Measurement of the tt production cross section in the fully hadronic nal state

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ATLAS detector

Overview

The high interaction rates, radiation doses, particle multiplicities and energies, as well as the requirements for precision measurements lead to the design of the ATLAS detector. Due to these experimental conditions, the detector subcomponents require fast and radiation-hard electronics and high granularity to handle the particle uxes and to reduce the in uence of overlapping events. The general requirements for the subdetector are: large acceptance in pseudorapidity with almost full azimuthal angle coverage, good charged-particle momentum resolution and reconstruction e ciency in the inner tracker, very good electromagnetic (EM) calorimeter for electron and photon identi cation and mea-surements of their energy, complemented by full-coverage hadronic calorimeter for accurate jet and missing transverse energy measurements, good muon identi cation and momentum resolution over a wide range of momenta, and ability to determine unambiguously the electric charge of high pT muons are fundamental requirements, highly e cient triggering on low transverse-momentum objects with su cient background rejection.
The overall ATLAS detector layout is shown in Figure 2.3. The detector is cylindrical in shape with a total length of 44 m and a radius of 12 m and it is divided into a barrel section and two end-caps. The total weight is approximately 7 103 tons. The ATLAS detector is nominally forward-backward symmetric with respect to the interaction point.

Magnetic System

Two di erent magnetic elds are generated in the ATLAS detector volume: a central magnetic eld, provided by a solenoid surrounding the inner detector, and an outer one, produced by a set of toroids surrounding the muon spectrometer [70]. The central superconducting solenoid provides a central magnetic eld of 2 T, while the peak value (at the superconductor face) is 2.6 T. In order to obtain the desired calorimetric performances, in particular for photon and electron energy measurements, a careful design to minimize the amount of dead material in front of the calorimeters has been performed: the solenoid is placed inside the vacuum vessel of the LAr calorimeter. The amount of dead material due to the solenoid and the cryostat wall is of about one radiation length. The magnetic eld in the barrel region of the muon spectrometer is provided by a system of 8 coils assembled radially with eight fold symmetry. The magnetic eld in the forward region is delivered by the end-cap coils system, which is rotated by 22:5o with respect to the barrel coils to provide radial overlap and to optimize the bending power in the interface regions of the two coil systems. The peak magnetic eld obtainable in the barrel region is about 4 T. The coils of the barrel are 25 m long and their height is 4.5 m and there is one cryostat per coil. In the endcap region there is only one cryostat within which the coils (5 m long and 4.5 m tall) are housed.

Inner detector

At design energy and luminosity approximately 1000 particles emerge from the collision point every 25 ns within j j < 2:5, leading to a very large track density in the detector. To achieve the momentum and vertex resolution requirements imposed by the benchmark physics processes, high-precision measurements must be made with ne detector granularity. The strategy used for the ATLAS tracker [71, 72] is to combine few high precision measurements close to the interaction point with a large number of lower precision measurements in the outer radius. The inner detector is immersed in a 2 T solenoidal eld and is made from three di erent technologies at di erent distances from the interaction point. The combination of three inner layers of pixels and four layers of silicon micro-strips allows hermetic and robust pattern recognition and good secondary vertex identi cation for charged tracks above a given pT threshold (nominally 0.5 GeV) and within a pseudorapidity range of j j < 2:5. It allows also good momentum measurements over j j < 2:0 and a wide range of energies (between 0.5 GeV and 150 GeV). The tracking is completed by continuous straw tube detectors with transition radiation detection capability in the outer part. The structure of the inner detector is shown in Figure 2.4. Table 2.2 summarizes the main parameters of the tracking system.
Close to the beam line is the Pixel Detector [73] with approximately 80 million silicon pixel struc-tured in 1744 sensors of size 50 400 m2 arranged in three layers in the barrel region and three end-cap disks at large pseudorapidity. At least three space points are measured by the Pixel Detec-tor, leading to the reconstruction of track segments independently from the outer detectors. The intrinsic hit resolutions in the barrel are 10 m in R and 115 m in z while in the disks are 10 m in R and 115 m in z. The pixel detector covers a pseudorapidity region of j j < 2:5 and ensures a high granularity in the area around the proton-proton collisions, where the density of charged tracks is very high. The main purpose of the Pixel Detector is to e ciently reconstruct tracks and vertices at each beam crossing. The innermost layer is commonly referenced as the b-layer because it is an essential ingredient to improve the tracks impact parameter which is crucial for the selection and identi cation of jet originating from b-quarks (b-jets).

