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JHEP08(2018)089

Published for SISSA by Springer

Received: May 7, 2018

Revised: July 23, 2018

Accepted: August 6, 2018

Published: August 16, 2018

Measurements of b-jet tagging eﬃciency with the

ATLAS detector using t

t events at

√

s = 13 TeV

The ATLAS collaboration

E-mail: atlas.publications@cern.ch

Abstract: The eﬃciency to identify jets containing b-hadrons (b-jets) is measured us-

ing a high purity sample of dileptonic top quark-antiquark pairs (t

t) selected from the

36.1 fb

−1

of data collected by the ATLAS detector in 2015 and 2016 from proton-proton

collisions produced by the Large Hadron Collider at a centre-of-mass energy

√

s = 13 TeV.

Two methods are used to extract the eﬃciency from t

t events, a combinatorial likelihood

approach and a tag-and-probe method. A boosted decision tree, not using b-tagging infor-

mation, is used to select events in which two b-jets are present, which reduces the dominant

uncertainty in the modelling of the ﬂavour of the jets. The eﬃciency is extracted for jets

in a transverse momentum range from 20 to 300 GeV, with data-to-simulation scale fac-

tors calculated by comparing the eﬃciency measured using collision data to that predicted

by the simulation. The two methods give compatible results, and achieve a similar level

of precision, measuring data-to-simulation scale factors close to unity with uncertainties

ranging from 2% to 12% depending on the jet transverse momentum.

Keywords: Hadron-Hadron scattering (experiments)

ArXiv ePrint: 1805.01845

Open Access, Copyright CERN,

for the beneﬁt of the ATLAS Collaboration.

Article funded by SCOAP

https://doi.org/10.1007/JHEP08(2018)089

JHEP08(2018)089

approach, referred to as the Likelihood method (LH), which is based upon a method used

during Run 1 (

√

s = 7 TeV and

√

s = 8 TeV) of the LHC [3]. Having two methods enables

reciprocal cross-checks to be made between them.

The b-jet tagging eﬃciency, ε

, is measured for jets in the pseudorapidity

range

|η| < 2.5 and with transverse momentum p

> 20 GeV for several operating points (OP).

Operating points are deﬁned by sets of selection criteria imposed upon the output of the

b-tagging algorithm designed to provide a certain b-jet tagging eﬃciency. Four operating

points are deﬁned, corresponding to 60%, 70%, 77% and 85% b-jet tagging eﬃciencies in

simulated t

t events. Two sets of four operating points are implemented to provide a single-

cut or a ﬂat-eﬃciency operating point. The single-cut operating point provides the stated

b-jet tagging eﬃciency when averaged over the transverse momentum distribution of b-jets

in t

t events, but the eﬃciency varies with jet p

. On the other hand, the ﬂat-eﬃciency

operating point has a varying cut value, ensuring a constant b-jet tagging eﬃciency as a

function of the jet p

. Results are also presented in the form of data-to-simulation eﬃciency

scale factors, deﬁned as ε

data

/ε

sim

, where ε

data

is the eﬃciency measured in data, while

sim

represents the eﬃciency predicted by simulation using Monte Carlo (MC) generator-

level information. In physics measurements, these scale factors can be applied jet by jet

to correct the rate of events after applying a b-tagging requirement. The scale factors

are measured for all operating points; however, this paper presents only results from a

number of selected working points as examples. Separate measurements have also been

made for the tagging eﬃciencies of jets containing c-hadrons, referred to as c-jets, and for

jets containing neither a b-hadron nor a c-hadron, referred to as light-ﬂavour jets, and are

presented in ref. [3].

The paper is organised as follows. In section 2, the ATLAS detector and physics

object reconstruction are described. Section 3 contains a description of the ATLAS b-

tagging algorithms. In section 4, the data and simulated samples used in the b-jet tagging

eﬃciency measurements are presented. Section 5 summarises the event selection criteria

applied for both calibration methods, while in section 6 the T&P and LH methods are

presented in detail. In section 7, the systematic uncertainties for each method are outlined,

and results are presented in section 8. Finally, conclusions are given in section 9.

2 The ATLAS detector and object reconstruction

The ATLAS detector [1] at the LHC covers nearly the entire solid angle around the collision

point. The detector comprises an inner tracking detector surrounded by a superconducting

solenoid producing a 2 T axial magnetic ﬁeld, a system of calorimeters, and a muon spec-

trometer (MS) incorporating three large toroid magnet assemblies. The inner detector (ID)

consists of four layers of silicon pixel sensors and four layers of silicon microstrip sensors,

ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in

the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre

of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r, φ) are used in the transverse

plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is deﬁned in terms of the polar

angle θ as η = − ln tan(θ/2). The angular distance ∆R is measured in η–φ phase space and is deﬁned as

(∆η)

+ (∆φ)

, where ∆η and ∆φ are the diﬀerences between the φ and η of the two objects respectively.

– 2 –

JHEP08(2018)089

providing precision tracking in the pseudorapidity range |η| < 2.5. The innermost pixel

layer, referred to as the insertable B-layer (IBL) [4, 5], was installed between Run 1 and

Run 2 of the LHC. The IBL provides a hit measurement at an average radius of 33.3 mm,

signiﬁcantly closer to the interaction point than the closest pixel layer in Run 1 (radius of

50.5 mm). The additional pixel layer has a signiﬁcant impact on the performance of both

the tracking and vertexing algorithms, resulting in improved b-tagging performance. A

straw-tube transition radiation tracker complements the measurements in the silicon layers

by providing additional tracking and electron identiﬁcation information for |η| < 2.0.

