Neural-Based Compression for the Spectral Data of the New Vacuum Solar Telescope
文献类型：期刊论文
| 作者 | Dong Y(董燕)2,3; Qiang, Zhenping3; Yang JY(杨家艳)2 ; Cai YF(蔡云芳)1,2; Chen, Qingyang3; Cao, Jia3
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| 刊名 | SOLAR PHYSICS
 |
| 出版日期 | 2025-03 |
| 卷号 | 300期号:3 |
| 关键词 | Instrumentation and data management Spectrum Visible Sunspots Velocity |
| ISSN号 | 0038-0938 |
| DOI | 10.1007/s11207-025-02447-7 |
| 产权排序 | 第2完成单位 |
| 文献子类 | Article |
| 英文摘要 | 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. |
| 学科主题 | 天文学 ; 天文学 ; 太阳与太阳系 |
| URL标识 | 查看原文 |
| 出版地 | VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS |
| 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] |
| WOS研究方向 | Astronomy & Astrophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:001439367900002 |
| 出版者 | SPRINGER |
| 资助机构 | 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] |
| 版本 | 出版稿 |
| 源URL | [http://ir.ynao.ac.cn/handle/114a53/28188]  |
| 专题 | 云南天文台_抚仙湖太阳观测站 云南天文台_其他 |
| 作者单位 | 1.Yunnan Key Laboratory of the Solar Physics and Space Science, Kunming, 650216, China 2.Yunnan Observatories, Chinese Academy of Sciences, Kunming, 650011, China; 3.College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming, 650224, China; |
| 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). |
入库方式： OAI收割
来源：云南天文台
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