Published for SISSA by

Springer

Received: January 21, 2015
Accepted: March 30, 2015
Published: April 21, 2015

The ATLAS collaboration
E-mail: atlas.publications@cern.ch
Abstract: Results of a search for H → τ τ decays are presented, based on the full setof proton-proton collision data recorded by the ATLAS experiment at the LHC during
2011 and 2012. The data correspond to integrated luminosities of 4.5 fb−1 and 20.3 fb−1 at√√centre-of-mass energies of s = 7 TeV and s = 8 TeV respectively. All combinations of
leptonic (τ → `ν ν̄ with ` = e, µ) and hadronic (τ → hadrons ν) tau decays are considered.
An excess of events over the expected background from other Standard Model processes
is found with an observed (expected) significance of 4.5 (3.4) standard deviations. This
excess provides evidence for the direct coupling of the recently discovered Higgs boson
to fermions. The measured signal strength, normalised to the Standard Model expectation, of µ = 1.43 +0.43−0.37 is consistent with the predicted Yukawa coupling strength in theStandard Model.
Keywords: Hadron-Hadron Scattering
ArXiv ePrint: 1501.04943

Open Access, Copyright CERN,
for the benefit of the ATLAS Collaboration.
Article funded by SCOAP3 .

doi:10.1007/JHEP04(2015)117

JHEP04(2015)117

Evidence for the Higgs-boson Yukawa coupling to tau
leptons with the ATLAS detector

Contents
2

2 The ATLAS detector and object reconstruction

3

3 Data and simulated samples

5

4 Event selection and categorisation
4.1 Event selection
4.2 Analysis categories
4.3 Higgs boson candidate mass reconstruction

7
7
11
13

5 Boosted decision trees

13

6 Background estimation
6.1 Background from Z → τ τ production
6.2 Background from misidentified leptons or hadronically decaying taus
6.3 Z → ee and Z → µµ background
6.4 W +jets background
6.5 Background from top-quark production
6.6 Diboson background
6.7 Contributions from other Higgs boson decays
6.8 Validation of background estimates

19
19
21
23
24
24
25
25
25

7 Systematic uncertainties
7.1 Experimental uncertainties
7.2 Background modelling uncertainties
7.3 Theoretical uncertainties

27
27
28
29

8 Signal extraction procedure32

9 Results

39

10 Cross-check with cut-based analysis

43

11 Conclusions

49

The ATLAS collaboration

58

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1 Introduction

1

Introduction

These measurements rely predominantly on studies of the bosonic decay modes,
H → γγ, H → ZZ ∗ and H → W W ∗ . To establish the mass generation mechanism forfermions as implemented in the SM, it is of prime importance to demonstrate the direct
coupling of the Higgs boson to fermions and the proportionality of its strength to mass [15].
The most promising candidate decay modes are the decays into tau leptons, H → τ τ , andbottom quarks (b-quarks), H → bb̄. Due to the high background, the search for decays
to bb̄ is restricted to Higgs bosons produced in modes which have a more distinct signature but a lower cross-section, such as H production with an associated vector boson.
The smaller rate of these processes in the presence of still large background makes theirdetection challenging. More favourable signal-to-background conditions are expected for
H → τ τ decays. Recently, the CMS Collaboration published evidence for H → τ τ decays
at a significance in terms of standard deviations of 3.2σ [16], and an excess corresponding
to a significance of 2.1σ in the search for H → bb̄ decays [17]. The combination of channels
provides evidence for fermionic couplings with a significance of 3.8σ [18]. The yield of
events in the search for H → bb̄ decays observed by the ATLAS Collaboration has a signal
significance of 1.4σ [19]. The Tevatron experiments have observed an excess corresponding
to 2.8σ in the H → bb̄ search [20].
In this paper, the results of a search for H → τ τ decays are presented, based on thefull proton-proton dataset collected by the ATLAS experiment during the 2011 and 2012
data-taking periods, corresponding to integrated luminosities of 4.5 fb −1 at a centre-of√√
mass energy of s = 7 TeV and 20.3 fb−1 at s = 8 TeV. These results supersede
the earlier upper limits on the cross section times the branching ratio obtained with the
7 TeV data [21]. All combinations of leptonic (τ → `ν ν̄ with ` = e, µ) and hadronic(τ → hadrons ν) tau decays are considered.1 The corresponding three analysis channels
are denoted by τlep τlep , τlep τhad , and τhad τhad in the following. The search is designed to besensitive to the major production processes of a SM Higgs boson, i.e. production via gluon
fusion (ggF) [22], vector-boson fusion (VBF) [23], and associated production (V H) with
V = W or Z. These production processes lead to different final-state signatures, which are
exploited by defining an event categorisation. Two dedicated categories are considered toachieve both a good signal-to-background ratio and good resolution for the reconstructed τ τinvariant mass. The VBF category, enriched in events produced via vector-boson fusion,
1

Throughout this paper the inclusion of charge-conjugate decay modes is implied.

