Optimizing selection for WZ → lvbb̄ Searches

Jasmine Sinanan-SinghHarvard University

Columbia University Summer 2016 REU

July 2016

Abstract

This project examines the WZ→ lvbb̄ decay and optimizes the selectionregion for the Z→ bb̄ decay against other background processes and signals.Simulated MC signal samples and backgrounds are compared to 13.2 fb−1,center of mass energy

√s = 13 TeV data from 2015 and 2016 runs at the

LHC. We examine the efficiency and sensitivity of our selection for WZ →lvbb̄ searches.

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Contents

1 Introduction 41.1 CERN and LHC . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.2 ATLAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.3 Gauge Bosons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 WZ → lνqq Resonance Reconstruction 82.1 Resonance and Decay . . . . . . . . . . . . . . . . . . . . . . . . . . 82.2 W → lν Boson Reconstruction . . . . . . . . . . . . . . . . . . . . . 92.3 Jet Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . 102.4 Jet Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132.5 Truth Jets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3 Selection Optimization 143.1 Data and MC Samples . . . . . . . . . . . . . . . . . . . . . . . . . 143.2 Baseline Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143.3 Efficiency and Significance . . . . . . . . . . . . . . . . . . . . . . . 153.4 Z→ bb̄ Region Selection . . . . . . . . . . . . . . . . . . . . . . . . . 173.5 Control Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

4 Conclusions 19

5 Acknowledgements 19

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You have to take seriously the notion that understanding the universe is yourresponsibility, because the only understanding of the universe that will be usefulto you is your own understanding. - Terrence Mckenna

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1 Introduction

1.1 CERN and LHC

Figure 1: The Large Hadron Collider and locations of various detector sites [9].

The CERN (European Council for Nuclear Research) convention was signed in1953 by 12 founding countries and has since grown to 22 member countries withthe recent induction of Romania this year. Located on the Franco-Swiss borderin Geneva, Switzerland, CERN is on the forefront of particle physics. It’s mainoperation is building machines like the Large Hadron Collider (LHC) for the useof particle physicists all over the world. The LHC is largest and most powerfulparticle accelerator in the world; A 27km ring of superconducting magnets andother accelerating structures that circulates two high energy proton beams inopposite directions, reaching speeds close to the speed of light before collisionsoccur at four main particle detector sites: ALICE, ATLAS, CMS, LHCb shownin Figure 1[7].

Over a billion particle interactions take place in the ATLAS detector everysecond, but only one in a million collisions are flagged as potentially interestingand recorded for further study[7]. The LHC is now in its second run which beganApril 2015 after a two-year shutdown to upgrade the machine for higher energiesand luminosity. Over the next 10 years, CERN will also devote resources tobuilding the High-Luminosity Large Hadron Collider (HL-LHC). This project aimsto increase the performance of the LHC and increase luminosity by a factor of 10beyond the LHC’s original design[16].

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1.2 ATLAS

Figure 2: Cross-section of the ATLAS detector[3].

ATLAS (A Large Toroidal ApparatuS) consists of six concentrically wrappeddetecting systems around the site of the proton-proton (p-p) collision, recordingthe trajectory, momentum, and energy of particles. The Inner Detector, a 1.2mcylindrical tracking chamber consists of three subdetectors: the Pixel Detector,Semiconductor Tracker (SCT), and Transition Radiation Tracker (TRT), whichtogether measure the direction, momentum, and charge of electrically-chargedparticles[7]. The Inner Detector provides high resolution measurements very closeto the beam pipe, while the SCT provides measurements of particle trajectoriesthat help determine particle vertex, and the TRT also tracks trajectories andidentifies electrons. Muons, protons, and electrons all leave traces in the InnerDectector (Figure 3)[26]. The Solenoid Magnet surrounds the Inner Detectorand produces a magnetic field that curves charged particles, allowing them to betracked and identified by the curvature of their path[7].

