Celestial Machine Learning: Discovering the Planarity, Heliocentricity, and Orbital Equation of Mars with AI Feynman

• URL: http://arxiv.org/abs/2312.12315v1
• Date: Tue, 19 Dec 2023 16:39:32 GMT
• Title: Celestial Machine Learning: Discovering the Planarity, Heliocentricity, and Orbital Equation of Mars with AI Feynman
• Authors: Zi-Yu Khoo, Gokul Rajiv, Abel Yang, Jonathan Sze Choong Low, St\'ephane Bressan
• Abstract summary: Johannes Kepler required two paradigm shifts to discover his First Law regarding the elliptical orbit of Mars. We extend AI Feynman, a physics-inspired tool for symbolic regression, to discover the heliocentricity and planarity of Mars' orbit.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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