ATLAS Pixel Detector Upgrade The Insertable B-Layer David Bertsche - - PowerPoint PPT Presentation

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Introduction Motivation Requirements Engineering Commissioning

ATLAS Pixel Detector Upgrade

The Insertable B-Layer David Bertsche November 8th, 2012

ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning

Introduction

◮ Experimental High Energy Physics (HEP) is done using particle accelerators and

detectors.

◮ The OU HEP group is part of the ATLAS detector collaboration. ◮ The innermost section suffers heavy radiation damage - thus the upgrade. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning Top Physics Higgs Studies

Motivation: b Physics

Figure: http://CPEPweb.org

◮ Free quarks hadronize into a collimated spray of particles called a jet. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning Top Physics Higgs Studies

Top Physics

Figure: t → Wb and subsequent decays

◮ Free top quarks have a lifetime of

∼10−25 s, not enough time to hadronize (∼10−23 s).

◮ The SM t → Wb branching fraction is

∼100%.

◮ b tagging efficiency will remove a large

amount of background for top physics (such as W +n jets and QCD).

◮ Observing a different branching fraction

could lead to physics beyond the SM.

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Introduction Motivation Requirements Engineering Commissioning Top Physics Higgs Studies

Higgs Studies

Figure: Theoretial Standard Model Higgs Boson branching ratios, including theoretical uncertainties. Figure: Experimental Higgs Boson branching ratios.

◮ If the SM Higgs mass is indeed ∼125 GeV, H → b¯

b is the dominant decay mode

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

LHC Accelerator

p-p Design Parameters:

◮ Max Energy = 14TeV ◮ 1.15×1011 particles per bunch ◮ 25 ns between bunch crossings ◮ 19 collisions per crossing (avg) ◮ Luminosity = 1034cm−2s−1

These parameters are unprecedented, requiring faster radiation-hard electronics.

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

The ATLAS Detector

◮ ATLAS > Inner Detector > Pixel Detector ◮ 4π solid angle coverage ◮ z points along beam, x to LHC ring center

and y vertically

ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

The ATLAS Inner Detector

◮ Functions are tracking and

vertexing

◮ The Insertable B-Layer (IBL)

will be the innermost layer of the detector.

◮ The IBL specializes in

identifying interaction vertices.

◮ 2 T solenoidal magnetic field

curves charged particle trajectory.

◮ Pixel Detector ◮ Silicon Microstrip Tracker

(SCT)

◮ Transition Radiation Tracker

(TRT)

Figure: Cut-away view of the Inner Detector.

ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

Radiation Passage Through Matter

◮ Particles are detected by the energy they deposit in the detector. ◮ Multiple scattering and energy loss should be minimized in the Inner Detector. ◮ Charged heavy particles primarily experience elastic collisions with electrons as

described by the Bethe-Bloch formula: dE dx = 2πNor2

e mec2ρ Zz2

Aβ2

• ln

2meγ2v2Wmax I 2

• − 2β2 − δ − 2 C

Z

• ∝ 1

β2 ln(const·β2γ2)

Figure: A charged pion traveling through

• silicon. (The dotted line shows density and

shell correction terms.)

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

Tracking

◮ The momentum and charge of a particle are determined from the track curvature.

Figure: First stable beam collision in with the ID fully powered. Figure: Multiple scattering worsens the momentum resolution.

ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

Vertexing and Impact Parameter Measurement

Figure: The Impact Parameter (IP) is determined from the distance of closest approach to the primary vertex. Figure: Vertices and Jets

◮ IBL improves primary vertex reconstruction resolution from 15 µm to 11 µm (in

x-y) and from 34 µm to 24µm (in z).

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

b Tagging

Figure: The Impact Parameter sign is determined from the relative geometry of the primary and secondary vertices. Figure: Relative transverse momentum can be used to differentiate between b and c jets.

◮ Up, down and strange quarks create light jets which cannot usually be

distinguished from each other.

◮ Jets from charm quarks are sometimes grouped with light jets and sometimes

uniquely identified.

◮ b hadrons (lifetime ∼10−12 s) can travel a few mm. b jets have a secondary

vertex with a large positive IP.

