Identification of new M 31 star cluster candidates from PAndAS images using convolutional neural networks
文献类型:期刊论文
作者 | Wang, Shoucheng3,4,5; Chen, Bingqiu4; Ma, Jun3,5; Long Q(龙潜)2; Yuan, Haibo1; Liu, Dezi4; Zhou, Zhimin5; Liu, Wei8; Chen, Jiamin7; He, Zizhao3,6 |
刊名 | ASTRONOMY & ASTROPHYSICS |
出版日期 | 2022-02-01 |
卷号 | 658 |
ISSN号 | 0004-6361 |
关键词 | galaxies: star clusters: general galaxies: star clusters: individual: M 31 |
DOI | 10.1051/0004-6361/202142169 |
产权排序 | 第4完成单位 |
文献子类 | Article |
英文摘要 | Context. Identification of new star cluster candidates in M 31 is fundamental for the study of the M 31 stellar cluster system. The machine-learning method convolutional neural network (CNN) is an efficient algorithm for searching for new M 31 star cluster candidates from tens of millions of images from wide-field photometric surveys. Aims. We search for new M 31 cluster candidates from the high-quality g- and i-band images of 21 245 632 sources obtained from the Pan-Andromeda Archaeological Survey (PAndAS) through a CNN. Methods. We collected confirmed M 31 clusters and noncluster objects from the literature as our training sample. Accurate double-channel CNNs were constructed and trained using the training samples. We applied the CNN classification models to the PAndAS g-and i-band images of over 21 million sources to search new M 31 cluster candidates. The CNN predictions were finally checked by five experienced human inspectors to obtain high-confidence M 31 star cluster candidates. Results. After the inspection, we identified a catalogue of 117 new M 31 cluster candidates. Most of the new candidates are young clusters that are located in the M 31 disk. Their morphology, colours, and magnitudes are similar to those of the confirmed young disk clusters. We also identified eight globular cluster candidates that are located in the M 31 halo and exhibit features similar to those of confirmed halo globular clusters. The projected distances to the M 31 centre for three of them are larger than 100 kpc. |
学科主题 | 天文学 ; 恒星与银河系 |
URL标识 | 查看原文 |
出版地 | 17, AVE DU HOGGAR, PA COURTABOEUF, BP 112, F-91944 LES ULIS CEDEX A, FRANCE |
WOS关键词 | KILO-DEGREE SURVEY ; GLOBULAR-CLUSTERS ; DATA RELEASE ; SKY SURVEY ; M31 ; I. ; CATALOG ; PHOTOMETRY ; GALAXY ; FIELD |
资助项目 | National Key R&D Program of China[2019YFA0405501] ; National Key R&D Program of China[2019YFA0405503] ; National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China (NSFC)[11803029] ; National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China (NSFC)[11873053] ; National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China (NSFC)[11773074] ; Yunnan University[C619300A034] |
WOS研究方向 | Astronomy & Astrophysics |
语种 | 英语 |
出版者 | EDP SCIENCES S A |
WOS记录号 | WOS:000749262400001 |
资助机构 | National Key R&D Program of China[2019YFA0405501, 2019YFA0405503] ; National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China (NSFC)[11803029, 11873053, 11773074] ; Yunnan University[C619300A034] |
版本 | 出版稿 |
源URL | [http://ir.ynao.ac.cn/handle/114a53/24845] |
专题 | 云南天文台_丽江天文观测站(南方基地) |
通讯作者 | Chen, Bingqiu |
作者单位 | 1.Department of Astronomy, Beijing Normal University, Beijing 100875, PR China; 2.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, PR China; 3.School of Astronomy and Space Sciences, University of Chinese Academy of Sciences, Beijing 100049, PR China; 4.South-Western Institute for Astronomy Research, Yunnan University, Kunming, Yunnan 650091, PR China; 5.Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, PR China; 6.Key Laboratory of Space Astronomy and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, PR China 7.School of Computer Science and Engineering, Central South University, Changsha 410083, PR China; 8.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, PR China; |
推荐引用方式 GB/T 7714 | Wang, Shoucheng,Chen, Bingqiu,Ma, Jun,et al. Identification of new M 31 star cluster candidates from PAndAS images using convolutional neural networks[J]. ASTRONOMY & ASTROPHYSICS,2022,658. |
APA | Wang, Shoucheng.,Chen, Bingqiu.,Ma, Jun.,Long Q.,Yuan, Haibo.,...&He, Zizhao.(2022).Identification of new M 31 star cluster candidates from PAndAS images using convolutional neural networks.ASTRONOMY & ASTROPHYSICS,658. |
MLA | Wang, Shoucheng,et al."Identification of new M 31 star cluster candidates from PAndAS images using convolutional neural networks".ASTRONOMY & ASTROPHYSICS 658(2022). |
入库方式: OAI收割
来源:云南天文台
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