Columbia University REU 2017 Nevis Labs August 2017

Transcription

1 Search for Xh qqbb resonances with the ATLAS detector Jackson Schall Supervisor: Kalliopi Iordanidou Columbia University REU 2017 Nevis Labs August 2017 Abstract This study focuses on the search for a new charged resonance (W Xh) decaying into the Standard Model Higgs boson (h), and a new particle (X), with a fully hadronic decay to qqbb (where q is any quark). Data collected from 2015 and 2016 using p-p collisions at an integrated luminosity of 36.1 fb -1 and s = 13 TeV center of mass energy. To search for W resonance, a combination of user defined fits is utilized, taking into account the background and expected Xh resonance production. 1

2 "Through our eyes, the universe is perceiving itself. Through our ears, the universe is listening to its harmonies. We are the witnesses through which the universe becomes conscious of its glory, of its magnificence." -Alan W. Watts 2

3 Contents 1 Introduction CERN and the Large Hadron Collider (LHC) The ATLAS Detector The Standard Model Higgs and X boson resonance and selection Resonance and Decay Jet Reconstruction Event Selection Search for Xh resonance Introduction X Mass Windows Fitting W Mass Plots With User Defined Fit Varying X Mass Window Implementation Parameters Conclusion 23 6 Acknowledgements 23 References 24 3

4 1 Introduction 1.1 CERN and the Large Hadron Collider (LHC) Figure 1: The Large Hadron Collider and the ATLAS, ALICE, CMS, and LHCb experiments [1] Established in 1954 CERN, or the European Organization for Nuclear Research, is home to largest and highest energy particle accelerator and includes 22 member states. CERN also refers to the laboratory in the northwestern suburb of Geneva, Switzerland. The objective of this organization is to provide accelerators and facilities to carry out high energy physics research and further push the boundaries of fundamental science through elementary physics research. The name LHC, or Large Hadron Collider, comes from the idea that it is the largest single machine ever built, along with the title as the the most complex experimental facility in the world. The LHC and CERN straddle the Swiss-French border, this has become the meeting point of over 10,000 scientists and engineers from more than 100 countries, most researchers are affiliated to universities and laboratories working in collaboration. The LHC is a 27 kilometer ring, consisting of 1232 dipole magnets that accelerate the two proton beams traveling in opposite directions. Since the proton is about 2 x meters in diameter [2], the precision needed to "squeeze" and direct the beams is equivalent to, "firing two needles 10 kilometers apart with such precision that they meet halfway" [3]. The high energy proton beams collide at one of the four detectors on the LHC ring, ATLAS, ALICE, CMS, LHCb shown in figure 1. Currently the LHC is in the second run period of collecting data, operating at 13 TeV center of mass with an instantaneous luminosity of cm -2 s -1. This run started 2015, preceding run 2, from February 2013, the LHC underwent a long shut down in order to upgrade the detectors and prepare for higher energies. Future plans for the LHC include increasing the luminosity of the beam with the High luminosity LHC, or HL-LHC. CERN plans to allocate a large percentage 4

5 of their budget over a 10 year period to the development of the High-Luminosity LHC. However, the HL-LHC upgrade is not scheduled be operational until some time after The ATLAS Detector Figure 2: A dissected view of the ATLAS detector [4] ATLAS is aptly named A Toroidal LHC ApparatuS, as one of 4 detectors on the LHC ring, ATLAS ranks the largest on many scales. The detector weighs in at a colossal 7,000 tonnes, the weight of one hundred 747 airliners [5], from 38 countries and more than 175 universities and labs collaborating with ATLAS [6]. Many sub-detectors, each preforming particular operations, make up the whole of ATLAS. Each section is crucial to the successful detection of the products produced from the p-p collision. Starting from the innermost region, closest to the beam pipe, ATLAS has the 1.2 meter cylindrical inner detector. The inner detector consists of 3 parts, starting nearest the beam pipe; the Pixel Detector, Semiconductor Tracker (SCT), and Transition Radiation Tracker (TRT) [5]. These subdetectors are responsible for tracking the transverse momentum (p T ), direction, and magnitude of charge of any electrically-charged particles. Utilizing a strong magnetic field surrounding the inner detector and interactions with material in precise locations, one can observe the curvature of particles, revealing information about charge and momentum. Employing the use of silicon, the Pixel Detector provides very precise tracking information on particles close to the beam pipe. The Semiconductor Tracker preforms a similar job to as the Pixel Detector yet on a larger scale, with fewer pixels, making coverage of a larger area practical. The outermost layer of the inner detector is the TRT, this component allows the detection of electrons and positrons using 298,000 5

