OmniFold Weights | CMS 2011A Open Data | Jet Primary Dataset | pT 375-700 GeV
DOI10.5281/zenodo.6519307Zenodo6519307MaRDI QIDQ6707894
Dataset published at Zenodo repository.
Author name not available (Why is that?)
Publication date: 5 May 2022
Copyright license: No records found.
Unfolding weights corresponding to a selection of jets from the Jet Primary Dataset of the CMS 2011A Open Data in MOD HDF5 formatand associated simulated datasets. The unfolding is performed in a high-dimensional mannerusing the OmniFold method, which can unfold all observables simultaneously.Particle Flow Networks are used in Step 1 and Step 2 of the OmniFold methodto process the full phase space information. The datasets and neural networkswere accessed/built via the EnergyFlow Python package. An upcoming version of the package will contain an example/demo demonstrating how to use these weights. The phase space selections for the data, sim, and gen datasets (using the terminology of the OmniFold paper) are: data:\(p_T^{\rm jet}\in [375, 700]\)GeV,\(|\eta^{\rm jet}|2.4\), jet quality\(\ge\)2 sim:\(p_{T,\text{corr}}^{\rm jet} \in [375, 700]\)GeV,\(|\eta^{\rm jet}| 2.4\), gen jet matched (gen_jet_pts != -1 in EnergyFlow), jets from the 170 and 1800 MC datasets are excluded gen: Matched to sim jet The omnifold_weights.npz file contains two arrays, wssim corresopnding to the Step 1 weights\(\omega_n\), and wsgen corresponding to the Step 2 weights\(\nu_n\),for iteration\(n\). The shape of each of these arrays is (6, 16489054), with the first axis being the iteration axis and the second axis being the event axis.There are 5 iterations, but 6 sets of weights in each array, with the 0th entry being the starting weights.
This page was built for dataset: OmniFold Weights | CMS 2011A Open Data | Jet Primary Dataset | pT 375-700 GeV
