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 DefenseMarch, 24 2014

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.

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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).

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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 TeVand 4 x 10-34 cm-2s-1.

√s

In 2011, collision at = 14 TeV and 4 x 10-33 cm-2s-1

√s

In 2012, collision at = 8 TeV and 7.7 x 10-33 cm-2s-1

√s

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Compact Muon Solenoid CMS

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Compact Muon Solinoid CMS

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Standard Model (SM)

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Z + Jet Angular Distribution

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

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What Do We Measure? Rapidity distributions of Z boson: |y

z|

Rapidity distributions of leading jet: |yjet

|

Rapidity difference: ydiff

= 0.5|yz-y

jet|

Related to the scattering angle at the center of momentum frame: tanh(y

diff) = β*cosθ*

Rapidity average: ysum

= 0.5|yz+y

jet|

Rapidity boost from the center of momentum frame to the lab frame

Rapidity is defined by y=12

ln ( E+pzE− pz )

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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.

MCFMMatrix element at NLO,without parton showering or hadronizationScale set to the dilepton massCTEQ 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)

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Dataset and HLT CMS data collected in 2011 for 5.1 ± 0.1 fb-1

Monte Carlo Simulations

JSON: Cert_160404-180252_7TeV_ReRecoNov08_Collisions11_JSON.txt

High Level Trigger

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Basic Kinematic Selections

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Basic Kinematic Properties

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Basic Kinematic Properties

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Basic Kinematic Properties

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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 IDselections with the scale factors

Obtain efficiency as a function of the four rapidity variables

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Muon ID Efficiency

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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

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Unfolding Correction on Data

Unfolding is consistent at one for all but yjet

distribution. Thus, we will unfold y

jet.

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Systematic Uncertainties

JES

JER

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Systematic Uncertainties

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Systematic Uncertainties

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Systematic Uncertainties

Summary

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

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Comparison to Theories

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Combined Results

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Combined Results

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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 ydiff

and ysum

.

Parton showering and matching scheme give the difference.

Provide feedback to theory community for improving theoretical predictions.

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Z + Jets Differential Cross Sections

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Z+jets

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What Do We Measure?

In this analysis, we measured the Z+jets differential cross sections ofup 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/ dpT

The Z+jets cross section as a function of the jet η : dσ/ dη

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Dataset CMS data collected in 2012 for 19.8 ± 0.1 fb-1

Monte Carlo Simulations

JSON: Cert_190456-208686_8TeV_22Jan2013ReReco_Collisions12_JSON.txt

High Level Trigger → HLT_Mu17_Mu8_v* with L1_DoubleMu3p5 seed

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Basic Muon Selections

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PU Reweighting

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The First Muon Candidate

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The Second Muon Candidate

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Efficiency Scale Factor

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Z Reconstruction

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Z Reconstruction

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Basic Jet Selections

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Z+Jets Control Plots

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Measured Observables

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Measured Observables

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Measured Observables

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Unfolding

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Unfolding

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Unfolding

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Systematic Uncertainties

JES

JER

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Systematic Uncertainties

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Systematic Uncertainties

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Systematic Uncertainties

Summary

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Results

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Results

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Z+Jets Summary

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Conclusions

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Back Up

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Background Systematic Uncertainty for Z + Jet Angular

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PU Systematic Uncertainty for Z + Jet Angular

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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

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Breakdown Differential Cross Section

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Breakdown Differential Cross Section