SemiConductor Tracker

The SemiConductor Tracker (SCT) is formed by silicon micro-strips arranged in four nested cylin-drical layers located in the barrel and nine disks in each end-cap. In the barrel region, SCT detector uses two di erent micro-strips with one set of strips in each layer parallel to the beam direction and a relative angle of 40 mrad. This stereoscopic geometry provides the capability to perform three-dimensional position measurements. In the end-cap region, the detectors have a set of strips running radially and a set of stereo strips at an angle of 40 mrad. The modules cover a surface of 63 m2 of silicon and provide almost hermetic coverage with at least four precision space-point measurements over the ducial coverage of the inner detector with intrinsic hit resolutions per module of 17 m in R and 580 m in z in the barrel region and of 17 m in R and 580 m in z in the disk. The total number of SCT read-out channels is approximately equal to 6.3 million.

Transition Radiation Tracker

The last tracking subsystem is the Transition Radiation Tracker (TRT), which is both a straw drift-tube tracker and a transition radiation detector. The TRT consists of 2 mm radius straw tubes, arranged in two barrel sections with straws parallel to the beam-axis and in two end-caps with straws arranged radially. In the barrel region, the straws are parallel to the beam axis and are 144 cm long. They are divided into two halves, approximately at = 0. In the end-cap region, the 37 cm long straws are arranged radially in wheels. The total number of TRT read-out channels is approximately equal to 350 thousand. The straw tubes are lled with a gas mixture (70% Xe, 27% CO2, 3% O2) with inside a tungsten wire. When charged particles cross a straw, they leave a trail of electron-ion pair in their wake. The electrons, drift towards the anode wire, gain energy and create other electron-ion pairs, generating an avalanche process in which a cascade of electron-ion pairs is created. The TRT can provide only R information, for which it has an intrinsic accuracy of 130 mm per straw, but the combination of precision silicon-based trackers at small radii with the TRT gives very robust pattern recognition and high precision hit measurements in both R and z coordinates. The straw hits contribute signi cantly to the momentum measurement, since the lower precision per point compared to silicon detectors is compensated by the large number of measurements, typically 36 per crossing track, and longer measured track length.

Calorimeters

The basic idea of the calorimeter system is to detect, within layers of active material, the particles created in the shower initiated by an incoming particle which pass through layers of a dense material (absorber). The calorimeter aims to have a precise measurement of the energy and position of the incoming particles, as well as a good estimation of the missing transverse energy in an event. ATLAS calorimetric systems di er in technology and materials depending on the pseudorapidity region. Liquid Argon (LAr) technology is used as active material for the electromagnetic (EM) calorimeters in all pseudorapidity ranges and for the hadronic calorimeter in the end-cap regions (HEC). In the end-cap regions the HEC and the EM calorimeter are hosted in the same cryostat. Di erent absorbers are used in the di erent regions: lead for the LAr in the barrel up to j j < 1:7 and in the end-caps (1:5 < j j < 3:2), copper for the HEC. An homogeneous LAr presampler detector is placed between the cryostat wall and the EM calorimeter in the region up to j j = 1:8. In the barrel region (j j < 1:7) the hadronic calorimeter is composed of an iron-scintillating tiles calorimeter (TileCal) subdivided into three parts: the central barrel covers up to j j ’ 1, while the two extended barrels cover up to j j < 1:7. In the very forward region, up to ’ 5, the system is completed by a very dense LAr calorimeter consisting of rod-shaped electrodes in a tungsten matrix. An overall view of the ATLAS calorimetric system is shown in Figure 2.5 while Table 2.3 shows the details of the segmentation of the calorimeters [74].