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JHEP04(2015)117

The investigation of the origin of electroweak symmetry breaking and, related to this, theexperimental confirmation of the Brout-Englert-Higgs mechanism [1–6] is one of the prime
goals of the physics programme at the Large Hadron Collider (LHC) [7]. With the discovery
of a Higgs boson with a mass of approximately 125 GeV by the ATLAS [8] and CMS [9]collaborations, an important milestone has been reached. More precise measurements ofthe properties of the discovered particle [10, 11] as well as tests of the spin-parity quantum
numbers [12–14] continue to be consistent with the predictions for the Standard Model(SM) Higgs boson.

is defined by the presence of two jets with a large separation in pseudorapidity. 2 The
boosted category contains events where the reconstructed Higgs boson candidate has alarge transverse momentum. It is dominated by events produced via gluon fusion withadditional jets from gluon radiation. In view of the signal-to-background conditions, andin order to exploit correlations between final-state observables, a multivariate analysis
technique, based on boosted decision trees (BDTs) [24–26], is used to extract the final
results. As a cross-check, a separate analysis where cuts on kinematic variables are appliedis carried out.

The ATLAS detector and object reconstruction

The ATLAS detector [27] is a multi-purpose detector with a cylindrical geometry. It comprises an inner detector (ID) surrounded by a thin superconducting solenoid, a calorimetersystem and an extensive muon spectrometer in a toroidal magnetic field. The ID tracking system consists of a silicon pixel detector, a silicon microstrip detector (SCT), and atransition radiation tracker (TRT). It provides precise position and momentum measurements for charged particles and allows efficient identification of jets containing b-hadrons(b-jets) in the pseudorapidity range |η| < 2.5. The ID is immersed in a 2 T axial magnetic
field and is surrounded by high-granularity lead/liquid-argon (LAr) sampling electromagnetic calorimeters which cover the pseudorapidity range |η| < 3.2. A steel/scintillator tile
calorimeter provides hadronic energy measurements in the central pseudorapidity range(|η| < 1.7). In the forward regions (1.5 < |η| < 4.9), the system is complemented by two
end-cap calorimeters using LAr as active material and copper or tungsten as absorbers.
The muon spectrometer (MS) surrounds the calorimeters and consists of three large superconducting eight-coil toroids, a system of tracking chambers, and detectors for triggering.
The deflection of muons is measured within |η| < 2.7 by three layers of precision drift
tubes, and cathode strip chambers in the innermost layer for |η| > 2.0. The trigger chambers consist of resistive plate chambers in the barrel (|η| < 1.05) and thin-gap chambers in
the end-cap regions (1.05 < |η| < 2.4).
A three-level trigger system [28] is used to select events. A hardware-based Level-1
trigger uses a subset of detector information to reduce the event rate to a value to 75 kHzor less. The rate of accepted events is then reduced to about 400 Hz by two software-based
trigger levels, Level-2 and the Event Filter.
The reconstruction of the basic physics objects used in this analysis is described in
the following. The primary vertex referenced below is chosen as the proton-proton vertex
candidate with the highest sum of the squared transverse momenta of all associated tracks.
Electron candidates are reconstructed from energy clusters in the electromagnetic
calorimeters matched to a track in the ID. They are required to have a transverse en2

The ATLAS experiment 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 direction. The x-axis points fromthe IP to the centre of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r, φ) are usedin the transverse (x, y) plane, φ being the azimuthal angle around the beam direction. The pseudorapidity
is defined p
in terms of the polar angle θ as η = − ln tan(θ/2). The distance ∆R in the η–φ space is definedas ∆R = (∆η)2 + (∆φ)2 .

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JHEP04(2015)1172

3

In the following, the τhad symbol always refers to the visible decay products of the τ hadronic decay.

–4–

JHEP04(2015)117

ergy, ET = E sin θ, greater than 15 GeV, to be within the pseudorapidity range |η| < 2.47,
and to satisfy the medium shower shape and track selection criteria defined in ref. [29].
Candidates found in the transition region between the end-cap and barrel calorimeters(1.37 < |η| < 1.52) are not considered. Typical reconstruction and identification efficiencies for electrons satisfying these selection criteria range between 80% and 90% dependingon ET and η.
Muon candidates are reconstructed using an algorithm [30] that combines informationfrom the ID and the MS. The distance between the z-position of the point of closest
approach of the muon inner-detector track to the beam-line and the z-coordinate of the
primary vertex is required to be less than 1 cm. This requirement reduces the contamination
due to cosmic-ray muons and beam-induced backgrounds. Muon quality criteria such as
inner detector hit requirements are applied to achieve a precise measurement of the muon
momentum and reduce the misidentification rate. Muons are required to have a momentum
in the transverse plane pT > 10 GeV and to be within |η| < 2.5. Typical efficiencies formuons satisfying these selection criteria are above 95% [30].
Jets are reconstructed using the anti-kt jet clustering algorithm [31, 32] with a radiusparameter R = 0.4, taking topological energy clusters [33] in the calorimeters as inputs.
Jet energies are corrected for the contribution of multiple interactions using a techniquebased on jet area [34] and are calibrated using pT - and η-dependent correction factors
determined from data and simulation [35–37]. Jets are required to be reconstructed in therange |η| < 4.5 and to have pT > 30 GeV. To reduce the contamination of jets by additional
interactions in the same or neighbouring bunch crossings (pile-up), tracks originating fromthe primary vertex must contribute a large fraction of the pT when summing the scalar pTof all tracks in the jet. This jet vertex fraction (JVF) is required to be at least 75% (50%)
for jets with |η| < 2.4 in the 7 TeV (8 TeV) dataset. Moreover, for the 8 TeV dataset, theJVF selection is applied only to jets with pT < 50 GeV. Jets with no associated tracks
are retained.
In the pseudorapidity range |η| < 2.5, b-jets are selected using a tagging algorithm [38].
The b-jet tagging algorithm has an efficiency of 60–70% for b-jets in simulated tt̄ events.
The corresponding light-quark jet misidentification probability is 0.1–1%, depending on
the jet’s pT and η.
Hadronically decaying tau leptons are reconstructed starting from clusters of energy
in the electromagnetic and hadronic calorimeters. The τhad 3 reconstruction is seeded by
the anti-kt jet finding algorithm with a radius parameter R = 0.4. Jet-specific cleaning
selection such as the JVF requirement is not needed for the tau candidate seeds, due tostricter vertex requirements. Tracks with pT > 1 GeV within a cone of radius 0.2 aroundthe cluster barycentre are matched to the τhad candidate, and the τhad charge is determinedfrom the sum of the charges of its associated tracks. The rejection of jets is provided in a
separate identification step using discriminating variables based on tracks with pT > 1 GeV
and the energy deposited in calorimeter cells found in the core region (∆R < 0.2) and in theregion 0.2 < ∆R < 0.4 around the τhad candidate’s direction. Such discriminating variables

