Satellite specific quenching for satellites #48
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.




This PR adds satellite-specific quenching for satellite haloes. It does so by adding 4 new parameters for the sigmoid of
frac_quench_sat, while keeping a separate 4-param sigmoid for the centrals'frac_quench_cen. There's a new parameter,upiddetermining if a halo is central or satellite, andfrac_quenchfor each halo takes thefrac_quench_cenorfrac_quench_satvalue depending onupid, usingjnp.where. There's a set of duplicate files in several folders with the suffix_satfracimplementing these changes.The plots below show results for SMDPL (no-merging). As a result of this change, there's an improvement in the fit quality of
p(sSFR | Mstar), for both centrals and satellites, especially for main sequence galaxies. The improvement is not spectacular, but visible if one compares back-and-forth with the model that uses the same frac_quench for both cen and sat. For SMDPL compare to #46.One worrisome feature is that the gradient descent gets halted because of a
nanin the gradients. I suspect the covariance must be hitting some of the boundaries, perhaps because of therho_bounds=(-0.3, 0.3), which might make the covariance non-positive definite. I want to test what happens if one uses a diagonal covariance.