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

b Tagging

Figure: Jet tagging weight distribution. Figure: Tagging efficiency must be balanced against light jet rejection.

◮ Computer algorithms are used to b tag, their parameters are adjusted with the

goal of maximizing efficiency while minimizing the number of jets erroneously b tagged.

◮ Typical efficiencies are 60%-70% with a mistag rate of ∼1%. ◮ Algorithms are tested and optimized using Monte Carlo simulations of detector

events. Efficiency = # of jets that were b tagged actual # of b jets

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

IBL Design Requirements

Primary motivation: Alleviate radiation damage and to provide improved measurement accuracy. Long term motivation: Prepare for the High Luminosity LHC (HL-LHC), planned in 2020.

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

IBL Design Requirements

Primary motivation: Alleviate radiation damage and to provide improved measurement accuracy. Long term motivation: Prepare for the High Luminosity LHC (HL-LHC), planned in 2020. Luminosity Requirements: With increased luminosity comes increased pileup and

• ccupancy

◮ Both are decreased by faster readout speed, smaller pixel size, and improved

vertexing and track reconstruction.

◮ IBL Increases B-layer lifetime integrated luminosity from 300 fb−1 to 550 fb−1. ◮ IBL Increases ID peak design luminosity from 1×1034 cm−2s−1 to 3×1034

cm−2s−1.

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Introduction Motivation Requirements Engineering Commissioning LHC Inner Detector Tracking b Tagging Design

IBL Design Requirements

Primary motivation: Alleviate radiation damage and to provide improved measurement accuracy. Long term motivation: Prepare for the High Luminosity LHC (HL-LHC), planned in 2020. Luminosity Requirements: With increased luminosity comes increased pileup and

• ccupancy

◮ Both are decreased by faster readout speed, smaller pixel size, and improved

vertexing and track reconstruction.

◮ IBL Increases B-layer lifetime integrated luminosity from 300 fb−1 to 550 fb−1. ◮ IBL Increases ID peak design luminosity from 1×1034 cm−2s−1 to 3×1034

cm−2s−1. Novel engineering solutions developed:

◮ Tight tolerances and clearances - no module overlap in z and sensors with thin

edges.

◮ Minimizing materials - thin sensor design, low density carbon foam staves, CO2

evaporative cooling and aluminum electrical conduits.

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Solid State Detectors

◮ The p-n junction diode is the building block of solid state detectors. ◮ The depleted junction region is useful. ◮ It is expanded by applying a reverse bias voltage. ◮ Ionizing radiation excites electrons from the valence band into the conduction

band, leaving a hole behind.

◮ Collected electrons are processed into a signal. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Pixel Detector Module

Figure: One cell. Figure: Sensor bump bonded to readout electronics.

◮ The sensor bulk is divided into many pixels. ◮ Electrons transferred to the electronics chip through a conducting bump bond. ◮ Proximity of sensor and FE chip allows for high readout speeds. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Sensor Design

Figure: n-in-n sensor design. Figure: Double-sided slim edge 3D sensor design.

◮ Planar thin edge n-in-n sensors for the low η region. ◮ 3D thin edge sensors for the high η region. ◮ n-in-n sensor design allows operation at less than full depletion voltage. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Readout Electronics

Figure: The FE-I4 chip is improved from the FE-I3 chip used on the ID. Figure: Calculation of time over threshold (ToT).

◮ Charge is collected, amplified and digitized into ToT. ◮ Hit data are stored in a buffer. ◮ 99.75% of the hits will not pass triggers. ◮ Cluster data retrieved to enhance tracking resolution. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Radiation Hardness

Radiation damage: displaces and transmutes atoms in the sensor material bulk. These defects can absorb, generate and delay charge carriers.

◮ Increases the leakage current. ◮ Reduces detection efficiency. ◮ Increases the necessary bias voltage. ◮ Leads to type inversion.

Can be addressed by:

◮ Adding oxygen impurities to the sensor bulk. ◮ Room temperature annealing for about a week. ◮ n-in-n sensor design.

Figure: Before (a) and after (b) type inversion. The sensor can be operated while only partially depleted.

