Improving Cosmological Constraints by Inferring the Formation Channel of Extreme-mass-ratio Inspirals

Liang-Gui Zhu, 良贵 朱, Hui-Min Fan, 会敏 范, Xian Chen, 弦 陈, Yi-Ming Hu, 一鸣 胡, Jian-dong Zhang and 建东 张
{"title":"Improving Cosmological Constraints by Inferring the Formation Channel of Extreme-mass-ratio Inspirals","authors":"Liang-Gui Zhu, 良贵 朱, Hui-Min Fan, 会敏 范, Xian Chen, 弦 陈, Yi-Ming Hu, 一鸣 胡, Jian-dong Zhang and 建东 张","doi":"10.3847/1538-4365/ad5446","DOIUrl":null,"url":null,"abstract":"Extreme-mass-ratio inspirals (EMRIs) could be detected by space-borne gravitational-wave (GW) detectors, such as the Laser Interferometer Space Antenna (LISA), TianQin, and Taiji. Localizing EMRIs by GW detectors can help us select candidate host galaxies, which can be used to infer the cosmic expansion history. In this paper, we demonstrate that the localization information can also be used to infer the formation channel of EMRIs, and can hence allow us to extract more precisely the redshift probability distributions. By conducting mock observations of the EMRIs that can be detected by TianQin and LISA, as well as the galaxies that can be provided by the future Chinese Space Station Telescope, we find that TianQin can constrain the Hubble–Lemaître constant H0 to a precision of ∼3%–8% and the dark energy equation-of-state parameter w0 to ∼10%–40%. The TianQin+LISA network, by increasing the localization accuracy, can improve the precisions of H0 and w0 to ∼0.4%–7% and ∼4%–20%, respectively. Then, considering an illustrative case in which all EMRIs originate in active galactic nuclei (AGNs), and combining the mock EMRI observation with a mock AGN catalog, we show that TianQin can recognize the EMRI–AGN correlation with ∼1300 detections. The TianQin+LISA network can reduce this required number to ∼30. Additionally, we propose a statistical method to directly estimate the fraction of EMRIs produced in AGNs, fagn, and show that observationally deriving this value could significantly improve the constraints on the cosmological parameters. These results demonstrate the potentials of using EMRIs as well as galaxy and AGN surveys to improve the constraints on cosmological parameters and the formation channel of EMRIs.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":"40 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Astrophysical Journal Supplement Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3847/1538-4365/ad5446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Extreme-mass-ratio inspirals (EMRIs) could be detected by space-borne gravitational-wave (GW) detectors, such as the Laser Interferometer Space Antenna (LISA), TianQin, and Taiji. Localizing EMRIs by GW detectors can help us select candidate host galaxies, which can be used to infer the cosmic expansion history. In this paper, we demonstrate that the localization information can also be used to infer the formation channel of EMRIs, and can hence allow us to extract more precisely the redshift probability distributions. By conducting mock observations of the EMRIs that can be detected by TianQin and LISA, as well as the galaxies that can be provided by the future Chinese Space Station Telescope, we find that TianQin can constrain the Hubble–Lemaître constant H0 to a precision of ∼3%–8% and the dark energy equation-of-state parameter w0 to ∼10%–40%. The TianQin+LISA network, by increasing the localization accuracy, can improve the precisions of H0 and w0 to ∼0.4%–7% and ∼4%–20%, respectively. Then, considering an illustrative case in which all EMRIs originate in active galactic nuclei (AGNs), and combining the mock EMRI observation with a mock AGN catalog, we show that TianQin can recognize the EMRI–AGN correlation with ∼1300 detections. The TianQin+LISA network can reduce this required number to ∼30. Additionally, we propose a statistical method to directly estimate the fraction of EMRIs produced in AGNs, fagn, and show that observationally deriving this value could significantly improve the constraints on the cosmological parameters. These results demonstrate the potentials of using EMRIs as well as galaxy and AGN surveys to improve the constraints on cosmological parameters and the formation channel of EMRIs.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过推断极端质量比启发星的形成通道改进宇宙学约束
激光干涉仪空间天线(LISA)、天琴号和太极号等空间引力波(GW)探测器可以探测到极端质量比吸气(EMRIs)。通过引力波探测器定位 EMRI 可以帮助我们选择候选宿主星系,从而推断宇宙膨胀的历史。在本文中,我们证明了定位信息也可以用来推断EMRIs的形成通道,从而可以更精确地提取红移概率分布。通过对天琴和LISA可以探测到的EMRIs以及未来中国空间站望远镜可以提供的星系进行模拟观测,我们发现天琴可以将哈勃-勒梅特常数H0的约束精度提高到∼3%-8%,将暗能量状态方程参数w0的约束精度提高到∼10%-40%。天琴+LISA网络通过提高定位精度,可以将H0和w0的精度分别提高到0.4%~7%和4%~20%。然后,考虑到所有 EMRI 都起源于活动星系核(AGN)的示例,并将模拟 EMRI 观测与模拟 AGN 目录相结合,我们证明天琴可以识别 EMRI 与 AGN 的相关性,其探测次数可达 1300 次。天琴+LISA网络可以将所需数量减少到∼30。此外,我们还提出了一种统计方法来直接估算AGN中产生的EMRIs的分量,即fagn,并表明观测得出的这个值可以显著改善对宇宙学参数的约束。这些结果表明,利用 EMRIs 以及星系和 AGN 勘测来改进对宇宙学参数和 EMRIs 形成通道的约束是很有潜力的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Identifying Light-curve Signals with a Deep-learning-based Object Detection Algorithm. II. A General Light-curve Classification Framework Optical Variability of Gaia CRF3 Sources with Robust Statistics and the 5000 Most Variable Quasars Metrics of Astrometric Variability in the International Celestial Reference Frame. I. Statistical Analysis and Selection of the Most Variable Sources Forecast of Foreground Cleaning Strategies for AliCPT-1 Catalog of Proper Orbits for 1.25 Million Main-belt Asteroids and Discovery of 136 New Collisional Families
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1