Tycho-2 TDSC Merge Best Neighbour

Table <code>tycho2tdsc_merge_best_neighbour</code> lists each matched external catalogue object with its best neighbour in Gaia. The cross-match algorithm is not symmetric and searches Tycho2tdscMerge source counterparts in Gaia. The best neighbour is chosen among good neighbours as the one with the highest value of the figure of merit, which evaluates the ratio between two opposite models/hypotheses: the counterpart candidate is a match or it is found by chance. Good neighbours are nearby objects in Gaia whose position is compatible within position errors with the external catalogue target. The cross-match algorithm is positional and exploits the full 5 parameter covariance matrix of the Gaia astrometric solution when available and the external catalogue positions and position errors. In addition it takes into account the Gaia environment using the local density.
Please note that the cross-match algorithm is a trade-off between multiple requirements, in particular between completeness and correctness. It is thus not limited to a simple cone search.
Reference papers:

Marrese et al. (2017)
Marrese et al. (2019)

表<code>tycho2tdsc_merge_best_neighbour</code>列出了每个匹配的外部星表天体及其在盖亚（Gaia）中的最佳邻源。该交叉匹配算法不具备对称性，其搜索目标为在盖亚星表中匹配Tycho2tdscMerge源的对应体。最佳邻源从合格邻源中遴选，即品质因数最高的对象；该品质因数用于评估两种对立模型/假设的比值：对应体候选为真实匹配，或是偶然探测得到的结果。合格邻源指盖亚星表中位置与外部星表目标的位置误差范围内相容的邻近天体。该交叉匹配算法基于位置信息，在可用时会利用盖亚天体测量解的完整五参数协方差矩阵，以及外部星表的天体位置与位置误差。此外，该算法还通过局域密度信息考量盖亚星表的天体环境。
请注意，该交叉匹配算法是多项需求之间的折中方案，尤其需在完备性与正确性之间取得平衡，因此其并不局限于简单的圆锥搜索。
参考文献：
Marrese等人（2017）
Marrese等人（2019）