High-granularity electromagnetic (EM) and hadronic sampling calorimeters cover the

region |η| < 4.9. All electromagnetic calorimeters, as well as the endcap and forward

hadronic calorimeters, use liquid argon as the active medium and lead, copper, or tungsten

absorber. The central hadronic calorimeter uses scintillator tiles as the active medium and

steel absorber. The muon spectrometer measures the deﬂection of muons with |η| < 2.7

using multiple layers of high-precision tracking chambers located in a toroidal ﬁeld of

approximately 0.5 T or 1 T in the central and endcap regions of ATLAS, respectively.

The ATLAS detector incorporates a two-level trigger system, with the ﬁrst level im-

plemented in custom hardware and the second level implemented in software. This trigger

system reduces the output from the detector electronics to about 1 kHz for oﬄine storage.

Vertices are reconstructed using tracks measured by the inner detector [6]. Events

are required to have at least one reconstructed vertex, with two or more associated tracks

which have p

> 400 MeV. The primary vertex is chosen as the vertex candidate with the

largest sum of the squared transverse momenta of associated tracks.

Electrons are reconstructed from energy deposits (clusters) in the electromagnetic

calorimeter matched to tracks reconstructed in the ID [7, 8]. Additionally, candidate clus-

ters in the calorimeter barrel/endcap transition region, deﬁned by 1.37 < |η

cluster

| < 1.52,

as well as those of poor quality, are excluded. Muons are reconstructed from track seg-

ments in the MS that are matched to tracks in the ID [9, 10]. Combined muon tracks

are then re-ﬁt using information from both the ID and MS systems. The lepton tracks

must be consistent with coming from the primary vertex of the event: the longitudinal im-

pact parameter z

must satisfy |z

sin θ| < 0.5 mm, while the transverse impact parameter

signiﬁcance, |d

|/σ(d

) must be less than 5 for electrons or less than 3 for muons. To re-

duce the contribution from hadronic decays (non-prompt leptons), photon conversions and

hadrons misidentiﬁed as leptons, both the electrons and muons must also satisfy isolation

and identiﬁcation criteria. The loose, medium and tight working points of the isolation and

identiﬁcation algorithms are deﬁned in ref. [8] for electrons, and in ref. [10] for muons. Two

types of leptons are deﬁned for the analyses presented in this paper. First, signal lepton

candidates are required to have p

> 27 GeV and |η| < 2.5, as well as to satisfy tight track-

and calorimeter-based isolation criteria. Signal electrons (muons) are required to pass the

medium electron (muon) identiﬁcation criteria. Second, loose leptons are required to have

> 7 GeV and |η| < 2.5, as well as to satisfy loose identiﬁcation and loose track-only

isolation criteria.

Jets are reconstructed from three-dimensional topological energy clusters [11] in the

calorimeter using the anti-k

algorithm [12] with a radius parameter of R = 0.4. These

– 3 –

JHEP08(2018)089

jets are referred to as calorimeter-jets. The clusters are calibrated to the electromagnetic

energy response scale prior to jet reconstruction. The reconstructed jets are then calibrated

to the jet energy scale (JES), corresponding to the particle scale,

using corrections derived

from simulation and in situ corrections based on 13 TeV data [13]. Jets are required to have

calibrated p

> 20 GeV and to be within the acceptance of the inner detector, |η| < 2.5.

Jet cleaning criteria are applied to identify jets arising from non-collision sources or noise

in the calorimeter [14, 15]. Any event containing such a jet is removed. In order to reduce

the contamination from jets arising from additional pp collisions in the same or nearby

bunch crossings, called pile-up, a requirement on the Jet Vertex Tagger (JVT) [16] output

is made. The JVT algorithm combines tracking information into a multivariate algorithm

to reject jets which do not originate from the primary vertex, and is applied to jets with

< 60 GeV and |η| < 2.4. Jets with p

> 60 GeV are assumed to have originated from

the primary vertex.

Jets are also reconstructed from inner-detector tracks using the anti-k

algorithm with

a radius parameter of R = 0.2. These jets are referred to as track-jets. The tracks used

in jet clustering are required to have p

> 0.5 GeV and to be matched to the primary

vertex using impact parameter requirements on the tracks. Only track-jets with at least

two tracks and with p

> 10 GeV and |η| < 2.5 are considered for the purposes of the

b-jet tagging eﬃciency measurement. The results presented in this paper correspond to

the jets reconstructed from the topological energy clusters in the calorimeter, which are

referred to as jets throughout. Equivalent b-jet eﬃciency measurements are also performed

for track-jets and the results made available to ATLAS analyses using those jets.

In order to avoid counting a single detector response as originating from two diﬀerent

objects, an overlap removal procedure is applied to the jet candidates and leptons pass-

ing the loose quality requirement. To prevent double-counting of electron energy deposits

reconstructed as jets, the closest jet lying ∆R < 0.2 from a selected electron is removed.

Electron candidates that lie ∆R < 0.4 from a jet surviving the selection are discarded to

reduce the background from electrons that originate from heavy-ﬂavour decays. Further-

more, to reduce the background from muons that originate from the decays of hadrons

containing a heavy quark inside selected jets, muon candidates are removed if they are

separated from the nearest selected jet by ∆R < 0.4. However, if this jet has fewer than

three associated tracks, the muon is kept and the jet is removed as it is likely that the

energy is deposited in the calorimeter by the muon.

The missing transverse momentum (with magnitude E

miss

) is deﬁned as the negative

vector sum of the transverse momenta of all selected and calibrated physics objects in the

event, with an extra “soft” term added to account for low-momentum contributions from

particles in the event that are not associated with any of the selected objects. This term is

calculated using inner-detector tracks matched to the primary vertex to reduce the pile-up

contamination [17].

The particle scale is deﬁned as consisting of stable particles emerging from the p-p collision before

interaction with the ATLAS detector.

– 4 –

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