The Completeness of Accreting Neutron Star Binary Candidates from the Chinese Space Station Telescope
文献类型：期刊论文
| 作者 | Shen H(申灏)2,3 ; Lan SY(兰顺义)2,3; Meng XC(孟祥存)1,3
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| 刊名 | RESEARCH IN ASTRONOMY AND ASTROPHYSICS
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| 出版日期 | 2024-09-01 |
| 卷号 | 24期号:9 |
| 关键词 | stars: neutron X-rays: binaries methods: analytical |
| ISSN号 | 1674-4527 |
| DOI | 10.1088/1674-4527/ad6bd6 |
| 产权排序 | 第1完成单位 |
| 文献子类 | Article |
| 英文摘要 | A neutron star (NS) has many extreme physical conditions, and one may obtain some important information about an NS via accreting neutron star binary (ANSB) systems. The upcoming Chinese Space Station Telescope (CSST) provides an opportunity to search for a large sample of ANSB candidates. Our goal is to check the completeness of the potential ANSB samples from CSST data. In this paper, we generate some ANSBs and normal binaries under the CSST photometric system by binary evolution and binary population synthesis method and use a machine learning method to train a classification model. Although the Precision (94.56%) of our machine learning model is as high as before study, the Recall is only about 63.29%. The Precision/Recall is mainly determined by the mass transfer rate between the NSs and their companions. In addition, we also find that the completeness of ANSB samples from CSST photometric data by the machine learning method also depends on the companion mass and the age of the system. ANSB candidates with a low initial mass companion star (0.1 M- circle dot to 1 M- circle dot) have a relatively high Precision (94.94%) and high Recall (86.32%), whereas ANSB candidates with a higher initial mass companion star (1.1 M circle dot to 3 M- circle dot) have similar Precision (93.88%) and quite low Recall (42.67%). Our results indicate that although the machine learning method may obtain a relatively pure sample of ANSBs, a completeness correction is necessary for one to obtain a complete sample. |
| 学科主题 | 天文学 ; 恒星与银河系 |
| URL标识 | 查看原文 |
| 出版地 | 20A DATUN RD, CHAOYANG, BEIJING, 100101, PEOPLES R CHINA |
| WOS关键词 | X-RAY BINARIES ; NUCLEAR-EQUATION ; IA SUPERNOVAE ; MASS ; EVOLUTION ; CATALOG ; JET ; EMISSION ; PULSAR ; DISKS |
| 资助项目 | National Natural Science Foundation of China[12288102]; National Natural Science Foundation of China[12333008]; National Key R&D Program of China[2021YFA1600403]; International Centre of Supernovae, Yunnan Key Laboratory[202302AN360001]; Yunnan Revitalization Talent Support Program-Science & Technology Champion Project[202305AB350003]; Yunnan Fundamental Research Projects[202401BC070007]; Yunnan Fundamental Research Projects[202201BC070003]; China Manned Space Project |
| WOS研究方向 | Astronomy & Astrophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:001299545500001 |
| 出版者 | NATL ASTRONOMICAL OBSERVATORIES, CHIN ACAD SCIENCES |
| 资助机构 | National Natural Science Foundation of China[12288102, 12333008] ; National Key R&D Program of China[2021YFA1600403] ; International Centre of Supernovae, Yunnan Key Laboratory[202302AN360001] ; Yunnan Revitalization Talent Support Program-Science & Technology Champion Project[202305AB350003] ; Yunnan Fundamental Research Projects[202401BC070007, 202201BC070003] ; China Manned Space Project |
| 版本 | 出版稿 |
| 源URL | [http://ir.ynao.ac.cn/handle/114a53/27569]  |
| 专题 | 云南天文台_大样本恒星演化研究组 |
| 作者单位 | 1.International Centre of Supernovae, Yunnan Key Laboratory, Kunming 650216, China 2.University of Chinese Academy of Sciences, Beijing 100049, China; 3.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, China; shenhao@ynao.ac.cn, xiangcunmeng@ynao.ac.cn; |
| 推荐引用方式 GB/T 7714 | Shen H,Lan SY,Meng XC. The Completeness of Accreting Neutron Star Binary Candidates from the Chinese Space Station Telescope[J]. RESEARCH IN ASTRONOMY AND ASTROPHYSICS,2024,24(9). |
| APA | 申灏,兰顺义,&孟祥存.(2024).The Completeness of Accreting Neutron Star Binary Candidates from the Chinese Space Station Telescope.RESEARCH IN ASTRONOMY AND ASTROPHYSICS,24(9). |
| MLA | 申灏,et al."The Completeness of Accreting Neutron Star Binary Candidates from the Chinese Space Station Telescope".RESEARCH IN ASTRONOMY AND ASTROPHYSICS 24.9(2024). |
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