Astrometry in wide-field surveys

We present a robust and fast algorithm for performing astrometry and source cross-identification on lists of two-dimensional points, such as between a catalog and an astronomical image, or between two images. The method is based on minimal assumptions: the lists can be rotated, magnified, and inverted with respect to each other in an arbitrary way. The algorithm is tailored to work efficiently on wide fields with a large number of sources and significant nonlinear distortions, as long as the distortions can be approximated with linear transformations locally over the scale length of the average distance between the points. The procedure is based on symmetric point matching in a newly defined continuous triangle space that consists of triangles generated by extended Delaunay triangulation. Our software implementation performed at the 99.995% success rate on ∼ 260,000 frames taken by the HATNet project.