Taxonomy of sub-kilometer NEOs with Machine Learning and Photometry
Abstract
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.
- Publication:
-
AAS/Division for Planetary Sciences Meeting Abstracts
- Pub Date:
- October 2020
- Bibcode:
- 2020DPS....5240905N