High-Resolution Observations of Bright Boulders on Asteroid Ryugu: 1. Size Frequency Distribution and Morphology
Chiho Sugimoto, Eri Tatsumi, Yuichiro Cho, Tomokatsu Morota, Rie, Honda, Shingo Kameda, Yosuhiro Yokota, Koki Yumoto, Minami Aoki, Daniella N., DellaGiustina, Tatsuhiro Michikami, Takahiro Hiroi, Deborah L. Domingue,, Patrick Michel, Stefan E. Schr\"oder, Tomoki Nakamura

TL;DR
This study provides detailed measurements and analysis of bright boulders on asteroid Ryugu, revealing their size distribution, morphology, and implications for the asteroid's geological history and surface processes.
Contribution
It offers the first comprehensive quantitative analysis of bright boulders on Ryugu, including size-frequency distributions and morphological properties, enhancing understanding of asteroid surface evolution.
Findings
Bright boulders follow power-law size distributions.
Many bright boulders are embedded in larger substrate boulders.
Bright boulders likely resulted from mixing during catastrophic disruption.
Abstract
The near-Earth asteroid (162173) Ryugu displays a Cb-type average spectrum and a very low average normal albedo of 0.04. Although the majority of boulders on Ryugu have reflectance spectra and albedo similar to the Ryugu average, a small fraction of boulders exhibit anomalously high albedo and distinctively different spectra. A previous study (Tatsumi et al., 2021) based on the 2.7-km observations and a series of low-altitude (down to 68 m) descent observations conducted prior to the first touchdown have shown that the spectra of these anomalous boulders can be classified into two distinct groups corresponding to S and C type asteroids. The former originate most likely from an impactor that collided with Ryugu's parent body, whereas the latter may be from portions of Ryugu's parent body that experienced a different temperature history than experienced by the majority of boulder…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
