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Massive data mining of image archives observed with large etendue facilitiesrepresents a great opportunity for orbital amelioration of poorly known virtualimpactor asteroids (VIs). There are more than 1000 VIs known today; most ofthem have very short observed arcs and many are considered lost as they becameextremely faint soon after discovery. We aim to improve the orbits of VIs andeliminate their status by data mining the existing image archives. Within theEuropean Near Earth Asteroids Research (EURONEAR) project, we developed theVirtual Impactor search using Mega-Precovery (VIMP) software endowed with avery effective (fast and accurate) algorithm to predict apparitions ofcandidate pairs for subsequent guided human search. Considering a simplegeometric model, the VIMP algorithm searches for any possible intersection inspace and time between the positional uncertainty of any VI and the boundingsky projection of any image archive. We applied VIMP to mine the data of 451914Blanco/DECam images observed between 12 Sep 2012 and 11 Jul 2019, identifying212 VIs that possibly fall into 1286 candidate images leading to eitherprecovery or recovery events. Following a careful search of candidate images,we recovered and measured 54 VIs in 183 DECam images. About 4000 impact orbitswere eliminated from both lists, 27 VIs were removed from at least one list,while 14 objects were eliminated from both lists. The faintest detections werearound V~24.0, while the majority fall between 21<V<23. The minimal orbitalintersection distances remains constant for 67% detections, increasing foreight objects and decreasing for 10 objects. Most eliminated VIs had shortinitial arcs of less than 5 days. Some unexpected photometric discovery hasemerged regarding the rotation period of 2018 DB, based on the close inspectionof longer trailed VIs and the measurement of their fluxes along the trails.

Dozens of virtual impactor orbits eliminated by the EURONEAR VIMP DECam data mining project