The Large Hadron Collider and the ATLAS detector 

Get Complete Project Material File(s) Now! »

The ATLAS Detector

ATLAS is the largest particle detector ever constructed. It is 46 m long, 25 m high, 25 m wide, weighs 7000 tons, and covers almost the whole 4π solid angle. The detector layout is shown in Fig. 2.4. ATLAS is composed of 3 subdetectors: the Inner Detector (ID), the calorimeter and the Muon Spectrometer (MS). The ID is composed of three subdetectors, the Pixel detector, the Silicon Micro strip (SCT) detector and the Transition Radiation Tracker (TRT) detector. The calorimeter, based on LAr and scintillating tile sections, has an electromagnetic component and a hadronic component. A solenoidal magnet surrounds the ID and provides a magnetic field of 2T inside its volume, while 3 toroid magnets generate the magnetic field needed for tracking inside the MS. To reduce the enormous amount of data produced by the pp collisions, ATLAS records events conditionally using an advanced “trigger” system that keeps only events that are potentially interesting for the ATLAS physics programme. The design performance goals of the ATLAS detector are summarized in Table 2.2. More details on the sub-detectors and their performance are given in the following sections. ATLAS uses the following right-handed Cartesian coordinate system. The origin of the coordinate system corresponds to the nominal beam interaction point, located at the center of the detector. The z-axis is given by the beam direction and the x − y plane is orthogonal to the beam direction. The x-axis points from the interaction point towards the center of the LHC ring. The y-axis points upwards. The azimuthal angle in the x-y plane is referred to as φ, while θ is the polar angle with respect to the z-axis. The pseudorapidity is defined as η = −ln[tan(θ/2)].

The Inner Detector

At design luminosity and centre-of-mass energy, about 1000 particles emerge from the collision point every 25 ns within the |η| < 2.5 region. Within the same brunching crossing, about 40 inelastic pp collisions, called “in-time pile-up”, take place at high instantaneous luminosity. This presents a challenge for the ATLAS Inner detector to disentangle a track from the others. Reconstructing the collision points (primary vertices), secondary vertices from decays of long-lived particles or interactions with the detector material and measuring precisely the charge particles’ momenta are achieved by the precision tracking detectors (Pixel and SCT detector) in conjunction with the TRT detector. A schematic view of the Inner detector is shown in Fig. 2.5. The Pixel and SCT detectors provide precision tracking in the |η| < 2.5 region. In the Pixel detector, three layers of concentric cylinders are arranged around the beam axis in the barrel region, with silicon pixel sensors whose intrinsic hit accuracies are 10μm ×115μm in R − φ × z. In the end-cap region there are six disks of sensors (three disks in each end-cap region) perpendicular to the beam axis, with silicon pixels providing intrinsic accuracies of 10μm ×115μm in R − φ × R. The innermost pixel layer (also called the B-layer) is located at a radius of 50 mm from the beampipe, and provides precision information for vertexing. The SCT consists of 8 layers of silicon micro strips in the barrel which provide 4 space points for a crossing track with stereo pairs of SCT layers, and nine disks in each end-cap. Its intrinsic accuracy is 17μm ×580μm in R−φ×z in the barrel region, and 17μm ×580μm in R−φ×R in the end-cap region. The TRT only provides R − φ information for the hit by means of straw tubes in |η| < 2.0. Typically, 36 hits per track are detected. The intrinsic accuracy is 130 μm in R − φ. In the barrel region, the straws are parallel to the beam axis while in the end-cap region they are arranged radially in wheels.

The Muon Spectrometer

The MS, shown in Fig. 2.8, surrounds the hadronic calorimeter. It provides, for charged particles passing beyond the HCAL, precision momentum measurement for |η| < 2.7 and trigger capability for |η| < 2.4. Muon momenta down to ∼3 GeV can be measured by the MS alone. The muon spectrometer can also provide adequate momentum resolution (about 10%) and excellent charge identification at very high pT , up to 3 TeV. In the barrel region, precision-tracking chambers are located between and on the eight coils of the superconducting barrel toroid magnet. The chambers are arranged in three concentric cylindrical shells around the beam axis at radii of approximately 5 m, 7.5 m and 10 m. In the end-cap region, the muon chambers are installed in front and behind the end-cap toroid magnets. They are located at distances of |z| ≈ 7.4 m, 10.8 m, 14 m and 21.5 m from the interaction point.