The electromagnetic calorimeter

As mentioned above the EM calorimeter is a sampling calorimeter, using lead as absorber and liquid argon as active material. It is segmented in three parts of di erent granularity. The rst part close to the tracking system is a ne granularity in pseudorapidity and azimuthal angle, to provide a precision measurement and to improve the = 0 and e= 0 separation. The thickness of the EM calorimeter is more than 24 radiation lengths (X0) in the barrel and 26 X0 in the end-caps. The energy resolution is given as a function of the energy E of incoming particle (in GeV) by the formula (2.2) in which the rst term takes into account the statistical uctuation due to the development of the shower, and the second one is a constant term that takes into account several systematic errors, like the inhomogeneity in the calorimeter response.

The hadronic calorimeter

The EM calorimeter is surrounded by the hadronic one. The barrel part uses the iron as absorber and scintillators as active materials. The end-cap hadronic calorimeter receives a much higher radiation dose and therefore uses the intrinsically radiation-hard LAr technology. The thickness of the hadronic calorimeters is more than 10 hadron interaction length. The equation (2.3) gives the design energy resolution for the barrel hadronic calorimeter, whereas the equation (2.4) is for the end-cap part.

The forward calorimeter

The forward calorimeter covers the pseudorapidity region 3:1 < j j < 4:9 and uses LAr technology with copper and tungsten as absorber. It consists of an electromagnetic part and two hadronic parts along the longitudinal direction. To avoid back-scattered neutrons in the Inner Detector system, the forward calorimeter is placed 1.2 meter further away from the interaction point, compared to the electromagnetic end-cap calorimeter.

Muon Spectrometer

The calorimeter system is surrounded by the muon spectrometer. It consists of an air-core toroid system, with a long barrel, in the central region, and two inserted end-cap magnets, for the coverage at small angles. They generate strong magnetic eld in a large volume with a relatively light struc-ture. Multiple-scattering e ects are therefore minimized, allowing an excellent muon momentum resolution with three layers of high precision tracking chambers. The muon spectrometer de nes the overall dimensions of the ATLAS detector.
The main features of the muon spectrometer [75] is the possibility of a precise standalone mea-surement of the muon momentum. The magnetic eld provided by the superconducting air-core toroid magnets de ects the muon trajectories that are measured by high precision tracking cham-bers. The magnetic eld in the j j < 1:0 range is provided by the barrel toroids, while the region 1:4 < j j < 2:7 is covered by the end-caps. In the so called transition region (1:0 < j j < 1:4) the combined contributions of both the barrel and end-caps provide the magnetic eld coverage. In the barrel region, the muon chambers are arranged in three cylindrical layers (stations), while in the end-cap they form three vertical walls. The transition region is instrumented with one extra sta-tion. Figure 2.6 o ers a three dimensional view of the spectrometer. The azimuthal layout follows the magnet structure with 16 sectors. The so-called Large Sectors lie between the coils, and they overlap with the Small Sectors, placed in correspondence with the coils themselves. The choice of the di erent chamber technologies follows the particle ux expectation in the di erent regions of the detector. Criteria of rate capability, granularity, aging properties and radiation hardness have been considered. Table 2.4 summarizes the chamber technologies used in the various pseudo-rapidity regions. The measurement of the track non-bending coordinate ( ) is provided in most of the region by the Monitored Drift Tubes (MDT), while at large pseudorapidity, the higher granularity Cathode Strip Chambers (CSC) are used.
To reach the transverse on the momentum resolution of pT =pT ’ 10% at 1 TeV requires an accuracy of the relative positioning of chambers traversed by a muon track that matches the intrinsic resolution and the mechanical tolerances of the precision chambers. The knowledge of the chamber positioning with an accuracy of 30 m is required within a projective tower. The accuracy required for the relative positioning of di erent towers to obtain adequate mass resolutions for multi-muon nal states is in the millimeter range. This accuracy can be achieved by the initial positioning and survey of the chambers at the installation time. The relative alignment of muon spectrometer, calorimeters and ID relies on the measurement of the high-momentum muon trajectories. The MDT chambers are equipped with an in-plane alignment system aiming at a measurement of the tube position displacements, with respect to their nominal positions at the assembly phase, with a precision of better than 10 m. To achieve this, the spectrometer is equipped with a laser, mounted at one side of a chamber which project a pattern to a CCD camera positioned at the other end of the chamber. From the displacement of the pattern- gure with respect to what is expected, corrections for chambers deformation can be computed. The chambers for the rst level (LVL1) muon trigger system covers the region j j < 2:4. Resistive Plate Chambers (RPC) are used in the barrel region, while the Thin Gap Chambers (TGC) are used in the end-cap. Their rst task is to identify without any ambiguity the bunch crossing of the triggered event. This requires a time resolution of better than 25 ns. Next, they have to provide a well de ned pT cuto for the LVL1 choice. This is obtained considering a window of a size de ned by the LVL1 pT threshold considered on the second RPC (or TGC) station once a super-hit has been obtained in the rst station. Finally, the trigger chambers measure the bending coordinate ( ), in a plane orthogonal to that measured by the precision chambers, with a typical precision of 5-10 mm.

