# Presentation: 534889

## Lepton and Photon ID at the Tevatron

- _Introduction:_
- High Pt leptons and photons  are very important objects - can trigger on them
-  Particle/object ID  requirements  driven by the physics
- Isolated leptons and photons (W/Z, high-Pt searches – Z', SUSY...)
- Non-isolated e/μ - tagging of the heavy quark jets
- Quantifying performance of ID techniques: **efficiencies**, **probabilities of misidentification**
- approaches: cut-based (“box”), likelihoods , neural networks
- Use - subject of a different talk

- P.Murat(FNAL) for the CDF and D0 collaborations

- many thanks to D.Denisov, Y.Gershtein(DO), D.Waters(CDF)

##  Central calorimeters : face to face

##  Electrons

- Electron clustering “box” ~ 0.3 x 0.3
- EM fraction > 0.9 (D0) , tighten later
- Shower shape consistent with that of EM shower
- track – shower max/preshower match ( σ~2-3mm)
- Consistency of the energy and momentum measurement: E/P < 2 (CDF)
- Isolated (calorimeter, sometimes – tracker), typical isolation cone size ~0.4
- Conversion removal
- both CDF and D0 reconstruct subclusters  within the electron clustering cone
- Correlation between the ID variables

##  Electron ID: efficiencies

- Measure ID efficiencies for high-Pt electrons using  Z->ee decays
- Several quality classes (tight, loose)
- Efficiency: 85-95%
- data-to-MC scale factors : <5%, uncertainties <1%
- Backgrounds for ID efficiency measurement small (same-sign events under the Z peak) , which makes the efficiency measurements  very robust
- SUSY (multileptons): isolated electrons above ~5 GeV
- Calibrations sample: low mass Drell-Yan e+e- events
-  Background : same-sign e+e-candidates
- Efficiencies/scale factors - similar to above
- Charge misID in the forward region: ~4% at |η| ~ 2

- Charge misID for Z->ee

##  exploiting shape of EM showers

- Both experiments use cluster shape variables in electron ID
- CDF : calculate lateral shower shape analytically
- EM cluster and a track
- Matching: track-cluster – shower max
- D0 - “H-matrix” - measurements in 9 layers( 5x5 matrix) calculate chi2 of the shower using 7 or 8 variables
- Account for the shower energy

##  Electrons: misidentification rates

- Typical QCD patterns:
- Converted leading photon
- Tails of the fragmentation: leading pi0 overlaps with pi+
- Normalization of the fake probabilities:
- “Per jet” (more traditional)
- energies of a jet and a fake electron are different
- Expect sample dependence (top plot)
- “Per EM object “– use the same variables
- MisID Probabilities are low
- D0: (0.6+/-0.1) %  per jet w/o preshower
- CDF : per jet is about 10-4
-  Sample dependence: ~ 30-50%
- In many cases  QCD backgrounds are small,  large uncertainty is more matter of principle

##  Electrons: likelihoods

- D0: “H-Matrix”
- Takes 7 or 8 longitudinal and lateral shower distribution variables and calculates a 2 discriminant
- Layer energy fractions
- Lateral shower widths
- Currently tuned with full Monte-Carlo simulations
- CDF:
- +5% efficiency
- 40% better QCD background rejection
- Decorrelation
- Stability wrt the definition of the likelihood

## Learning from the likelihoods

- Why likelihood-based approach performs better? - no E/P cut
- What does this cut remove ?
- asymmetric conversion pairs
- CDF Si tracker – 15% of rad length in average
- CMS – up to 1.5 X0 ... 35%... + pileup

##  Electrons: summary

- Run II : improve and extend identification techniques first developed in Run I
- ID efficiencies for (Pt> 20GeV) ~ 85-95%  up to |eta| ~ 2
- MisID probabilities: “per jet” vs “per EM object”
- Low, calorimeter alone (D0): 6*10-3 , preradiator commissioned
- Using shower max information (CDF): ~ (1-2)e-4
- Forward region (CDF) ~ (5-6)*10-4
- Shower shape important
- [jet] sample dependence: ~30-50%
- Conversion removal: important at the Tevatron, even more at LHC (material, pileup)
- Likelihood-based approaches:
- Typically better S/B than the box-type cuts
- Useful for estimating the backgrounds
- Breakdown of improvemnts: x*(better technique) +(1-x)* smarter people
**X = ?**

## Photons

**A photon:**
- Narrow EM shower in the calorimeter, no tracks
- Cluster in  shower max detector, consistent with EM profile
-  No other clusters in shower max detector
- always “an isolated photon”
- Major background: jets fragments into leading pi0 with 2 photons merged
- CDF shower max ~ 1.8m from the interaction point, symmetric pi0  decay:
- Δ(Rφ) ~ 50cm/Et, cluster width ~ 2cm
- Can't resolve 2 EM showers above ~50 GeV
- Preradiator: ~ 1 X0, probability to have a shower started in the coil: **P(****π****0****) ~ 2*P(****γ) ****independent on how close the 2 photons are**
- Extend Et range above  50 GeV

## Photons: ID efficiency

- ID efficiencies: no tagged photons
- Use Z->ee data, remove electron tracks
-  suppress bremsstralung: 0.9 < E/P < 1.1
- Compare to Z->ee MC , determine scale factor
-  ε**ID**** ~ 90%  (Et > 20 GeV, |****η****|<1)**
**Scale factor stable: ~ (94****±****2.3)%**

