1. ZZ→llnn Analysis Thomas Barber University of Cambridge
ATLAS UK SM Meeting, September 2007

2. Tom Barber, University of Cambridge
Outline
Results of ZZ→llnn analysis with and Monte Carlo.
Physical Motivation
Analysis procedure and description of CSC datasets used.
Electron and muon identification in Eventview.
Parameters used in cut-based selection.
Comparison of full-simulation yields to previous fast sim results.
Signal and background yields using tuned cuts.
Summary and outlook.
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Tom Barber, University of Cambridge

3. Neutral Diboson Couplings
Standard Model Production Diagrams
Forbidden in SM
Neutral diboson (ZZ) production in ATLAS
By examining cross section at high Z pT, we can put limits on anomalous neutral triple gauge couplings (NTGC).
See Pat’s Talk
Other groups studying ZZ4 leptons
In comparison, the ZZ→llnn (l=e,m) channel has:
Larger background (no second lepton pair)
But ~6 times larger cross section (0.397 pb)
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Tom Barber, University of Cambridge

4. Tom Barber, University of Cambridge
Analysis Procedure
Athena analysis using EventView
Using Distributed Analysis framework with
Ganga for LCG datasets.
pAthena for BNL datasets.
Event Generators mostly either Pythia or one AcerMC sample.
Event Weights in are handled by subtracting negative events from positive distributions and yields.
Cross Sections calculated by running appropriate DC3 joboptions transform to generate ~10,000 events.
For combine production CS with branching ratio from PDG.
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Tom Barber, University of Cambridge

5. Tom Barber, University of Cambridge
Monte Carlo Datasets
Analysis done on both CSC11 and CSC12 signal and background datasets.
Two different signal datasets used:
Signal (blue)
csc Pythiazzllnunu.recon.AOD.v
Pythia generator: leading order
48700 events.
Signal (red)
user.HongMa.trig1_misal1_mc McAtNlo0310_JIMMY_ZZ_llnunu.recon.AOD.v _pUM02203
generator: next-to-leading order.
events
Dataset currently unofficial, official sample in production.
In case of datasets, 1mm Bug-fix applied where needed.
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Tom Barber, University of Cambridge

6. Tom Barber, University of Cambridge
Version Datasets
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Tom Barber, University of Cambridge

7. Tom Barber, University of Cambridge
Version Datasets
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Tom Barber, University of Cambridge

8. Tom Barber, University of Cambridge
EventView Inserters
EventView used to
Create NTuples
Remove overlap (R = 0.1).
Insertion order:
Electrons (+ loose electrons)
Photons
Muons (+ loose muons)
TauJets
TauJetCollection pT > 5 GeV, either TauRec or 1p3p
Particle Jets
ConeTowerParticleJets, R = 0.5, pT > 5 GeV
Need robust electron and muon identification
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Tom Barber, University of Cambridge

9. Tom Barber, University of Cambridge
Electron ID
Electrons from egamma
(isEM & 0x7FF) == 0, ie no TRT
Isolation: Et(R=0.45) < 8 GeV
pT > 5 GeV, || < 2.5
11.0.4: Efficiency = 75.0%
12.0.6: Efficiency = 62.6%
Much lower in
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Tom Barber, University of Cambridge

10. Tom Barber, University of Cambridge
Muon ID
Muon from MuID algorithm
Require a best match, with
2(match)/ndof < 10
2(fit)/ndof < 5
Isolation: Et(R=0.45) < 5 GeV
pT > 5 GeV, || < 2.5
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Tom Barber, University of Cambridge

11. Tom Barber, University of Cambridge
Muon Efficiency
11.0.4:
Efficiency = 86.3%
12.0.6:
Efficiency = 87.7%
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Tom Barber, University of Cambridge

12. Tom Barber, University of Cambridge
Lepton Kinematics
Electrons and muons show good agreement.
Treat them as leptons for rest of analysis.
pT shows good agreement between two versions.
Z-width not yet implemented in (planned for future)
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Tom Barber, University of Cambridge

