Astronomy20 papers
Mean-motion resonances in the Solar system
A curated collection of essential papers on mean-motion resonances in the asteroid belt, TNO, and beyond.
ES
Evgeny Smirnov
All Reviews
AstronomySkim
intermediate
Artificial neural network classification of asteroids in the M1:2 mean-motion resonance with Mars
Carruba, V. et al. (2021)
- Published
- Apr 7, 2021
- Journal
- Monthly Notices of the Royal Astronomical Society · Vol. 504 · No. 1
- DOI
- 10.1093/mnras/stab914
At a GlanceAI
A neural network classified Mars-resonant asteroid orbits with over 85% accuracy, extending resonance studies to many known asteroids.
SummaryAI
This study brings artificial neural networks into asteroid dynamics by automatically identifying orbital behavior in asteroids influenced by the Mars 1:2 mean-motion resonance. The authors report better than 85% performance on standard classification metrics and use supervised learning, optimized with genetic algorithms, to assign orbital status across numbered and multi-opposition asteroids in the region. The work shows that machine learning can scale resonance classification and reinforces that this resonance chiefly affects the Massalia, Nysa, and Vesta asteroid families.
Method SnapshotAI
The paper uses supervised artificial neural network classification, with genetic algorithm optimization, to label resonance-related asteroid orbital behavior.
BackgroundAI
Basic background in asteroid orbital dynamics, mean-motion resonances, and introductory machine learning is helpful.