## Photon ID: misidentification rates

- Fake rate:
- probability for a pi0 to be reconstructed as a photon
- Measure in the data (jet samples with different trigger thresholds 20, 50, 70 and 100 GeV)
- Order jets in Et, ignore the  1st one (trigger bias)
- use 3rd, 4th, 5th ..., highest ET  jets
**Jet#2: measure lower mis-ID rate than jet#3**
**Lower fraction of prompt photons**

**Ε****fake**** ****~ ****(5+/-5)10****-4**** @ 50 GeV**

## Muon:  
track pointing to 1 or more stubs in the muon chambers
D0 : 3 stubs , 2-3 layers of sc. Counters, standalone measurement of muon momentum
 CDF: 2 stubs, 1 layer of scintillators not in the trigger
Consistent with MIP energy deposition in the calorimeter (D0 – cross check only)
Isolated in the calorimeter, less often -  in the tracker
Timing: muon scintillators/ CDF calorimeter scintillators

- Muon:
- track pointing to 1 or more stubs in the muon chambers
- D0 : 3 stubs , 2-3 layers of sc. Counters, standalone measurement of muon momentum
-  CDF: 2 stubs, 1 layer of scintillators not in the trigger
- Consistent with MIP energy deposition in the calorimeter (D0 – cross check only)
- Isolated in the calorimeter, less often -  in the tracker
- Timing: muon scintillators/ CDF calorimeter scintillators

- Muons

## Muons: ID efficiency

- Need to deal with
- Muon stub reconstruction efficiency
- Track extrapolation
- fringed magnetic fields
- Multiple scattering
- alignment
- Fake muons - hadrons punching through
- Real muons  from pi/K decays in flight – suppress by requiring good quality of the track  fit
- Cosmic muons
- Several categories of muons – from tight to loose
- CDF(EID) ~ 90% for the “best quality muons”
**Data-to-mc scale factor consistent with 1**

## Muons: misidentification probability

- Mis-ID probability (CDF):
- probability for a high-Pt track to be reconstructed as a muon
- Of the order of 1%  (CDF), significantly lower for D0
- Use generic jet samples, accuracy severely limited statistically
- backgrounds due to the fake central muons are small
- might be useful to implement special backup triggers  aimed in misID rate measurements

## Rejection of the cosmic muons

- D0 uses robustness and redundancy of the muon system
- Timing from the muon scintillators + track impact parameter
- CDF relies  on the efficiency and resolution of the drift chamber
- For each muon candidate try to reconstruct its 2nd leg
- If found, test if 2 legs correspond to:
- 2 particles
- 1 particle
- If the best chi2 corresponds to 1 particle may call it a cosmic muon
- for inclusive W and Z cross section measurements background from cosmic muons is negligible

##  Tau ID: reconstructing pi0's

- Tau decays result in many pi0's/photons in the final state
- Coordinate resolution of the calorimeter alone not enough to resolve them
- Both Tevatron experiments demonstrated their ability to reconstruct pi0 using
- shower max detector (CDF) with coordinate resolution about 2-3 mm
-  preshower (D0), similar resolution

## Tau ID: neural networks (D0)

- D0  measured Z->tau tau cross section using neural network-based approach
- Trigger on muons, identify Z->τ(μ) τ(e/h) events
- 3 classes of events, 3 separate NN's
- τ- -> π-/K- ν
- τ- -> π n(π0 / γ) nu / e νν(rho-type)
- τ- -> π- π- π+ ν  (K..)
- Training: use single τ +minbias events MC and QCD data
- ε**ID****  platoes at ~ 80%, jet misID rate ~ 5-10% **(caveat: normalized to “type2-looking jet”, x5)
- Flattish distribution in XNN  for background useful for cross checks

## Tau ID: cut-based approach (CDF)

- Target on hadronic decays of taus
- Signature: narrow jet with low track multilicity
- Find narrow clusters in the calorimeter, count **tracks pointing to a cluster**
- Use shower max detector to reconstruct **pi0's /photons** down to ~0.5 GeV (resolution in pi0 energy about 25-30%)
- M(tracks+pi0) < Mtau
- Require tau candidate to be isolated
**Diference with NN-based approach: understand effect of each cut separately**
**Electron removal**: require energy deposition in the hadron compartment not to be small compated to the sum of track momenta (typical cut values used ~0.1-0.2)

## Tau ID: 

- efficiency platoes at about 50%.
- Fake probability falls with energy (mass cut)
- ~1% at 20 GeV, 0.2% at 100GeV
- Need to understand different from NN dependence on energy
- Sample dependence: ~50%
- 2D parametrization: Ejet,  γ = Ejet/Mjet reduces sample dependence to ~20%
- Jet and tau reconstruction  algorithms calculate parameters of the same object differently - d**etermine fake probability per “very loose tau candidate” (~3 times higher)**
- Still art, more intellectual effort needed

## Summary

- Lepton/photon ID techniques at the Tevatron are well established
- Reliable calibration sources (W/Z, J/psi's, upsilons)  exist in Pt range ~ few-50 GeV
- Electrons/muons/photons ( Pt > 20 GeV ): εID are 90% and above, fake probabilities low (10-3-10-4)
- Taus – ID efficiencies in the range (50-80)% demonstrated, fake rates vary significantly depending on the approach (NN vs “box” )  (0.2-2% at 100 GeV)
- QCD mis-ID probabilities: sample-dependent at the level of 30-50%, still art
- understanding misidentification needs a lot of thought put into design of the calibration/backup triggers

**Backup triggers with prescales above 10 often not enough**