Photon Reconstruction

Photons in ATLAS are reconstructed through their interactions with the ECAL or by detecting their conversions to e+e− in the material upstream of the calorimeter. The reconstruction of photon conversions increases the reconstruction efficiency of particles decaying to photon final states, e.g. Higgs boson or graviton decaying to photon pairs.
Mapping the photon conversion vertices also provides a precise localisation of the Inner Detector materials.
Both photons and electrons deposit their energy in the EMC, forming a cluster of calorimeter cells with significant energy deposits. Electrons and photon conversions are characterized by at least one track mateched to an EM cluster. In the case of photon conversions, the track (tracks) is (are) originating from a conversion vertex candidate.
The unconverted photons are reconstructed as a cluster with no track matched to it. Photons which convert within a radial distance of 300 mm from the beam axis may be reconstructed with high efficiency from standard Si-seeds tracks (inside-out tracking), while photons which convert further from beam axis may be reconstructed from tracks formed with TRT seeds with few Si hits (outside-in tracking) or no Si hits at all (TRTstandalone).
The inside-out track reconstruction is sensitive to conversions inside Pixel detector. A segment is first formed using the hits in the silicon detectors. A Kalman fitter is thenused to add successive hits to the track. Finally, a possible TRT extension is used to do a global fit. According to the fit quality with or without additional TRT extension, the reconstructed inside-out tracks are classified into three categories:
• Tracks with extensions which are used in the global fit.
• Tracks with extensions which are not used in the global fit.
• Tracks without TRT extension (|η| > 2).

Photon Energy Calibration

The photon energy is reconstructed by summing the energy of all the cells of the four layer of the ECAL belonging to a a cluster of fixed size, and is corrected by applying a dedicated energy calibration afterwards. The number of cells used in the energy reconstruction depends on the photon conversion status. In the barrel region, a cluster with transverse size of η×φ = 3×5 in units of second layer cells around the photon shower barycenter is used for unconverted photons while a cluster with size η × φ = 3 × 7 in the same units is used for converted photons. The wider size in the φ direction is used to compensate for the opening between the conversion products due to the solenoidal magnetic field. In the end-cap, where the opening of the conversion electrons is smaller due to the smaller inner radius of the calorimeter, the same cluster size η × φ = 5 × 5 is used for converted and unconverted photons.

READ  EVOLUTIONARY STABLE MIXED MATING IN A VARIETY OF GENETIC SYSTEMS

Photon Trigger Optimization for the 2012 data taking

An overview of the ATLAS trigger system has been given in section 2.2.5. The hardware-based L1 trigger and the software-based high-level (L2 and EF) trigger reduce the rate to an acceptable level for the ATLAS data recording system. During the 2011 data taking period, the trigger rate was reduced to about 60 kHz at L1 level to below 5 kHz at L2 level, and then below 400 Hz at EF level. Part of this bandwidth was allocated to “loose” photon triggers, used to collect events with high-pT photons, for Standard Model cross-section measurements and searches of high-mass diphoton resonances (Higgs boson, graviton, …). The loose trigger criteria apply cuts on the Rhad(Rhad1), Rη and wη2 shower information.
For the 2012 data taking period, the EF-level trigger selections were re-optimized to limit the trigger rate to below 530 Hz while maintaining a good signal selection efficiency even for large pile-up. A simple strategy to reduce the trigger rate is to prescale it: only 1 out of Nprescale events passing the trigger are recorded, while for the others the trigger response is reset to false. This strategy, however, implies a reduction by a factor Nprescale of the signal efficiency. In order to maintain full efficiency for a possible di-photon signal from a Higgs boson and for the SM di-photon cross section measurement, a different strategy was adopted for the (di)photon triggers. The goal is to increase the jet rejection of the photon trigger by a factor around 1.5, in order for the di-photon triggers to use have a few Hz of unique rate, while keeping the efficiency with respect to photons passing the offline identification criteria close to 100%. This is achieved by a reoptimization of the requirements on the shower shape variables used in the loose trigger and by additional requirements on discrimination variables used for the offline photon selection but not exploited in the photon triggers used in 2011. A second goal of these studies is also to reduce the dependence of the trigger efficiency on pile-up, in order to maintain similar efficiency over the large range of number of pile-up collisions per bunch crossing expected to take place during the 2012 run.
These two targets have been achieved by loosening the cuts on the most pile-up dependent quantities used in the loose photon triggers, Rhad and Rη, which are sensitive to the energy deposited in the hadronic calorimeter and around the core of the photon cluster in the second layer of the ECAL, while tightening the requirement on wη2, and adding to the trigger selection a requirement on Eratio, a DV computed from the energy deposited in the first layer which shows weak correlation with the other variables already exploited at trigger level and which is peaked near 1 for signal but has a broad, flat tail extending down towards 0 for fake photons. Different sets of cuts on Eratio (“loose++”, “medium”, “medium++”, “tight”) have been investigated, and the corresponding signal and background efficiencies have been studied. Care has been taken to ensure that the requirements applied to Eratio at trigger level are always looser than the ones applied to photon candidates at offline level. The left plot of Fig. 3.1 shows the efficiencies of the different selections as a function of the number of primary vertices, while the right one shows their corresponding background rejection, for single-photon triggers with a nominal pT threshold of 20 GeV, estimated on samples of simulated di-jet events. For comparison the curves corresponding to the 2011 trigger (“EF_g20_loose”) are also shown. The re-optimized trigger menus are significantly less pile-up dependent than the trigger used during 2011, and the jet rejection compared to the 2011 trigger is increased, for different requirements on Eratio, between 30% and 85%. The efficiency of the various trigger menus for true photons in photon-jet events passing the offline photon identification requirements is shown in Fig. 3.2. For any of the alternative trigger selections the efficiency is higher than 99% for any value of the transverse momentum above the nominal threshold.

