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File-based retrieval of large astronomical catalogs using a HEALPix-R-Tree hybrid index

文献类型：期刊论文

作者Ren SY(任思颖)1,2; Wang CJ(王传军)1,2; Fan, Dongwei2,3; Fang, Yuan4; Ding X(丁旭)1; Shu P(舒鹏)1; Xiao HC(肖恒初)1,2
刊名ASTRONOMY AND COMPUTING
出版日期2026-04
卷号55
关键词Astroinformatics Data structures Large-scale astronomical data Two-level spatial index
ISSN号2213-1337
DOI10.1016/j.ascom.2026.101094
产权排序第1完成单位
文献子类Article
英文摘要With the rapid growth of astronomical datasets, efficient and accessible methods for catalog management and retrieval are crucial. Database systems offer powerful queries but incur setup and maintenance overhead, while file-based management is straightforward yet lacks efficient indexing. Conventional single-level sky-partitioning indexes may reach their limit as data volume increases. To address these limitations, this study proposes a two-level spatial indexing framework that combines sky partitioning with secondary spatial indexing. HEALPix provides a coarse-grained, first-level index; within each partition, an R-tree index is built for fine-grained spatial filtering. For a cone search centered at (292 degrees, 10 degrees) with a 0.1 degrees radius on the Gaia DR3 catalog, the proposed method reduces the number of angular-distance calculations by 97.1% (from 342,749 to 13,246) and decreases query time from 9098 ms to 1874 ms at partitioning level 7, compared with single-level HEALPix indexing. Experiments across multiple regions further demonstrate stable performance improvements across different source-density conditions. Deployed on the Lijiang 2.4-meter Telescope's server, this framework furthermore supports batch object identification and catalog fusion, demonstrating its practical scalability as a general-purpose extension to traditional single-level indexing.
学科主题天文学 ; 天文学其他学科 ; 计算机科学技术 ; 计算机应用
URL标识查看原文
出版地RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
资助项目National Key R&D Program of China[2022YFF0711500]; National Key R&D Program of China[2023YFA1608300]; National Natural Science Foundation of China[12573114]; National Natural Science Foundation of China[12103088]; Yunnan Revitalization Talent Support Program, China (Young Talent Project: Research on the Key Technologies of the Observation Control System Based on Data-Driven Methods); Yunnan Basic Research Program, China[202501AT070027]
WOS研究方向Astronomy & Astrophysics ; Computer Science
语种英语
WOS记录号WOS:001709517900001
出版者ELSEVIER
资助机构National Key R&D Program of China[2022YFF0711500, 2023YFA1608300] ; National Natural Science Foundation of China[12573114, 12103088] ; Yunnan Revitalization Talent Support Program, China (Young Talent Project: Research on the Key Technologies of the Observation Control System Based on Data-Driven Methods) ; Yunnan Basic Research Program, China[202501AT070027]
版本出版稿
源URL[http://ir.ynao.ac.cn/handle/114a53/29034]  
专题云南天文台_应用天文研究组
通讯作者Ren SY(任思颖)
作者单位1.Yunnan Observatories (YNAO), Chinese Academy of Sciences (CAS), Kunming, 650216, China;
2.School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing, 101408, China;
3.National Astronomical Observatories (NAO), Chinese Academy of Sciences (CAS), Beijing, 100101, China;
4.South-Western Institute for Astronomy Research, Yunnan University, Kunming, 650504, China
推荐引用方式
GB/T 7714		 Ren SY,Wang CJ,Fan, Dongwei,et al. File-based retrieval of large astronomical catalogs using a HEALPix-R-Tree hybrid index[J]. ASTRONOMY AND COMPUTING,2026,55.
APA 任思颖.,王传军.,Fan, Dongwei.,Fang, Yuan.,丁旭.,...&肖恒初.(2026).File-based retrieval of large astronomical catalogs using a HEALPix-R-Tree hybrid index.ASTRONOMY AND COMPUTING,55.
MLA 任思颖,et al."File-based retrieval of large astronomical catalogs using a HEALPix-R-Tree hybrid index".ASTRONOMY AND COMPUTING 55(2026).

入库方式： OAI收割

来源：云南天文台

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