Asteroids, Comets, Meteors - ACM2017 - Montevideo A FRAMEWORK FOR INFERRING TAXONOMIC CLASS OF ASTEROIDS

Introduction: Taxonomic classification of asteroids based on their visible / near-ir spectra or multi band photometry has proven to be a useful tool to infer other properties about asteroids. Meteorite analogs have been identified for several taxonomic classes, permitting detailed inference about asteroid composition [1], [2]. Trends have been identified between taxonomy and measured asteroid density [3]. Thanks to NEOWise and Spitzer, approximately twice as many asteroids have measured albedos than the number with taxonomic classifications. (If one only considers spectroscopically determined classifications, the ratio is > 40.) We present a bayesian framework that provides probabilistic estimates of the taxonomic class of an asteroid based on its albedo. Although probabilistic estimates of taxonomic classes are not a replacement for spectroscopic or photometric determinations, they can be a useful tool for identifying objects for further study or for asteroid threat assessment models [4].