Direct parameter inference from global EoR signal with Bayesian statistics

doi:10.1093/mnras/staa052

CORC > 国家天文台 > 中国科学院国家天文台

	Direct parameter inference from global EoR signal with Bayesian statistics
	Gu, Junhua 1; Wang, Jingying 2
刊名	MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
	2020-03-01
卷号	492 期号:3 页码:4080-4096
关键词	methods: numerical methods: statistical cosmology: observations dark ages, reionization, first stars diffuse radiation
ISSN号	0035-8711
DOI	10.1093/mnras/staa052
英文摘要	In the observation of sky-averaged H I signal from Epoch of Reionization (EoR), model parameter inference can be a computation-intensive work, which makes it hard to perform a direct one-stage model parameter inference by using Markov Chain Monte Carlo (MCMC) sampling method in Bayesian framework. Instead, a two-stage inference is usually used, i.e. the parameters of some characteristic points on the EoR spectrum model are first estimated, which are then used as the input to estimate physical model parameters further. However, some previous works had noticed that this kind of method could bias results, and it could he meaningful to answer the question of whether it is feasible to perform direct one-stage MCMC sampling and obtain unbiased physical model parameter estimations. In this work, we studied this problem and confirmed the feasibility, We find that unbiased estimations to physical model parameters can be obtained with a one-stage direct MCMC sampling method. We also study the influence of some factors that should be considered in practical observations to model parameter inference. We find that a very tiny amplifier gain calibration error (10(-5) relative error) with complex spectral structures can significantly bias the parameter estimation: the frequency-dependent antenna beam and geographical position can also influence the results, so that should be carefully handled.
资助项目	Astronomical Information Technology Group ; Public Technology Service Center ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; High Performance Computing Cluster of NAOC ; National Key R&D Programme of China[2018YFA0404600] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB23010300] ; Key Projects of Frontier Science of Chinese Academy of Sciences[QYZDY-SSW-SLH022]
WOS关键词	21-CM SIGNAL ; COSMIC DAWN ; REIONIZATION ; SIGNATURES ; UNIVERSE ; EPOCH
WOS研究方向	Astronomy & Astrophysics
语种	英语
出版者	OXFORD UNIV PRESS
WOS记录号	WOS:000518143200071
资助机构	Astronomical Information Technology Group ; Astronomical Information Technology Group ; Public Technology Service Center ; Public Technology Service Center ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; High Performance Computing Cluster of NAOC ; High Performance Computing Cluster of NAOC ; National Key R&D Programme of China ; National Key R&D Programme of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Strategic Priority Research Program of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences ; Astronomical Information Technology Group ; Astronomical Information Technology Group ; Public Technology Service Center ; Public Technology Service Center ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; High Performance Computing Cluster of NAOC ; High Performance Computing Cluster of NAOC ; National Key R&D Programme of China ; National Key R&D Programme of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Strategic Priority Research Program of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences ; Astronomical Information Technology Group ; Astronomical Information Technology Group ; Public Technology Service Center ; Public Technology Service Center ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; High Performance Computing Cluster of NAOC ; High Performance Computing Cluster of NAOC ; National Key R&D Programme of China ; National Key R&D Programme of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Strategic Priority Research Program of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences ; Astronomical Information Technology Group ; Astronomical Information Technology Group ; Public Technology Service Center ; Public Technology Service Center ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; National Astronomical Observatories, Chinese Academy of Sciences (NAOC) ; High Performance Computing Cluster of NAOC ; High Performance Computing Cluster of NAOC ; National Key R&D Programme of China ; National Key R&D Programme of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Strategic Priority Research Program of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences ; Key Projects of Frontier Science of Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.bao.ac.cn/handle/114a11/54280]
专题	中国科学院国家天文台
通讯作者	Gu, Junhua; Wang, Jingying
作者单位	1.Chinese Acad Sci, Natl Astron Observ, 20A Datun Rd, Beijing 100101, Peoples R China 2.Univ Western Cape, Dept Phys & Astron, ZA-7535 Cape Town, South Africa
推荐引用方式 GB/T 7714	Gu, Junhua,Wang, Jingying. Direct parameter inference from global EoR signal with Bayesian statistics[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2020,492(3):4080-4096.
APA	Gu, Junhua,&Wang, Jingying.(2020).Direct parameter inference from global EoR signal with Bayesian statistics.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,492(3),4080-4096.
MLA	Gu, Junhua,et al."Direct parameter inference from global EoR signal with Bayesian statistics".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 492.3(2020):4080-4096.