1. Differential Z Cross Section in the Electron Channel Bryan Dahmes, Giovanni Franzoni, Jason Haupt, Kevin Klapoetke, Jeremy Mans, Vladimir Rekovic 8/2/20111V.Rekovic, Differential xsec Z->ee, EWK Preapproval

2. Outline Theory and motivation for the analysis Measurement – Strategy – Efficiencies and acceptance – Bin migration and unsmearing – Errors – Sensitivity to PDF’s The result – With 32 pb -1 in frozen AN-10-367 and AN-11-029 Updated results – With 36pb -1 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval2

3. Motivation for Z shape studies Parton density functions are critical for all processes at a hadron collider. PDF’s need to be measured from LHC data. We want to measure them with Z differential cross sections, Y and q T. Z/Drell Yan Production 8/2/20113V.Rekovic, Differential xsec Z->ee, EWK Preapproval Changes due primarily to inclusion of ds/dY from Tevatron.

4. Pythia Tunes 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval4

5. Measurement Strategy Analysis equation: We conduct two separate analyses: X is either rapidity (Y) or transverse momentum (q T ) of Z boson. This is a Shape measurement. We are not measuring cross section. Main components of the analysis: – Z Fast MC Bin Migration and Unfolding – Error estimation 8/2/20115V.Rekovic, Differential xsec Z->ee, EWK Preapproval

6. Measurement Strategy II In the q T analysis  consider only ECAL electrons with|η|< 2.1 to match muon analysis. In the Y analysis  consider ECAL electrons within tracking acceptance |η|< 2.5.  use HF electrons to significantly extend the accessible rapidity range; HF electron ID based on longitudinal and transverse shower shape variables.  Not currently using electrons in ECAL outside the tracker acceptance. HF ECAL 8/2/20116V.Rekovic, Differential xsec Z->ee, EWK Preapproval

7. Data for the Analyses 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval7 Dataset /EG/Run2010A-Dec22ReReco v1/RECO 2.9 pb -1 /Electron/Run2010B-Dec22ReReco v1/ 29.1 pb -1 An error in a GoodLumi file was found immediately before the pre-approval freeze. As a result, only 32 pb−1, not 36 pb−1, is used in the frozen ANs. HLT

8. Z Definitions/Electron Selection Z definition in d σ /dY Electron 1 (HLT matched)Electron 2 ECAL-ECALECAL + track + HLTECAL + track ECAL-HFECAL + track + HLTHF ECAL Electron1 (2) Definition GSF track matched EWK Electron WP80 (WP95) P T > 20 GeV HLT HF Electron Definition HF EM Cluster HF Electron ID P T > 20 GeV 8/2/20118V.Rekovic, Differential xsec Z->ee, EWK Preapproval Single electron efficiencies are measured with the tag & probe technique and framework Tag = ECAL electron, that passed WP80 and matches to HLT path Probe = With invariant mass (60-120 GeV) SCluster → GsfElectron → WP80(95)→ HLT Z definition in d σ /dq T Electron 1 (HLT matched)Electron 2 ECAL 2.1-ECAL 2.1ECAL with |η| <2.1 + track + HLTECAL with |η| <2.1 + track

9. Factorization of Single Electron Efficiencies Offline electron efficiency can be factorized due to several contributions: HLT efficiency is measured w.r.t. offline: For HF there is no trigger nor track requirement: 8/2/20119V.Rekovic, Differential xsec Z->ee, EWK Preapproval

10. Single Electron Efficiencies Z-shape measurement is differential in Y, q T. Therefore integral efficiencies don’t suffice. In view of the convolution step they need to be extracted as a function of: p T, η det In Tag and Probe, side band background subtraction for single electron efficiency Z-shape measurement is differential in Y, q T. Therefore integral efficiencies don’t suffice. In view of the convolution step they need to be extracted as a function of: p T, η det In Tag and Probe, side band background subtraction for single electron efficiency 8/2/201110V.Rekovic, Differential xsec Z->ee, EWK Preapproval

11. Efficiency * Acceptance To extract the efficiency of measured Z as a function of the Z rapidity or Z transverse momentum we start with Z->ee events from “fast” Monte Carlo and convolve single electron efficiencies. You may want to think about it as MC evaluation of : where X is standing for either Y or q T.. – “Fast” Monte Carlo uses smearing functions on gen level particles (with FSR in a cone) to shift their p T, positions in HF, and to simulate ECAL energy resolution. 8/2/201111V.Rekovic, Differential xsec Z->ee, EWK Preapproval,

12. X ee meas is not necessarily equal to X ee true, due to physics and detector effects. FSR photon can fall outside its cluster so X meas can be altered. emission of bremsstrahlung photons, energy loss in the tracker, intrinsic resolution of calorimeter energy and position measurements. If these effects are uneven across measurement range, the measured spectrum X can be different from the true spectrum, due to events migrating across the bins. We can correct the measurement by unsmearing it using either of the two recipes: 1.by average response for each bin, measured by ratio which in analysis equation replaces by 2.by migration matrix that accounts for all possible migrations properly weighted. Inverted migration matrix can then used to unfold the final measurement. In case of low statistics this artificially introduces large errors. Bin Migration 8/2/201112V.Rekovic, Differential xsec Z->ee, EWK Preapproval

13. Fast MC: Data-driven smearing for ECAL/HF Model energy resolution for MC smearing: Derive smearing parameters by comparing invariant mass of smeared MC (eg colored histograms) to DATA, to Minimize χ 2 to obtain function terms. 8/2/201113V.Rekovic, Differential xsec Z->ee, EWK Preapproval For HF σ is of a Gaussian, for EE, EB σ is of a Crystal Ball

14. Fast MC reproduces single electron and di-electron variables that compare well to data Leading Electron P T ECAL-HF dielectron mass Type 1 ECAL- ECAL Z 8/2/201114V.Rekovic, Differential xsec Z->ee, EWK Preapproval Type 2 ECAL-HF Z HF Electron P T ηeηe ηeηe

15. Eff x Acc of Measured Z 8/2/201115V.Rekovic, Differential xsec Z->ee, EWK Preapproval q T [GeV]

16. Unsmearing due to Average Bin Migration Unsmearing for ds/dY Unsmearing for ds/dq T 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval16

17. Systematic Uncertainties Different sources of systematic errors are considered: – From electron efficiencies – Energy scale – Background subtraction Uncertainties in the PDF’s used to compute efficiencies give rise to systematics to the measurement 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval17 small significant

18. Error from Energy Scale 8/2/201118V.Rekovic, Differential xsec Z->ee, EWK Preapproval Two sources of systematatic: Vary energy scale: +/- 1% EB, +/- 3% EE Vary local energy scale to account for uncertainty in transparency corrections: +/- 0.13% |eta| for EB +/-2 +/- 1.5% |eta| for EE Y q T [GeV]

19. Background (QCD) Extract BG contribution from DATA = SIGNAL + BG – SIGNAL is described with POWHEG smeared Fast MC. – BG sample is the QCD enriched sample obtained by inverting ID cuts: candidates that fail ECAL WP95 (ID or isolation) or HF ID. – For each bin derive nominal line shape of BG, described as where For each bin, fit M ee to SIGNAL + BG shapes. Uncertainty in BG is dominated by statistics. Will decrease with future increased data sample. 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval19 Eg: 0.2 < Y Z < 0.3

20. PDF systematic 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval20 POWHEG + FastMC is used to determine EffxAcc for the measurement. How much is the uncertainty on EffxAcc coming from used PDF model affecting the uncertainty of the measurement? Is it compromising the sensitivity to PDF constraints? Ansewer: NO. impact 0.1% in the central Y region, and below 0.5% in Y measurement range Impact at most 0.6% in qT measurement range SAMPLE: 40 M events in POWHEG passed through FastMC, reweighted for 52 PDF CT10w vectors. SAMPLE: 200 M events in POWHEG with |η e | < 2.5 through FastMC, reweighted for 52 PDF CT10w vectors. |η gen,e | < 2.5

21. PDF Sensitivities – Can we constrain PDFs? Largest sensitivity in Y – vector 23Largest sensitivity in q T – vector 5 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval21 CT10w vector 23 CT10w vector 5 Y q T [GeV] CT10w consist of 26 vectors, each with +ive and –ive variation Y and qT analysis suggest largest sensitivity to different PDF vectors of CT10w.

22. Sensitivities of Y and q T Analyses to CT10w 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval22 As expected: Y and qT analyses have different sensitivity to PDF models in CT10w. Maximum sensitivity is about 3%.

23. All Errors for Y Analysis 8/2/201123V.Rekovic, Differential xsec Z->ee, EWK Preapproval Statistics dominated. Largest systematic from BG (stat), which will decrease with more acquired integrated luminosity. Negligible PDF errors & unsmearing

24. All Errors for q T Analysis 8/2/201124V.Rekovic, Differential xsec Z->ee, EWK Preapproval Largest systematic from Energy Scale and BG (stat). The later will decrease with more acquired integrated luminosity. Negligible PDF & unsmearing errors

25. Result for Y 8/2/201125V.Rekovic, Differential xsec Z->ee, EWK Preapproval

26. The Final Result for |Y| 8/2/201126V.Rekovic, Differential xsec Z->ee, EWK Preapproval

27. The Final Result for q T (linear) 8/2/201127V.Rekovic, Differential xsec Z->ee, EWK Preapproval smeared

28. The Final Result for q T (log) 8/2/201128V.Rekovic, Differential xsec Z->ee, EWK Preapproval smeared

29. 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval29 Updates: Results with 36 pb -1

30. Result for Y with 36 pb -1 8/2/201130V.Rekovic, Differential xsec Z->ee, EWK Preapproval

31. The Final Result for |Y|with 36 pb -1 8/2/201131V.Rekovic, Differential xsec Z->ee, EWK Preapproval

32. The Final Result for q T with 36 pb -1 (linear) 8/2/201132V.Rekovic, Differential xsec Z->ee, EWK Preapproval

33. The Final Result for q T with 36 pb -1 8/2/201133V.Rekovic, Differential xsec Z->ee, EWK Preapproval

34. Conclusions We performed a measurement of differential cross section in Y and q T of the Z boson in electron channel with 32 pb -1 of 2010 data – Analyses are statistically dominated – Important systematic is on BG estimation which will be reduced with increased data sample in 2011. Notes AN-10-367 and AN-11-029 are frozen, but updates are included in this presentation. – We add 4 pb -1 of data with new JSON file released few days before freeze. – Final plots of POHEG prediction in frozen q T AN-11-029 were not unfolded for smearing. The updates with 36 pb -1 presented today include unsmearing. – As a cross check, we measured inclusive cross section, and observed agreement with the result from VBTF – Comparison of data will be discussed in the following talk. 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval34

35. BACK-UP 8/2/201135V.Rekovic, Differential xsec Z->ee, EWK Preapproval

36. Single Electron Efficiencies (T&P) This is probably for BACK-UP 8/2/201136V.Rekovic, Differential xsec Z->ee, EWK Preapproval

37. Eff x Acc vs. qT wrt Mesarued and wrt True Z 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval37

38. Bin migration and unfolding in Y 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval38 Migration matrix from the FSR and smearing implemented in fast Monte Carlo Unfolding matrix obtained by inversion Systematics from unfolding, less or much less than 1%: Base unfolding matrix based on smearing parameters Compare it with results from varying ±1σ the smearing in fast Monte Carlo Systematic defined as quadrature sum of variations in each bin

39. Bin migration and unfolding in q T 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval39 Migration matrix from the FSR and smearing implemented in fast Monte Carlo Unfolding matrix obtained by inversion Systematics from unfolding, less or much less than 1%: Base unfolding matrix based on smearing parameters Compare it with results from varying ±1σ the smearing in fast Monte Carlo Systematic defined as quadrature sum of variations in each bin

40. Systematic Uncertainty on Bin Migration for Y 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval40 for average bin unfolding Cumulative syst error due to Fast MC is 0.2%. For matrix unfolding cumulative syst error due to Fast MC is 0.2%.

41. Systematics from electron efficiencies: statisticalbin correlated qTqT 8/2/201141V.Rekovic, Differential xsec Z->ee, EWK Preapproval Slide for BACK UP

42. PDF errors to Eff x Acc vs q T 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval42 Den = No cut on Y of gen Z Den =|Y (genZ) < 2 Den = ECAL-ECAL CT10w 40 M POWHEG events CT10w 400 M POWHEG events

43. Inclusive Cross Section 8/2/2011V.Rekovic, Differential xsec Z->ee, EWK Preapproval43 From ds/dY analysis From ds/dqT analysis