Design a HHtobbyy workflow
Elise has to initiate a merge request for the features that have been implemented. Below is the initial list of features for inclusion in the HHtobbgg workflow, which have not been previously included:
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Inherit the HHtobbgg workflow from the Hgg base workflow-> can adapt and extend the functionalities from Hgg workflow without the need to rewrite the existing code -
Update the HHbbgg process function according to the update in Hgg base process function -
Add the HHbbgg workflow examples here: https://gitlab.cern.ch/HiggsDNA-project/HiggsDNA/-/tree/master/docs/source/standalone_examples?ref_type=heads -
Maybe useful to explicitly name the variables of diphoton system as "diphoton_{variable}". But this might get inconsistent with the other workflows which has just {variable}. Have to decide to change it or not. -
Use of ParticleNet AK4 tagger for b-jet energy and tagging. This ParticleNet simultaneously performs jet flavour tagging, tau tagging as well as flavour-aware jet energy regression. Have a look at these slides. -
Use of Pnet instead of DeepJet for b-tagging -
b-jet energy: ParticleNet correction factors to be applied to the raw jet pT are already available in in NanoAOD v12 onwards -
b-tagging: ParticleNet tagger info is also available in NanoAOD v12 onwards. Some info about the scale factors are available here --> To do : add b-tagging SF corrections and systematics -
there are also ParticleTransformer based tagger scores saved in the NanoAOD. Have to ask the BTV experts regarding which one to use : should be "Jet_btagRobustParTAK4B"
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Currently, a cut is applied on the invariant mass of the dijet system (70 GeV < dijet_mass < 190 GeV). The workflow has to be adapted for resonant analysis (X->YH->bbgg), where the mass of Y can be beyond the range [70, 190] GeV. -
Save first N (maybe 6) jets with preselection , otherwise pad with zeros: -
Four vector, ParticleNet scores, Deep Jet scores : in MR -
Any other information needed ? -
Check if dR(jet, diphoton) needed.
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For ttH killer: -
Save 2 leading electrons and muons each -
PuppiMET info -
Save other higher-level variables as required
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Addition of truth information for the conditional classifiers: mX for X->HH, mY for Y->bb or Y->gg, kt, kl, CV, C2V, etc. -
Already added kt, kl, c2,CV, C2V, C3, BulkGraviton_M (mX), Radion_M (mX) -
Bug fixes needed -
Add mY info when the sample request is submitted
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Addition of fatjets, i.e. at least AK8 or even AK15, along with all the relevant b-tagging info -
Preselection: pT>250 GeV, dR>0.8 from photons -
Order by PNet scores -
Save first 4 fatjets -
Add SubJets and GenJetAK8 matched to FatJets
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Addition of GenJetAK8 matched with gen H->bb within dR <0.8 and SubGenJetAK8 belonging to the matched GenJetAK8 -
VBF-jets selection implementation -
Addition of other gen variables to optimize the reconstruction (ME level) -
gen_mHH (for nonres reco test) -
4 momenta of the two generated Higgs -
4 momenta of the vector bosons (if it exists) -
4 momenta of gen_top (if it exists)
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The jet systematics has been updated in the base processor. Update this also in HHbbgg workflow
References:
- Full Run 2 analysis: HIG-19-018 (arXiv:2011.12373) with ANs CMS AN-2017/286 and CMS AN-2019/149
Edited by Yu-Hsuan Chou