Aod ntuple

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This page contains basic prescriptions to get physics objects from the AOD and the AOD-based Root ntuple.

Some comments on quality selection cuts will be added as work progresses.


Electron

Electron in AOD/Ntuple
AOD Container Name AOD Variable Ntuple Variable Variable Type Comment
ElectronCollection (*elecTES)->size() n_elec Int Number of electrons in the Ntuple
(*elecItr)->hlv().x() px_elec Double Px
(*elecItr)->hlv().y() py_elec Double Py
(*elecItr)->hlv().z() pz_elec Double Pz
(*elecItr)->hlv().perp() pt_elec Double Pt
(*elecItr)->hlv().eta() eta_elec Double Eta
(*elecItr)->hlv().phi() phi_elec Double Phi
(*elecItr)->isEM() isem_elec Int isEM flag (see below)
(*elecItr)->hasTrack() hastrk_elec Int (bool) HasTrack flag: presence of charged track in the Inner Detector
(*elecItr)->z0wrtPrimVtx() z0vtx_elec Double Intersection (z) of track with the beam axis
(*elecItr)->d0wrtPrimVtx() d0vtx_elec Double Transverse impact parameter d0
(*elecItr)->numberOfBLayerHits() nblayerhits_elec Int Number of hits in the Pixel B-layer
(*elecItr)->numberOfPixelHits() npixelhits_elec Int Number of hits in the Pixel detector
(*elecItr)->numberOfSCTHits() nscthits_elec Int Number of hits in the SCT
(*elecItr)->numberOfTRTHits() ntrthits_elec Int Number of hits in the TRT
(*elecItr)->numberOfTRTHighThresholdHits() ntrththits_elec Int Number of high threshold hits in the TRT
(*elecItr)->author() auth_elec Int (enum) Algorithm used to create the electron: unknown=0, egamma=1, softe=2
(*elecItr)->parameter(ElectronParameters::EoverP) eoverp_elec Double E/P ratio
(*elecItr)->parameter(ElectronParameters::etcone) etcone_elec Double Energy deposition in a cone dR=0.45 around the electron cluster
(*elecItr)->parameter(ElectronParameters::etcone20) etcone20_elec Double Energy deposition in a cone dR=0.20 around the electron cluster. Standard cone size for ATLFAST
(*elecItr)->parameter(ElectronParameters::etcone30) etcone30_elec Double Energy deposition in a cone dR=0.30 around the electron cluster. Currently empty
(*elecItr)->parameter(ElectronParameters::etcone40) etcone40_elec Double Energy deposition in a cone dR=0.40 around the electron cluster
(*elecItr)->parameter(ElectronParameters::emWeight) emwgt_elec Double Weight for electrons (see below)
(*elecItr)->parameter(ElectronParameters::pionWeight) piwgt_elec Double Weight for pions (see below)

There are 3 types of quality cuts you can perform on the electron candidates:

  1. Cuts based on the isEM flag
  2. Cuts based on likelihood
  3. Cuts based on NeuralNet output

1. The isEM flag uses both calorimeter and tracking information in addition to TRT information. The flag is a bit field which marks whether the candidate passed or not some safety checks.

The bit field marks the following checks:

  Cluster based egamma
  ClusterEtaRange        =  0,
  ClusterHadronicLeakage =  1,
  ClusterMiddleSampling  =  2,
  ClusterFirstSampling   =  3,
  Track based egamma
  TrackEtaRange          =  8,
  TrackHitsA0            =  9,
  TrackMatchAndEoP       = 10,
  TrackTRT               = 11

In 9.0.4 there is a problem with TRT simulation so one has to mask TRT bit to recover the lost efficiency.

To get the flag in your AOD analysis you should use:

(*elec)->isEM()

To mask the TRT bits you should use: (*elec)->isEM()&0x7FF==0

If you use isEM then you will select electrons with an overall efficiency of about 80% in the barrel but much lower in the crack and endcap.

2. The likelihood ratio is constructed using the following variables: energy in different calorimeter samplings, shower shapes in both eta and phi and E/P ration. No TRT information is used here. You need to access two variables called emweight and pionweight then you can construct the likelihood ratio, defined by: emweight/(emweight+pionweight).

In AOD, you use the following code:

ElecEMWeight = elec*->parameter(ElectronParameters::emWeight); ElecPiWeight = elec*->parameter(ElectronParameters::pionWeight);

Then form the variable: X = ElecEMWeight/(ElecEMWeight+ElecPiWeight);

Requiring X > 0.6 will give you more than 90% efficiency for electrons.


3. The NeuralNet variable uses as inputs the same variables used for likelihood. To use it in AOD you should proceed as follow:

ElecepiNN = elec*->parameter(ElectronParameters::epiNN);

Requiring ElecepiNN > 0.6 will give you about 90% eff for electrons.

However, you should be aware that the NN was trained in full eta range while the likelihood was computed in 3 bins in eta: barrel, crack and endcap. So I would suggest to use likelihood for now.

To require an isolated electron, you have to cut on the energy deposited in the cone around the electron cluster. ATLFAST for example requires Et<10 GeV in a cone of dR=0.2. You can simulate the ATLFAST cut by requiring etcone20<10.*GeV

Photon

Muon

Muon in AOD/Ntuple
AOD Container Name AOD Variable Ntuple Variable Variable Type Comment
MuonCollection (*elecTES)->size() n_muon Int Number of muons in the Ntuple

Tau

Jet

BJet

Missing Et

External References

Container/Object Names for AOD

Particle Preselection Cuts