TY - JOUR
T1 - Mining archival data from wide-field astronomical surveys in search of near-Earth objects
AU - Saifollahi, Teymoor
AU - Kleijn, Gijs Verdoes
AU - Williams, Rees
AU - Micheli, Marco
AU - Santana-Ros, Toni
AU - Helmich, Ewout
AU - Koschny, Detlef
AU - Conversi, Luca
N1 - Funding Information:
We would like to thank the referee for their comments and suggestions to improve the quality of this work. We are happy to acknowledge and are grateful to Angela Maria Raj, Katya Frantseva, Migo Müller, Stephen Gwyn, Ylse de Vries, Konrad Kuijken, Danny Boxhoorn, Willem-Jan Vriend, KiDS DR5 production team, Michiel Rodenhuis, Thomas Wijnen, Edwin Valentijn and the Kapteyn institute. This work was executed as part of ESA contract no. 4000134667/21/D/MRP (CARMEN) with their Planetary Defence Office. The Big Data Layer of the Target Field Lab project Mining Big Data was used. The Target Field Lab is supported by the Northern Netherlands Alliance (SNN) and is financially supported by the European Regional Development Fund. The data science software system ASTROWISE runs on powerful databases and computing clusters at the Donald Smits Center of the University of Groningen and is supported, among other parties, by NOVA (the Dutch Research School for Astronomy). TSR acknowledges funding from the NEO-MAPP project (H2020-EU-2-1-6/870377). This work was (partially) supported by the Spanish MICIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe by the European Union through grant PID2021-122842OB-C21, and the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia Maria de Maeztu) through grant CEX2019-000918-M. This research has made use of the Aladin sky atlas (Bonnarel et al. 2000; Boch & Fernique 2014) developed at CDS, Strasbourg Observatory, France and SAOIm-ageDS9 (Joye & Mandel 2003). This work has been done using the following software, packages and PYTHON libraries: Astro-WISE (Begeman et al. 2013; McFarland et al. 2013), NUMPY (van der Walt et al. 2011), SCIPY (Virtanen et al. 2020), ASTROPY (Astropy Collaboration 2018)
Funding Information:
We would like to thank the referee for their comments and suggestions to improve the quality of this work. We are happy to acknowledge and are grateful to Angela Maria Raj, Katya Frantseva, Migo Müller, Stephen Gwyn, Ylse de Vries, Konrad Kuijken, Danny Boxhoorn, Willem-Jan Vriend, KiDS DR5 production team, Michiel Rodenhuis, Thomas Wijnen, Edwin Valentijn and the Kapteyn institute. This work was executed as part of ESA contract no. 4000134667/21/D/MRP (CARMEN) with their Planetary Defence Office. The Big Data Layer of the Target Field Lab project “Mining Big Data” was used. The Target Field Lab is supported by the Northern Netherlands Alliance (SNN) and is financially supported by the European Regional Development Fund. The data science software system A STRO WISE runs on powerful databases and computing clusters at the Donald Smits Center of the University of Groningen and is supported, among other parties, by NOVA (the Dutch Research School for Astronomy). TSR acknowledges funding from the NEO-MAPP project (H2020-EU-2-1-6/870377). This work was (partially) supported by the Spanish MICIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” by the “European Union” through grant PID2021-122842OB-C21, and the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia “María de Maeztu”) through grant CEX2019-000918-M. This research has made use of the Aladin sky atlas (Bonnarel et al. 2000; Boch & Fernique 2014) developed at CDS, Strasbourg Observatory, France and SAOIm-ageDS9 (Joye & Mandel 2003). This work has been done using the following software, packages and PYTHON libraries: Astro-WISE (Begeman et al. 2013; McFarland et al. 2013), N UMPY (van der Walt et al. 2011), S CIPY (Virtanen et al. 2020), A STROPY (Astropy Collaboration 2018).
Publisher Copyright:
© The Authors 2023.
PY - 2023/5
Y1 - 2023/5
N2 - 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.
AB - 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.
KW - Asteroids: general
KW - Astrometry
KW - Astronomical databases: miscellaneous
KW - Methods: data analysis
KW - Methods: observational
KW - Minor planets
KW - Techniques: photometric
UR - http://www.scopus.com/inward/record.url?scp=85160424643&partnerID=8YFLogxK
U2 - 10.1051/0004-6361/202345957
DO - 10.1051/0004-6361/202345957
M3 - Article
AN - SCOPUS:85160424643
SN - 0004-6361
VL - 673
JO - Astronomy and astrophysics
JF - Astronomy and astrophysics
M1 - A93
ER -