2019:groups:tools:correlations
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2019:groups:tools:correlations [2019/06/25 18:27] sabine.kraml |
2019:groups:tools:correlations [2019/06/27 17:10] (current) sezen.sekmen [Quantifying overlaps between analysis search regions using ADLs] |
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| ====== Study: correlations between signal regions ====== | ====== Study: correlations between signal regions ====== | ||
| - | //Members: Sophie, Wolfgang, Humberto, Benj, Andy, Sabine, Sezen // | + | //Members: **Sophie**, Wolfgang, Humberto, Benj, Andy, Sabine, Sezen // |
| Problem statement: to identify pairs of signal regions of the analyses in the PAD database that can safely be treated as approximately uncorrelated. | Problem statement: to identify pairs of signal regions of the analyses in the PAD database that can safely be treated as approximately uncorrelated. | ||
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| | CMS-SUS-16-039 | multilepton EWK | TChiWZ(off), TChiWH, TChipmSlep... | UL | | | CMS-SUS-16-039 | multilepton EWK | TChiWZ(off), TChiWH, TChipmSlep... | UL | | ||
| + | ==== Quantifying overlaps between analysis search regions using ADLs ==== | ||
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| + | Members: Sezen, Wolfgang (, Harrison) | ||
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| + | Find and visualize overlaps in a model-independent way, without generating events using simple descriptions done using an [[[[2019:groups:tools:adl|analysis description language]]. Directly sample the event selection. Useful for analysis design phase, or quick comparisons within experiments (e.g. Run2 CMS SUSY pMSSM combination) | ||
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| + | * Start from the analysis description, which lists objects and event selections. | ||
| + | * Construct a feature space from all mathematically orthogonal "basic" variables (e.g. MET, jet1.pt, jet2.pt, electron1.eta, ...). | ||
| + | * Randomly sample the feature space for each analysis based on cuts on the feature space components (jet1.pt > 100, MET > 299, etc.). | ||
| + | * Use the sampled points to compute values for "composite" variables such as HT(jets), dphi(jets), MT(lepton, MET), etc. | ||
| + | * Compare feature spaces between analyses, find and visualize overlaps and exclusions. | ||
| + | * As a very simple first step, we simply check if two analyses are disjoint in any of the basic variables. | ||
2019/groups/tools/correlations.1561480061.txt.gz · Last modified: 2019/06/25 18:27 by sabine.kraml
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