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Staves

Figure: Schematic showing an z cross-section of the stave design. The coverage gap in the z direction is minimized by using sensors with slim edges. Figure: Schematic showing an x-y cross-section of the stave design.

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Layout

Figure: Schematic showing an x-y cross-section of the IBL design. Figure: CAD model showing an x-y cross-section of the IBL design.

◮ Free space of 8.5 mm presently exists. Beam pipe reduced from 29 mm to 25

• mm. IBL will be inserted into 12.5 mm radial space.

◮ Full hermetic coverage in φ by tilting the staves by about 27◦. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Supporting Hardware

Figure: CAD model showing an x-y cross-section of the IBL service. Figure: Service for one stave.

◮ Cooling fluid (CO2) will maintain

temperature of -15◦C to reduce noise and thermal variation.

◮ Copper-clad aluminum wires are

used for LV supply to minimize radiation length of the electrical service material.

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Manufacturing

Figure: CAD model showing an x-y cross-section of the IBL design.

◮ Wafers are thinned and diced. ◮ Sensor and FE reflow bump bonded. ◮ Flex and wire bonds added to form

module.

◮ Modules attached to staves with

integrated connections.

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Introduction Motivation Requirements Engineering Commissioning Detector Layout Support Manufacturing Installation

Installation

Figure: The present (a) and future (b) beam pipe and pixel detector. Figure: Installation tooling

◮ ATLAS end caps removed to gain access to the ID. ◮ A 7.3 m section of the existing beryllium beam pipe will be removed. ◮ Special tooling has been developed for disconnecting associated supports, flanges,

collars and wires.

◮ An IBL Support Tube (IST) will first be inserted. ◮ Each step will first be tested on a full scale mock-up of the Pixel Detector ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning

Commissioning

◮ Test the cooling system and communication links. ◮ Measure the leakage current, depletion voltage and bump connectivity. ◮ Calibrate the discriminator threshold. ◮ Test data flow with random noise triggers. ◮ Preliminary alignment with cosmic ray data. ◮ After installation the IBL will function as part of the Pixel Detector, sharing the

same data processing technology and software.

Figure: ATLAS cosmic ray event

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Introduction Motivation Requirements Engineering Commissioning

Conclusion

◮ b tagging is essential for ATLAS physics goals. ◮ Radiation damage seriously deteriorates the Pixel Detector. ◮ The IBL will restore full vertexing functionality and improve resolution. ◮ Many novel engineering solutions were developed. ◮ Installation planned for mid 2013. ◮ OU students at CERN are working on the IBL. ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Introduction Motivation Requirements Engineering Commissioning

Bibliography

The ATLAS Collaboration, “The ATLAS Experiment at the CERN Large Hadron Collider,” JINST 3 S08003, (2008).

• T. Aaltonen et al. [CDF and D∅ Collaborations], “Evidence for a particle

produced in association with weak bosons and decaying to a bottom-antibottom quark pair in Higgs boson searches at the Tevatron,” Phys. Rev. Lett. 109, 071804 (2012). The ATLAS Collaboration, “ATLAS Insertable B-Layer Technical Design Report,” ATLAS-TDR-19, (2010).

• R. Kehoe, M. Narain and A. Kumar, “Review of Top Quark Physics Results,” Int.
• J. Mod. Phys. A 23, 353 (2008).
• L. Evans and P. Bryant, “LHC Machine,” JINST 3, S08001 (2008).
• J. Beringer et al. (Particle Data Group), “The Review of Particle Physics,” Phys.
• Rev. D86, 010001 (2012).
• G. Aad et al. [ATLAS Collaboration], “Expected Performance of the ATLAS

Experiment - Detector, Trigger and Physics,” (2008).

• G. Lutz, Semiconductor Radiation Detectors, Springer, Germany, (1999).
• L. Rossi et al., Pixel Detectors, Springer, The Netherlands, (2006).
• M. Karagounis et al., “Development of the ATLAS FE-I4 pixel readout IC for

b-layer Upgrade and Super-LHC,” TWEPP proceedings, (2008).

