Efficiency and fake rate of the cut-based electron ID for Run 2.
Samples
Signal samples from the CSA production can be found in
DAS
, by typing in the query window:
- dataset = /RSGravToZZ*/*Spring14dr*/AODSIM
To implement the cut-based electron identification we produced private MINIAODSIM samples with few events (100K), using the common ID and Isolation Toolkit
CITK
.
To access the private samples from lxplus, you have to obtain a valid grid proxy (
voms-proxy-init --voms cms
). The
process.source
in your configure file should look like the following:
process.source = cms.Source("PoolSource",
fileNames = cms.untracked.vstring('root://cmsxrootd.fnal.gov//store/user/jruizvar/RSGravToZZ/M1000/RSGravToZZ_kMpl01_M-1000_Tune4C_13TeV-pythia8_MINIAODSIM_PU20bx25_1.root')
)
Matching categories
MINIAODSIM samples contain information about generated and reconstructed particles. Our matching algorithm identifies the closest
GenElectron for every
RecoElectron, as well as the particle ID of the
GenElectron's ancestor. This procedure allows to define four matching categories as described in the following table:
1 |
Unmatched |
deltaR(closest gen electron, reco electron) > 0.02 |
2 |
True electron from W |
deltaR(closest gen electron, reco electron) < 0.02 AND (ancestor PID == 24) |
3 |
True electron from Z |
deltaR(closest gen electron, reco electron) < 0.02 AND (ancestor PID == 23) |
4 |
Anything else |
What remains from above |
Isolation
Particle flow isolation with delta beta correction is calculated as follows:
reco::GsfElectron::PflowIsolationVariables pfIso = el->pfIsolationVariables();
absiso = pfIso.sumChargedHadronPt + std::max(0.0 , pfIso.sumNeutralHadronEt + pfIso.sumPhotonEt - 0.5 * pfIso.sumPUPt );
relIsoWithDBeta = absiso/pt;
Internally, the isolation variables use the standard recommended cone size
deltaR = 0.3
. Details
here
.
* Electron isolation after different cut-based selections
Efficiency and fake rate
The efficiency is the number of signal electrons passing the ID divided by the total. The fake rate was estimated in a similar way but using the non-signal electrons.
To access the
electronID
, which is a member function of the
pat::Electron
class, we used a line like the following:
int passID = ( el->electronID("cutBasedElectronID-CSA14-PU20bx25-V0-standalone-veto") > 0.5 );
Working points
The cut-based electron identification recommended by EGM for Run 2 analyses, determines four working points:
veto,
loose,
medium, and
tight. A detailed description
here
.
Preliminary results
To estimate the efficiency and fake rate of the electron identification, we classified the electrons according to its matching category and the
passID associated to the
cutBasedElectronID-CSA14 working points.
The classification for each working point is displayed as a TH2 histogram with two bins in the Y axis associated to the passID variable, and four bins in the X axis corresponding to the matching categories. The number of entries inside each box of the histogram indicates the number of electrons in a given matching category with a given passID.
- Electron classification, global efficiency, and fake rate using sample RSGravToZZ 1 TeV
- Electron classification, global efficiency, and fake rate using sample RSGravToZZ 4.5 TeV
Efficiency and fake rate as function of pT and etaSC are shown below:
- Efficiency and fake rate as function of electron's pT
- Efficiency and fake rate as function of etaSC
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