I have been working on making machine-learning methods dimensionless (in the sense of units). In this context, a question arises: Is it possible to learn that there is a missing dimensional input to a physics problem, using machine learning? Soledad Villar (JHU) and I ignored some of our required work today and wrote some code to explore this problem, using as a toy example the Planck Law example we explained in this paper. We found that maybe you can discover a missing dimensional constant? We have lots more to do to decide what we really have.
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