Optimizing selection for WZ lvb b Searches

Optimizing selection for WZ lvb b Searches Jasmine Sinanan-Singh Harvard University Columbia University Summer 2016 REU July 2016 Abstract This project examines the WZ lvb b decay and optimizes the selection region for the Z b b 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 lvb b searches. 1

Contents 1 Introduction 4 1.1 CERN and LHC............................ 4 1.2 ATLAS................................. 5 1.3 Gauge Bosons.............................. 6 2 WZ lνqq Resonance Reconstruction 8 2.1 Resonance and Decay.......................... 8 2.2 W lν Boson Reconstruction..................... 9 2.3 Jet Reconstruction........................... 10 2.4 Jet Selection............................... 13 2.5 Truth Jets................................ 13 3 Selection Optimization 14 3.1 Data and MC Samples......................... 14 3.2 Baseline Selection............................ 14 3.3 Efficiency and Significance....................... 15 3.4 Z b b Region Selection......................... 17 3.5 Control Regions............................. 18 4 Conclusions 19 5 Acknowledgements 19 2

You have to take seriously the notion that understanding the universe is your responsibility, because the only understanding of the universe that will be useful to you is your own understanding. - Terrence Mckenna 3

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 in 1953 by 12 founding countries and has since grown to 22 member countries with the recent induction of Romania this year. Located on the Franco-Swiss border in Geneva, Switzerland, CERN is on the forefront of particle physics. It s main operation is building machines like the Large Hadron Collider (LHC) for the use of particle physicists all over the world. The LHC is largest and most powerful particle accelerator in the world; A 27km ring of superconducting magnets and other accelerating structures that circulates two high energy proton beams in opposite directions, reaching speeds close to the speed of light before collisions occur at four main particle detector sites: ALICE, ATLAS, CMS, LHCb shown in Figure 1[7]. Over a billion particle interactions take place in the ATLAS detector every second, but only one in a million collisions are flagged as potentially interesting and recorded for further study[7]. The LHC is now in its second run which began April 2015 after a two-year shutdown to upgrade the machine for higher energies and luminosity. Over the next 10 years, CERN will also devote resources to building the High-Luminosity Large Hadron Collider (HL-LHC). This project aims to increase the performance of the LHC and increase luminosity by a factor of 10 beyond the LHC s original design[16]. 4

1.2 ATLAS Figure 2: Cross-section of the ATLAS detector[3]. ATLAS (A Large Toroidal ApparatuS) consists of six concentrically wrapped detecting systems around the site of the proton-proton (p-p) collision, recording the trajectory, momentum, and energy of particles. The Inner Detector, a 1.2m cylindrical tracking chamber consists of three subdetectors: the Pixel Detector, Semiconductor Tracker (SCT), and Transition Radiation Tracker (TRT), which together measure the direction, momentum, and charge of electrically-charged particles[7]. The Inner Detector provides high resolution measurements very close to the beam pipe, while the SCT provides measurements of particle trajectories that help determine particle vertex, and the TRT also tracks trajectories and identifies electrons. Muons, protons, and electrons all leave traces in the Inner Dectector (Figure 3)[26]. The Solenoid Magnet surrounds the Inner Detector and produces a magnetic field that curves charged particles, allowing them to be tracked and identified by the curvature of their path[7]. The calorimeters are wrapped around the Solenoid Magnet and measure the energy of particles by absorbing them. The electromagnetic (EM) calorimeter absorbs particles that interact with matter electromagnetically i.e. electrons and photons, while the hadron calorimeter absorbs particles that continue through the EM calorimeter. In Figure 3, photons are first visible in this subdetector and both photons and electrons end their paths here, depositing their energy and allowing very precise measurements. The hadron calorimeter measures the interactions of these particles with atomic nuclei and the protons and neutrons end their trajectories here, though their paths differ: we can see in Figure 3, 5

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 identifies and measures the momenta of muons. These chambers are formed around the barrel and on the end-caps of the detector. The Magnet System bends particles around these various layers to help contain the tracks of the particles in the detector 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 Spectrometer. 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 with intriguing characteristics. It selects in real time approximately 100 events per second out of the staggering 1000 million total. A two-tiered trigger system is used to filter the events; the first of which is implemented in the hardware and the 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 particle physics, though it is not yet complete and cannot describe many things, such as gravity. Particles are divided into two types: fermions, which have half integer spin, and bosons, which have integer spin. The gauge, or vector, bosons are the 6

