A neural network algorithm leans physical law and the result is published in Physical Review Letters, one of the leading journals in Physics.
The abstract reads as follow.
"Despite the success of neural networks at solving concrete physics problems, their use as a general-purpose tool for scientific discovery is still in its infancy. Here, we approach this problem by modelling a neural network architecture after the human physical reasoning process, which has similarities to representation learning. This allows us to make progress towards the long-term goal of machine-assisted scientific discovery from experimental data without making prior assumptions about the system. We apply this method to toy examples and show that the network finds the physically relevant parameters, exploits conservation laws to make predictions, and can help to gain conceptual insights, e.g. Copernicus’ conclusion that the solar system is heliocentric."
We all know that the earth revolves around the Sun. But, without giving this information, how can a computer algorithm can predict? It has been successfully predicted by a neural network for the first time. The authors wants to predict the laws of quantum physics using this neural network. This prediction of planetary law is one of the first step on their way.
This work has been highlighted by Nature as "AI Copernicus ‘discovers’ that Earth orbits the Sun"
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