== Electron Mis-Charge Rate Measurement of WWW Analysis Cristinel Diaconu, Yanwen Liu, Emmanuel Monnier,Ruiqi Zhang

= 1 Introduction  To estimate the background with electron charge mis-identification, we need to measure the charge mis-identification rate.  The muon mis-charge rate is negligible.  Rates are measured using Z->ee events selected from data with likelihood method.  Truth method using Z->ee MC as cross check.  Use template method to subtract the background contribution in the rates and treat it as systematic.  Compare the truth rates measured with Zee MC and WZ MC.  Requested by the SM convener.

= 2 Likelihood and Truth Methods Electrons are divided into different eta/pT bins since mis-charge rates are related to their eta/pT. Etbins:{15.,30.,40.,50.,60.,80.,120.,1000.} GeV Etabins:{0.,0.8,1.15,1.60,1.80,2.0,2.2,2.3,2.4,2.5} Likelihood Method Use Tminuit to calculate, Ntot and Nss(events with a pair of same sign electrons) are input. Truth Method Compare the electrons’ charge with truth charge of coresponded true electron. Two cluster electron A,B and two true electrons decayed from Z in Z->ee MC. Calculate deltaR of any possible combination. If dR[A,C]+dR[B,D] > dR[A,D]+dR[B,C], A matched with D and B matched with C. Else A matched with C and B matched with D.

= 3 Event and Electron Selection Event Selection Trigger : EF_e24vhi_medium1 or EF_e60_medium1 Exactly 2 electrons passing electrons selection. Trigger Match, |InvMee-Zmass|<10 GeV. Electron Selection Author 1 or 3 and OQ. Fabs(eta)<2.47 and crack region removed. pT>15 GeV TightPP Etcone20/pT 20 GeV and Etcone20<0.07 for pT<20 GeV Ptcone20/pT<0.04 |d0/sigmad0|<3.0 |z0*sin(theta)|<0.5 Elec/elec and elec/muon overlap removal.

= 4 Likelihood & Truth Rates from MC Rates here are measured from Z->ee MC samples. LL Rates agree well with truth rates considering their stat errs except two bins(the first one whose LL rate is extremely small and the second one is Etabin1,Etbin0) Likelihood method is ok through this comparison.

= 5 LL Rates from data with stat errors

= 6 Background Subtraction

= 7 Method In Tminuit, Ntot and Nss(with a pair of same sign electrons) are input. Use Template fit to get the background amount in Ntot and Nss which are input for Tminuit. Need background and signal InvMee shapes as templates Use Z->ee MC and the WWW electron selection to get the signal template. Use polynomial fit to get the background template. Need signal and background InvMee passing background selection from data. Because events are divided into many bins according to eta/et of their electrons. Have to merge the bins to get more statictic to do fit. Will show the results with etbins merged. Events will be divided into 9*9 etabins. Will show the background subtraction of [etabin0,etabin2] in detail.

= 8 InvMee Selections Signal Event Selection Trigger : EF_e24vhi_medium1 or EF_e60_medium1 Exactly 2 electrons passing electrons selection. Trigger Match, |InvMee-Zmass|<10 GeV. Electron selection WWW electrons selection except z0 and pT. Z0 is 0.5mm and pT is 15GeV. Background Event Selection Trigger : EF_e24vhi_medium1 or EF_e60_medium1 Choose the leading and subleading electrons and at least one of these 2 electrons stastified the background electron selection and use those 2 electrons to calculate the InvMee. Electron Selection Pass author,pT,eta,OQ and fail isolation and TightPP.

= 9 InvMee Hists Background Mee from Egamma Zee passing Bkg selection This is the Mee in [etabin0,etabin2] of Ntot

= 10 Polynomial Fit Use 4 th order polynomial function and Zee passing bkg selection to fit the "Bkg" hist measured from Egamma samples. Show polynomial fit of [etabin0,etabin2]. Blue is fit. Red is Signal. Orange is polynomial function. Black is "Bkg" from data. More plots of polynomial fit at ： /afs/cern.ch/user/r/ruzhang/public/Plots/z005/ polynomial

= 11 Template Fit Use Mee from Zee MC as signal template and the polynomial function fitted before as bkg to fit Mee from Egamma. Show the fit of [etabin0,etabin2]. Blue is fit. Red is Signal. Orange is polynomial function. Black data. More plots of polynomial fit at ： /afs/cern.ch/user/r/ruzhang/public/Plots/z005/ template

= 12 fSig and its error of Ntot Two tables here show the fSig measured with template fit and its statistic errors for Ntot.

= 13 fSig of Nss Because the statistic of Nss events is not enough to do fine fit. So we get the global fSig of Nss and Nos. And define SF = global_fSig_Nss/global_fSig_Nos. Left is Polynomial fit for Bkg. Right is Template fit for data. Orange is Bkg, Red is Zee and black is data. Blue is fit. fSig is Err is

= 14 fSig of Nss(2) Global fSig of Nos is , global fSig of Nss is , so reweight fSigs of Nos with this SF, then we can get the fSigs of Nss in different bins. Left is Nss and right is Nos.

= 15 Background systematic

= 16 Comparison with WZ rates

= 17 Introduction Apply the truth method to Z->ee and WZ MC samples. mc12_8TeV PowhegPythia8_AU2CT10_WZ_Wm13Z11_mll5p0d0_mll30GeV.merge.NTUP_SMWZ.e1524_s1499_s1504_r3658_r3549_p1328 mc12_8TeV PowhegPythia8_AU2CT10_WZ_W13Z11_mll5p0d0_mll30GeV.merge.NTUP_SMWZ.e1524_s1499_s1504_r3658_r3549_p1328 For lacking of statistic, set fewer bins here. Etabin : 0.,1.15,1.80,2.2,2.5 Etbin : 0.,60.,100.,1000. GeV

= 18 Truth Rate Comparison

= 19 Summary The electron mis-charge rate measurement of WWW analysis is presented. Use the rates measured from Z->ee events selected from data with LL method. Rates with truth method as cross check. Background subtracted and treated as systematic. Comparison with WZ truth rates done. Compatible between Z->ee MC and WZ MC.