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2019:groups:tools:adl [2019/06/27 15:19] sezen.sekmen [Quantifying overlaps between analysis search regions using ADLs] |
2019:groups:tools:adl [2019/06/27 17:05] sezen.sekmen [Quantifying overlaps between analysis search regions using ADLs] |
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Questions for us to answer: | Questions for us to answer: | ||
- | * What is the ideal physics content for an ADL? An inclusive list discussed at the [[Fermilab ADL workshop]] is [[https://docs.google.com/document/d/1KrSarg4_c_Ph76SI8i9_b-wBEN6V90mWNLTaZq3y85E/edit?usp=sharing|in this googledoc]]. You are welcome to take a look and edit. | + | * What is the ideal physics content for an ADL? An inclusive list discussed at the [[https://indico.cern.ch/event/769263/|Fermilab ADL workshop]] is [[https://docs.google.com/document/d/1KrSarg4_c_Ph76SI8i9_b-wBEN6V90mWNLTaZq3y85E/edit?usp=sharing|in this googledoc]]. You are welcome to take a look and edit. |
* What is the best syntax for expressing composite particles, like Zs, tops, Higgsses, etc.? How can we access information on the constituents? | * What is the best syntax for expressing composite particles, like Zs, tops, Higgsses, etc.? How can we access information on the constituents? | ||
* What is the minimal list of math and HEP functions/operators we need for describing the analysis? | * What is the minimal list of math and HEP functions/operators we need for describing the analysis? | ||
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==== Quantifying overlaps between analysis search regions using ADLs ==== | ==== 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. Directly sample the event selection. Useful for analysis design phase, or quick comparisons within experiments (e.g. Run2 CMS SUSY pMSSM combination) | ||
* Start from the analysis description, which lists objects and event selections. | * Start from the analysis description, which lists objects and event selections. | ||
- | * Construct a feature space from all mathematically orthogonal variables (e.g. MET, jet1.pt, jet2.pt, electron1.eta, ...). | + | * 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. | + | * 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 obtain values for higher order variables, such as HT, MT, 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. | * 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. | ||
==== ADLs for recasting ==== | ==== ADLs for recasting ==== |