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Generated renormalization SV does not work at N3LO (and beyond) #144
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Yes for the moment N3LO ren sv is not supported but surely we can add (and I will as soon as I have time to do it). Is this needed now? |
Oh damn, thanks for checking @felixhekhorn,
Yes they are needed for DIS where we do have N3LO effects. |
But wait, for DIS we have them from Yadism, so are the codes doing the correct thing here? |
This I know but I believed that for DIS |
yes, I was more worried about n3loxs or Higgs (or in general the N3LO pheno) |
For the moment we do not have even the N3LO central for most of the datasets, so we are not using anywhere the N3LO sv (apart from DIS and for few DY points, as far as I know) |
wait at N3LO only ren scale are available in yadism: NNPDF/yadism#150
So far I was using the scale varied KF or computing sv directly using the given n3lo code, but I believe this feature can be quite useful in pineko in future. |
you're right and I'm wrong - there is neither fact. nor ren. SV at N3LO in yadism 😱 the ren should be here, but it isn't:
does this mean we the N3LO fits are safe for the moment? (or do we need to panic?) |
Yes sure I will do this, I was just asking to know if I need to do this now or if it can wait. I would say it can wait |
What? N3LO sv are not in yadism then? |
But what about this then ? We added only NNLO? Aren't we messing up with names? |
you're right - I'm sorry, I successfully confused myself ... I was remembering correctly in the first place - for yadism however, here in pineko we could not rely on |
In case, this is a dependency we can afford in Pineko https://docs.sympy.org/latest/modules/functions/combinatorial.html It's stable, and in Pineko performances are not critical (the tools to which is delegating the workload are responsible for performances). |
So my understanding is that N3LO fits should be safe as the variant with DY KF should come with SV in the kfactor and Regarding the baseline fits, ren scale variations at N3LO will come from yadism. |
ren_sv_coeffs
does not work at N3LO, as it seems hardcoded to NNLO:pineko/src/pineko/scale_variations.py
Lines 56 to 63 in e2cb241
If you don't want to do the fully general math (which I guess should be Bell polynomials - look at the second formula image under properties), you could still do an explicit spell out (as N4LO is far future, hopefully) ...
The relevant coeffs can be found in the MHOU paper:
cc @giacomomagni
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