• M. Lindner et al., “Comparison of hybrid pixel detectors with Si and GaAs

sensors,” Nuclear Inst. and Methods in Phys. Research A 466, 1 (2001).

• T. Rohe, “Sensor Concepts for Pixel Detectors in High Energy Physics.”,

www.slac.stanford.edu/econf/C020909/trpaper.pdf

• G. Steinbruck “Top Quark Physics: Flavor Physics from the Tevatron to the LHC

DESY summer student lectures” (2011).

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Backup Slides

Calculation of t → Wb branching ratio: R = B(t→Wb)

B(t→Wq) = |Vtb|2 |Vtb|2+|Vts|2+|Vtd |2

Where: | Vtb | 0.999100+0.000034

−0.000004

Giving: R >0.88 at 68%C.L. and R >0.79 at 95%C.L.

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Introduction Motivation Requirements Engineering Commissioning

Bethe-Bloch formula is given by; dE dx = 2πNor2

e mec2ρ Zz2

Aβ2

• ln

2meγ2v2Wmax I 2

• − 2β2 − δ − 2 C

Z

• .

where 2πNor2

e mec2 = 0.1535 MeVc2/g;

x is the path length in g/cm2; re =

e2 4πmec2 = 2.817 × 10−13 cm and is the classical electron radius;

me is the electron mass; No = 6.022 × 1023mol−1 and is Avogadro’s number; I is the effective ionization potential averaged over all electrons; Z is the atomic number of the medium; A is the atomic weight of the medium; ρ is the density of the medium; z is the charge of a traversing particle; β = v

c , the velocity of the traversing particle in units of the speed of light;

γ =

1

√

1−β2 ;

δ is a density correction; C is a shell correction; and Wmax =

2mec2βγ2 1+2 me

M

• 1+β2γ2+( me

M )2 is the maximum energy transfer possible in a single

collision.

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Introduction Motivation Requirements Engineering Commissioning

Total Energy Loss of Electrons

Since electrons are light the Bethe-Bloch formula is altered: dE dx = 2πNor2

e mec2ρ Z

Aβ2

• ln

meβ2c2γ2Wmax I 2

• + F(γ)
• Bremsstrahlung occurs if

particles are accelerated by a Coulomb field.

dE dx ∝ E m2

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Introduction Motivation Requirements Engineering Commissioning

• V. Bartsch et al., “An algorithm for calculating the Lorentz angle in silicon detectors,”

arXiv:physics/0204078 [physics.ins-det], (2002).

ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)

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Performance of the ATLAS Transition Radiation Tracker

Kevin Finelli, on behalf of the ATLAS collaboration

Duke University International Conference on High Energy Physics, University of Melbourne, 4-11 July 2012 Abstract

The ATLAS Transition Radiation Tracker (TRT) is an integral subsystem for precision tracking at

• ATLAS. In addition, transition radiation signa-

tures allow for particle identification capabilities. Monitoring the performance of the TRT helps es- tablish the necessary foundation for understand- ing higher level tracking reconstruction and parti- cle identification. We present our current studies

• n how the TRT is performing, in particular as

the number of interactions per bunch crossing in- creases.

The ATLAS Inner Detector

Figure 1: The ATLAS inner detector

The inner detector consists of the silicon pixel, sil- icon strip, and transition radiation tracker subde-

• tectors. The TRT’s role in tracking is to provide a

large lever-arm to complement the semiconductor trackers closer to the beamline. The TRT also pro- vides a vital component in particle identification through the application of transition radiation.

Figure 2: pT resolution of the inner detector, illustrating the importance of the TRT at high momentum.

TRT Overview

Figure 3: Depiction of gas ionization and transition radiation by electron and pion tracks in a view transverse to beam direction.

The TRT is the outermost component of the inner detector, consisting of a barrel and two end-cap partitions. Immersed in a 2T magnetic field, it provides tracking and particle identification coverage out to |η| < 2.0.

◮4mm-diameter Kapton straws filled with Xe/CO2/O2 gas provide tracking coverage. As

charged particles pass through the straws, they ionize the gas and electrons collect on the wires at the straw center.