The calorimeters are wrapped around the Solenoid Magnet and measure theenergy of particles by absorbing them. The electromagnetic (EM) calorimeterabsorbs particles that interact with matter electromagnetically i.e. electrons andphotons, while the hadron calorimeter absorbs particles that continue throughthe EM calorimeter. In Figure 3, photons are first visible in this subdetectorand both photons and electrons end their paths here, depositing their energyand allowing very precise measurements. The hadron calorimeter measures theinteractions of these particles with atomic nuclei and the protons and neutronsend their trajectories here, though their paths differ: we can see in Figure 3,

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since neutrons have no charge, they are only visible in the hadronic calorimeter.Together, these calorimeters stop most particles except for muons and neutrinos[7].

The Muon Spectrometer consists 4,000 individual muon chambers, and identi-fies and measures the momenta of muons. These chambers are formed around thebarrel and on the end-caps of the detector. The Magnet System bends particlesaround these various layers to help contain the tracks of the particles in the detec-tor more easily. Consisting of a single barrel magnet and two torodial magenets,one for each end-cap, this system provides bending power for the Muon Spectrom-eter. Because muons are visible for their entire path through the subdetectors,the ATLAS system has particularly good measurements for them[26].

The Trigger System helps reduce the high flow of data by selecting events withintriguing characteristics. It selects in real time approximately 100 events persecond out of the staggering 1000 million total. A two-tiered trigger system isused to filter the events; the first of which is implemented in the hardware andthe other by software[7].

Figure 3: Trajectories of various types of particles in the ATLAS detector[9].

1.3 Gauge Bosons

The Standard Model (SM) is currently the most well-validated theory in particlephysics, though it is not yet complete and cannot describe many things, such asgravity. Particles are divided into two types: fermions, which have half integerspin, and bosons, which have integer spin. The gauge, or vector, bosons are the

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Figure 4: Diagram of Standard Model[21].

force carriers of fundamental interactions. Photons mediate the electromagneticforce; gluons mediate the strong force; and the W± and Z0 mediate the weak force.Fermions are further broken down into quarks, which are charged under the strongforce, and leptons, which are not[26].

The W± and Z0 bosons mediate weak interactions between fermions of differentflavors i.e. all quarks and leptons. The W boson has either a positive or nega-tive electric charge of 1 (relative to the electron charge), and each is the others’antiparticle. The Z boson is electrically neutral and is its own antiparticle. Allthree particles have a spin of 1 and are extremely short-lived with a half-life ofapproximately 3× 10−25s. The W± and Z0 are heavy compared to other particleswith masses of 80.4 GeV and 91.2 GeV respectively (almost 100 times larger thanthe proton), and this heavy mass in turn limits the range of the weak force[22].

Figure 5: Decay possibilities for W and Z bosons[26].

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2 WZ → lνqq Resonance Reconstruction

2.1 Resonance and Decay

The cross-section of two particles interacting as a function of energy will sometimeshave a peak at a particular energy. This peak is called a resonance which could becaused by the creation of a particle, whose invariant mass is that of the resonance’senergy, or the peak may just be the resonance itself, not a particle[11]. We searchfor this invariant mass bump above the background from the signal to find newparticles (Figure 6, right). The invariant mass is the rest mass (m0) of the particleand is the same in any frame of reference, where it is calculated from energy, E,and momentum, p: m2

0 = E2 − ||p||2. The invariant mass of a particle can alsobe calculated using the energy and momentum from the decay products of thatparticle.

Figure 6: Left: Graph of Breit-Wigner Resonance - distribution of the mass energyof an unstable particle[12]; Right: Example of invariant mass bump.

The resonance is characterized by the mass at which the peak occurs and thespectrum width of the peak, Γ (Figure 6, left); this information also corresponds tothe probability of resonance decay. With resonances that correspond to particles,the energy uncertainty, ∆E, is reflected in the spectrum width and so the impliedlifetimes are roughly ~/Γ ≈lifetime[23]. The W± and Z0 bosons decay on the orderof ∼ 10−25s, far too quickly to be directly observed, and thus we must observe theirresonances through their final states. These vector bosons can decay hadronicallyor leptonically, shown in Figure 7 on the left. W bosons can decay to a lepton andneutrino or to a quark-antiquark pair, while Z bosons decay into a fermion and itsanti-particle. However, neither boson can decay into the higher-mass top quark,which is the most massive elementary particle and only decays through the weakforce into a W boson and quark[22].

