Impact Parameter Significance studies

1. Impact Parameter Significance studies Nick Edwards (University of Glasgow), Shih-Chieh Hsu (LBNL)

2. Introduction & Outline • Impact Parameter Significance definition: • Useful in Electroweak analyses to reject heavy flavour backgrounds, as well as background from light quark backgrounds. • Need to understand how well MC models the distribution observed in data, and derive smearing factors to reproduce data distribution in MC. d0Sig = d0 / σ(do)

3. Data MC consistency • Plots from T&P in Z mass peak 81 – 101 GeV with tight muons and Medium electrons with pT > 20 GeV, |η| < 2.5 • MC underestimates d0Sig – need to apply smearing • Strange spike in the electron distribution around 5 – this is also seen in the unbiased distribution Central muon biased d0Sig wrt PV Central electron biased d0Sig wrt PV

4. Track Brem Refit • Shoulder of d0Sig distribution is due to Brem • Refitting track to account for energy lost to brem and recalculating d0Sig could solve this • Two approaches to Brem refitting: • GSF (Gaussian Sum Filter) : The non linear effects of Bremsstrahlung are taken into account by modelling the energy loss at each material surface by sum of Gaussians  which is then convolved with the original PDF describing the track parameters.   • DNA  (Dynamic noise adjustment)  At each material layer it performs a single parameter fit to determine if any energy was lost at that surface.  If it detects  that there was energy loss it will increase the the uncertainty of the track parameters (hence noise adjustment) by an amount corresponding to the  measured energy loss.

5. Shih-Chieh Hsu Single lepton efficiencies: electrons • Select medium central electrons following ZZ baseline selection (no isolation or d0). Apply d0cuts and measure efficiency • d0Sig has larger rejection efficiency for conversion electrons • Brem refit d0Sig has better rejection efficiency for heavy flavour • d0Sig and unbiased d0Sig lose more signal efficiency for the same background rejection compared to brem refit d0Sig • Endcap rejection is larger for conversion compared to heavy flavour. Barrel Barrel Endcap Barrel • |DNA d0Sig| < 10 remains 99% signal efficiency with 15~20% rejection rate • |DNA d0Sig| < 8 remains 98% signal efficiency with 20~30% rejection rate for different types of backgrounds source

6. Shih-Chieh Hsu IP Smearing • Dataset: 2011 Egamma/Muon stream (B~E1) • mc10 is normalized to 205pb-1 • Select Zee/Zmumu within 81<mll<101 Region • Project d0Sig histogram • Extract the width of the Gaussian core (+- 1σ) • Derive Smearing factor: • Smearing = sqrt(σdata2 - σMC2 )

7. Shih-Chieh Hsu Data – MC smearing factors • d0Sig Biased Electron d0error is underestimated such that width is larger than for muon. However, the additional smearing factor 0.5σ is universal, with no obvious eta dependence • d0Sig Unbiased: Combined muon unbiased d0Sig is from combined track instead of ID only track for unbiased d0Sig. For muons, the endcap smearing factor is smaller than barrel. Electron smear factor is not trivial Eta Eta

8. Shih-Chieh Hsu Data – MC smearing factors: Brem refit • Electron DNA refit d0Sig: (below) smearing factor average is approximately 0.4. Flatter η distribution than for the un-refitted variables • Electron GSF refit d0Sig: (right) MC has larger width than Data. Why does MC underestimate d0Err ? Eta Eta Eta Eta

9. Conclusions and Issues • Clearly Impact parameter significance resolution worse in data than MC -> need smearing. • Using brem track refitted parameters gives better background rejection / signal efficiency. • Is it valid to use brem refitted track for d0 but not for other cuts (eta, isEM….)? • Which is best refit algorithm to use? • Is it valid to apply smearing to d0 Significance rather than to d0 ?

10. Backup

11. Loose Object Definition • Central Electrons • Author = 1 or 3 • Use cluster energy, track direction following egamma recommendation • Et > 15 GeV , |ηCluster|<2.47 • |Z0|< 10mm • Remove overlap with muons in cone dR < 0.1 • Overlapping electrons: remove the one with lowest ET in cone dR < 0.1 • Object quality (OQ & 1664 == 0) • Loose (at least 2 medium) • Forward Electrons • Author = 8 • Et > 15 GeV 2.5 < |ηCluster| < 2.9 • Overlap removal • Loose • https://twiki.cern.ch/twiki/bin/view/AtlasProtected/SMZZSummer2011 • Muons • STACO Tight. • MCP track Quality Cuts • Pt > 7GeV • |η| < 2.5 • |Z0|< 10mm • Forward Muons • STACO Tight • Pt> 15 GeV • 2.5 < |η|< 2.7 • Apply electron momentum smearing and muon momentum smearing and scaling to MC. • <μ> Reweighting applied to MC using data weights for all 2011 • Data: 2011 B2 – E1 205pb-1 • MC: mc10a, SMWZ d3pd

12. Loose Event Selection • Good Run List: data11_7TeV.periodAllYear_DetStatus-v13-pro08-02_WZjets_allchannels.xml • Data: Remove events with Noise Burst and Data Integrity Error • Event Preselection: • Require at least 4 tracks associated to primary vertex (to be discussed) • Trigger: 4mu: (EF_mu18_MG OR EF_mu18) . 4e: EF_e20_medium 2e2mu: either trigger • Exactly four leptons as defined previously, >= 2 central leptons • Require at least one lepton Pt > 25 GeV • ZZ formation: • Z01 : Choose closest same-flavour pair to the Z pole with at least one central lepton, q0*q1 <= 0 • Z34: Same-Flavour • Z Mass Cuts: 66 GeV < MZ1< 116 GeV, 20 GeV < MZ2< 300 GeV • Z34 Opposite sign: q3*q4 <= 0 • Impact Parameter significance:d0PV / σ(d0PV) < 10

13. Datasets