Figure 4: Diagram of Standard Model[21]. force carriers of fundamental interactions. Photons mediate the electromagnetic force; gluons mediate the strong force; and the W ± and Z 0 mediate the weak force. Fermions are further broken down into quarks, which are charged under the strong force, and leptons, which are not[26]. The W ± and Z 0 bosons mediate weak interactions between fermions of different flavors i.e. all quarks and leptons. The W boson has either a positive or negative 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. All three particles have a spin of 1 and are extremely short-lived with a half-life of approximately 3 10 25 s. The W ± and Z 0 are heavy compared to other particles with masses of 80.4 GeV and 91.2 GeV respectively (almost 100 times larger than the 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]. 7

2 WZ lνqq Resonance Reconstruction 2.1 Resonance and Decay The cross-section of two particles interacting as a function of energy will sometimes have a peak at a particular energy. This peak is called a resonance which could be caused by the creation of a particle, whose invariant mass is that of the resonance s energy, or the peak may just be the resonance itself, not a particle[11]. We search for this invariant mass bump above the background from the signal to find new particles (Figure 6, right). The invariant mass is the rest mass (m 0 ) of the particle and is the same in any frame of reference, where it is calculated from energy, E, and momentum, p: m 2 0 = E 2 p 2. The invariant mass of a particle can also be calculated using the energy and momentum from the decay products of that particle. Figure 6: Left: Graph of Breit-Wigner Resonance - distribution of the mass energy of an unstable particle[12]; Right: Example of invariant mass bump. The resonance is characterized by the mass at which the peak occurs and the spectrum width of the peak, Γ (Figure 6, left); this information also corresponds to the probability of resonance decay. With resonances that correspond to particles, the energy uncertainty, E, is reflected in the spectrum width and so the implied lifetimes are roughly /Γ lifetime[23]. The W ± and Z 0 bosons decay on the order of 10 25 s, far too quickly to be directly observed, and thus we must observe their resonances through their final states. These vector bosons can decay hadronically or leptonically, shown in Figure 7 on the left. W bosons can decay to a lepton and neutrino or to a quark-antiquark pair, while Z bosons decay into a fermion and its anti-particle. However, neither boson can decay into the higher-mass top quark, which is the most massive elementary particle and only decays through the weak force into a W boson and quark[22]. 8

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 has not been observed yet, but is suggested to exist from theories going beyond the Standard Model. It is possible that it would decay to vector bosons. Thus, this project will study the one-lepton channel WZ lvqq final state (Figure 7, on the right) 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 for studying the Z b b decay against the background and signals: HVT WZ, HVT WW and Randall-Sundrum bulk graviton (RS G*), a hypothetical elementary particle 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 selected and identified using different working points. The LooseLH and TightLH correspond respectively to 96% and 88% identification efficiencies for signal electrons at E T = 100 GeV. The electrons are required to have η < 2.47 but excluding 1.52 > η > 1.37 to ensure the calorimeter crack region is avoided and also must have p T > 27 GeV because the trigger threshold is at 26 GeV. For the muons, Loose and Medium working points are used from four identification quality levels (Very Loose, Loose, Medium, and Tight). The Loose working point includes muons identified from a combination of inner detector (ID) and muon spectrometer (MS) (combined muons), ID and a few MS segments (segment-tagged), purely from the MS (standalone muons) outside the ID coverage η > 2.5, or from the calorimeters (calo-tagged) in the region η < 0.1 which lacks MS coverage.the Medium working point excludes calo-tagged muons, imposes a stricter selection on the segment-tagged, and requires p T > 25 GeV. After selecting exactly one signal lepton, the lepton must pass an electron trigger or for the muon channel, a MET trigger, in order to keep the event. Since data samples from 2 different years were used, the triggers vary for year and particle type. Electrons must pass only one of the three triggers in Table 1. 9