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Figure 7: W and Z boson decay possibilities (left); WW/WZ decay to lνqq (right).

The heavy vector triplet, HVT, is a hypothetical heavy particle, which hasnot been observed yet, but is suggested to exist from theories going beyond theStandard Model. It is possible that it would decay to vector bosons. Thus, thisproject will study the one-lepton channel WZ→lvqq final state (Figure 7, on theright) where W decays into a lepton (either an electron or a muon) and neutrino,and Z decays hadronically into a jet or jets. We optimize the selection region forstudying the Z→ bb̄ decay against the background and signals: HVT WZ, HVTWW and Randall-Sundrum bulk graviton (RS G*), a hypothetical elementaryparticle that mediates the force of gravitation.

2.2 W → lν Boson Reconstruction

First we select a lepton, either an electron or muon. This signal lepton is selectedand identified using different working points. The ”LooseLH” and ”TightLH” cor-respond respectively to 96% and 88% identification efficiencies for signal electronsat ET = 100 GeV. The electrons are required to have |η| < 2.47 but excluding1.52 > |η| > 1.37 to ensure the calorimeter crack region is avoided and also musthave pT > 27 GeV because the trigger threshold is at 26 GeV. For the muons,”Loose” and ”Medium” working points are used from four identification qualitylevels (Very Loose, Loose, Medium, and Tight). The Loose working point includesmuons identified from a combination of inner detector (ID) and muon spectrome-ter (MS) (combined muons), ID and a few MS segments (segment-tagged), purelyfrom the MS (standalone muons) outside the ID coverage |η| > 2.5, or from thecalorimeters (calo-tagged) in the region |η| < 0.1 which lacks MS coverage.TheMedium working point excludes calo-tagged muons, imposes a stricter selectionon the segment-tagged, and requires pT > 25 GeV.

After selecting exactly one signal lepton, the lepton must pass an electrontrigger or for the muon channel, a MET trigger, in order to keep the event. Sincedata samples from 2 different years were used, the triggers vary for year andparticle type. Electrons must pass only one of the three triggers in Table 1.

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Triggers 2015 2016

Electrons

passHLT e24 lhmedium L1EM20VH

passHLT e60 lhmedium

passHLT e120 lhloose

passHLT e26 lhtight nod0 ivarloose

passHLT e60 lhmedium nod0

passHLT e140 lhloose nod0

Muons passHLT xe70 passHLT xe100 mht L1XE50

Table 1: Triggers for the electron and muon channels.

Since neutrinos do not interact with the detectors, the neutrino energy mustbe calculated from conservation of momentum inferring the Emiss

T as the pT ofthe neutrino. The Emiss

T is calculated using reconstructed objects such as taus,electrons, muons, and jets. Photons and hadronically decaying τ ’s are includedin the Emiss

T as jets, and charged tracks not associated to these hard objects arealso taken into account. We require the Emiss

T > 100 GeV to reduce quantumchromodynamic (QCD) background. We create the neutrino pT from the Emiss

T ,which is only in the transverse plane, but as the energy is not balanced parallel tothe beam pipe, we calculate the pz component in the z direction from the pT of theselected lepton, Emiss

T , and truth W boson mass. Then the reconstructed leptonLorentz vector and neutrino vector can be summed to reconstruct W Lorentzvector (we will also refer to this vector as lν for clarity). The W transverse masscan also be calculated now from:

m2T = 2pTE

missT (1− cos

(φl − φEmiss

T

)) (1)

Where pT is from the lepton, and φl and φEmissT

are the azimuthal angles of the

lepton and EmissT respectively.