◮The space between straws is filled with radiator material, the surfaces of which provide

interfaces of different indices of refraction which can lead to the emission of transition radiation as a particle traverses these interfaces. This in turn is used for particle identification (see below).

Performance at High Pileup

Recent run conditions provide increased challenges for tracking in the inner detector. As instantaneous luminosity increases, the number of interactions per bunch-crossing (µ) will also increase, leading to increased detector occupancy. µ is a measure of both in-time and out-of-time pileup, and depends proportionally on the instantaneous luminosity. For example, in 2011 data, µ = 22 corresponds to L ≈ 6 × 1033 cm−2s−1.

Number of primary vertices 1 2 3 4 5 6 7 8 9 : Position Residual [mm] σ 0.12 0.121 0.122 0.123 0.124 0.125 > 10 GeV

T p Data

ATLAS Preliminary

Figure 4: Position residuals

• f

TRT tracks as a function of the number of primary vertices. Figure 5: The frac- tion of TRT track hits that are precision hits versus µ. Non- precision hits are due to overlapping tracks, poorly measured drift times, and out-of-time pileup. Figure 6: The fraction

• f tracks found in the

silicon that have ex- tensions found in the TRT as a function of µ. Figure 7: HT frac- tion for electron candi- dates passing through the TRT barrel and end-cap wheel A as a function of µ

LB,BCID >| µ < 5 10 15 20 25 30 35 40 HT Fraction 0.2 0.25 0.3 0.35 0.4 0.45 0.5

=8 TeV) s Data 2012 ( Simulation |<1.07 η 0.625<|

• 1

dt L = 535 pb

∫

ATLAS Preliminary

• 4

10 × 0.38) ± Slope of linear fit to Simulation: (8.87

• 4

10 × 1.70) ± Slope of linear fit to Data: (6.55

Studies in high pileup conditions indicate that tracking becomes inherently more difficult when detector occupancy reaches high levels; position residuals increase and the number of precision hits decreases with increasing µ. Despite high pileup conditions, the TRT is continuing to perform well in tracking and electron identification, indicated by the extension fraction and high threshold fraction remaining relatively flat.

Signal Digitization

Figure 8: Dia- gram depicting the digitization

• f

a TRT low threshold signal from a single straw.

TRT tracking information is read out in 24 time bins of 3.12 ns using a low threshold (LT) of 300

• eV. In addition, electron identification information

is read out in 3 time bins of 25 ns using a high threshold (HT) of 6 keV.

Electron Identification

Figure 9: HT turn-on curve for the TRT barrel region.

The probability of emitting transition radiation depends on a particle’s relativistic gamma factor. We use the fraction of hits with a HT bit to dis- criminate between high γ and low γ particles, pro- viding an effective means of distinguishing elec- trons from heavier particles like pions.

Figure 10: Fraction of HT hits

• n

track for electron and pion candidates in the TRT barrel region.

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b-tagging efficiencies in data and simulation (top) and the corresponding scaling factors (bottom) for the SV0 tagging algorithm at 50 % signal efficiency [1].

Dominik Duda*

• n behalf of the ATLAS collaboration

*Bergische Universität Wuppertal

Measuring the b-jet tagging efficiency using top anti-top events with ATLAS data wit

Introduction

Since the decay of a ttbar pair has a very clear signature and because of the fact that the top quark almost exclusively decays to a W boson and a b-quark, a sample of top anti-top events is ideal for calibrating the various b-tagging algorithms used in ATLAS analyses. A Likelihood fit is performed to estimate the b-tagging efficiency by assuming that the expected number of events containing n b-tagged jets is given by where i, j and k are the number of b-, c- and light- flavor jets before applying b-tagging, while i', j'

Tag counting method

〈N t

t〉= ∑i, j,k {{t  t⋅BF⋅At t⋅L⋅F ijk t  tN bkg⋅Fijk bkg} ×

∑i' j'k'=nCi

i'⋅b i'⋅1−b i−i'⋅C j j '⋅c j'⋅1−c j− j'⋅C k k'⋅b k'⋅1−light k−k' } The b-tag weight distribution for the uncorrected sample (unfilled histogram), for the estimated background sample (filled histogram) and the corrected distribution calculated from the difference (data points) [3].