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 must be calculated from conservation of momentum inferring the ET miss as the p T of the neutrino. The ET miss is calculated using reconstructed objects such as taus, electrons, muons, and jets. Photons and hadronically decaying τ s are included in the ET miss as jets, and charged tracks not associated to these hard objects are also taken into account. We require the ET miss > 100 GeV to reduce quantum chromodynamic (QCD) background. We create the neutrino p T from the ET miss, which is only in the transverse plane, but as the energy is not balanced parallel to the beam pipe, we calculate the p z component in the z direction from the p T of the selected lepton, ET miss, and truth W boson mass. Then the reconstructed lepton Lorentz vector and neutrino vector can be summed to reconstruct W Lorentz vector (we will also refer to this vector as lν for clarity). The W transverse mass can also be calculated now from: ( ) m 2 T = 2p T ET miss (1 cos φ l φ E miss ) (1) T Where p T is from the lepton, and φ l and φ E miss T lepton and ET miss respectively. are the azimuthal angles of the 2.3 Jet Reconstruction Because there is less precise information from the detector concerning jets compared to what the detector collects about muons, electrons, and photons, the first step of reconstructing the lvqq final state is to reconstruct the jets and then select jets with proper attributes for our analysis, vetoing any event with particles or jets lacking certain qualities. For reference, the geometric distance between two jets is approximated from R = η 2 + φ 2 where φ is the azimuthal angle and orthogonal to r in a cylindrical coordinate system (r,z,φ) where z is the in the beam pipe direction. η = ln(tan( θ )) where θ is the angle with respect to the 2 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 hadronic jets limit the accuracy of the jet reconstruction[14]. The anti-k T algorithm is used to reconstruct jets of different cone sizes (R). It combines pairs of constituents sequentially with these combinations depending on the jet p T and a minimum relative angular distance from each other. The algorithm then clusters the highest 10

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 (p T ), or boosted particles, their jets sometimes merge together in the calorimeter and cannot be effectively separated by the anti-k T algorithm for R = 0.4 (Figure 8). Another technique is also used with this algorithm that can reconstruct boosted particles with large-r jets (R = 1.0) which cover all hadronic activities from the decay after an optimization that found the R = 1.0 cone size is sufficient to reconstruct these boosted jets [15][5]. Along with this new algorithm, trimming is also applied to reduce the effects of pile-up and other underlying event activities for the Large-R jets. The anti-k T algorithm creates subjets of a certain radius (smaller than the cone radius of the jet) from the constituents of the large-r jet, and then any subjets failing a p T requirement - p T i/p T < f cut - are removed, shown in Figure 9. This reduces QCD contamination and controls pile-up activity[27]. Figure 9: Illustration of k T trimming algorithm [27]. The three types of jets used in this study were: AntiKt2PV0TrackJets, track jets with R = 0.2; AntiKt4EMTopoJets, topo-cluster jets with R = 0.4; and AntiKt10LCTopoTrimmedPtFrac5SmallR20Jets, large-r jets with R = 1.0. track jets are reconstructed from the charged particle tracks and have better angular resolution compared to the 0.4 topo-cluster jet reconstruction used for the other types of jets [18]. Using these track jets, we reconstruct small-r jets inside the large-r jet while the 0.4 small-r jets are used to reconstruct small-r jets outside the large-r jet. After a small-r jet passed preliminary cuts (see 2.4) and is identified as b-jet with b-tagging, we calculate the R between the small-r jet and the large-r jet to determine if it is outside or inside. 11

As the Z decay we are interested in is to b b, b-tagging is used to determine which small-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 to identify them [4]. The working point efficiency used for our b-tagging is 85%. We must then try to find a large-r jet that originated from a Z boson. The highest p T large-r jet is selected as the V (vector boson) candidate jet, which could be from either a W or Z boson, and the substructure of the large-r jet is used to help determine the type of the jet. The substructure variable (D 2 ) examines the structure of the jet by comparing the p T and angular distance between pairs and triplets of the jet s constituents and is p T dependent (2). E CF 1 = i p Ti E CF 2 = ij E CF 3 = ijk p Ti p Tj R ij p Ti p Tj p Tk R ij R jk R ki (2) ( ) 3 D β=1 ECF 1 2 = E CF 3 E CF 2 Figure 10: Jet substructure inside cone of fixed radius[19]. This method however has only 50% efficiency because the working point of the substructure tagger is limited by the mass cut s efficiency. Thus, we check both passing and failing the substructure tagger of the large-r jet to determine which cut improves the selection region s significance against the background more. To identify the V candidate as either W or Z, jet mass, substructure, and p T are considered with the highest p T large-r jet passing one of the boson mass cuts being the ideal candidate for further study and selection. Furthermore, during event selection we apply overlap removal to ensure the quality of the events. For example, since an electron creates activity in the 12