2.3 Jet Reconstruction

Because there is less precise information from the detector concerning jets com-pared to what the detector collects about muons, electrons, and photons, the firststep of reconstructing the lvqq final state is to reconstruct the jets and then selectjets with proper attributes for our analysis, vetoing any event with particles orjets lacking certain qualities. For reference, the geometric distance between twojets is approximated from ∆R =

√∆η2 + ∆φ2 where φ is the azimuthal angle

and orthogonal to r in a cylindrical coordinate system (r,z,φ) where z is the in thebeam pipe direction. η = −ln(tan( θ

2)) where θ is the angle with respect to the

z-axis.Hadronic jets include both electromagnetic (EM) and hadronic energy and are

quite large, especially in the boosted case; The QCD processes inherent in hadronicjets limit the accuracy of the jet reconstruction[14]. The anti-kT algorithm is usedto reconstruct jets of different cone sizes (R). It combines pairs of constituentssequentially with these combinations depending on the jet pT and a minimumrelative angular distance from each other. The algorithm then clusters the highest

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Figure 8: Example of resolved vs boosted jets[25].

energy constituents first. We use this algorithm for three sizes of jets with R =1.0, 0.4, and 0.2. For particles with high transverse momentum (pT ), or boostedparticles, their jets sometimes merge together in the calorimeter and cannot beeffectively separated by the anti-kT algorithm for R = 0.4 (Figure 8). Anothertechnique is also used with this algorithm that can reconstruct boosted particleswith large-R jets (R = 1.0) which cover all hadronic activities from the decay afteran optimization that found the R = 1.0 cone size is sufficient to reconstruct theseboosted jets [15][5].

Along with this new algorithm, trimming is also applied to reduce the effectsof pile-up and other underlying event activities for the Large-R jets. The anti-kTalgorithm creates subjets of a certain radius (smaller than the cone radius of thejet) from the constituents of the large-R jet, and then any subjets failing a pTrequirement - pT i/pT < fcut - are removed, shown in Figure 9. This reduces QCDcontamination and controls pile-up activity[27].

Figure 9: Illustration of kT trimming algorithm [27].

The three types of jets used in this study were: AntiKt2PV0TrackJets, trackjets with R = 0.2; AntiKt4EMTopoJets, topo-cluster jets with R = 0.4; andAntiKt10LCTopoTrimmedPtFrac5SmallR20Jets, large-R jets with R = 1.0. trackjets are reconstructed from the charged particle tracks and have better angularresolution compared to the 0.4 topo-cluster jet reconstruction used for the othertypes of jets [18]. Using these track jets, we reconstruct small-R jets inside thelarge-R jet while the 0.4 small-R jets are used to reconstruct small-R jets outsidethe large-R jet. After a small-R jet passed preliminary cuts (see 2.4) and isidentified as b-jet with b-tagging, we calculate the ∆R between the small-R jetand the large-R jet to determine if it is outside or inside.

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As the Z decay we are interested in is to bb̄, b-tagging is used to determine whichsmall-R jets are from b-quarks. Usually quark jets are virtually indistinguishable,but b-tagging exploits the b-quark’s long lifetime, high mass and multiplicity toidentify them [4]. The working point efficiency used for our b-tagging is 85%. Wemust then try to find a large-R jet that originated from a Z boson. The highestpT large-R jet is selected as the V (vector boson) candidate jet, which could befrom either a W or Z boson, and the substructure of the large-R jet is used tohelp determine the type of the jet. The substructure variable (D2) examines thestructure of the jet by comparing the pT and angular distance between pairs andtriplets of the jet’s constituents and is pT dependent (2).

ECF1 =∑i

pTi

ECF2 =∑ij

pTipTj∆Rij

ECF3 =∑ijk

pTipTjpTk∆Rij∆Rjk∆Rki

Dβ=12 = ECF3

(ECF1

ECF2

)3

(2)

Figure 10: Jet substructure inside cone of fixed radius[19].

This method however has only 50% efficiency because the working point of thesubstructure tagger is limited by the mass cut’s efficiency. Thus, we check bothpassing and failing the substructure tagger of the large-R jet to determine whichcut improves the selection region’s significance against the background more. Toidentify the V candidate as either W or Z, jet mass, substructure, and pT areconsidered with the highest pT large-R jet passing one of the boson mass cutsbeing the ideal candidate for further study and selection.

