The Hitchhiker’s Guide to the Galaxy Catalog Approach for Dark Siren Gravitational-wave Cosmology
The Hitchhiker’s Guide to the Galaxy Catalog Approach for Dark Siren Gravitational-wave Cosmology
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DOI：
10.3847/1538-3881/acca78
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发表时间：
2022-12
期刊：
影响因子：
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通讯作者：
J. Gair;A. Ghosh;R. Gray;D. Holz;S. Mastrogiovanni;Suvodip Mukherjee;A. Palmese;N. Tamanini;T. Baker;F. Beirnaert;Maciej Bilicki;Hsin-Yu Chen;G. D'alya;J. Ezquiaga;W. Farr;M. Fishbach;J. García-Bellido;T. Ghosh;Hsiang-Yu Huang;C. Karathanasis;K. Leyde;I. M. Hernandez;J. Noller;G. Pierra;P. Raffai;A. E. Romano;M. Seglar-Arroyo;D. Steer;C. Turski;M. P. Vaccaro;S. Vallejo-Peña
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文献类型：
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作者：
J. Gair;A. Ghosh;R. Gray;D. Holz;S. Mastrogiovanni;Suvodip Mukherjee;A. Palmese;N. Tamanini;T. Baker;F. Beirnaert;Maciej Bilicki;Hsin-Yu Chen;G. D'alya;J. Ezquiaga;W. Farr;M. Fishbach;J. García-Bellido;T. Ghosh;Hsiang-Yu Huang;C. Karathanasis;K. Leyde;I. M. Hernandez;J. Noller;G. Pierra;P. Raffai;A. E. Romano;M. Seglar-Arroyo;D. Steer;C. Turski;M. P. Vaccaro;S. Vallejo-Peña
我们概述了“黑暗的警笛”星系目录方法的宇宙学推断使用引力波（GW）的标准警笛，澄清了一些常见的误解，在实施这种方法。当一个有信心的瞬变电磁对应的GW事件是不可用的，一个独特的主机星系的识别一般是具有挑战性的。相反，正如Schutz最初提出的那样，人们可以查阅星系目录，并实施一种将所有潜在的宿主星系纳入本地化体积的暗警报统计方法。Trott & Huterer最近声称，这种方法在模拟数据上实现时，即使做出乐观的假设，也会导致哈勃常数H 0的有偏估计。我们明确地表明，如先前所示，由多个独立的组，暗警报统计方法导致一个无偏后，当该方法被正确地应用于数据。我们强调了在模拟数据的生成和统计框架的实施中可能出现的常见错误来源，包括选择效应的错误建模和贝叶斯框架的不一致实施，这可能导致虚假的偏见。
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, H 0, 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.