Photon Trigger Efficiency Measurement

In measurements with photons in the final state performed on data collected with photon triggers, like H → γγ or SM prompt photon cross section measurements, the trigger efficiency with respect to the off-line tight selection is a quantity that has to be known in order to extract the signal cross section. Two methods have been developed by ATLAS in order to measure this efficiency from the data, the bootstrap and the radiative Z decay methods. The bootstrap method uses collision events passing looser triggers, typically a pre-scaled lower-threshold L1 trigger being part of a chain where the HLT trigger is in pass-through mode. The efficiency of the HLT trigger is then measured with respect to the off-line photons matched to L1 trigger objects, and multiplied by the L1 trigger efficiency with respect to the off-line selection (≈100%), measured with minimumbias events. More detail can be found in the Ref. [48]. Here, I focus on my work on the measurement of the trigger efficiency using the other method, based on a clean sample of prompt, isolated photons of relatively low transverse momentum from Z → ℓℓγ (ℓ = e, μ) decays, in which a photon is produced from the final state radiation (FSR) of one of the two leptons from the Z boson decay. These events are selected by kinematic requirements on the di-lepton pair and on the three-body invariant mass and quality requirements on the two leptons, thus not biasing the reconstruction and selection of the photon probe.

Table of contents :

Introduction
1 Phenomenology 
1.1 The Gauge Principle
1.2 The Electroweak Unification
1.3 Spontaneous Symmetry Breaking
1.4 The Higgs Mechanism
1.5 Constraints on the Standard Model Higgs Boson Mass
1.6 Higgs Boson Production and Decay
1.7 The H → γγ and H → Zγ Decays
2 The Large Hadron Collider and the ATLAS detector 
2.1 The Large Hadron Collider
2.2 The ATLAS Detector
2.3 Photon Reconstruction
2.4 Photon Identification
2.5 Photon Energy Calibration
2.6 Lepton Reconstruction and Identification
2.7 Jet and Missing ET Reconstruction
3 Photon performance 
3.1 Photon Trigger Optimization for the 2012 data taking
3.2 Photon Trigger Efficiency Measurement
3.3 Photon Identification Efficiency Measurements
3.4 Pile-up Dependence of the Photon Identification Efficiency
3.5 Summary
4 Search for a Higgs boson in H → Zγ → ℓℓγ 
4.1 Introduction
4.2 Data and Simulation Samples
4.3 Event Selection
4.4 Discriminating Variable
4.5 Event Classification
4.6 Data-driven Background Estimation
4.7 Signal Parameterization
4.8 Background Properties
4.9 Systematic Uncertainties
4.10 Statistical Method
4.11 Exclusion Limits and p-values
4.12 Conclusions and Prospects
5 Observation of the Higgs boson in γγ events 
5.1 Introduction
5.2 Data and Simulation Samples
5.3 Event Selection and Category
5.4 Data-driven Background Estimation
5.5 Signal and Background Modelling
5.6 Systematic Uncertainties
5.7 Results
5.8 The Higgs Boson Properties Measurements in Combined Channels .
5.9 The Higgs Boson Properties Measurements in H → γγ Channel with the CMS Detector
Conclusion
Bibliography 

GET THE COMPLETE PROJECT

Related Posts