Furthermore, during event selection we apply overlap removal to ensure thequality of the events. For example, since an electron creates activity in the

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calorimeter, it can be easily misidentified as a jet and then analyzed incorrectly;if the lepton we have reconstructed from the W decay is an electron, then thatelectron should not be inside the large-R jet.

2.4 Jet Selection

Table 2 displays the cut selection used to preliminarily select jets. The |η| re-quirement for the track jets is to ensure the jets are within the coverage of theInner Detector. The Jet Vertex Tagger (JVT) is a multivariate combination of twotrack-based variables and hard-scatter vertex information that helps suppress pile-up and spurious jets due to local pile-up activity to improve jet selection. JVT,however, is modeled only for jets passing the following requirements: R = 0.4,20 < pT < 50GeV, |η| < 2.4 [1].

R = 1.0 Large R-JetspT > 200 GeVM > 50 GeV|η| < 2.0

R = 0.2 Track JetspT > 20 GeV|η| < 2.5

R = 0.4 JetspT > 20 GeV|η| > 2.4 or pT > 60 GeV or JVT> 0.59

Table 2: Jet selection cuts.

2.5 Truth Jets

Truth particles from the MC were used to reconstruct truth jets i.e. jets built fromall stable MC particles from the hard interaction only, including the underlyingevent activity[20]. These truth jets were then compared to the reconstructed jetsto check the reconstruction efficiency of these large-R and small-R jets. For large-R jets the highest pT truth jet (AntiKt10TruthWZTrimmedPtFrac5SmallR20Jets)is selected and the ∆R between it and the V candidate jet is plotted in Figure 11on the right, and on the left is a comparison of the large-R jet masses which bothshow high agreement between the truth and reconstructed jets.

The small-R (R = 0.4) truth jets (AntiKt4TruthWZJets) were compared tothe reconstructed small-R 0.4 jets based on the smallest ∆R between the jets. InFigure 12 the mass (left) and pT (right) of matched truth and reconstructed jetsare shown. Since we used the leading 0.2 track b-jet inside the large-R jet, wecheck the 0.4 jets to see the fraction of momentum that goes to these small-Rjets. The topo-cluster algorithm for R = 0.4 as mentioned before leads to moremis-reconstruction. There is also an optimization that the 0.2 track jets performbetter than the 0.4 jets in this case.

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Figure 11: Matched Truth jets and reconstructed large-R jets.

3 Selection Optimization

3.1 Data and MC Samples

This analysis considers data sampled from both 2015 and 2016 with center-of-massenergy at 13 TeV and integrated luminosity of 13.2 fb−1. This is the second yearthe LHC is running at a collision energy of 13 TeV. Recently ATLAS and CMShave passed the threshold 10 fb−1 for 2016, and the goal is to reach 40 fb−1 by theend of 2016 [7]. Luminosity is proportional to the number of collision events thatoccur in a given amount of time and indicates the performance of the acceleratoras more data increases the likelihood of observing rare processes [16].

Monte Carlo (MC) event generators were used to simulate jets of the p-pcollision and include background samples of W+ jets, Z+ jets, Standard ModelDibosons (SMDB), and tt̄. The V+ jets from Sherpa v2.2[10]; SMDB from Sherpaas well[10]; tt̄ from Powheg-Pythia[24]. No multi-jets were considered as this studyis concerned with the one lepton channel WZ decay (lvqq), and the multi-jetbackground is suppressed due to the requirement for charged leptons and Emiss

T .Three signals are considered: HVT WZ, HVT WW, and RS G* with signal samplesfrom MadGraph+Pythia8 with a mass width ∼6%[24] [6] [17]. The MC samplesand signals have been scaled by (1).

Scale Factor =Cross Section x Filter Efficiency x Luminosity

Initial Events(3)

3.2 Baseline Selection

The baseline selection for studying the lvqq state is as follows:Where lν is the Lorentz vector formed from the lepton (electron or muon)

passing the cuts indicated in Table 3 in (1), (2). (1) ensures that only 1 leptonis selected to avoid other possible final states with more leptons. (3) is to help

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Figure 12: Matched Truth jets and reconstructed small-R (R = 0.4) jets.

