Pythia/Herwig + Delphes Jet Datasets for OmniFold Unfolding (Q6707877)

Datasets of QCD jets used for studyingunfolding in OmniFold: A Method to Simultaneously Unfold All Observables. Four different datasets are present: Herwig 7.1.5 with the default tune Pythia 8.243 with tune 21 (ATLAS A14 central tune with NNPDF2.3LO) Pythia 8.243 with tune 25 (ATLAS A14 variation 2+ of tune 21) Pythia 8.243 with tune 26 (ATLAS A14 variation 2- of tune 21) \(Z \)+ jet events (with the\(Z \)set to be stable) were generated for each of the above generator/tune pairs with the\(Z\)boson\(\hat p_{T}^\text{min}150\,\text{GeV} \)and\(\sqrt{s}=14\,\text{TeV}\). Events were then passed through the Delphes 3.4.2 fast detector simulation of the CMS detector. Jets with radius parameter\(R=0.4\)were found with the anti-\(k_T\)algorithm at both particle level (gen), where all non-neutrino, non-\(Z\)particle are used,and detector level (sim), where reconstructed energy flow objects (tracks, electromagnetic calorimeter cells, and hadronic calorimeter cells) are used. Only jets with transverse momentum greater than\(10\,\text{GeV}\)are kept (note that sim jets have a simplejet energy correction applied by Delphes).The hardest jet from events with a\(Z\)boson with a final transverse momentum of\(200\,\text{GeV}\)or greater are kept, yielding approximately 1.6 million jets at both gen-level and sim-levelfor each generator/tune pair. Each zipped NumPy file consists of several arrays, the names of which begin with either gen_ or sim_ depending on which set of jets they correspond to. The name of each array ends in a key word indicating what it contains. With the exception of gen_Zs (which contains the\((p_T,\,y,\,\phi)\)of the final\(Z\)boson), there is both a gen and sim version of each array. The included arrays are (listed by their key words): jets - The jet axis four vector, as\((p_T^\text{jet},\,y^\text{jet},\,\phi^\text{jet},\,m^\text{jet})\)where\(y^\text{jet}\)is the jet rapidity,\(\phi^\text{jet}\)is the jet azimuthal angle, and\(m^\text{jet}\)is the jet mass. particles - The (rescaled, translated)constituents of the jets as\((p_T/100,\,y-y^\text{jet},\,\phi-\phi^\text{jet},\,f_\text{PID})\)where\(f_\text{PID}\)is a small float corresponding to the PDG ID of the particle. The PIDs are remapped according to\(22\to0.0,\,211\to0.1,\,-211\to0.2,\)\(130\to0.3,\,11\to0.4,\,-11\to0.5,\,13\to0.6,\,-13\to0.7,\,321\to0.8,\,-321\to0.9,\)\(2212\to1.0,\,-2212\to1.1,\,2112\to1.2,\,-2112\to1.3\).Note that ECAL cells are treated as photons (id 22) and HCAL cells are treated as\(K_L^0\)(id 130). mults - The constituent multiplicity of the jet. lhas - The Les Houches (\(\beta=1/2\)) angularity. widths - The jet width(\(\beta=1\)angularity). ang2s - The\(\beta=2\)angularity (note that this is very similar to the jet mass, but does not depend on particle masses). tau2s - The 2-subjettiness with\(\beta=1\). sdms - The groomed mass with Soft Drop parameters\(z_\text{cut}=0.1\)and\(\beta=0\). zgs - The groomed momentum fraction (same Soft Drop parameters as above). If you use this dataset, please cite this Zenodo record as well as the corresponding paper: A. Andreassen, P. T. Komiske, E. M. Metodiev, B. Nachman,J. Thaler, OmniFold: A Method to Simultaneously Unfold All Observables,arXiv:1911.09107. The datasets can be downloaded and read into python automatically using theEnergyFlow Python package.