122 Padova, Italy
2023en
ABI

Аннотация

Gravitational-wave black-hole spectroscopy provides a unique opportunity to test the strong-field regime of gravity and the nature of the final object formed in the aftermath of a merger. Here we investigate the prospects for black-hole spectroscopy with third-generation gravitational-wave detectors, in particular the Einstein Telescope in different configurations, possibly in combination with Cosmic Explorer. Using a state-of-the-art population model for stellar-origin binary black holes informed by LIGO-Virgo-KAGRA data, we compute the average number of expected events for precision black-hole spectroscopy using a Fisher-matrix analysis. We perform our analysis on the dominant mode (2, 2, 0) and a set of subdominant modes $[(3,3,0),(2,1,0),(4,4,0)]$ using amplitude and phase fits corresponding to the aligned spin configurations. We find that the Einstein Telescope will measure two independent quasinormal modes within $\mathcal{O}(1)%$ (resp $\mathcal{O}(10)%$) relative uncertainty for at least $\mathcal{O}(1)$ [resp $\mathcal{O}(500)$] events per year, with similar performances in the case of a single triangular configuration or two L-shaped detectors with same arm length. A 15-km arm-length configuration would improve rates by roughly a factor of two relative to a 10-km arm-length configuration. When operating in synergy with Cosmic Explorer the rates will improve significantly, reaching few-percent accuracy for $\mathcal{O}(100)$ events per year.

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