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Trigger system

The ATLAS trigger system is designed to reject the largest rate of the background and at same time to select with a satisfactory e ciency the potential interesting events. The ATLAS trigger and data-acquisition system is based on three on-line event selection. More detail on the trigger system, as well as the data-taking and monitoring are presented and discussed in the Chapter 3.

Computing

The complexity of the ATLAS experiment imposes the use of new paradigms concerning the data processing once they are made available on mass storage. The event rate of few hundred Hz (see Chapter 3), the size of the events ( 1:6 MB per event) and the number of physicists involved in the analysis require that the data distribution, processing and analysis is carried out according to a multi-tier schema that is well suited to distribute the computing and storage loads among the di erent participating institutes. Similar strategies have been used in the past for other experi-ments, but it is the rst time that this kind of distributed analysis is performed on an LHC-size scale requiring the development of completely new software tools [76]. At the output of the data acquisition system, the raw data are transferred to the CERN computing center, called Tier-0, the rst layer of the ATLAS analysis system. In Tier-0 is stored a complete copy of the raw data and a rst-pass reconstruction is made producing ESD (Event Summary Data) and AOD (Analysis Object Data). The ESD data-format contains the reconstructed quantities measured by the detec-tor (energy in the calorimeter cells, clusters information, tracks, vertices) as well as reconstructed physics objects (electrons, photon, jets, taus, muons). The event size foreseen for the ESD format is about 0.8 MB/evt. The small-sized data in AOD format (0.15 MB per event) are well suited for data distribution. Here only the physics objects are recorded. Tier-0 has also the responsibility to run calibration and alignment algorithms that will be re ned in future steps. The distribution of the data to the ATLAS community is performed by copying raw data, ESD, AOD to the Tier-1s. Tier-1s are big regional or national computer centers spread around the world. Tier-1s have also the responsibility to reprocess raw data performing more accurate reconstructions. Updated version of ESD, AOD are therefore constantly produced and spread among the di erent computer centers. Most of the physics analysis is performed at the Tier-2 centers. The Tier-2 are allowed to connect to di erent Tier-1s and Tier-2s from a di erent cloud. They have the responsibility for the o cial Monte Carlo production (the simulated data are stored in the Tier-1s) and physics analysis. The development and re nement of calibration and reconstruction algorithms are also performed at the Tier-2 centers. The physics analysis are performed on AOD data sets or on even more compact Derived Physics Data (DPD). DPD format is a subsample reduced data set with stricter event selection, reducing in size the information per object and dropping unwanted data objects. The multi-tier paradigm is deployed using GRID technology [77].
An e cient trigger system is required to select the events produced by the proton-proton collision in the LHC challenging environment. The aim of data acquisition systems of the LHC experi-ments consists in ltering and selecting the relevant physics events from the background of soft interactions. Section 3.1 provides an overview of the ATLAS trigger structure including a general description of its three trigger levels. In particular, a description of the jet and muon trigger as well as the tracking algorithms used in ATLAS are provided in Section 3.2. Section 3.3 gives a detailed description of the b-jet trigger. Section 3.4 is devoted to the data quality online monitoring of the b- and -jet trigger algorithms.

