Asteroid Taxonomy from Cluster Analysis of Spectrometry and Albedo
Max Mahlke, Benoit Carry, Pierre-Alexandre Mattei

TL;DR
This paper introduces an improved asteroid taxonomy that classifies partial and complete spectrometry and albedo data, providing probabilistic class assignments and accommodating new observational datasets.
Contribution
It presents a novel taxonomy method incorporating albedo and partial data, with probabilistic classifications, based on a significantly larger dataset than previous work.
Findings
Identified 17 asteroid classes including a new Z-class.
Resolved spectral degeneracy of the X-complex using albedo.
Classified over 6000 observations of more than 4500 asteroids.
Abstract
The classification of the minor bodies of the Solar System based on observables has been continuously developed and iterated over the past 40 years. While prior iterations followed either the availability of large observational campaigns or new instrumental capabilities opening new observational dimensions, we see the opportunity to improve primarily upon the established methodology. We developed an iteration of the asteroid taxonomy which allows the classification of partial and complete observations (i.e. visible, near-infrared, and visible-near-infrared spectrometry) and which reintroduces the visual albedo into the classification observables. The resulting class assignments are given probabilistically, enabling the uncertainty of a classification to be quantified. We built the taxonomy based on 2983 observations of 2125 individual asteroids, representing an almost tenfold…
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Taxonomy
TopicsIsotope Analysis in Ecology · Astro and Planetary Science · Geochemistry and Geologic Mapping
