top of page
While neural networks and other machine learning algorithms are very good at finding accurate approximations of the underlying function relating a given input to an output, it is in general hard to interpret what that mapping is doing.
Genetic programming is technique to find analytic expressions that approximate the underlying function.
We have applied this technique to find analytic expressions that predict the star-formation rate density (SFRD) just a function of redshift and the value of the cosmological and astrophysical parameters. The below formulae can be used with the IllustrisTNG simulations.
bottom of page