ATLAS trigger infrastructure

The trigger of the ATLAS experiment [78] is designed as a three level system that reduces the event rate from 40 MHz to about 500 Hz at which events1 can be written to mass storage. Figure 3.1 gives an overview of the ATLAS trigger and data-taking system showing its three levels structure and describing the di erent steps of the trigger system, starting from the input signals received from the calorimeter and the muon spectrometer up to the storing of the data events. The input rate of the proton-proton collision and the consequent reduction performed by the trigger system are also presented. Each step re nes the previous decision by using a larger fraction of the data and more advanced and time-demanding algorithms. The di cult task at each trigger consists on reaching a decision quickly enough to handle the output rate of the previous level.

First Level Trigger (LVL1)

The LVL1 trigger is a hardware-based system that receives signals from the calorimeter and muon detectors of ATLAS. Its task is to reduce the event rate from 40 MHz to 75 kHz within a latency of 2:5 s. During that time the data from all detectors are stored in pipeline memories. The LVL1 objects information, recorded in the so called ‘Regions-of-Interest’ (RoI) (spatially limited areas in the detector with candidates for phenomena to be triggered) are sent to the Central Trigger Processor (CTP), which implements the di erent trigger combinations, trigger menu, as well as the possible con guration pre-scale factors2. It provides information to the High Level Trigger for selected events indicating which signatures were ful lled. The total number of allowed L1 con gurations (also called L1 items) that can be deployed at any time is 256. The data-taking run is subdivided into time ranges of about one minute, called luminosity blocks. The luminosity blocks represent the smallest size at which the data will be monitored and available for the physics analysis. Within a lumonosity blocks the trigger menu, con guration and pre-scale values, remain unchanged.
2A trigger pre-scale allow the optimization of the bandwidth usage for di erent luminosity and background conditions by recording only part of the data triggered: the portion of the recorded data is governed by the pre-scale factor.

Second Level Trigger (LVL2)

The LVL2 trigger is based on software selection algorithms running in processor farms. LVL2 can access data from all sub-detectors of ATLAS in the RoIs that were identi ed by the LVL1 system. A seed is constructed for each trigger accepted by LVL1 that consists of a pT threshold and an position. The LVL2 algorithms use this seed to construct an RoI window around the seed position.
LVL2 is the rst stage of the ATLAS trigger system that has access to data from the tracking sub-detectors. Hence speci c algorithms to select events containing jets originating from b-quarks can be implemented at this stage. The processing time available for LVL2 algorithms is 40 ms in average, during this time the trigger algorithm should be able to perform a its events rejection. The LVL2 system must provide a reduction of the LVL1 input rate from 75 kHz to 2 kHz at nominal operations.

Table of contents :

