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After chatting with @Pablo-Lemos on Friday, we felt it could be a good idea to implement galaxy bias models at the level of a cobaya theory class, in order that the parameters can be seen by multiple likelihoods (and the code only needs to be implemented or hooked into once etc).
I would start this at either end of the complexity scale:
A 1 parameter scale and redshift linear bias model
I think this is a good idea. My recommendation is to do both, but to start with the simpler model. This way you can get everything working with breaking out that part of the theory calculation from the XcorrLikelihood, as well as work out all the kinks of creating a new Theory with the simple case. After that has been done, it should be easier to implement velocileptors as a Theory, and that work can be separate from the adjustments needed to the user likelihoods.
After chatting with @Pablo-Lemos on Friday, we felt it could be a good idea to implement galaxy bias models at the level of a cobaya theory class, in order that the parameters can be seen by multiple likelihoods (and the code only needs to be implemented or hooked into once etc).
I would start this at either end of the complexity scale:
Does this seem sensible to others?
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