Neural-Based Compression for the Spectral Data of the New Vacuum Solar Telescope

doi:10.1007/s11207-025-02447-7

YNAO OpenIR > 抚仙湖太阳观测和研究基地

	Neural-Based Compression for the Spectral Data of the New Vacuum Solar Telescope
	Dong Y(董燕)1,2; Qiang, Zhenping 1; Yang JY(杨家艳)2 ; Cai YF(蔡云芳)2,3 ; Chen, Qingyang 1; Cao, Jia 1
发表期刊	SOLAR PHYSICS
	2025-03
卷号	300 期号:3
DOI	10.1007/s11207-025-02447-7
产权排序	第2完成单位
收录类别	SCI
关键词	Instrumentation and data management Spectrum Visible Sunspots Velocity
摘要	Due to the rapid increase in spectral data generation as well as storage and transmission constraints, data compression has become particularly important for the New Vacuum Solar Telescope (NVST) at Yunnan Observatory. In this paper, we present a method for compressing NVST Ca II (8542 & Aring;) spectral data based on a Convolutional Variational Autoencoder (VAE). Our results show that the compression ratios of the VAE-based approach may achieve as high as 107, while keeping the error between the decompressed data and the original data within the inherent error range of the raw data. This is much better than the appropriate compression ratio of 30 that is attained using the current PCA-based approach. Furthermore, the stability of the VAE approach is demonstrated by the almost constant differences between the VAE-compressed data and the raw data when the compression ratio ranges from 8 to 107. We also investigated Doppler velocity images deduced from the VAE-compressed data and found that the error in Doppler velocity is significantly less than 5 km s-1 when the compression ratio does not exceed 107.
资助项目	National Natural Science Foundation of China (NSFC)[12163004]; National Natural Science Foundation of China (NSFC)[12373115]; National Natural Science Foundation of China (NSFC)[12273110]; Yunnan Fundamental Research Projects (CN)[202301BD070001-008]; Yunnan Fundamental Research Projects (CN)[202401AW07006]; Yunnan Province XingDian Talent Support Program; The Yunnan Revitalization Talent Support Program Innovation Team Project[202405AS350012]
项目资助者	National Natural Science Foundation of China (NSFC)[12163004, 12373115, 12273110] ; Yunnan Fundamental Research Projects (CN)[202301BD070001-008, 202401AW07006] ; Yunnan Province XingDian Talent Support Program ; The Yunnan Revitalization Talent Support Program Innovation Team Project[202405AS350012]
语种	英语
学科领域	天文学 ; 天文学 ; 太阳与太阳系
文章类型	Article
出版者	SPRINGER
出版地	VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN	0038-0938
URL	查看原文
WOS记录号	WOS:001439367900002
WOS研究方向	Astronomy & Astrophysics
WOS类目	Astronomy & Astrophysics
引用统计
文献类型	期刊论文
版本	出版稿
条目标识符	http://ir.ynao.ac.cn/handle/114a53/28188
专题	抚仙湖太阳观测和研究基地其他
作者单位	1.College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming, 650224, China; 2.Yunnan Observatories, Chinese Academy of Sciences, Kunming, 650011, China; 3.Yunnan Key Laboratory of the Solar Physics and Space Science, Kunming, 650216, China
第一作者单位	中国科学院云南天文台
推荐引用方式 GB/T 7714	Dong Y,Qiang, Zhenping,Yang JY,et al. Neural-Based Compression for the Spectral Data of the New Vacuum Solar Telescope[J]. SOLAR PHYSICS,2025,300(3).
APA	董燕,Qiang, Zhenping,杨家艳,蔡云芳,Chen, Qingyang,&Cao, Jia.(2025).Neural-Based Compression for the Spectral Data of the New Vacuum Solar Telescope.SOLAR PHYSICS,300(3).
MLA	董燕,et al."Neural-Based Compression for the Spectral Data of the New Vacuum Solar Telescope".SOLAR PHYSICS 300.3(2025).

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