3

Data and simulated samples

After data quality requirements, the integrated luminosities of the samples used are 4.5 fb −1√√
at s = 7 TeV and 20.3 fb−1 at s = 8 TeV.
Samples of signal and background events were simulated using various Monte Carlo(MC) generators, as summarised in table 1. The generators used for the simulation of thehard-scattering process and the model used for the simulation of the parton shower, of thehadronisation and of the underlying-event activity are listed. In addition, the cross section
values to which the simulation is normalised and the perturbative order in QCD of therespective calculations are provided.
The signal contributions considered include the three main processes for Higgs boson production at the LHC: ggF, VBF, and associated V H production processes. The
contributions from the associated tt̄H production process are found to be small and areneglected. The ggF and VBF production processes are simulated with Powheg [42–45]
interfaced to Pythia8 [46]. In the Powheg event generator, the CT10 [47] parameter-–5–

JHEP04(2015)117

are combined in a boosted decision tree and three working points, labelled tight, medium
and loose [39], are defined, corresponding to different τhad identification efficiency values.
In this analysis, τhad candidates with pT > 20 GeV and |η| < 2.47 are used. The τhadcandidates are required to have charge ±1, and must be 1- or 3-track (prong) candidates.
In addition, a sample without the charge and track multiplicity requirements is retained
for background modelling in the τhad τhad channel, as described in section 6.2. The identification efficiency for τhad candidates satisfying the medium criteria is of the order of
55–60%. Dedicated criteria [39] to separate τhad candidates from misidentified electrons
are also applied, with a selection efficiency for true τhad decays of 95%. The probability to
misidentify a jet with pT > 20 GeV as a τhad candidate is typically 1–2%.
Following their reconstruction, candidate leptons, hadronically decaying taus and jets
may point to the same energy deposits in the calorimeters (within ∆R < 0.2). Suchoverlaps are resolved by selecting objects in the following order of priority (from highest
to lowest): muons, electrons, τhad , and jet candidates. For all channels, the leptons thatare considered in overlap removal with τhad candidates need to only satisfy looser criteria
than those defined above, to reduce misidentified τhad candidates from leptons. The pT
threshold of muons considered in overlap removal is also lowered to 4 GeV.
miss ) is reconstructed using the
The missing transverse momentum (with magnitude ETenergy deposits in calorimeter cells calibrated according to the reconstructed physics objects (e, γ, τhad , jets and µ) with which they are associated [40]. The transverse momenta
miss calculation, with the energy depositedof reconstructed muons are included in the ET
by these muons in the calorimeters taken into account. The energy from calorimeter cells
not associated with any physics objects is scaled by a soft-term vertex fraction and also
miss calculation. This fraction is the ratio of the summed scalar p ofincluded in the ET
T
tracks from the primary vertex not matched with objects to the summed scalar pT of all
tracks in the event also not matched to objects. This method allows to achieve a more
miss in high pile-up conditions [41].
accurate reconstruction of the ET

Additional corrections to the shape of the generated pT distribution of Higgs bosons
produced via ggF are applied to match the distribution from a calculation at NNLO including the NNLL corrections provided by the HRes2.1 [64] program. In this calculation, theeffects of finite masses of the top and bottom quarks
q [64, 65] are included and dynamical

