Les Houches

interested people: fabio.maltoni@uclouvain.be, sabine.kraml@gmail.com, gabriel.facini@cern.ch, D.Grellscheid@gmail.com, ssekmen@cern.ch, J.Butterworth@ucl.ac.uk, nishita.desai@umontpellier.fr, andy.buckley@cern.ch, fuks@lpthe.jussieu.fr, eric.conte@iphc.cnrs.fr, peter.richardson@durham.ac.uk, luca.perrozzi@cern.ch, olivier.mattelaer@uclouvain.be, Pasquale.Musella@cern.ch, andre.lessa@cern.ch, alexandra.oliveira@cern.ch, ursula.laa@lpsc.in2p3.fr, kristin.lohwasser@cern.ch, thrynova@mail.cern.ch, efe.yazgan@cern.ch, philippe.gras@cern.ch, sylvain@ift.unesp.br

This page is meant to collect information on the recasting discussions.

Outcome of the first meeting Fri, Jun 16th

• Feasibility study of the implementation/portability of complicated MVA techniques (BDT, NN,…) into the analyses
• Improvement of results and recastability: how to provide correlations signal systematics, possibility of providing a few key observables unfolded.
• Comparison of between DELPHES results and simple object smearing.
• Trying out the use of particle-level measurements to constrain model models

• Object efficiency tables : which format (HEPDATA?)

• Implementation of analyses of increasing complexity in the Analysis Description Format (LHADA Proposal) and in (BSM) Rivet and their comparison.
  1. Choose an analysis of ATLAS or CMS which has cutflow and detector effects provided in some form, and possibly is already been implemented in the recasting codes CheckMate/MadAnalysis/Rivet/ATOM/.
  2. Implement the same analysis in LHADA and then use the dedicated parsers to provide the analysis for the recasting codes.
  3. Reproduce the NP interpretation of the original paper (=validation implementation).
  4. Recast the analysis for an other new physics model and compare the results.
  5. Go to point one and choose a more complicated analysis…

• How to validate the analyses.

• Analysis proposals
  1. arxiv:1605.03814 - Jets+MET - ATLAS - 13 TeV
     • Experimental cards –> Ben. The procedure for event generation is depicted multijet.pdf (Section 02), the three parameter_cards are given param_cards.tgz and the Pythia configuration files are py8_scripts.tgz
     • Plot conditions: HEPMC (after jet clustering), HEPMC + cuts, HEPMC + Detector effects, HEPMC + Detector effects + cuts
     • Plots: pT of 1j, 2j and 3j, and MET: range [0,1] TeV, 50 bins
     • Plots: eta of 1j, 2j and 3j: range [-5,5], 20 bins
     • Analysis cutflows: Tables 1-7 in http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2015-06/
     • 100K HepMC events with MG5_aMC LO, masses: gluino 1600, N1 0 –> Olivier+Nishita https://cernbox.cern.ch/index.php/s/3Ci4I2cgQmKwDXt
       • Results: here
     • ?K HepMC events with MG5_aMC LO, masses: gluino 1100, N1 700 –> Olivier+Nishita
       • Results: here
  2. arxiv:1704.03848 - Monophoton - ATLAS - 13 TeV
  3. CMS-SUS-16-039 - 3 leptons + MET - CMS - 13 TeV
  4. arxiv:1706.04402 - 1 lepton + MET + Jets (>=1b) - CMS - 13 TeV

• LHADA Proposal
• Contur

https://cds.cern.ch/record/2242860/files/NOTE2017_001.pdf

https://arxiv.org/abs/1603.03061

Improvements of the basic proposal of the CMS note:

• Use of exponential nuisance parameters to avoid negative rates. Implementation in GAMBIT, tests using the examples in CMS note.

• Availability of elementary sources of uncertainties? Release as weights? Opens the possibility of implementing general uncertainties on both signal and background. More generally, opens th possibility of

having the covariance matrix dependent on parameters of interest.

• Implementation in GAMBIT, MadAnalysis?