6 drift tubes filled with a gas that become ionized when a charged particle passes through. Outside of the inner detector are the two layers of calorimeters [5]. Figure 3: Particle trajectories within the six layers of the detector. [7] The calorimeters encircle the Solenoid Magnet and provide readings of particles by absorbing their energy. First, the electromagnetic (EM) calorimeter, this device absorbs energy from particles that interact through the EM force, such as electrons and photons. Using lead, stainless steel, and liquid argon (LAr) the calorimeter precisely measures where the energy is deposited and the angle between the beam axis and its trajectory, or pseudorapidity (η) [5]. In figure 3 this is the first section that stops particles, by absorbing their energy. The EM calorimeter stops photons and electrons, however the larger hadronic calorimeter is needed to measure and absorb particles that pass through the EM calorimeter but do not interact via the strong force. Overall, the first 5 layers of ATLAS absorb the bulk of particles produced by the p-p collision; yet, neutrinos and muons are more difficult to absorb, since they do not interact strongly and rely solely on the weak interaction. This is where the last layer becomes useful, the muon spectrometer. The muon spectrometer is composed of 4,000 individual muon chambers, covering 12,000 square meters in surface area, and the largest volume of any other subdetector [5]. This layer is very similar to the inner detector, in the same way it utilizes three toroidal magnets to effectively bend the path of the muon and observe the momentum. The paths of the muons are visible in every other layer of ATLAS, therefore, the combined data collected by all the subdetectors provides adequate measurements of the muons. Neutrinos, on the other hand, are never detected by any layer; accordingly, one must assume the production of such a particle by observing missing energy in the transverse plane of a particle decay or collision [5]. 6

7 One can start to see the shear magnitude of data collected by ATLAS; with an integrated luminosity at 36.1 fb -1, means there are over one billion collisions per second, this produces about 1 petabyte of raw data per second [6]. This is far too much data for physicists to analyze, there rises a need to only select certain events from the collisions, this is sole purpose for the ATLAS trigger system. The trigger system operates using two tiers to process events in real time. The first tier intakes data being collected by the calorimeter and muon detectors. This trigger makes a decision to keep data from an event 2.5 microseconds after a collision. Identifying regions of interest (ROI), this level allows only about 100,000 events through to the second tier. The second trigger, or high level trigger (HLT), is a farm of CPUs that process the full event data. This data is then passed to a data storage system for offline analysis [8]. 1.3 The Standard Model The Standard Model (SM) was fully developed in the 1970s and currently acts as the most adequate, yet far from complete, model of current particle physics. The SM accurately describes the building blocks of the universe and three of the four forces that governs these interactions. However, there are still many things that this model cannot describe, as a consequence the SM is nowhere near complete. For example, the force of gravity is neglected, any explanation to dark matter and the accelerating expansion of the universe is not included, and it does not fully explain the baryon asymmetry [9]. Even with a large lapse in description of our universe, the Standard Model is extremely useful to theorists for accurate predictions of particle interactions. Figure 4: A common depiction of the Standard Model [9] 7