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[1] The ATLAS Collaboration, “Calibrating the b-Tag Efficiency and Mistag Rate in 35 pb-1 of Data with the ATLAS Detector ”, ATLAS-CONF-2011-089. [2] The ATLAS Collaboration, “Expected performance of the ATLAS experiment: detector, trigger and physics", 2009. [3] https://twiki.cern.ch/twiki/bin/view/AtlasPublic/ FlavorTaggingPublicResults

Resources

The b-tagging efficiency can be estimated using the equation where , and are the fractions of b-, c- and light jets within the selected sample, while is the fraction of jets coming from the fake lepton background. The mistag efficiencies for charm and for light jets as well as the fractions

• f the various jet flavors are calculated using all the

selected events in simulation, while the tagging efficiency of the jets coming from the fake lepton background and the fraction of tagged jets are obtained from data. While in a dileptonic selection the b-jet purity is due to lower background contamination already up to 80 %, one has to apply a pre-tag in the lepton+jets selection to enrich the signal purity. The tagging efficiency is determined in case of the lepton+jets selection by using the leading jet (if the second leading jet is tagged)

• r the three subleading jets (if the leading jet is b-

tagged), while in the dileptonic case only the two leading jets are taken into account.

Kinematic selection method

Decay of an top anti-top pair in the lepton + jets channel (top) and the branching ratios into all possible final states (bottom).

The calibration results are presented in the form

• f data-to-simulation scale factors

in which the measured b-tagging efficiency is divided by the b-tagging efficiency in simulated

• events. Currently three different ttbar

calibration methods are in use, where both the lepton+jets and the dileptonic decay channels are considered [1] [2]. The kinematic fit method takes advantage of the event structure of the semileptonic ttbar decay by reconstructing both the hadronic and the leptonic top quark decay. The fit assigns the leading jets in the event to originate either from the W-boson or the b-quarks, and provides a probability measure that this is the correct

• assignment. When taking only the four leading jets

into account 12 various permutations are possible. Only the permutation with the lowest is chosen to form the ttbar candidate. The sample is futher purified by requiring that the jet assumed to be the b-jet on the hadronic side of the event is b-tagged, while the two jets assigned to the W-boson are required to not be b-tagged. The measurement of the b-tag efficiency is then performed on the jet assigned to be the b-jet on the leptonic side of the event.

Distribution of the χ2 value for the most important backgrounds, the correct and the wrong combinations [2]

This jet is however not always a b-jet due to the kinematic fit assigning the jets wrongly. The fraction of wrong combinations in the signal sample is estimated using an orthogonal background sample, where one of the jets associated to the W-boson is required to be b-

• tagged. The number of events in the

background sample with large fit are normalized to the corresponding number of events in the signal sample.The shape of the background sample is then used to estimate the fraction of background in the low region of the signal sample. The b-tag output weight distribution in this background-subtracted signal sample is then used to derive the b-tag efficiency in data.

Kinematic fit



2

flavor jets before applying b-tagging, while i', j' and k' represent the number of those jets after b-

• tagging. is the number of permutations

with =i,j,k for the three jet flavours. is the fraction of events (before tagging) containing i b- jets, j c-jets and k light-flavour jets. BF is the branching ratio, is the selection acceptance and L is the integrated luminosity. The b-tag efficiency can then be determined by fitting this expected n-tag distribution to that observed in data.

Fitted b-tagged jet multiplicity distribution superimposed on the observed distribution in the dilepton (left) and lepton+jets (right) tag counting measurements [1]. 2-dimensional contour for the measured b-tag efficiency and the top anti top cross section in the dilepton (left) and lepton+jets (right) tag counting measurements [1].

c

light

xb

xtag

xc

xlight x fake fake C

' ! ' !−'!



Fijk At

t



2



2

b

data / sim.= b data

b

sim.



b= 1 xb xtag−c xc−light xlight− fake x fake



2

ATLAS Pixel Detector Upgrade: The Insertable B-Layer (IBL)