Using dust shed from asteroids as microsamples to link remote measurements with meteorite classes

Area of Science:

• Planetary Science
• Astrogeology
• Space Mission Instrumentation

Background:

• Asteroid compositional diversity necessitates remote analysis methods for origin determination.
• In situ dust detectors offer a viable alternative to sample return missions for asteroid characterization.
• Understanding asteroid origins is crucial for deciphering the early solar system's history.

Purpose of the Study:

• To assess the feasibility of classifying asteroid types using in situ analysis of ejected dust particles.
• To model the abundance and detectability of asteroid-shed microsamples during flyby missions.
• To determine the minimum number of detected particles required for robust meteorite classification.

Main Methods:

• Extending models of the Lunar Reconnaissance Orbiter Camera (LROC) dust cloud data from the Lunar Atmosphere and Dust Environment Explorer (LADEE) mission.
• Utilizing Monte Carlo simulations to model particle ejection and detection probabilities.
• Analyzing the relationship between parent body properties (radius, heliocentric distance) and microsample abundance.

Main Results:

• The abundance of detectable impact-generated microsamples is dependent on parent body radius, heliocentric distance, flyby distance, and speed.
• Detecting several tens to hundreds of randomly ejected particles during a flyby is sufficient for classifying the parent body.
• The proposed method allows for classification into ordinary chondrite, basaltic achondrite, and other meteorite classes.

Conclusions:

• In situ dust detection provides a practical method for asteroid classification and origin studies.
• This approach complements traditional remote sensing techniques like imaging and multispectral analysis.
• Characterizing small, airless bodies is achievable through the analysis of shed microsamples.