8 The SM is composed of two varieties of particles, those of half integer spin (fermions), and whole integer spin (bosons). Spin is the property of a particle that is analogous to the magnetic moment of said particle. Fermions make up all of the matter one can observe in the universe, as seen in figure 4, this group can be further broken into quarks and leptons. There are 6 quarks all together, and they come in an assortment of three generations, each increasing in rarity and energy: up, down, strange, charm, top, and bottom. The quarks carry a charge as well as hypercharge, often called color charge. Some of the most common particles, like the proton and neutron, consist of 3 quarks held together by gluons, these are referred to as hadrons [10]. Mesons are particles that only consist of two quarks, a given quark and its anti partner, bound together by the strong force. With these few elementary particles one can make every element, and nearly all the observable mass in the universe. Leptons also originate in three generations: electron (e), muon (µ), and tau (τ). The neutrinos are elusive leptons that hardly interact with matter, interacting only via the weak force. They come in three flavors, electron neutrino (ν e ), muon neutrino (ν µ ), and tau neutrino (ν τ ). It is confirmed that these particles have a non-zero mass, however there is no explanation to how they acquire that property [10]. On the other hand, there are bosons. Possessing a spin of 1, excluding the Higgs which holds a spin of zero. Gauge bosons act as force carriers, and carry out the processes between particle interactions. As before stated, the gluon, photon, and W ± & Z 0 mediate the strong, electromagnetic, and weak force respectively. Along with the quark, the gluon also holds a color charge, in addition they also have an anti-color charge. This means that the gluons not only interact with the quarks, they can also interact with themselves [10]. These processes can easily become extremely complicated, this is where the theory of Quantum Chromo-dynamics (QCD) elegantly describes the strong force interactions. The gluon and the photon are the only known massless particles in our universe, however the W ± & Z 0 bosons are relatively massive bosons. The W has a mass of 80.3 GeV and a charge of ±1, and the neutral Z 0 boson has the mass of 91.2 GeV, this is almost 100 times the mass of the proton [11]. 2 Higgs and X boson resonance and selection This study focuses on identifying an Xh (W ) resonance; therefore, it is important to find a final state with at least 2 hadronic objects, also having properties compatible with the X and Higgs boson. This section will give a comprehensive description of the hadronic decays and the selection that is carried out for this analysis. 2.1 Resonance and Decay Resonance can be thought of as a peak at a particular mass point from examining the cross section of a particle decay as a function of mass. The life time of these resonant particles is extremely short, on the order of seconds, as a result of strong interactions. Due to the instability, or lifetime, these particles are often observed in a mass spectrum, rather than one value [12]. This peak we observe is called as the resonance, and can either be a particle, or the resonance itself. The invariant mass is the same as the rest mass (m 0 ) of a particle; this quantity is the same in any frame of reference, where it is calculated from energy and momentum. m 2 0 = E2 p 2 (1) 8

9 Finding new particles entails looking for these invariant mass "bumps". We observe the peak, and label the maximum value, m, as the resonance mass, and the spectrum width as Γ. Looking for these deviations, as a function of energy, is when the fit becomes important. Since the peak should be separate from the observed background, multiple fits and parameters are needed, this will be discussed in a later section of this paper. 2.2 Jet Reconstruction The term "Jet" refers to the shower of hadrons produced in a collision, taking the geometry of a cone as the QCD processes progress. After the proton-proton collision, a shower of particles is created from the constituent high energy quarks. When p T of the particle is high, the decay products are high boosted and can appear inside a single jet. Boosted jets form cone geometries close together as seen in figure 5. The detector s precision, when looking at jets, is much less precise than the data collected on electrons, muons, and photons. Consequently, there are many requirements in order to classify a jet. Firstly, in a boosted topology, the jets form closely in the same region. We can observe relations between hadron showers, and then inspect their angular separation. Working in cylindrical coordinates, (r, z, φ) setting the z-axis as the beam pipe, the angular separation between jets is calculated by R = η 2 + φ 2, where η is the pseudorapidity, defined by η = ln(tan(θ/2)), θ being the angle from the z-axis, and φ is the azimuth angle from the beam pipe. The Anti-k T algorithm, used in jet reconstruction, compares the p T and minimum R on groups of jets, attempting to classify them as boosted jets. Common types of jets detected by ATLAS are regular jets (R = 0.4), large-r jets (R = 1.0), and R = 0.2 jets. We are interested in the case of the large-r jet (R = 1.0), since we are studying the boosted/merged regime. The jets classified as R = 0.2 are used for jet tagging, in this case they are the track-jets that form the large-r jets[13]. Figure 5: Jets created at rest (left), jets created in a boosted frame (right). Large-R jets can be further broken down for this analysis; track jets are tracks that are associated to calorimeter activity that compose the large-r jets. Track-jets are built by clustering Inner Detector tracks with pt > 500 MeV using the anti-kt algorithm with a small-r parameter of

