Chrome Extension
WeChat Mini Program
Use on ChatGLM

Hubble Parameter Estimation Via Dark Sirens with the LISA-Taiji Network

National Science Review(2021)SCI 1区

Beijing Normal Univ | Chinese Acad Sci | Shenzhen Technol Univ

Cited 25|Views27
Abstract
The Hubble parameter is one of the central parameters in modern cosmology, and describes the present expansion rate of the universe. The values of the parameter inferred from late-time observations are systematically higher than those inferred from early-time measurements by about 10%. To reach a robust conclusion, independent probes with accuracy at percent levels are crucial. Gravitational waves from compact binary coalescence events can be formulated into the standard siren approach to provide an independent Hubble parameter measurement. The future space-borne gravitational wave observatory network, such as the LISA-Taiji network, will be able to measure the gravitational wave signals in the millihertz bands with unprecedented accuracy. By including several statistical and instrumental noises, we show that, within a five-year operation time, the LISA-Taiji network is able to constrain the Hubble parameter within 1% accuracy, and possibly beats the scatters down to 0.5% or even better.
More
Translated text
Key words
gravitational waves,Hubble parameter,super massive black hole
PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Curt Cutler
1997

被引用425 | 浏览

Alison Abbott
2017

被引用810 | 浏览

2017

被引用293 | 浏览

Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:本文提出利用LISA-Taiji网络通过暗 sirens方法测量哈勃参数,实现了1%的精确度,有望进一步降低至0.5%以下,为解决宇宙膨胀率分歧提供了一种独立的高精度测量手段。

方法】:采用暗 sirens方法,即通过引力波观测紧凑双星合并事件来估计哈勃参数。

实验】:通过模拟包括统计和仪器噪声在内的LISA-Taiji网络五年运行数据,结果显示该网络能够将哈勃参数的约束精度提高至1%以内。