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Celestial Machine Learning: Discovering the Planarity, Heliocentricity, and Orbital Equation of Mars with AI Feynman
December 19, 2023 Β· Declared Dead Β· π International Conference on Information Integration and Web-based Applications & Services
"No code URL or promise found in abstract"
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Authors
Zi-Yu Khoo, Gokul Rajiv, Abel Yang, Jonathan Sze Choong Low, StΓ©phane Bressan
arXiv ID
2312.12315
Category
astro-ph.EP
Cross-listed
cs.LG
Citations
0
Venue
International Conference on Information Integration and Web-based Applications & Services
Last Checked
3 months ago
Abstract
Can a machine or algorithm discover or learn the elliptical orbit of Mars from astronomical sightings alone? Johannes Kepler required two paradigm shifts to discover his First Law regarding the elliptical orbit of Mars. Firstly, a shift from the geocentric to the heliocentric frame of reference. Secondly, the reduction of the orbit of Mars from a three- to a two-dimensional space. We extend AI Feynman, a physics-inspired tool for symbolic regression, to discover the heliocentricity and planarity of Mars' orbit and emulate his discovery of Kepler's first law.
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