NAOC Open IR
Baryon acoustic oscillations reconstruction using convolutional neural networks
Mao, Tian-Xiang1,2; Wang, Jie1,2; Li, Baojiu3; Cai, Yan-Chuan4; Falck, Bridget5; Neyrinck, Mark6,7; Szalay, Alex5
2021-02-01
Source PublicationMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
ISSN0035-8711
Volume501Issue:1Pages:1499-1510
AbstractWe propose a new scheme to reconstruct the baryon acoustic oscillations (BAO) signal, which contains key cosmological information, based on deep convolutional neural networks (CNN). Trained with almost no fine tuning, the network can recover large-scale modes accurately in the test set: the correlation coefficient between the true and reconstructed initial conditions reaches 90 per cent at k <=Psi 0.2 hMpc(-1), which can lead to significant improvements of the BAO signal-to-noise ratio down to k similar or equal to 0.4 hMpc(-1). Since this new scheme is based on the configuration-space density field in sub-boxes, it is local and less affected by survey boundaries than the standard reconstruction method, as our tests confirm. We find that the network trained in one cosmology is able to reconstruct BAO peaks in the others, i.e. recovering information lost to non-linearity independent of cosmology. The accuracy of recovered BAO peak positions is far less than that caused by the difference in the cosmology models for training and testing, suggesting that different models can be distinguished efficiently in our scheme. It is very promising that our scheme provides a different new way to extract the cosmological information from the ongoing and future large galaxy surveys.
Keywordcosmological parameters dark energy large-scale structure of Universe
Funding OrganizationNational Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud
DOI10.1093/mnras/staa3741
WOS KeywordLARGE-SCALE STRUCTURE ; COSMIC DENSITY FIELD ; DARK ENERGY SURVEY ; ITERATIVE RECONSTRUCTION ; DISTANCE MEASUREMENTS ; INITIAL CONDITIONS ; GALAXIES ; I. ; PERTURBATION ; SIMULATIONS
Language英语
Funding ProjectNational Natural Science Foundation of China (NSFC)[11873051] ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud
Funding OrganizationNational Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Astronomical Big Data Joint Research Center ; Astronomical Big Data Joint Research Center ; National Astronomical Observatories, Chinese Academy of Sciences ; National Astronomical Observatories, Chinese Academy of Sciences ; Alibaba Cloud ; Alibaba Cloud
WOS Research AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000608474800112
PublisherOXFORD UNIV PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/79761
Collection中国科学院国家天文台
Corresponding AuthorMao, Tian-Xiang
Affiliation1.Chinese Acad Sci, Natl Astron Observ, Beijing 100012, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Univ Durham, Inst Computat Cosmol, Dept Phys, Durham DH1 3LE, England
4.Univ Edinburgh, Inst Astron, Royal Observ, Blackford Hill, Edinburgh EH9 3HJ, Midlothian, Scotland
5.Johns Hopkins Univ, Dept Phys & Astron, Baltimore, MD 21218 USA
6.Basque Fdn Sci, Ikerbasque, E-48080 Bilbao, Spain
7.Univ Basque Country, Dept Phys, E-48080 Bilbao, Spain
Recommended Citation
GB/T 7714
Mao, Tian-Xiang,Wang, Jie,Li, Baojiu,et al. Baryon acoustic oscillations reconstruction using convolutional neural networks[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2021,501(1):1499-1510.
APA Mao, Tian-Xiang.,Wang, Jie.,Li, Baojiu.,Cai, Yan-Chuan.,Falck, Bridget.,...&Szalay, Alex.(2021).Baryon acoustic oscillations reconstruction using convolutional neural networks.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,501(1),1499-1510.
MLA Mao, Tian-Xiang,et al."Baryon acoustic oscillations reconstruction using convolutional neural networks".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 501.1(2021):1499-1510.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Mao, Tian-Xiang]'s Articles
[Wang, Jie]'s Articles
[Li, Baojiu]'s Articles
Baidu academic
Similar articles in Baidu academic
[Mao, Tian-Xiang]'s Articles
[Wang, Jie]'s Articles
[Li, Baojiu]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Mao, Tian-Xiang]'s Articles
[Wang, Jie]'s Articles
[Li, Baojiu]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.