renormalisation and factorisation scales, µR , µF = m2H + p2T , are used. A reweighting is
performed separately for events with no more than one jet at particle level and for eventswith two or more jets. In the latter case, the Higgs boson pT spectrum is reweighted tomatch the MinLo HJJ predictions [66]. The reweighting is derived such that the inclusive
Higgs boson pT spectrum and the pT spectrum of events with at least two jets match theHRes2.1 and MinLo HJJ predictions respectively, and that the jet multiplicities are inagreement with (N)NLO calculations from JetVHeto [67–69].
The NLO EW corrections for VBF production depend on the pT of the Higgs boson, varying from a few percent at low pT to ∼ 20% at pT = 300 GeV [70]. The pT
spectrum of the VBF-produced Higgs boson is therefore reweighted, based on the difference between the Powheg+Pythia calculation and the Hawk [57, 58] calculation which
includes these corrections.
The main and largely irreducible Z/γ ∗ → τ τ background is modelled using Z/γ ∗ → µµ
events from data,4 where the muon tracks and associated energy depositions in the calorimeters are replaced by the corresponding simulated signatures of the final-state particles of thetau decay. In this approach, essential features such as the modelling of the kinematics ofthe produced boson, the modelling of the hadronic activity of the event (jets and underlying
event) as well as contributions from pile-up are taken from data. Thereby the dependence
on the simulation is minimised and only the τ decays and the detector response to thetau-lepton decay products are based on simulation. By requiring two isolated, high-energymuons with opposite charge and a dimuon invariant mass mµµ > 40 GeV, Z → µµ events
can be selected from the data with high efficiency and purity. To replace the muons inthe selected events, all tracks associated with the muons are removed and calorimeter cell
energies associated with the muons are corrected by subtracting the corresponding energy
depositions in a single simulated Z → µµ event with the same kinematics. Finally, boththe track information and the calorimeter cell energies from a simulated Z → τ τ decay are
4

These processes are hereafter for simplicity denoted by Z → τ τ and Z → µµ respectively, even though
the whole continuum above and below the Z peak is considered.

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JHEP04(2015)117

isation of the parton distribution functions (PDFs) is used. The overall normalisation of
the ggF process is taken from a calculation at next-to-next-to-leading-order (NNLO) [48–53] in QCD, including soft-gluon resummation up to next-to-next-to-leading logarithm
terms (NNLL) [54]. Next-to-leading order (NLO) electroweak (EW) corrections are also
included [55, 56]. Production by VBF is normalised to a cross section calculated withfull NLO QCD and EW corrections [57–59] with an approximate NNLO QCD correction
applied [60]. The associated V H production process is simulated with Pythia8. The
Cteq6L1 [61] parameterisation of PDFs is used for the Pythia8 event generator. The
predictions for V H production are normalised to cross sections calculated at NNLO in
QCD [62], with NLO EW radiative corrections [63] applied.

4
4.1

Event selection and categorisation
Event selection

Single lepton, dilepton and di-τhad triggers were used to select the events for the analysis. A
summary of the triggers used by each channel at the two centre-of-mass energies is reported
in table 2. Due to the increasing luminosity and the different pile-up conditions, the online
pT thresholds increased during data-taking in 2011 and again for 2012, and more stringent
identification requirements were applied for the data-taking in 2012. The pT requirementson the objects in the analysis are usually 2 GeV higher than the trigger requirements, toensure that the trigger is fully efficient.
In addition to applying criteria to ensure that the detector was functioning properly,
requirements to increase the purity and quality of the data sample are applied by rejecting
non-collision events such as cosmic rays and beam-halo events. At least one reconstructedvertex is required with at least four associated tracks with pT > 400 MeV and a posi-–7–

JHEP04(2015)117

added to the data event. The decays of the tau leptons are simulated by Tauola [71]. The
tau lepton kinematics are matched to the kinematics of the muons they are replacing, including polarisation and spin correlations [72], and the mass difference between the muonsand the tau leptons is accounted for. This hybrid sample is referred to as embedded datain the following.
Other background processes are simulated using different generators, each interfaced
to Pythia [46, 73] or Herwig [74, 75] to provide the parton shower, hadronisation and themodelling of the underlying event, as indicated in table 1. For the Herwig samples, thedecays of tau leptons are also simulated using Tauola [71]. Photon radiation from charged
leptons for all samples is provided by Photos [76]. The samples for W/Z+jets production
are generated with Alpgen [77], employing the MLM matching scheme [78] between thehard process (calculated with LO matrix elements for up to five partons) and the parton
shower. For W W production, the loop-induced gg → W W process is also generated, using
the gg2WW [79] program. In the AcerMC [80], Alpgen, and Herwig event generators,
the Cteq6L1 parameterisation of the PDFs is used, while the CT10 parameterisation isused for the generation of events with gg2WW. The normalisation of these backgroundcontributions is either estimated from control regions using data, as described in section 6,
or the cross sections quoted in table 1 are used.
For all samples, a full simulation of the ATLAS detector response [81] using theGeant4 program [82] was performed. In addition, events from minimum-bias interactions were simulated using the AU2 [83] parameter tuning of Pythia8. The AU2 tune
includes the set of optimized parameters for the parton shower, hadronisation, and multiple parton interactions. They are overlaid on the simulated signal and background events
according to the luminosity profile of the recorded data. The contributions from these pileup interactions are simulated both within the same bunch crossing as the hard-scattering
process and in neighbouring bunch crossings. Finally, the resulting simulated events areprocessed through the same reconstruction programs as the data.

