Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors
Autor: | Zazzera, Stefano, Fonseca, José, Baker, Tessa, Clarkson, Chris |
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Rok vydání: | 2024 |
Předmět: | |
Druh dokumentu: | Working Paper |
Popis: | Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like the Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary (CB) mergers. These detections, coupled with galaxy surveys by instruments such as DESI, Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies which host them. In this paper, we focus on how these cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBH). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multi-tracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\sim50\%$. However, third-generation detectors like ET, when cross-correlated with LSST data, can improve clustering bias measurements to within $2.5\%$. Furthermore, we demonstrate that these cross-correlations can enable a percent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $1 < z < 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure. Comment: 12 pages, 6 figures, comments welcome |
Databáze: | arXiv |
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