부산대학교 도서관

Massive data mining of image archives observed with large etendue facilities represents a great opportunity for orbital amelioration of poorly known virtual impactor asteroids (VIs). There are more than 1000 VIs known today; most of them have very short observed arcs and many are considered lost as they became extremely faint soon after discovery. We aim to improve the orbits of VIs and eliminate their status by data mining the existing image archives. Within the European Near Earth Asteroids Research (EURONEAR) project, we developed the Virtual Impactor search using Mega-Precovery (VIMP) software endowed with a very effective (fast and accurate) algorithm to predict apparitions of candidate pairs for subsequent guided human search. Considering a simple geometric model, the VIMP algorithm searches for any possible intersection in space and time between the positional uncertainty of any VI and the bounding sky projection of any image archive. We applied VIMP to mine the data of 451914 Blanco/DECam images observed between 12 Sep 2012 and 11 Jul 2019, identifying 212 VIs that possibly fall into 1286 candidate images leading to either precovery or recovery events. Following a careful search of candidate images, we recovered and measured 54 VIs in 183 DECam images. About 4000 impact orbits were eliminated from both lists, 27 VIs were removed from at least one list, while 14 objects were eliminated from both lists. The faintest detections were around V~24.0, while the majority fall between 21Comment: Accepted for publication in Astronomy & Astrophysics (27 July 2020)