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 that electron 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 requirement for the track jets is to ensure the jets are within the coverage of the Inner Detector. The Jet Vertex Tagger (JVT) is a multivariate combination of two track-based variables and hard-scatter vertex information that helps suppress pileup 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 < p T < 50GeV, η < 2.4 [1]. R = 1.0 Large R-Jets R = 0.2 Track Jets R = 0.4 Jets p T > 200 GeV M > 50 GeV η < 2.0 p T > 20 GeV η < 2.5 p T > 20 GeV η > 2.4 or p T > 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 from all stable MC particles from the hard interaction only, including the underlying event activity[20]. These truth jets were then compared to the reconstructed jets to check the reconstruction efficiency of these large-r and small-r jets. For large- R jets the highest p T truth jet (AntiKt10TruthWZTrimmedPtFrac5SmallR20Jets) is selected and the R between it and the V candidate jet is plotted in Figure 11 on the right, and on the left is a comparison of the large-r jet masses which both show high agreement between the truth and reconstructed jets. The small-r (R = 0.4) truth jets (AntiKt4TruthWZJets) were compared to the reconstructed small-r 0.4 jets based on the smallest R between the jets. In Figure 12 the mass (left) and p T (right) of matched truth and reconstructed jets are shown. Since we used the leading 0.2 track b-jet inside the large-r jet, we check the 0.4 jets to see the fraction of momentum that goes to these small-r jets. The topo-cluster algorithm for R = 0.4 as mentioned before leads to more mis-reconstruction. There is also an optimization that the 0.2 track jets perform better than the 0.4 jets in this case. 13

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-mass energy at 13 TeV and integrated luminosity of 13.2 fb 1. This is the second year the LHC is running at a collision energy of 13 TeV. Recently ATLAS and CMS have passed the threshold 10 fb 1 for 2016, and the goal is to reach 40 fb 1 by the end of 2016 [7]. Luminosity is proportional to the number of collision events that occur in a given amount of time and indicates the performance of the accelerator as more data increases the likelihood of observing rare processes [16]. Monte Carlo (MC) event generators were used to simulate jets of the p-p collision and include background samples of W+ jets, Z+ jets, Standard Model Dibosons (SMDB), and t t. The V+ jets from Sherpa v2.2[10]; SMDB from Sherpa as well[10]; t t from Powheg-Pythia[24]. No multi-jets were considered as this study is concerned with the one lepton channel WZ decay (lvqq), and the multi-jet background is suppressed due to the requirement for charged leptons and ET miss. Three signals are considered: HVT WZ, HVT WW, and RS G* with signal samples from MadGraph+Pythia8 with a mass width 6%[24] [6] [17]. The MC samples and 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 lepton is selected to avoid other possible final states with more leptons. (3) is to help 14

Figure 12: Matched Truth jets and reconstructed small-r (R = 0.4) jets. # Baseline Selection 1 Exactly one signal lepton and one loose lepton (Electron or Muon) 2 ET miss > 100 GeV 3 p T ( lν )> 200 GeV 4 At least one large-r jet 6 p T ( leading J)> 200 GeV 7 p T ( lν )/ M V V > 0.4 8 p T ( leading J )/ M V V > 0.4 9 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 p T large-r jet which is V candidate jet. The VV is the Lorentz vector formed from the lν and the V candidate. (7) and (8) check for balance between the bosons p T, which is expected in the WW/WZ decay. The final discriminant is the M V V. (9) is used to suppress the t t background which, as shown 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 which they are implemented. Additional selections are now used to further study the sensitivity 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 definite cuts in the Zb b selection, but we must determine whether pass or failing the substructure trigger improves the signal s efficiency. The efficiency of the selection 15

