First Results from the Rapid-Response Spectrophotometric Characterization of Near-Earth Objects using UKIRT

Abstract

Using the Wide Field Camera for the United Kingdom Infrared Telescope, we measure the near-infrared colors of near-Earth objects (NEOs) in order to put constraints on their taxonomic classifications. The rapid-response character of our observations allows us to observe NEOs when they are close to the Earth and bright. Here we present near-infrared color measurements of 86 NEOs, most of which were observed within a few days of their discovery, allowing us to characterize NEOs with diameters of only a few meters. Using machine-learning methods, we compare our measurements to existing asteroid spectral data and provide probabilistic taxonomic classifications for our targets. Our observations allow us to distinguish between S-complex, C/X-complex, D-type, and V-type asteroids. Our results suggest that the fraction of S-complex asteroids in the whole NEO population is lower than the fraction of ordinary chondrites in the meteorite fall statistics. Future data obtained with UKIRT will be used to investigate the significance of this discrepancy.

arXiv comment27 pages, 6 figures, accepted by AJ

References in corpus (6)

• Scikit-learn: Machine Learning in Python
• The UKIRT Infrared Deep Sky Survey (UKIDSS)
• The UKIRT Infrared Deep Sky Survey ZYJHK Photometric System: Passbands and Synthetic Colours
• The UKIRT Wide Field Camera ZYJHK Photometric System: Calibration from 2MASS
• JHK Observations of Faint Standard Stars in the Mauna Kea Near-Infrared Photometric System
• The Need for Speed in Near-Earth Asteroid Characterization

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• SsODNet: The Solar system Open Database Network
• Near-Earth asteroids spectroscopic survey at Isaac Newton Telescope
• V-type candidates and Vesta family asteroids in the Moving Objects VISTA (MOVIS) Catalogue
• Machine Learning applied to asteroid dynamics
• The size-frequency distribution of H>13 NEOs and ARM targets detected by Pan-STARRS1
• Characterization of Near-Earth Asteroids using KMTNet-SAAO
• Taxonomy and Light-Curve Data of 1000 Serendipitously Observed Main-Belt Asteroids
• A Taxonomic Study of Asteroid Families from KMTNet-SAAO Multi-band Photometry
• First Results from the rapid-response spectrophotometric characterization of Near-Earth Objects