I am an astronomer studying galaxies. I have observations of about 500 galaxies. For each galaxy, I can measure two quantities (call them $X$ and $Y$).
I want to compare my observations to some theoretical (physical, not statistical) models. I have about 10,000 numerical models of all kinds of galaxies (describing their size, structure, and observable properties), some of which are quite different than the ones I am studying.
I want to "thin down" the sample of theoretical models until the distributions of $X$ and $Y$ across all the models look like the observed distributions of $X$ and $Y$. Is there a good algorithm to do this?