CSST星系巡天与引力波观测的协同：利用暗标准汽笛推断哈勃常数
Synergy between CSST galaxy survey and gravitational-wave observation: Inferring the Hubble constant from dark standard sirens
AI总结：
本文通过模拟CSST星系星表与第三代引力波探测器5年数据，研究利用暗汽笛方法推断哈勃常数，结果显示测量精度可达亚百分比水平，证明二者协同对精确宇宙学具有重要意义。
摘要：
致密双星并合产生的引力波（GWs）编码了GW源的绝对光度距离。一旦知道GW源的红移，就可以利用距离-红移关系来约束宇宙学参数。获得红移的一种方法是通过GW观测对GW源进行定位，然后利用星系星表，通过对潜在宿主星系红移信息的统计分析来确定红移，这种方法通常被称为暗汽笛方法。第三代（3G）GW探测器计划在2030年代投入运行，将观测到大量的致密双星并合事件。将这些GW事件用作暗汽笛需要来自未来巡天项目的高质量星系星表。中国空间站望远镜（CSST）将于2024年发射，将在17500平方度的巡天区域内观测数十亿个星系，红移最高可达z~4，提供测光和光谱星系星表。在这项工作中，我们模拟了CSST星系星表和来自3G GW探测器的5年GW数据，并将它们结合起来推断哈勃常数（H_0）。我们的结果表明，H_0的测量精度可以达到亚百分比水平，满足精确宇宙学的标准。我们得出结论，CSST与3G GW探测器之间的协同作用在测量哈勃常数方面具有重要意义。
英文摘要：
Gravitational waves (GWs) from compact binary coalescences encode the absolute luminosity distances of GW sources. Once the redshifts of GW sources are known, one can use the distance-redshift relation to constrain cosmological parameters. One way to obtain the redshifts is to localize GW sources by GW observations and then use galaxy catalogs to determine redshifts from a statistical analysis of redshift information of the potential host galaxies, commonly referred to as the dark siren method. The third-generation (3G) GW detectors are planned to work in the 2030s and will observe numerous compact binary coalescences. Using these GW events as dark sirens requires high-quality galaxy catalogs from future sky survey projects. The China Space Station Telescope (CSST) will be launched in 2024 and will observe billions of galaxies within a 17500 deg$^2$ survey area with redshift up to $z\sim 4$, providing photometric and spectroscopic galaxy catalogs. In this work, we simulate the CSST galaxy catalogs and the 5-year GW data from the 3G GW detectors and combine them to infer the Hubble constant ($H_0$). Our results show that the measurement precision of $H_0$ could reach the sub-percent level, meeting the standard of precision cosmology. We conclude that the synergy between CSST and the 3G GW detectors is of great significance in measuring the Hubble constant.
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