Signal (mH = 125 GeV)

MC generator

σ × B [pb]√s = 8 TeV

ggF, H → τ τPowheg [42–45]

1.22

NNLO+NNLL[48–53, 84][57–59, 84]+ Pythia8 [46]Powheg + Pythia8

0.100(N)NLOW H, H → τ τPythia80.0445

NNLO[62, 84]

ZH, H → τ τPythia8

0.0262

NNLO[62, 84]

BackgroundMC generator

σ × B [pb]√s = 8 TeV

W (→ `ν), (` = e, µ, τ )Alpgen [77]+Pythia8

36800

NNLO

[85, 86]

Alpgen+Pythia8

3910

NNLO

[85, 86]

Alpgen+Herwig [87]

13000

NNLO

[85, 86]

Sherpa [88]1.1∗Z/γ (→ ``),
60 GeV< m`` < 2 TeV
Z/γ ∗ (→ ``),
10 GeV< m`` < 60 GeV
VBF Z/γ ∗ (→ ``)tt̄
Single top : W t
Single top : s-channel
Single top : t-channelq q̄ → W W
gg → W W
W Z, ZZ
H → WW

Powheg + Pythia8
Powheg + Pythia8
Powheg + Pythia8
AcerMC [80]+Pythia6 [73]Alpgen+Herwig
gg2WW [79]+Herwig

253
22

same as for H → τ τ signal

†

5.6

†

87.8
54

†

NNLO+NNLL[88][89–94]

NNLO

[95]

NNLO

[96]

NNLO

[97]

†

NLO

[98]

†

NLO

[79]

†

NLO

[98]

1.4
30

Herwig

LO
†

4.7

†

Table 1.
Monte Carlo generators used to model the signal and the background processes at√
s = 8 TeV. The cross sections times branching fractions (σ × B) used for the normalisation ofsome processes (many of these are subsequently normalised to data) are included in the last column
together with the perturbative order of the QCD calculation. For the signal processes the H → τ τSM branching ratio is included, and for the W and Z/γ ∗ background processes the branching ratios
for leptonic decays (` = e, µ, τ ) of the bosons are included. For all other background processes,
inclusive cross sections are quoted (marked with a †).

tion consistent with the beam spot. It has been verified that, after object selection cuts,
contributions from other primary vertices are negligible.
With respect to the object identification requirements described in section 2, tighter
criteria are applied to address the different background contributions and compositionsin the different analysis channels. Higher pT thresholds are applied to electrons, muons,and τhad candidates according to the trigger conditions satisfied by the event, as listed intable 2. For the channels involving leptonic tau decays, τlep τlep and τlep τhad , additional
isolation criteria for electrons and muons, based on tracking and calorimeter information,
are used to suppress the background from misidentified jets or from semileptonic decaysof charm and bottom hadrons. The calorimeter isolation variable I(ET , ∆R) is defined–8–

JHEP04(2015)117

VBF, H → τ τ√s = 7 TeV

Trigger
Trigger

Analysis level thresholds [GeV]

level
thresholds,

τlep τlep

pT [GeV]
20−22

peT > 22 − 24eµ:pµT > 10pµT1 > 20
pµT2 > 10
pµT > 20
peT > 15
peT1 > 15
peT2 > 15µµ:Single muon

18eµ:Di-electron

12/12

Di-τhad

29/20

ee:

peT > 25–

pτT > 20pµT > 22–pτT > 20–––
pτT1 > 35ττ:pτT2 > 25

s = 8 TeV

Trigger

Analysis level thresholds [GeV]

level
thresholds,

τlep τlep

pT [GeV]eµ:Single electron

µτ :

–
√

Triggereτ :τhad τhad24
ee:Single muon

24

Di-electron

12/12

ee:

Di-muon18/8µµ:

Electron+muon

12/8

eµ:

Di-τhad29/20

τlep τhad

τhad τhadpeT > 26
pµT > 10peT1 > 26
peT2 > 15–
peT1 > 15

eτ :

µτ :

peT > 26–

pτT > 20pµT > 26–

pτT > 20
–

–

–

–

pµT > 10

–

–

–

–

peT2 > 15
pµT1 > 20
pµT2 > 10
peT > 15ττ:pτT1 > 35
pτT2 > 25

Table 2. Summary of the triggers used to select events for the different analysis channels at thetwo centre-of-mass energies. The transverse momentum thresholds applied at trigger level and in
the analysis are listed. When more than one trigger is used, a logical OR is taken and the trigger
efficiencies are calculated accordingly.

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JHEP04(2015)117

Single electronτlep τhad7 TeVElectrons
8 TeV
7 TeV
Muons
8 TeV

τlep τlep
I(pT , 0.4) < 0.06
I(ET , 0.2) < 0.08
I(pT , 0.4) < 0.17
I(ET , 0.2) < 0.09
I(pT , 0.4) < 0.06
I(ET , 0.2) < 0.04
I(pT , 0.4) < 0.18
I(ET , 0.2) < 0.09

