User Tools

Site Tools


2017:groups:tools:recasting

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
Last revision Both sides next revision
2017:groups:tools:recasting [2017/06/22 01:53]
sylvain.fichet
2017:groups:tools:recasting [2018/02/05 11:49]
sezen.sekmen
Line 48: Line 48:
      - 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. ​
Line 64: Line 66:
         * ?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 +    - **CMS-SUS-16-039** - (Now superseded by paper: http://​cms-results.web.cern.ch/​cms-results/​public-results/​publications/​SUS-16-039/​index.html) ​3 leptons + MET - CMS - 13 TeV (BDT with ~15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 ==
Line 75: Line 79:
   * [[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
  
 +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?)
 +
 +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.
 +
 +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 https://​arxiv.org/​abs/​1603.03061
  
-Improvements ​of the basic proposal of the CMS note:+  * Use of exponential nuisance parameters to avoid negative rates.
  
-  * Use of exponential nuisance ​parameters ​to avoid negative ratesImplementation in GAMBITtests using the examples given in CMS note.+  * Implement a covariance matrix dependent on the parameters ​of interestHappens for example if there are uncertainties on both signal and background. Depends on availability of elementary sources of uncertainties. If released as weightswill open possibilities.
  
-  * Implement covariance matrix dependent on parameters of interest. For exampleif there are uncertainties on both signal and background. Availability of elementary sources of uncertainties?​ Release ​as weights? Will open possibilities.+SFSimplified likelihoods ​as an alternative to unfolding: comparison between both methods can be done in a specific example
  
-  * Implementation in GAMBIT, MadAnalysis(?​)+== 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.
  
  
2017/groups/tools/recasting.txt · Last modified: 2018/02/05 11:50 by sezen.sekmen