# Baseline Selection

1 Exactly one signal lepton and one loose lepton (Electronor Muon)

2 EmissT > 100 GeV

3 pT ( lν )> 200 GeV4 At least one large-R jet6 pT ( leading J)> 200 GeV7 pT ( lν )/ MV V > 0.48 pT ( leading J )/ MV V > 0.49 No b-jets outside the large-R jet (b-veto)

Table 3: Baseline Selection Cuts.

reduce background from other possible decays involving a lepton and neutrino.(4),(5), and (6) keep the highest pT large-R jet which is V candidate jet. The VVis the Lorentz vector formed from the lν and the V candidate. (7) and (8) checkfor balance between the bosons’ pT , which is expected in the WW/WZ decay. Thefinal discriminant is the MV V . (9) is used to suppress the tt̄ background which, asshown in Figure 13, most often decays into a W boson and b-quark [13].

These cuts are optimized in this sequence and ordered in the way in whichthey are implemented. Additional selections are now used to further study thesensitivity of the signal selection against the background activities.

3.3 Efficiency and Significance

Identifying b-jets inside the large-R jet and passing the Z mass window are defi-nite cuts in the Zbb̄ selection, but we must determine whether pass or failing thesubstructure trigger improves the signal’s efficiency. The efficiency of the selection

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Figure 13: tt̄ background processes [8].

is determined by

Efficiency =# of events passing cuts

# events before cuts(4)

Cuts here refer to those after baseline selection. Theoretically, since we are onlypassing events with b-tags in the large-R jet, we can calculate the expected effi-ciency ratio from Figure 14. Our b-tagging working point efficiency is 85%, andthe possibility of misidentifying a c-quark for a b-quark is: c branching-ratio ×b-tagging inefficiency ≈ 14.5%. Thus we expect the efficiency to be ∼21% usingthe predicted branching ratios in Figure 14.

Figure 14: Z boson decay relative branching ratios[2].

The plot in Figure 15 shows the efficiency before the substructure tagger isapplied, and Figure 16 shows the efficiency after the substructure tagger fails.Figure 15 in the mid-mass region (1-3 TeV) corresponds well to the theoreticalprediction expected of these cuts. However, in the low mass region, the pT is nothigh enough to guarantee that a large-R jet will exist. In the high mass region,the high pT means the b-jets are very close together and easily misidentified, plusthe jet mass resolution is worse in this region because the mass window decreasesthe efficiency.

The Figure 15 however shows that the WW signal leaks into the lvbb region.We expect the efficiency for the WW signal to be much less than the WZ sincesome jets from the W boson will also be misidentified as b-jets. Since hadronicdecay for the W boson is ∼ 2

3we expect the possibility for mis-identification to

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Figure 15: Efficiency of signals against background before substructure tagger.

be only ∼5%[13]. Failing the substructure tagger though controls some of thisleakage and maintains efficiency for the WZ signal.

Figure 16: Efficiency of signals against background after failing substructure tag-ger.

3.4 Z→ bb̄ Region Selection

For the Zbb̄ signal region (Z→ bb̄ SR), the Z+ jet and SM Diboson backgroundsare very small and thus are taken directly from the MC simulations while the W+jets and tt̄ backgrounds are data driven. The Zbb̄ selection, shown in Table 4, isthe baseline selection with the addition of the following finalized cuts, includingthe substructure optimization.

In Table 4, (1) b-tagging cut is applied on 0.2 track jets inside the highest pTlarge-R jet. To improve the efficiency of this cut, at least one b-jet is required

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# Zbb̄ Selection

1 At least 1 b-jet inside the highest pT large-R jet(R = 1.0)

2 Fail substructure tagger3 Pass the Z mass window: ∼60-120 GeV

Table 4: Zbb̄ SR Cuts.

instead of exactly two as the decay products suggest. In boosted jets, the b-jetsare closer together and can often be mistaken for only one jet. Thus, one b-tagis sufficient to keep the event. Since the substructure variable has a 50% workingpoint efficiency, we check both cases and find that failing this tagger (2) providesthe optimal selection. The Zbb̄ SR is shown in Figures 17-20.

