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Taxonomy of sub-kilometer NEOs with Machine Learning and Photometry

Presentation #409.05D in the session “Asteroids: NEOs Physical Properties 1”.

Published onOct 26, 2020
Taxonomy of sub-kilometer NEOs with Machine Learning and Photometry

As part of our multi-observatory, multi-filter campaign, we present results from observations of 237 near-Earth Objects (NEOs) obtained with the RATIR instrument on the 1.5 m robotic telescope at the San Pedro Martir’s National Observatory in Mexico. Our project is focused on rapid response photometric observations of NEOs with absolute magnitudes in the range 20-25. Our data with coverage in the near infrared and optical range was analyzed with Machine Learning techniques, while optical-only data was analyzed via Monte Carlo simulations. Our method allows us to obtain taxonomic classification of sub-kilometer objects using photometry and small telescopes, representing a convenient characterization strategy.


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