Improving Catalogue Matching By Supplementing Astrometry with Additional Photometric Information

Improving Catalogue Matching By Supplementing Astrometry with Additional Photometric Information
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通过用额外的光度信息补充天体测量来改进目录匹配

DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
T. Naylor
T. Naylor
中科院分区：
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文献类型：
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作者：
T. Wilson;T. Naylor

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作者感谢裁判的全面报告， 有用的意见，这有助于我们改进这份文件。 TJW感谢STFC助学金的支持。 这项工作利用了SciPy（Jones等人，2001年）， NumPy（货车der Walt等人，2011）、Matplotlib（Hunter 2007）和F2 PY（Peterson 2009）Python模块。 本文利用了作为研究的一部分所获得的数据， 北方银道面INT测光H_2巡天 （IPHAS，www.iphas.org）在艾萨克·牛顿 望远镜（INT）。INT在La岛上运营 Isaac Newton Group在西班牙的Obser Vatorio del Roque de los Muchachos Astro_sica de Canarias.所有IPHAS数据均由 剑桥天文调查组， 剑桥的天文学教授合并后的DR 2 cata- 在天体物理学研究中心（Centre for Astrophysics Re） 搜索，赫特福德大学，由STFC支持 授权ST/J 001333/1。 本出版物使用了 两微米全天巡天，这是一个联合项目， 马萨诸塞州大学和红外处理和 分析中心/加州理工学院，资助 由美国国家航空航天局和 国家科学基金会。 这项工作利用了来自 欧洲航天局（欧空局）盖亚使命 (http：//www.cosmos.esa.int/gaia），由 盖亚数据处理和分析联盟（DPAC， http://www.cosmos.esa.int/web/gaia/dpac/consortium). DPAC的资金由国家机构提供， 特别是参加《教育法》的机构 盖亚多边协定。
The authors thank the referee for their thorough report and useful comments, which helped us to improve this paper. TJW acknowledges support from an STFC Studentship. This work has made use of the SciPy (Jones et al. 2001), NumPy (van der Walt et al. 2011), Matplotlib (Hunter 2007), and F2PY (Peterson 2009) Python modules. This paper makes use of data obtained as part of the INT Photometric H_ Survey of the Northern Galactic Plane (IPHAS, www.iphas.org) carried out at the Isaac Newton Telescope (INT). The INT is operated on the island of La Palma by the Isaac Newton Group in the Spanish Obser- vatorio del Roque de los Muchachos of the Instituto de Astro_sica de Canarias. All IPHAS data are processed by the Cambridge Astronomical Survey Unit, at the Institute of Astronomy in Cambridge. The bandmerged DR2 cata- logue was assembled at the Centre for Astrophysics Re- search, University of Hertfordshire, supported by STFC grant ST/J001333/1. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This work has made use of data from the European Space Agency (ESA) mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, http://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national insti- tutions, in particular the institutions participating in the Gaia Multilateral Agreement.