Rediscovering celestial mechanics with machine learning

A group of scientists using machine learning "rediscovered" the law of universal gravitation.

To do this, they trained a "graph neural network" to simulate the dynamics of the Sun, planets and large moons of the solar system from 30 years of observations. Then they used symbolic regression to discover the analytical expression for the force law implicitly learned by the neural network.

The result, as expected, was Newton's law of universal gravitation.

Initially, the system had no idea about the masses of the Sun, planets and physical constants. They were derived during the research.

According to the scientists, this study represents a key step towards realizing the potential of machine learning to accelerate scientific discovery.

More details can be found at https://arxiv.org/pdf/2202.02306.pdf