Gair, Jonathan R. and Ghosh, Archisman and Gray, Rachel and Holz, Daniel E. and Mastrogiovanni, Simone and Mukherjee, Suvodip and Palmese, Antonella and Tamanini, Nicola and Baker, Tessa and Beirnaert, Freija and Bilicki, Maciej and Chen, Hsin-Yu and Dálya, Gergely and Ezquiaga, Jose Maria and Farr, Will M. and Fishbach, Maya and Garcia-Bellido, Juan and Ghosh, Tathagata and Huang, Hsiang-Yu and Karathanasis, Christos and Leyde, Konstantin and Hernandez, Ignacio Magaña and Noller, Johannes and Pierra, Gregoire and Raffai, Peter and Romano, Antonio Enea and Seglar-Arroyo, Monica and Steer, Danièle A. and Turski, Cezary and Vaccaro, Maria Paola and Vallejo-Peña, Sergio Andrés (2023) The Hitchhiker's Guide to the Galaxy Catalog Approach for Dark Siren Gravitational-wave Cosmology. The Astronomical Journal, 166 (1). p. 22. ISSN 0004-6256
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Abstract
We outline the "dark siren" galaxy catalog method for cosmological inference using gravitational wave (GW) standard sirens, clarifying some common misconceptions in the implementation of this method. When a confident transient electromagnetic counterpart to a GW event is unavailable, the identification of a unique host galaxy is in general challenging. Instead, as originally proposed by Schutz, one can consult a galaxy catalog and implement a dark siren statistical approach incorporating all potential host galaxies within the localization volume. Trott & Huterer recently claimed that this approach results in a biased estimate of the Hubble constant, H0, when implemented on mock data, even if optimistic assumptions are made. We demonstrate explicitly that, as previously shown by multiple independent groups, the dark siren statistical method leads to an unbiased posterior when the method is applied to the data correctly. We highlight common sources of error possible to make in the generation of mock data and implementation of the statistical framework, including the mismodeling of selection effects and inconsistent implementations of the Bayesian framework, which can lead to a spurious bias.
Item Type: | Article |
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Subjects: | STM Academic > Physics and Astronomy |
Depositing User: | Unnamed user with email support@stmacademic.com |
Date Deposited: | 17 Nov 2023 04:27 |
Last Modified: | 17 Nov 2023 04:27 |
URI: | http://article.researchpromo.com/id/eprint/1788 |