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arXiv 2103.01923astro-ph.COastro-ph.IMgr-qc
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引力波探测器网络:宇宙学和修正引力理论的标准警报

Gravitational-Wave Detector Networks: Standard Sirens on Cosmology and Modified Gravity Theory

Tao Yang

摘要:

基于未来的引力波(GW)探测器网络,构建了标准塞壬(StS)星表,第二代地基先进LIGO+先进Virgo+KAGRA+LIGO-India(HLVKI),第三代地基爱因斯坦望远镜+两个宇宙探测器(ET+2CE),以及天基LISA+太极。从每个网络的相应电磁(EM)对应探测器中,我们从概率中抽取联合GW+EM探测,以构建HLVKI 10年探测,ET+2CE 5年探测和LISA+Taiji 5年探测的标准警报器的哈勃图,我们估计这些探测器将在21世纪30年代可用并发布。因此,我们从这些地面和空间探测器网络构建了一个组合的哈勃图,以探索我们宇宙从红移0到7的膨胀历史。本文对GW标准塞壬的星表和哈勃图以及它们在21世纪30年代研究宇宙学和修正引力理论方面的潜力作了保守而现实的估计。我们采用两种预测策略。一种是传统的模型拟合马尔可夫链蒙特卡罗方法(MCMC)。结果表明,组合StS可以将哈勃常数约束在$0.34\%$的精度水平上,比目前最精确的测量方法\textit{Planck} +BAO+Pantheon的精度高1.76倍。联合StS与当前的EM实验将改善宇宙学参数的约束显着。修正的重力理论可以用来自GW传播的$0.46\%$误差来约束。在第二种策略中,我们使用机器学习非参数重建技术,即,高斯过程(GP)与人工神经网络(ANN)作为比较。GP重建可以给出与MCMC相当的结果。我们期待着更多的工作和研究这些主题。

英文摘要:

We construct the catalogues of standard sirens (StS) based on the future gravitational wave (GW) detector networks, i.e., the second-generation ground-based advanced LIGO+advanced Virgo+KAGRA+LIGO-India (HLVKI), the third-generation ground-based Einstein Telescope+two Cosmic Explorer (ET+2CE), and the space-based LISA+Taiji. From the corresponding electromagnetic (EM) counterpart detectors for each networks, we sample the joint GW+EM detections from the probability to construct the Hubble diagram of standard sirens for 10 years detections of HLVKI, 5 years detections of ET+2CE, and 5 years of detections of LISA+Taiji, which we estimate would be available and released in the 2030s. Thus we construct a combined Hubble diagram from these ground and spaced-based detector networks to explore the expansion history of our Universe from redshift 0 to 7. We give a conservative and realistic estimation of the catalogue and Hubble diagram of GW standard sirens and their potential on studying cosmology and modified gravity theory in the 2030s. We adopt two strategies for the forecasts. One is the traditional model-fitting Markov-Chain Monte-Carlo method (MCMC). The results show that the combined StS alone can constrain the Hubble constant at the precision level of $0.34\%$, 1.76 times more tightly than the current most precise measurement from \textit{Planck}+BAO+Pantheon. The joint StS with current EM experiments will improve the constraints of cosmological parameters significantly. The modified gravity theory can be constrained with $0.46\%$ error from the GW propagation. In the second strategy, we use the machine-learning nonparametric reconstruction techniques, i.e., the Gaussian process (GP) with the Artificial Neural Networks (ANN) as a comparison. GP reconstructions can give comparable results with MCMC. We anticipate more works and research on these topics.

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