Mining archival data from wide-field astronomical surveys in search of near-Earth objects^★

¹ Kapteyn Astronomical Institute, University of Groningen, PO Box 800, 9700 AV Groningen, The Netherlands
e-mail: teymur.saif@gmail.com
² ESA PDO NEO Coordination Centre, Largo Galileo Galilei 1, 00044 Frascati, Italy
³ Instituto de Física Aplicada a las Ciencias y las Tecnologías, Universidad de Alicante, San Vicente del Raspeig, 03080 Alicante, Spain
⁴ Institut de Ciències del Cosmos (ICCUB), Universitat de Barcelona (IEEC-UB), Carrer de Martí i Franquès 1, 08028 Barcelona, Spain
⁵ European Space Agency (ESA/ESTEC), Keplerlaan 1, 2200 XH Noordwijk, The Netherlands
⁶ Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany
⁷ European Space Agency (ESA/ESRIN), Largo Galileo Galilei 1, 00044 Frascati, Italy

Received: 20 January 2023
Accepted: 3 March 2023

Abstract

Context. Increasing our knowledge of the orbits and compositions of near-earth objects (NEOs) is important for a better understanding of the evolution of the Solar System and life. The detection of serendipitous NEO appearances among the millions of archived exposures from large astronomical imaging surveys can provide a contribution which is complementary to NEO surveys.

Aims. Using the ASTROWISE information system, this work aims to assess the detectability rate, the achieved recovery rate and the quality of astrometry when data mining the European Southern Observatory (ESO) archive for the OmegaCAM wide-field imager at the VLT Survey Telescope (VST).

Methods. We developed an automatic pipeline that searches for NEO appearances inside the ASTROWISE environment. Throughout the recovery process the pipeline uses several public web tools (SSOIS, NEODyS, JPL Horizons) to identify possible images that overlap with the positions of NEOs, and acquires information on the NEOs’ predicted position and other properties (e.g. magnitude, rate, and direction of motion) at the time of observations. Considering these properties, the pipeline narrows down the search to potentially detectable NEOs, searches for streak-like objects across the images, and finds a matching streak for the NEOs.

Results. We recovered 196 appearances of NEOs from a set of 968 appearances predicted to be recoverable. It includes appearances for three NEOs that were on the impact risk list at that point. These appearances occurred well before their discovery. The subsequent risk assessment using the extracted astrometry removes these NEOs from the risk list. More generally, we estimate a detectability rate of ~0.05 per NEO at a signal-to-noise ratio higher than 3 for NEOs in the OmegaCAM archive. Our automatic recovery rates are 40% and 20% for NEOs on the risk list and the full list, respectively. The achieved astrometric and photometric accuracy is on average 0.12″ and 0.1 mag.

Conclusions. These results show the high potential of the archival imaging data of the ground-based wide-field surveys as useful instruments for the search, (p)recovery, and characterization of NEOs. Highly automated approaches, as possible using ASTROWISE, make this undertaking feasible.