Taxonomic Classification of Asteroids Using the KMTNet Multiband Photometry Data Set

Sangho Choi, Hong Kyu Moon, Dong Goo Roh, Min Su Shin, Myung Jin Kim, Young Jong Sohn

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

We report the multiband photometry of asteroids observed over 14 nights from 2015 December to 2017 December using the Korea Microlensing Telescope Network telescopes with the taxonomic classification of those objects. The data set contains the photometry of 6793 asteroids in the Sloan Digital Sky Survey griz bands. Following the method of DeMeo & Carry, we define classification criteria on the 2D color plane to assign nine taxonomic types (A, B, C, K, L&D, O, S, V, and X) for the observed objects. We also determine asteroid taxonomy in the newly defined 3D color space as suggested by Roh et al. with seven distinct types based on their novel semisupervised machine-learning model. Both methods distinguish between the S type and others but have difficulty separating the X and C types due to their weak and indistinguishable features and broad distribution in the color spaces. The heliocentric distribution of the observed asteroids with their taxonomic assignments confirms similar trends in the previous works; the number of S types decreases, while the fraction of C types increases with the heliocentric distance in the main belt. On the other hand, the D type dominates in the Jupiter Trojans.

Original languageEnglish
Article number49
JournalPlanetary Science Journal
Volume4
Issue number3
DOIs
Publication statusPublished - 2023 Mar 1

Bibliographical note

Publisher Copyright:
© 2023. The Author(s). Published by the American Astronomical Society.

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Geophysics
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science

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