10 The choice of the R relies on the fact that tracks have better angular resolution compared to calorimeter clusters. Using the GhostAntiKt2TrackJet, which groups hadrons based on their R, allows us to look at the jet substructure as collections of decay products. 2.3 Event Selection Applying "cuts" on the data allows for us to select only events that could be candidates for the study. The following cuts were applied to the jets for my analysis, η as pseudorapidity, m as mass, and p T as transverse momentum. Jet Cuts Cut Value Anti-k T reconstruction Selects stable circular jets η η < 2.5 m m > 50 GeV p T p T > 250 GeV In this study we are looking for the decay of a predicted W particle, which involves two bosons decaying hardonically, W Xh, X qq, and h bb. We are looking for a decay consisting of the Higgs boson and an "X" boson, which is an entirely new particle. This analysis was preformed by looking at the two leading p T jets in each event, after utilizing the anti-k T algorithm. First, out of the jets we want to analyze one needs to have a p T above 450 GeV, then both need to pass a p T cut above 250 GeV and mass greater than 50 GeV. After using these cuts, we select the leading and sub-leading, or the two highest p T, jets. Thereafter, the two selected jets are further analyzed by looking at their substructure. By inspecting the substructure of the jets, we can further select where a di-boson decay has taken place. Observing the substructure of the large-r jet, can tell us information about the particles that created them. Since our X candidate should have a two body decay, we utilize the D 2 substructure cut. This cut identifies two prong structures of the large-r jets. Our X boson decays into two quarks, also giving it a two prong structure. We are interested in the case where h bb. The D 2 substructure cut currently only operates at a 50% working efficiency. The substructure cut is defined as follows. D β=1 2 = E CF3 (E CF1 /E CF2 ) 3 Where ECF are the energy correlation functions which are representations of the jet i-th constituents, pairs and triplet of constituents. 10

11 E CF1 = p Ti i E CF2 = p Ti p Tj R ij ij E CF2 = p Ti p Tj p Tk R ij R jk R ki ijk The large-r jets are composed of track-jets, which are then analyzed and we select the two highest transverse momentum track-jets. Both track jets have a preceding cut of p T > 20 GeV and η < 2.5. For this analysis we only look at track jets with the possibility of being b-jets. These b- jets are jets produced from bottom quarks, which the Higgs boson should produce. Utilizing the prolonged lifetime of these bottom quarks the vertex created by their decay is observed further from the original vertex. Identifying this is the process called b-tagging; by applying a cut that requires MV2c10 > we select these as b-jets at an 77% working efficiency. Following the cuts on the jets, we are now ready to select our candidate particles from the potential W decay. From the two leading large-r jets, we assume that they were created in the Xh decay. The Higgs is selected as the large-r jet within the mass range of 95 < m < 145 GeV. The X boson s mass is unknown and only for the interpretation of the results slices of m X are selected. Addressing the case where both bosons are within the Higgs mass range, we select the Higgs as the large-r jet with more b-tagged jets. However, there can be another case when the X and h bosons are both within the Higgs mass range and have the same number of b-tagged jets; in this case we select the leading p T large-r jet as the Higgs boson, and the subleading as the X boson. 3 Search for Xh resonance 3.1 Introduction Beginning with a few plots run on signal serves as a method to test the analysis code. The following histograms display the p T, η, and mass of our candidate particles. In figure 7 the p T of the Xh is relatively low; this can be further explained by looking at figure 9, Xh is massive therefore has a low p T. This same property can be seen in figure 10 and 11, the more massive Xh exits the detector at a lower η implying its relatively large mass. The following plots were created using 4 different signals as follows in the table. Signal samples Signal color Xh mass X mass Blue 1000 GeV 110 GeV Red 2000 GeV 130 GeV Green 3000 GeV 160 GeV black 4000 GeV 250 GeV 11

12 Figure 6: p T of X boson Figure 7: p T of Xh boson Figure 9: m of Xh boson Figure 8: m of X boson Figure 11: η of Xh boson Figure 10: η of X boson 12

