Overcoming separation between counterparts due to unknown proper motions in catalogue cross-matching
Overcoming separation between counterparts due to unknown proper motions in catalogue cross-matching
复制标题
克服目录交叉匹配中未知自行导致的对应物之间的分离
DOI：
10.1093/rasti/rzac009
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Wilson T
中科院分区：
文献类型：
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作者：
Wilson T
为了执行精确的光度计目录交叉匹配-在两个单独的数据集之间分配对应物-我们需要描述物体位置中所有可能的不确定性来源。随着观测之间的时间基线不断增加，如2001年的2 MASS和下一代的调查，如Vera C。鲁宾天文台的时空遗产巡天（LSST）、欧几里得和南希·格蕾丝·罗曼望远镜，我们能够鲁棒地描述和建模恒星运动对光度星表中源位置的影响至关重要。虽然盖亚以其高精度的天体测量彻底改变了天文学，但它只能提供100%的LSST源的运动;此外，LSST本身无法为低于其单次访问深度的源提供高质量的运动信息，其他调查可能根本没有测量运动。这使得大量的物体具有潜在的显著位置漂移，这可能会错误地导致匹配算法将天空中相隔太远的两个检测视为对应物。为了克服这一点，在本文中，我们描述了一个模型的统计分布的天空运动的源给定的天空坐标和亮度，允许交叉匹配过程中考虑到这种额外的潜在的银河系源之间的分离。我们进一步详细介绍了如何将这些概率自行折叠到贝叶斯交叉匹配框架中，例如Wilson & Naylor的框架。这将极大地提高恢复，例如，非常红的物体在光学红外匹配，并降低测光目录对应分配的错误匹配率。
To perform precise and accurate photometric catalogue cross-matches – assigning counterparts between two separate data sets – we need to describe all possible sources of uncertainty in object position. With ever-increasing time baselines between observations, like 2MASS in 2001 and the next generation of surveys, such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST),Euclid, and theNancy Grace Romantelescope, it is crucial that we can robustly describe and model the effects of stellar motions on source positions in photometric catalogues. WhileGaiahas revolutionized astronomy with its high-precision astrometry, it will only provide motions for ≈10 per cent of LSST sources; additionally, LSST itself will not be able to provide high-quality motion information for sources below its single-visit depth, and other surveys may measure no motions at all. This leaves large numbers of objects with potentially significant positional drifts that may incorrectly lead matching algorithms to deem two detections too far separated on the sky to be counterparts. To overcome this, in this paper, we describe a model for the statistical distribution of on-sky motions of sources of given sky coordinates and brightness, allowing for the cross-match process to take into account this extra potential separation between Galactic sources. We further detail how to fold these probabilistic proper motions into Bayesian cross-matching frameworks, such as those of Wilson & Naylor. This will vastly improve the recovery of, for example, very red objects across optical-infrared matches, and decrease the false match rate of photometric catalogue counterpart assignment.