Papers › The Hitchhiker's guide to the galaxy catalog approach for gravitational wave cosmology

The Hitchhiker's guide to the galaxy catalog approach for gravitational wave cosmology

16 Dec 2022arXiv:2212.08694links table onlyarchive 2025-07-28

Jonathan R. Gair, Archisman Ghosh, Rachel Gray, Daniel E. Holz, Simone Mastrogiovanni, Suvodip Mukherjee, Antonella Palmese, Nicola Tamanini, Tessa Baker, Freija Beirnaert, Maciej Bilicki, Hsin-Yu Chen, Gergely Dálya, Jose Maria Ezquiaga, Will M. Farr, Maya Fishbach, Juan Garcia-Bellido, Tathagata Ghosh, Hsiang-Yu Huang, Christos Karathanasis, Konstantin Leyde, Ignacio Magaña Hernandez, Johannes Noller, Gregoire Pierra, Peter Raffai, Antonio Enea Romano, Monica Seglar-Arroyo, Danièle A. Steer, Cezary Turski, Maria Paola Vaccaro, Sergio Andrés Vallejo-Peña

The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.

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 (1986), one can consult a galaxy catalog and implement a dark siren statistical approach incorporating all potential host galaxies within the localization volume. Trott & Hunterer 2021 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.

PaperPDFCode

Code

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections