Sung-Won Lee 1 Study of Jets Production Association with a Z boson in pp Collision at 7 and 8 TeV with the CMS Detector Kittikul Kovitanggoon Ph. D. Thesis Defense March,

2 Outline Motivation. Large Hadron Collier (LHC) and Compact Muon Solenoid (CMS). Overview of Standard Model (SM). Measurements of Angular Distributions for Z+jet events at 7 TeV.  Theory.  Data Samples and Event Reconstructions.  Unfolded Results with Uncertainties. Differential Cross Section of Jets Associated to Z boson at 8 TeV.  Theory.  Data Samples and Event Reconstructions.  Unfolded Results with Uncertainties. Conclusions.

3 Motivation For Z boson decays into μ+μ-, the trigger system is very efficient and nearly background free. Provide good feedback to the theoretical physics community to improve the precision of perturbative QCD and to event generator experts. Measurements of the rapidity distributions and differential cross sections are one of the crucial test of the SM prediction. Major background processes for various new physics searches such as Higgs and Supersymmetry (SUSY).

4 Large Hadron Collider (LHC) A 27 km in circumference. To collide rotating beams of protons or heavy ions. Maximum energy of proton- proton collisions at = 14 TeV and 4 x cm -2 s -1. In 2011, collision at = 14 TeV and 4 x cm -2 s -1 In 2012, collision at = 8 TeV and 7.7 x cm -2 s -1

5 Compact Muon Solenoid CMS

6 Compact Muon Solinoid CMS

7 Standard Model (SM)

8 Z + Jet Angular Distribution

9 Z+jet '' Z+jet'' events are predominantly produced by quark exchange processes (i.e. qq ̄ → Z 0 g and qg → Z 0 q)

10 What Do We Measure? Rapidity distributions of Z boson: |y z | Rapidity distributions of leading jet: |y jet | Rapidity difference: y diff = 0.5|y z -y jet |  Related to the scattering angle at the center of momentum frame: tanh(y diff ) = β*cosθ* Rapidity average: y sum = 0.5|y z +y jet |  Rapidity boost from the center of momentum frame to the lab frame Rapidity is defined by

11 Analysis Procedure (1) Selects events containing a Z(→μμ) and a jet that satisfy kinematic and ID selections. (2) Derive efficiency from MC and correct it with data-to-MC scale factors via tag and probe method. (3) Unfold the distribution of y jet  Other variable have unfolding correction consistent with one. (4) Evaluate Systematic uncertainties. (5) Compare shapes with MCFM, MADGRAPH, and SHERPA MC simulations. MCFM Matrix element at NLO,without parton showering or hadronization Scale set to the dilepton mass CTEQ 6.1 m (NLO PDFs) MADGRAPH+PYTHIA Matrix element at LO with MLM matching Scale set to the square root sum of dilepton mass and p T (jet) CTEQ 6L1 m (LO PDFs) SHERPA Matrix element at LO with CKKW matching Scale set to the dilepton mass CTEQ 6.6M (NLO PDFs)

12 Dataset and HLT CMS data collected in 2011 for 5.1 ± 0.1 fb -1 Monte Carlo Simulations JSON: Cert_ _7TeV_ReRecoNov08_Collisions11_JSON.txt High Level Trigger

13 Basic Kinematic Selections

14 Basic Kinematic Properties

15 Basic Kinematic Properties

16 Basic Kinematic Properties

17 Muon ID Scale Factors ID scale factors from Particle Object Group Use Tag & Probe with Data & MC  Select a pair of muons: one passing tight selections (tag) and the other passing or failing loose selections (probe)  The scale is computed from the ratio of tag+passing probe and tag+failing probe Use Muon Particle Object Group recommendations Obtain the data-to-MC ID efficiency scale factors in bins of p T and η Re-weight the MC events that pass ID selections with the scale factors Obtain efficiency as a function of the four rapidity variables

18 Muon ID Efficiency

19 Unfolding Unfolding methods 1. Bayesian 2. Bin-by-Bin 3. Singular Value Decomposition: Criteria: if unfolding correction is consistent with zero within MC statistical uncertainty, do not unfold Only Yjet of Z analysis needs to be unfolded In order to compare experimental result with theoretical prediction, the experimental need to be corrected due to the detector effects. ==> The method is called unfolding. Response matrices of rapidity: the comparison shows mostly diagonal elements

20 Unfolding Correction on Data Unfolding is consistent at one for all but y jet distribution. Thus, we will unfold y jet.

21 Systematic Uncertainties JES JER

22 Systematic Uncertainties

23 Systematic Uncertainties

24 Systematic Uncertainties Summary

25 Comparison to Theories Shape comparisons of CMS data, MADGRAPH, and SHERPA to MCFM are shown.

26 Comparison to Theories

27 Combined Results

28 Combined Results

29 Conclusions CMS detector was used to measure the angular distributions of the products from Z+1jet events Madgraph+Pythia, Sherpa, and MCFM have similar agreement with data for y z and y jet. For Z + 1jet, Sherpa agrees better with data for y diff and y sum.  Parton showering and matching scheme give the difference. Provide feedback to theory community for improving theoretical predictions.

30 Z + Jets Differential Cross Sections

31 Z+jets

32 What Do We Measure? In this analysis, we measured the Z+jets differential cross sections of up to two jets associated with Z → μ + μ -. The Z+jets production cross section as a function of the jet multiplicity : dσ/ dN J The Z+jets cross section as a function of the jet pT : dσ/ dp T The Z+jets cross section as a function of the jet η : dσ/ dη

33 Dataset CMS data collected in 2012 for 19.8 ± 0.1 fb -1 Monte Carlo Simulations JSON: Cert_ _8TeV_22Jan2013ReReco_Collisions12_JSON.txt High Level Trigger → HLT_Mu17_Mu8_v* with L1_DoubleMu3p5 seed

34 Basic Muon Selections

35 PU Reweighting

36 The First Muon Candidate

37 The Second Muon Candidate

38 Efficiency Scale Factor

39 Z Reconstruction

40 Z Reconstruction

41 Basic Jet Selections

42 Z+Jets Control Plots

43 Measured Observables

44 Measured Observables

45 Measured Observables

46 Unfolding

47 Unfolding

48 Unfolding

49 Systematic Uncertainties JES JER

50 Systematic Uncertainties

51 Systematic Uncertainties

52 Systematic Uncertainties Summary

53 Results

54 Results

55 Z+Jets Summary

56 Conclusions

57 Back Up

58 Background Systematic Uncertainty for Z + Jet Angular

59 PU Systematic Uncertainty for Z + Jet Angular

60 Combination of Electron and Muon Best Linear Unbiased Esttimator Andrea Valassi, NIM, A500, 391 Louis Lyons, Duncan Gibaut, and Peter Clifford, NIM, A207, 110 JES and PU uncertainties are 100% correlated between electron and muon channel The covariance matrix has 2N dimension N is the number of bins with non-zero contents For each channel of y jet, the bin-by-bin correlation is obtained from the covariance matrix of RooUnfold after unfolding For every bin of the observable, the uncorrelated uncertainty is at least 3 times of the correlated uncertainty

61 Breakdown Differential Cross Section

62 Breakdown Differential Cross Section