13 3.2 X Mass Windows Since the X boson ultimately has an unknown mass, we intelligently select in which mass windows to search. The m X spectrum is split into small windows along which the m W spectrum can be scanned. Each one of the windows is selected by taking into account the estimated m X resolutions each window size is set to be at least equal to double the resolution size at the center of the window. Since the two signal regions are fitted together the window width is chosen to be the same and therefore the largest resolution is kept for each estimation. The windows are allowed to overlap, however they are treated independently. Due to a lack of data, the 1 b-jet mass windows above 500 GeV and 2 b-jet mass windows above GeV are merged into one histogram. To optimize the binning for every m X window the resolution of m W is used. The bins are chosen to be at least equal to the signal mass resolution and to contain expected background events with relative expected background uncertainty less than 75%. Only m W masses in the range between TeV are interpreted, with the overflow included in the highest bin. The optimal bins are found to be the same for all windows, however in the high m X region the first bins would be in the resolved regime, and are dropped. 3.3 Fitting The goals of this fit are to accurately describe our background and any possible signal peaks. The fit applied in this analysis is a combination of two lesser fits. The first models a smoothly falling background, displayed in equation (2). There are three parameters and one constant available in this equation. This VV qqqq search also uses this function to fit the background [14]. The other function, equation (3), is a Lorentzian peak function. This function is intended to model signal peaks above the background. The combination of the two equations creates an ideal fit for this analysis which should be able to fit the background and recognize any deviations (signal). To test this hypothesis, the fit was run on a sample with signal injection. In figure 12, the injected signal had an Xh mass of 3 TeV, the fit preforms well and clearly shows signal. However, it doesn t represent the tail well. But, since we are just looking for deviations this doesn t effect the outcome. dn dx = p 0 (1 x) p 1 ξ p 2 x p 2 (2) 1 π 1 2 p 3 p 4 (x p 5 ) 2 +( 1 2 p 4) 2 (3) 13

14 Figure 12: The fit modeling with an injected signal (Xh mass 3 TeV) A large part of how well the fit "fits" is choosing the correct starting point. In this case, it is optimal to fit above 1.2 TeV. However, in certain higher mass windows of the X boson, 1.2 TeV lies within the resolved regime. Two different topologies are defined according to the experimental feasibility to reconstruct the quarks from the X and h decays as two separated jets with small radius parameter or a single jet with large radius parameter. Hereafter these are referred to as resolved and merged regimes respectively, however for this search only the merged regime is studied in the fully hadronic final state of Xh qqbb. Utilizing the threshold of merged and resolved regime, this analysis implements a selection to start fitting above this boundary, which allows the fit to only be applied in the merged regime. 14

15 4 W Mass Plots With User Defined Fit The fits for all X mass windows are presented in section 4.1, and the corresponding parameters are listed in the table in Varying X Mass Window Implementation 15

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21 4.2 Parameters Smoothly Falling Background Lorentz Peak Function Mass (GeV) p 0 p 1 p 2 p 3 p 4 p

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23 5 Conclusion We were able to successfully classify large-r jets as our candidate bosons, using signal and data, while implementing selections in cases of ambiguity. The user defined fit preformed well with injected signal; however, there are no significant deviations from background that point to the existence of an Xh resonance. With observations in many different mass windows for the X as well as both one and two b-jet regions, the user defined fit function did not identify any resonance above the background. 6 Acknowledgements I would like to thank The National Science Foundation and the Columbia REU program for providing me with this unreal learning and travel experience. Most importantly I would like to thanks my advisor, Dr. Kalliopi Iordanidou, for leading me through this project with patience and intellectual acuity. Also, I am extremely grateful for Dr. John Parsons for allowing me to conduct hands on research at CERN this summer. Overall, the Columbia ATLAS group has been very welcoming and I am exceedingly thankful for being able to take part in this experience. 23

24 References [1] Large Hadron Collider beauty Experiment, [2] W. Francis Sears. University Physics. Addison Wesley, [3] The Large Hadron Collider. Jan [4] G. Aad et al. The atlas experiment at the cern large hadron collider. The ATLAS Collaboration, (JINST 3), [5] ATLAS Experiment. Detector and technology, [6] ATLAS Experiment. Atlas fact sheet, [7] ATLAS Experiment. Atlas multimedia, [8] Patrick Czodrowski. The atlas trigger system: Ready for run ii, [9] The Standard Model. Jan [10] Glenn Elert. The physics hypertextbook, [11] Beringer et al. Review of Particle Physics. 86(1), July [12] Chris Dudley. What is a resonance particle?, [Online; accessed July 25, 2017]. [13] Gregory Soyez Matteo Cacciari, Gavin P. Salam. The anti-k t jet clustering algorithm. Apr [14] Search for resonances with boson-tagged jets in 15.5 fb 1 of pp collisions at s = 13 TeV collected with the ATLAS detector. Technical Report ATLAS-CONF , CERN, Geneva, Aug