13. Tom Barber, University of Cambridge
Signal Topology
ZZ→llnn signal characterised by 2 high-pT leptons and ET(miss).
Atlantis event displays
Define cuts to separate signal from background channels.
Main backgrounds from channels with:
Large C.S. (ttbar and Zll)
Similar topology (WZ and WW)
Following plots are
normalised to unit area to compare shapes
before any cuts applied
Show distributions (unless specified)
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Tom Barber, University of Cambridge

14. Tom Barber, University of Cambridge
Lepton Cuts
ZZ→llnn signal channel shown in red.
Lepton pT > 20 GeV
Reduces soft electron background, eg ttbar (magenta) & Z (turquoise)
|mll – 91.2 GeV| < 10 GeV
Reduces non-Z background, ttbar (magneta), Z (turquoise) & WWll (purple)
20 GeV
±10 GeV
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Tom Barber, University of Cambridge

15. Tom Barber, University of Cambridge
Third Lepton Veto
Require exactly two oppositely charged leptons
Define “Loose Leptons” is anything left in Electron/Muon after initial lepton ID, with pT > 5 GeV.
N(leptons) = N(quality) + N(loose)
Veto events with N(lepton) > 2 to cut down WZ background.
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Tom Barber, University of Cambridge

16. Tom Barber, University of Cambridge
Missing Energy
Using AOD keys:
METFinal (11.0.4)
METRefFinal_1mmCorrection ( )
METRefFinal (> )
Absolute MET cut > 50 GeV removes Zll (blue), Z4l (orange).
Also require magnitude and direction to match that of the Z(ll).
|MET-Zpt|/Zpt < 0.35
|f(z)-f(met)| < 35 deg
Both cuts are set at ~2s from the centre of the signal peak.
Helps to remove background from the WZ channel.
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Tom Barber, University of Cambridge

17. Tom Barber, University of Cambridge
Jet Veto
Reduces background from ttbar and Zll (high pT Z)
Require events to have no jets with
pT > 30 GeV and || < 3.0
Discrepancy between jet multiplicity and signal due to Generator, Pythia (LO) vs. (NLO)
In the truth, average number of jets per event:
11.0.4: : 5.3
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Tom Barber, University of Cambridge

18. Tom Barber, University of Cambridge
Final Cut
Cut on pT of the Z.
In fast simulation, pT(Z) > 150 GeV
For full simulation, only require pT(Z) > 100 GeV
Final value can be set to obtain a required S/B ratio.
Anomalous coupling enhance cross section at high Z pT, so this cut will not harm anomalous coupling studies.
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Tom Barber, University of Cambridge

19. Fast Simulation Comparison
Run analysis with cuts identical to fast simulation study, by Hassani (ATL-COM-PHYS )
Top table reproduction of fast sim results, lower table full simulation with data. (except Wt channel, which is )
Now signal is only ~60% of fast simulation prediction.
Larger backgrounds from Z+jets and WZ channels.
Other channels, no events pass, low statistics.
Events expected in 100fb-1 of data
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Tom Barber, University of Cambridge

20. Tom Barber, University of Cambridge
Full Simulation Cuts
Now apply MET matching cuts and reduce pT(Z) cut.
Plot shows events after cuts, normalised to 100fb-1
Signal efficiency increased, background reduced:
 = 3.2%  = 2.6%
S/B = S/B =1.96
Errors on ttbar & Zll large due to low statistics.
Events expected in 100fb-1 of data
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Tom Barber, University of Cambridge

21. Signal Selection Efficiency
Plots show number of reco events passing cuts compared to number of true events passing cuts.
No ZpT cut is applied.
Shows a drop in efficiency at high Z pt.
Possibly due to Jet Veto removing high pT(Z) events that also have a high pT jet recoiling.
Needs further investigation – possibly tune the jet veto.
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Tom Barber, University of Cambridge

22. Conclusions and Outlook
Good agreement between two CSC datasets except:
Lower electron efficiency
No Z width in ( dataset)
Comparison to Fast Simulation shows lower signal efficiency and higher backgrounds.
Requiring Missing Et to match the Z pT and  gives much better yields.
Still to do:
Investigate and optimise the jet veto (to reduce ttbar) and 3rd lepton veto (to reduce WZ).
Trigger Aware Analysis still needs to be performed.
Investigate Multi-variate analysis techniques, eg ANN, BDT
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Tom Barber, University of Cambridge