Figure 13: t t background processes [8]. is determined by Efficiency = # of events passing cuts # events before cuts Cuts here refer to those after baseline selection. Theoretically, since we are only passing events with b-tags in the large-r jet, we can calculate the expected efficiency ratio from Figure 14. Our b-tagging working point efficiency is 85%, and the 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% using the predicted branching ratios in Figure 14. (4) Figure 14: Z boson decay relative branching ratios[2]. The plot in Figure 15 shows the efficiency before the substructure tagger is applied, 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 theoretical prediction expected of these cuts. However, in the low mass region, the p T is not high enough to guarantee that a large-r jet will exist. In the high mass region, the high p T means the b-jets are very close together and easily misidentified, plus the jet mass resolution is worse in this region because the mass window decreases the 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 since some jets from the W boson will also be misidentified as b-jets. Since hadronic decay for the W boson is 2 we expect the possibility for mis-identification to 3 16

Figure 15: Efficiency of signals against background before substructure tagger. be only 5%[13]. Failing the substructure tagger though controls some of this leakage and maintains efficiency for the WZ signal. Figure 16: Efficiency of signals against background after failing substructure tagger. 3.4 Z b b Region Selection For the Zb b signal region (Z b b SR), the Z+ jet and SM Diboson backgrounds are very small and thus are taken directly from the MC simulations while the W+ jets and t t backgrounds are data driven. The Zb b selection, shown in Table 4, is the baseline selection with the addition of the following finalized cuts, including the substructure optimization. In Table 4, (1) b-tagging cut is applied on 0.2 track jets inside the highest p T large-r jet. To improve the efficiency of this cut, at least one b-jet is required 17

# Zb b Selection 1 At least 1 b-jet inside the highest p T large-r jet (R = 1.0) 2 Fail substructure tagger 3 Pass the Z mass window: 60-120 GeV Table 4: Zb b SR Cuts. instead of exactly two as the decay products suggest. In boosted jets, the b-jets are closer together and can often be mistaken for only one jet. Thus, one b-tag is sufficient to keep the event. Since the substructure variable has a 50% working point efficiency, we check both cases and find that failing this tagger (2) provides the optimal selection. The Zb b SR is shown in Figures 17-20. (a) Zb b SR VV Mass (b) Zb b SR lν transverse mass Figure 17: Zb b SR plots 3.5 Control Regions Finally, we look at two control regions to examine the Z b b region selection by checking the fit of the selection region to the control regions. The W+ jet control region (WCR) is the same selection as the Zb b, but it inverts both the W and Z mass cut to avoid the inverted D2 (passing the substructure tagger) leakage in the control regions (Figures 25-28). The t t control region (TCR) is the same as Zb b, 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 all the plots agree well with the data, and the WCR and Zbb region agree well. 18

4 Conclusions After the cut based analysis on WZ lνqq for 13.2 fb 1, 13 TeV data, we conclude that the Zbb search is feasible despite the low efficiency. However, the efficiency drop 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 requiring exactly two 0.2 track b-jets, and passing D2 (the substructure tagger) is vetoed to avoid WW signal leakage. The control regions both show the normalizations and shapes of the plots are good and agree to the data with the differences covered by the statistical uncertainties. For a 2 TeV WZ signal we expect 1.68 ± 0.03 signal events, 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 Science Foundation, and Professor Parsons for granting me this opportunity to live and work abroad on the frontier of particle physics at CERN. And many thanks to the Columbia ATLAS group for being such a welcoming community. 19

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(a) Zb b SR V candidate Mass (b) Zb b SR V candidate p T (c) Zb b SR V candidate η (d) Zb b SR V candidate φ Figure 18: Zb b SR V candidate plots. 22

(a) Zb b SR lepton p T (b) Zb b SR lepton η (c) Zb b SR lepton φ (d) Zb b SR Number of large-r jets Figure 19: Zb b SR lepton plots and number of large-r jets. 23

(a) Zb b SR E miss T (b) Zb b SR D2 Figure 20: Zb b 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 p T (c) TCR V candidate η (d) TCR V candidate φ Figure 22: TCR V candidate plots. 25

(a) TCR lepton p T (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 E miss T (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 p T (c) WCR V candidate η (d) WCR V candidate φ Figure 26: WCR V candidate plots. 28

(a) WCR lepton p T (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 E miss T (b) WCR D2 Figure 28: WCR plots 30