Introduction 
1 Theoretical framework 
1.1 The Standard Model of particle physics
1.1.1 Elementary particles
1.1.2 The Standard Model
1.1.2.1 Quantum Electrodynamic theory
1.1.2.2 Electroweak theory
1.1.3 Quantum Chromodinamic theory
1.1.4 The Higgs mechanism
1.1.4.1 Higgs boson production
1.1.4.2 Higgs boson Couplings
1.1.4.3 Higgs boson decay
1.1.5 Discovery of the Higgs boson
1.2 Top quark physics
1.2.1 Top quark production
1.2.2 Single top quark production
1.2.3 Top quark decays
1.2.4 Top quark properties
1.2.4.1 Top quark mass
1.2.4.2 Electric charge
1.2.4.3 Helicity of W boson
1.2.4.4 Spin correlation
1.2.4.5 Yukawa coupling
1.2.5 tt Higgs associated production
2 Accelerator and Detector 
2.1 LHC accelerator
2.2 ATLAS detector
2.2.1 Overview
2.2.2 Magnetic System
2.2.3 Inner detector
2.2.4 Calorimeters
2.2.4.1 The electromagnetic calorimeter
2.2.4.2 The hadronic calorimeter
2.2.4.3 The forward calorimeter
2.2.5 Muon Spectrometer
2.3 Trigger system
2.4 Computing
3 ATLAS Trigger system 
3.1 ATLAS trigger infrastructure
3.1.1 First Level Trigger (LVL1)
3.1.2 Second Level Trigger (LVL2)
3.1.3 Event Filter (EF)
3.2 Trigger objects
3.2.1 Jet trigger objects
3.2.2 L1.5 Jet Trigger
3.2.3 Jet trigger performance
3.2.4 Tracking objects
3.2.5 Muon trigger objects
3.3 On-line b-tagging algorithm
3.3.1 The role of the b-tagging in physics analyses
3.3.2 b-jet trigger implementation
3.3.2.1 Primary vertex reconstruction
3.3.2.2 b-tagging discriminant variables
3.3.2.3 JetProb method
3.3.2.4 The likelihood-ratio method
3.3.2.5 The SV1 algorithm
3.3.2.6 The combined algorithm
3.3.2.7 b-jet trigger rate
3.3.3 -in-jet trigger
3.4 Trigger Monitoring
3.4.1 Data Quality Monitoring online
3.4.1.1 DQMD for the b-jet signature
3.4.2 Online Histogram Presenter
3.4.3 Oine DQMF framework
3.4.3.1 -jet trigger
3.5 Conclusion
4 Measurement of the tt production cross section in the fully hadronic nal state 
4.1 The tt fully hadronic channel topology
4.2 Data and Monte Carlo datasets
4.3 Data and MC treatment at pre-analysis level
4.3.1 Pile-up
4.4 Object identification and selection
4.4.1 Jets
4.4.1.1 Jet vertex fraction
4.4.2 Lepton and missing transverse momentum
4.4.2.1 Electrons
4.4.2.2 Muons
4.4.2.3 Missing Transverse Energy
4.4.3 O,ine identification of b-jets
4.5 Event Selection
4.6 Characterization of the background sources to the tt fully hadronic events
4.6.1 W and Z boson production
4.6.2 tt non hadronic background
4.6.3 Multi-jet QCD background
4.7 Kinematic Fit Likelihood
4.7.1 Top mass distribution
4.8 Multi-jet QCD background modeling
4.9 Minimum 2 discriminant
4.10 Event Probability
4.11 Cross-section measurement
4.12 Control Plots for the main kinematic variables
4.13 Systematic uncertainties
4.13.1 Jet energy scale (JES) and the associated uncertainty
4.13.1.1 Flavour composition and response
4.13.1.2 b-jet energy scale (b-JES)
4.13.1.3 Close by jets
4.13.1.4 Pile-up
4.13.2 Jet reconstruction eciency (JRE)
4.13.3 Jet energy resolution (JER)
4.13.4 Trigger eciency
4.13.5 b-tagging eciency and mistag rate
4.13.6 Theoretical Uncertainty
4.13.6.1 Initial and Final State Radiation (ISR and FSR)
4.13.6.2 Parton Distribution Function (PDF)
4.13.6.3 Parton shower and generator uncertainties
4.13.7 Luminosity
4.13.8 Background modelling
4.14 Summary of systematic uncertainties
4.15 Final results for tt cross section measurement in the fully hadronic nal state
5 Search for associated Higgs boson production together with tt pairs
5.1 Motivation
5.2 Previous results on the search for ttH (H ! b b)
5.3 Background contributions
5.4 Data and MC simulation samples
5.5 The fully hadronic ttH(H ! b b) event topology
5.6 Event Selection
5.7 ttHTopology reconstruction
5.8 QCD multi-jets background estimation: \ABCD » method
5.9 Multivariate (MVA) technique
5.10 Application of \ABCD » method to the ttH (H ! b b) analysis
5.10.1 ttH(H ! b b) validation and discriminant variable distributions
5.11 Systematic uncertainties
5.11.1 Luminosity
5.11.2 Jet energy scale
5.11.3 Jet energy resolution and Jet reconstruction eciency
5.11.4 Heavy avour tagging
5.11.5 ttH modelling
5.11.6 Discussion on QCD multi-jet background systematic
5.12 Conclusion
Conclusions

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