τlep τhad
I(pT , 0.4) < 0.06
I(ET , 0.2) < 0.06
I(pT , 0.4) < 0.06
I(ET , 0.2) < 0.06
I(pT , 0.4) < 0.06
I(ET , 0.2) < 0.06
I(pT , 0.4) < 0.06
I(ET , 0.2) < 0.06

as the sum of the total transverse energy in the calorimeter in a cone of size ∆R aroundthe electron cluster or the muon track, divided by the ET of the electron cluster or thepT of the muon respectively. The track-based isolation I(pT , ∆R) is defined as the sumof the transverse momenta of tracks within a cone of ∆R around the electron or muontrack, divided by the ET of the electron cluster or the muon pT respectively. The isolation
requirements applied are slightly different for the two centre-of-mass energies and are listed
in table 3.
In the τhad τhad channel, isolated taus are selected by requiring that there are no tracks
with pT > 0.5 GeV in an isolation region of 0.2 < ∆R < 0.6 around the tau direction.
This requirement leads to a 12% (4%) efficiency loss for hadronic taus, while 30% (10%)
of contamination from jets is rejected in 8 (7) TeV data.
After the basic lepton selection, further channel-dependent cuts are applied, as detailed
in the following. The full event selection is summarised in table 4.
The τlep τlep channel: exactly two isolated leptons with opposite-sign (OS) electriccharges, passing the pT threshold listed in table 2, are required. Events containing aτhad candidate are vetoed. For the τhad candidates considered, the criteria used to reject
electrons misidentified as τhad candidates are tightened to a working-point of 85% signal
efficiency [39].
In addition to the irreducible Z → τ τ background, sizeable background contributions
from Z → `` and from tt̄ production are expected in this channel. Background contributions from Z decays, but also from low mass resonances (charmonium and bottomonium),are rejected by requirements on the invariant mass mvisτ τ of the visible tau decay products,
miss . To rejecton the angle ∆φ`` between the two leptons in the transverse plane and on ET
the large Z → `` contribution in events with same-flavour (SF) leptons (ee, µµ), more
miss are applied for these events than for events
stringent cuts on the visible mass and on ET
with different-flavour (DF) leptons (eµ). For SF final states, an additional variable named
miss (E miss,HPTO ) is also used to reject background from Z/γ ∗ production.
high-pT objects ET
T
It is calculated from the high-pT objects in the event, i.e. from the two leptons and frommiss variables
jets with pT > 25 GeV. Due to the presence of real neutrinos, the two ET– 10 –JHEP04(2015)117

Table 3. Summary of isolation requirements applied for the selection of isolated electrons andmuons at the two centre-of-mass energies. The isolation variables are defined in the text.

The τlep τhad channel: exactly one isolated lepton and one τhad candidate with OS
charges, passing the pT thresholds listed in table 2, are required. The criteria used toreject electrons misidentified as τhad are also tightened in this channel to a working-pointof 85% signal efficiency [39].
The production of W +jets and of top quarks constitute the dominant reducible background in this channel. To substantially reduce the W +jets contribution, a cut on thetransverse mass7 constructed from the lepton and the missing transverse momentum isapplied and events with mT > 70 GeV are rejected. Contributions from tt̄ events are
reduced by rejecting events with a b-jet with pT > 30 GeV.
The τhad τhad channel: one isolated medium τhad candidate and one isolated tight τhadcandidate with OS charges are required. Events with electron or muon candidates aremiss > 20 GeV
rejected. For all data, the missing transverse momentum must satisfy ET
and its direction must either be between the two visible τhad candidates in φ or within∆φ < π/4 of the nearest τhad candidate. To further reduce the background from multijet
production, additional cuts on the ∆R and pseudorapidity separation ∆η between the twoτhad candidates are applied.
With these selections, there is no overlap between the individual channels.
4.2

Analysis categories

To exploit signal-sensitive event topologies, two analysis categories are defined in an exclusive way.
5

Misidentified leptons and τhad candidates are also referred to as “fake” in this paper.
The variable pvis is defined as the total momentum of the visible decay products of the tau lepton whilepmis is definedp as the momentum of the neutrino system reconstructed using the collinear approximation.
7
missmT = 2p`T ET· (1 − cos ∆φ), where ∆φ is the azimuthal separation between the directions of the
lepton and the missing transverse momentum.
6– 11 –JHEP04(2015)117

are strongly correlated for signal events but only loosely correlated for background fromZ → ee and Z → µµ decays.
To further suppress background contributions from misidentified leptons 5 a minimum
value of the scalar sum of the transverse momenta of the two leptons is required. Contributions from tt̄ events are further reduced by rejecting events with a b-jet with pT > 25 GeV.
Within the collinear approximation [99], i.e. assuming that the tau directions are
given by the directions of the visible tau decay products and that the momenta of theneutrinos constitute the missing transverse momentum, the tau momenta can be reconstructed. For tau decays, the fractions of the tau momenta carried by the visible decay
products,6 xτ,i = pvis,i /(pvis,i + pmis,i ), with i = 1, 2, are expected to lie in the interval
0 < xτ,i < 1, and hence corresponding requirements are applied to further reject non-tau
background contributions.
Finally, to avoid overlap between this analysis and the search for H → W W ∗ → `ν`ν
decays, the τ τ mass in the collinear approximation is required to satisfy the conditionmcollτ τ > mZ − 25 GeV.

Channelτlep τlepτhad τhad
Channelτlep τlep
τlep τhad

τhad τhad
Channelτlep τlep
All

Table 4. Summary of the event selection for the three analysis channels. The requirements used inboth the preselection and for the definition of the analysis categories are given. The labels (1) and(2) refer to the leading (highest pT ) and subleading final-state objects (leptons, τhad , jets). The
variables are defined in the text.

