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2017:groups:tools:recasting [2017/06/22 09:14] benjamin.fuks |
2017:groups:tools:recasting [2018/02/05 11:50] sezen.sekmen |
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- Recast the analysis for an other new physics model and compare the results. | - Recast the analysis for an other new physics model and compare the results. | ||
- Go to point one and choose a more complicated analysis... | - Go to point one and choose a more complicated analysis... | ||
+ | |||
+ | AB: would be interesting to see how Delphes performance looks without analysis-specific cards, since a lot of people (outside the "big" recasting groups) are using it that way. | ||
* How to validate the analyses. | * How to validate the analyses. | ||
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* ?K HepMC events with MG5_aMC LO, masses: gluino 1100, N1 700 --> Olivier+Nishita | * ?K HepMC events with MG5_aMC LO, masses: gluino 1100, N1 700 --> Olivier+Nishita | ||
* **Results:** [[2017:groups:tools:recasting:results_gluino_1100_N1_700|here]] | * **Results:** [[2017:groups:tools:recasting:results_gluino_1100_N1_700|here]] | ||
- | - **arxiv:1704.03848** - Monophoton - ATLAS - 13 TeV | + | * LHADA implementation: [[https://github.com/lhada-hep/lhada/tree/master/analyses/ATLASSUSY1605.03814]] |
- | - **CMS-SUS-16-039** - 3 leptons + MET - CMS - 13 TeV | + | - **arxiv:1704.03848** - Monophoton - ATLAS - 13 TeV Cutflow: https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/EXOT-2016-32/. hepmc files: /eos/user/p/pgras/Houches2017Recast/DM_monophoton/hepmc.1/. Accessible from [[https://cernbox.cern.ch/index.php/s/8EZVNwJbSlovEBF|https://cernbox.cern.ch/index.php/s/8EZVNwJbSlovEBF]]. Asked Philippe Gras for direct access permissions to the eos directory. |
- | - **arxiv:1706.04402** - 1 lepton + MET + Jets (>=1b) - CMS - 13 TeV | + | * LHADA implementation: [[https://github.com/lhada-hep/lhada/tree/master/analyses/ATLASEXOT1704.03848]] |
+ | - **CMS-SUS-16-039** - (Now superseded by paper: http://cms-results.web.cern.ch/cms-results/public-results/publications/SUS-16-039/index.html) 3 leptons + MET - CMS - 13 TeV (BDT with ~15 inputs; eff. 20-90%). Cutflows: http://cms-results.web.cern.ch/cms-results/public-results/preliminary-results/SUS-16-039/index.html Efficiencies: https://twiki.cern.ch/twiki/bin/view/CMSPublic/SUSMoriond2017ObjectsEfficiency | ||
+ | - **arxiv:1706.04402** - 1 lepton + MET + Jets (>=1b) - CMS - 13 TeV (topness variable?) | ||
== References == | == References == | ||
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* [[2017:groups:tools:Contur|Contur]] | * [[2017:groups:tools:Contur|Contur]] | ||
+ | |||
== Simplified likelihood framework == | == Simplified likelihood framework == | ||
--> Andy, Sylvain | --> Andy, Sylvain | ||
+ | CMS formalism: | ||
https://cds.cern.ch/record/2242860/files/NOTE2017_001.pdf | https://cds.cern.ch/record/2242860/files/NOTE2017_001.pdf | ||
- | https://arxiv.org/abs/1603.03061 | + | AB implementations in GAMBIT and SciPy, marginalising over correlated background uncertainties (by unitary transformation + integral, and by MC sampling respectively). MadAnalysis: (Benj: I would like to do it, but time is my main problem. Anyone to help here? AB: Maybe my Python code, when finished?) |
- | Improvements of the basic proposal of the CMS note: | + | AB: reporting of SR n & b arrays and covariance matrix (matrices?) currently ad hoc / non-standardised. Would be //really// good to establish a standard -- ideally in HepData. |
- | * Use of exponential nuisance parameters to avoid negative rates. Implementation in GAMBIT, tests using the examples given in CMS note. | + | Canonical example: CMS 0-lepton search with 174 SRs and covariance matrix: |
+ | http://cms-results.web.cern.ch/cms-results/public-results/publications/SUS-16-033/index.html | ||
+ | |||
+ | Improvements to the basic CMS proposal: | ||
+ | https://arxiv.org/abs/1603.03061 | ||
+ | |||
+ | * Use of exponential nuisance parameters to avoid negative rates. | ||
* Implement a covariance matrix dependent on the parameters of interest. Happens for example if there are uncertainties on both signal and background. Depends on availability of elementary sources of uncertainties. If released as weights, will open possibilities. | * Implement a covariance matrix dependent on the parameters of interest. Happens for example if there are uncertainties on both signal and background. Depends on availability of elementary sources of uncertainties. If released as weights, will open possibilities. | ||
- | * Implementation in GAMBIT, MadAnalysis (Benj: I would like to do it, but time is my main problem. Anyone to help here?) | + | SF: Simplified likelihoods as an alternative to unfolding: comparison between both methods can be done in a specific example |
+ | |||
+ | == LHADA == | ||
- | * Simplified likelihoods as an alternative to unfolding: comparison between both methods can be done in a specific example | + | Examples of analysis descriptions in LHADA format: |
+ | * https://github.com/lhada-hep/lhada/blob/master/lhada2rivet.d/CMS-PAS-SUS-16-015.lhada | ||
+ | * https://github.com/lhada-hep/lhada/blob/master/lhada2rivet.d/CMS-PAS-SUS-16-015.lhada | ||
+ | A first version of arxiv:1605.03814 is written. It will be added/linked here after some cleanup. | ||