(a) Zbb̄ SR VV Mass (b) Zbb̄ SR lν transverse mass

Figure 17: Zbb̄ SR plots

3.5 Control Regions

Finally, we look at two control regions to examine the Z→ bb̄ region selection bychecking the fit of the selection region to the control regions. The W+ jet controlregion (WCR) is the same selection as the Zbb̄, but it inverts both the W and Zmass cut to avoid the inverted D2 (passing the substructure tagger) leakage inthe control regions (Figures 25 - 28). The tt̄ control region (TCR) is the same asZbb̄, but it reverses the b-veto, requiring at least 1 b-jet outside the Large-R fet(Figures 21 - 24). For both TCR and WCR, the normalizations and shapes of allthe plots agree well with the data, and the WCR and Zbb region agree well.

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4 Conclusions

After the cut based analysis on WZ→ lνqq for 13.2 fb−1, 13 TeV data, we concludethat the Zbb search is feasible despite the low efficiency. However, the efficiencydrop in the very high mass region could be improved using a mass constraint.The final cuts were passing the Z mass window, requiring at least one 0.2 track b-jets inside the large-R jet, which increases the efficiency with respect to requiringexactly two 0.2 track b-jets, and passing D2 (the substructure tagger) is vetoed toavoid WW signal leakage. The control regions both show the normalizations andshapes of the plots are good and agree to the data with the differences covered bythe statistical uncertainties. For a 2 TeV WZ signal we expect 1.68 ± 0.03 signalevents, and for the background we expect 25.0 ± 0.5 events.

5 Acknowledgements

I especially want to thank Dr. Kalliopi Iordanidou for all of her immense support,brilliance, and lunches. I am grateful to the Nevis REU Program, National ScienceFoundation, and Professor Parsons for granting me this opportunity to live andwork abroad on the frontier of particle physics at CERN. And many thanks to theColumbia ATLAS group for being such a welcoming community.

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[23] P. Siegel. Lecture 10: Resonances, Jul 2016.

[24] T. Sjostrand, S. Mrenna, and P. Skands. Pythia 6.4 physics and manual.Journal of High Energy Physics, 2006(05):026, 2006.

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[26] B. C. Smith. Measurement of the transverse momentum spectrum of Wbosons produced at

√s = 7 TeV using the ATLAS detector. May 2011.

[27] E. Thompson. Jet grooming in atlas. 2012.

21

(a) Zbb̄ SR V candidate Mass (b) Zbb̄ SR V candidate pT

(c) Zbb̄ SR V candidate η (d) Zbb̄ SR V candidate φ

Figure 18: Zbb̄ SR V candidate plots.

22

(a) Zbb̄ SR lepton pT (b) Zbb̄ SR lepton η

(c) Zbb̄ SR lepton φ (d) Zbb̄ SR Number of large-R jets

Figure 19: Zbb̄ SR lepton plots and number of large-R jets.

23

(a) Zbb̄ SR EmissT (b) Zbb̄ SR D2

Figure 20: Zbb̄ SR plots

(a) TCR VV Mass (b) TCR lν transverse mass

Figure 21: TCR plots

24

(a) TCR V candidate Mass (b) TCR V candidate pT

(c) TCR V candidate η (d) TCR V candidate φ

Figure 22: TCR V candidate plots.

25

(a) TCR lepton pT (b) TCR lepton η

(c) TCR lepton φ (d) TCR Number of large-R jets

Figure 23: TCR lepton plots and number of large-R jets.

26

(a) TCR EmissT (b) TCR D2

Figure 24: TCR plots

(a) WCR VV Mass (b) WCR lν transverse mass

Figure 25: WCR plots

27

(a) WCR V candidate Mass (b) WCR V candidate pT

(c) WCR V candidate η (d) WCR V candidate φ

Figure 26: WCR V candidate plots.

28

(a) WCR lepton pT (b) WCR lepton η

(c) WCR lepton φ (d) WCR Number of large-R jets

Figure 27: WCR lepton plots and number of large-R jets.

29

(a) WCR EmissT (b) WCR D2

Figure 28: WCR plots

30