Application of Regularization Methods in the Sky Map Reconstruction of the Tianlai Cylinder Pathfinder Array

IF 1.8 4区 物理与天体物理 Q3 ASTRONOMY & ASTROPHYSICS Research in Astronomy and Astrophysics Pub Date : 2023-12-02 DOI:10.1088/1674-4527/ad1223
Kaifeng Yu, S. Zuo, Fengquan Wu, Yougang Wang, Xuelei Chen
{"title":"Application of Regularization Methods in the Sky Map Reconstruction of the Tianlai Cylinder Pathfinder Array","authors":"Kaifeng Yu, S. Zuo, Fengquan Wu, Yougang Wang, Xuelei Chen","doi":"10.1088/1674-4527/ad1223","DOIUrl":null,"url":null,"abstract":"\n The Tianlai cylinder pathfinder is a radio interferometer array to test 21 cm intensity mapping techniques in the post-reionization era. It works in passive drift scan mode to survey the sky visible in the northern hemisphere. To deal with the large instantaneous field of view and the spherical sky, we decompose the drift scan data into $m$-modes, which are linearly related to the sky intensity. The sky map is reconstructed by solving the linear interferometer equations. Due to incomplete $uv$ coverage of the interferometer baselines, this inverse problem is usually ill-posed, and regularization method is needed for its solution. In this paper, we use simulation to investigate two frequently used regularization methods, the Truncated Singular Value Decomposition (TSVD), and the Tikhonov regularization techniques. Choosing the regularization parameter is very important for its application. We employ the generalized cross validation (GCV) method and the L-curve method to determine the optimal value. We compare the resulting maps obtained with the different regularization methods, and for the different parameters derived using the different criteria. While both methods can yield good maps for a range of regularization parameters, in the Tikhonov method the suppression of noisy modes are more gradually applied, produce more smooth maps which avoids some visual artefacts in the maps generated with the TSVD method.","PeriodicalId":54494,"journal":{"name":"Research in Astronomy and Astrophysics","volume":"70 5","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research in Astronomy and Astrophysics","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1088/1674-4527/ad1223","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
引用次数: 0

Abstract

The Tianlai cylinder pathfinder is a radio interferometer array to test 21 cm intensity mapping techniques in the post-reionization era. It works in passive drift scan mode to survey the sky visible in the northern hemisphere. To deal with the large instantaneous field of view and the spherical sky, we decompose the drift scan data into $m$-modes, which are linearly related to the sky intensity. The sky map is reconstructed by solving the linear interferometer equations. Due to incomplete $uv$ coverage of the interferometer baselines, this inverse problem is usually ill-posed, and regularization method is needed for its solution. In this paper, we use simulation to investigate two frequently used regularization methods, the Truncated Singular Value Decomposition (TSVD), and the Tikhonov regularization techniques. Choosing the regularization parameter is very important for its application. We employ the generalized cross validation (GCV) method and the L-curve method to determine the optimal value. We compare the resulting maps obtained with the different regularization methods, and for the different parameters derived using the different criteria. While both methods can yield good maps for a range of regularization parameters, in the Tikhonov method the suppression of noisy modes are more gradually applied, produce more smooth maps which avoids some visual artefacts in the maps generated with the TSVD method.
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
正则化方法在天来圆柱探路者阵列天图重建中的应用
天来圆柱体探路者是一种无线电干涉仪阵列,用于测试后再电离时代的21厘米强度测绘技术。它在被动漂移扫描模式下工作,以测量北半球可见的天空。为了处理大的瞬时视场和球形天空,我们将漂移扫描数据分解成与天空强度线性相关的$m$-模式。通过求解线性干涉仪方程,重构了天象图。由于干涉仪基线的不完全覆盖,该逆问题通常是不适定的,需要正则化方法来求解。本文通过仿真研究了截断奇异值分解(TSVD)和Tikhonov正则化技术这两种常用的正则化方法。正则化参数的选择对正则化算法的应用至关重要。我们采用广义交叉验证(GCV)法和l曲线法来确定最优值。我们比较了不同正则化方法得到的结果图,以及使用不同准则得到的不同参数。虽然这两种方法都可以为一系列正则化参数生成良好的映射,但在Tikhonov方法中,对噪声模式的抑制更逐步地应用,生成更光滑的映射,从而避免了TSVD方法生成的映射中的一些视觉伪影。
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
Research in Astronomy and Astrophysics
Research in Astronomy and Astrophysics 地学天文-天文与天体物理
CiteScore
3.20
自引率
16.70%
发文量
2599
审稿时长
6.0 months
期刊介绍: Research in Astronomy and Astrophysics (RAA) is an international journal publishing original research papers and reviews across all branches of astronomy and astrophysics, with a particular interest in the following topics: -large-scale structure of universe formation and evolution of galaxies- high-energy and cataclysmic processes in astrophysics- formation and evolution of stars- astrogeodynamics- solar magnetic activity and heliogeospace environments- dynamics of celestial bodies in the solar system and artificial bodies- space observation and exploration- new astronomical techniques and methods
期刊最新文献
Comparison of NH3 and 12CO, 13CO, C18O Molecular Lines in the Aquila Rift Cloud Complex SFNet: Stellar Feature Network with CWT for Stellar Spectra Recognition A Study of the Comets with Large Perihelion Distances C/2019 L3 (ATLAS) and C/2019 O3 (Palomar) Understanding the Impact of H2 Diffusion Energy on the Formation Efficiency of H2 on the Interstellar Dust Grain Surface Leveraging the Empirical Wavelet Transform in Combination with Convolutional LSTM Neural Networks to Enhance the Accuracy of Polar Motion Prediction
×
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