• The VBF category targets events with a Higgs boson produced via vector boson fusion
and is characterised by the presence of two high-pT jets with a large pseudorapidity
separation (see table 4). The ∆η(j1 , j2 ) requirement is applied to the two highestpT jets in the event. In the τlep τhad channel, there is an additional requirement∗that mvisτ τ > 40 GeV, to eliminate low-mass Z/γ events. Although this category isdominated by VBF events, it also includes smaller contributions from ggF and V H
production.
• The boosted category targets events with a boosted Higgs boson produced via ggF.

– 12 –JHEP04(2015)117

τlep τhad

Preselection cuts
Exactly two isolated opposite-sign leptons
Events with τhad candidates are rejected
30 GeV < mvisτ τ < 100 (75) GeV for DF (SF) events∆φ`` < 2.5
miss > 20 (40) GeV for DF (SF) eventsET
miss,HPTOET> 40 GeV for SF events`1
pT + p`T2 > 35 GeV
Events with a b-tagged jet with pT > 25 GeV are rejected
0.1 < xτ1 , xτ2 < 1mcoll
τ τ > mZ − 25 GeV
Exactly one isolated lepton and one medium τhad candidate with opposite charges
mT < 70 GeV
Events with a b-tagged jet with pT > 30 GeV are rejected
One isolated medium and one isolated tight opposite-sign τhad -candidate
Events with leptons are vetoed
miss > 20 GeVET
miss points between the two visible taus in φ, or min[∆φ(τ, E miss )] < π/4ETT
0.8 < ∆R(τhad1 , τhad2 ) < 2.4∆η(τhad1 , τhad2 ) < 1.5
VBF category selection cuts
At least two jets with pjT1 > 40 GeV and pjT2 > 30 GeV∆η(j1 , j2 ) > 2.2
At least two jets with pjT1 > 50 GeV and pjT2 > 30 GeV∆η(j1 , j2 ) > 3.0mvisτ τ > 40 GeV
At least two jets with pjT1 > 50 GeV and pjT2 > 30 GeV
pjT2 > 35 GeV for jets with |η| > 2.4∆η(j1 , j2 ) > 2.0
Boosted category selection cuts
At least one jet with pT > 40 GeV
Failing the VBF selectionpH
T > 100 GeV

Higgs boson candidates are therefore required to have large transverse momentum,HpH
T > 100 GeV. The pT is reconstructed using the vector sum of the missing transverse momentum and the transverse momentum of the visible tau decay products.
In the τlep τlep channel, at least one jet with pT > 40 GeV is required. The jet remiss of same-flavour events
quirement selects a region of the phase space where the ET
is well modelled by simulation. In order to define an orthogonal category, events
passing the VBF category selection are not considered. This category also includes
small contributions from VBF and VH production.

4.3

Higgs boson candidate mass reconstruction

The di-tau invariant mass (mMMC) is reconstructed using the missing mass calculatorττ(MMC) [100]. This requires solving an underconstrained system of equations for six toeight unknowns, depending on the number of neutrinos in the τ τ final state. These unknowns include the x-, y-, and z-components of the momentum carried by the neutrinos
for each of the two tau leptons in the event, and the invariant mass of the two neutrinos
from any leptonic tau decays. The calculation uses the constraints from the measured xand y-components of the missing transverse momentum, and the visible masses of bothtau candidates. A scan is performed over the two components of the missing transverse
momentum vector and the yet undetermined variables. Each scan point is weighted by its
miss resolution and the tau decay topologies. The estimatorprobability according to the ET
for the τ τ mass is defined as the most probable value of the scan points.
The MMC algorithm provides a solution for ∼99% of the H → τ τ and Z → τ τevents. This is a distinct advantage compared to the mass calculation using the collinear
approximation where the failure rate is higher due to the implicit collinearity assumptions.
miss
The small loss rate of about 1% for signal events is due to large fluctuations of the ET
measurement or other scan variables.
Figure 1 shows reconstructed mMMC
mass distributions for H → τ τ and Z → τ τττevents in the τlep τhad VBF and boosted categories. The mass resolution, defined as theratio between the full width at half maximum (FWHM) and the peak value of the mass
distribution (mpeak ), is found to be ≈ 30% for all categories and channels.

5

Boosted decision trees

Boosted decision trees are used in each category to extract the Higgs boson signal from thelarge number of background events. Decision trees [24] recursively partition the parameter– 13 –JHEP04(2015)117

While these categories are conceptually identical across the three channels, differencesin the dominant background contributions require different selection criteria. For bothcategories, the requirement on jets is inclusive and additional jets, apart from those passing
the category requirements, are allowed.
For the τhad τhad channel, the so-called rest category is used as a control region. In thiscategory, events passing the preselection requirements but not passing the VBF or boosted
category selections are considered. This category is used to constrain the Z → τ τ andmultijet background contributions. The signal contamination in this category is negligible.

