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Galaxy formation is inherently chaotic i.e. it exhibits sensitive dependence to initial conditions. My first thought upon reading your comment is that an ANN approach must be wrong because of chaos. But of course a purely numerical gravitational simulation will also be wrong because of chaos.

So how do you tell which method is ... less wrong?

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Ah, we use the ML methods to understand what happens to a large collection of galaxies (maybe 100k - 1 million), all co-evolving together. Trying to use these methods v.s. direct simulation on individual galaxies is a no-go, too many nonlinearities exist.

Your comment about a numerical gravitational simulation being 'wrong' because of chaos may be true on an individual resolution element level, yes, but our simulations are made up of many billions of individual particles. Like traditional CFD simulations we can also demonstrate some level of convergence.

Thanks. I suspected the answer might be "we're only concerned with characterizing extremely macroscopic behavior" and you confirmed that.

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