allow for host halo ellipticity--alignment strength dependence for central alignments.
Opened this issue · 4 comments
I think @jablazek is particularly interested in this idea.
general trend should be that less elliptical haloes display less alignment with central galaxies.
One disadvantage of a Monte Carlo based on sample-and-rejection is that it's harder to implement residual correlations. The natural CAM way to implement this would be to use sliding_conditional_percentile to calculate Prob(< e | Mvir), and use those as the values passed to the CDF inverse function. How were you thinking of implementing such correlations?
1.) Some new code would need to be written and it might be slower, but I don't see why this couldn't be done.
2.) I don't actually think the CAM framework is right for this. The misalignment distribution is not observable, so a forward model approach where alignment_strength = f(m_vir, e_halo) seems reasonable to me.
Well, it just depends on how you want to get the nonlinear correlations in there. You can still properly forward-model from CAM, so long as you Monte Carlo draw from modeled/parameterized distributions instead of directly from the data.
Your approach to have the PDF parameters themselves depend on {e, M} should also work; I was just asking what the strategy is to minimize the number of parameters.
I rescind my previous comment point (2). A CAM like approach is probably ideal for this issue. we really don't want to add too many parameters if we ever want to MCMC constrain this model.