0.2
0.18
0.16

Fraction of Events / 5 GeV

Fraction of Events / 5 GeV

0.22
ATLAS

τlepτhad VBF

m peak(Z →ττ) = 92.4 GeV

Z →ττ
H (125)→ττm peak(H →ττ) = 123.2 GeV
FWHM/ m peak ≈ 30 %

0.14
0.12
0.1
0.08

0.22
0.2
0.18
0.16

0.1
0.08
0.04

0.02

0.02
150

200

0
0

50

100

[GeV]
mMMC
ττ

150

200

[GeV]
mMMC
ττ

(a)

(b)

Figure 1. The reconstructed invariant τ τ mass, mMMC
ττ

for H → τ τ (mH = 125 GeV) and Z → τ τevents in MC simulation and embedding respectively, for events passing (a) the VBF category
selection and (b) the boosted category selection in the τlep τhad channel.

space into multiple regions where signal or background purities are enhanced. Boostingis a method which improves the performance and stability of decision trees and involves
the combination of many trees into a single final discriminant [25, 26]. After boosting,the final score undergoes a transformation to map the scores on the interval −1 to +1.
The most signal-like events have scores near 1 while the most background-like events havescores near −1.
Separate BDTs are trained for each analysis category and channel with signal and√background samples, described in section 6, at s = 8 TeV. They are then applied tothe analysis of the data at both centre-of-mass energies. The separate training naturally
exploits differences in event kinematics between different Higgs boson production modes.
It also allows different discriminating variables to be used to address the different background compositions in each channel. A large set of potential variables was investigated, ineach channel separately, and only those variables which led to an improved discrimination
performance of the BDT were kept. For the training in the VBF category, only a VBF
Higgs production signal sample is used, while training in the boosted category uses ggF,
VBF, and V H signal samples. The Higgs boson mass is chosen to be mH = 125 GeV forall signal samples. The BDT input variables used at both centre-of-mass energies are listed
in table 5. Most of these variables have straightforward definitions, and the more complex
ones are defined in the following.
• ∆R(τ1 , τ2 ): the distance ∆R between the two leptons, between the lepton and τhad ,or between the two τhad candidates, depending on the decay mode.
• pTotal: magnitude of the vector sum of the transverse momenta of the visible tau
T
miss .
decay products, the two leading jets, and ET– 14 –JHEP04(2015)117

0.04

100

m peak(H →ττ) = 122.3 GeV
FWHM/ m peak ≈ 30 %

0.12

0.06

50

m peak(Z →ττ) = 90.4 GeV

Z →ττ
H (125)→ττ

0.14

0.06

0
0

ATLAS

τlepτhad Boosted

• Sum pT : scalar sum of the pT of the visible components of the tau decay products
and of the jets.

• Sphericity: a variable that describes the isotropy of the energy flow in the event [101].
It is based on the quadratic momentum tensor
P α β
p p
αβ
S = Pi i 2i .
(5.1)
pi |
i |~
In this equation, α and β are the indices of the tensor. The summation is performed
over the momenta of the selected leptons and jets in the event. The sphericity of theevent (S) is then defined in terms of the two smallest eigenvalues of this tensor, λ2
and λ3 ,3S = (λ2 + λ3 ).
(5.2)
2• min(∆η`1 `2 ,jets ): the minimum ∆η between the dilepton system and either of thetwo jets.
• Object η centrality: a variable that quantifies the η position of an object (an isolated
lepton, a τhad candidate or a jet) with respect to the two leading jets in the event. It
is defined as
"

 #
−4
η1 + η2 2
Cη1 ,η2 (η) = exp
η−
,
(5.3)
(η1 − η2 )22
where η, η1 and η2 are the pseudorapidities of the object and the two leading jets
respectively. This variable has a value of 1 when the object is halfway in η between
the two jets, 1/e when the object is aligned with one of the jets, and < 1/e when theobject is not between the jets in η. In the τlep τlep channel the η centrality of a third
jet in the event, Cη1 ,η2 (ηj3 ), and the product of the η centralities of the two leptons
are used as BDT input variables, while in the τlep τhad channel the η centrality of
the lepton, Cη1 ,η2 (η` ), is used, and in the τhad τhad channel the η centrality of each τ ,Cη1 ,η2 (ητ1 ) and Cη1 ,η2 (ητ2 ), is used. Events with only two jets are assigned a dummy
value of −0.5 for Cη1 ,η2 (ηj3 ).
Among these variables the most discriminating ones include mMMC
, ∆R(τ1 , τ2 ) andττ∆η(j1 , j2 ). Figures 2 and 3 show the distributions of selected BDT input variables. For
the VBF category, the distributions of ∆η(j1 , j2 ) and centrality variables are shown formiss φall three channels. For the boosted category, the distributions of ∆R(τ1 , τ2 ) and ET– 15 –JHEP04(2015)117

miss φ centrality: a variable that quantifies the relative angular position of the miss• ET
ing transverse momentum with respect to the visible tau decay products in the transverse plane. The transverse plane is transformed such that the direction of the tau
decay products are orthogonal, and that the smaller φ angle between the tau decay
miss φ centralproducts defines the positive quadrant of the transformed plane. The ET
miss unit vector in this
ity is defined as the sum of the x- and y-components of the ET
transformed plane.

Variable

VBF

Boostedτlep τhad

τhad τhadτlep τlep

τlep τhad

τhad τhad

mMMC
ττ

•

•

•

•

•

•

∆R(τ1 , τ2 )

•

•

•

•

•

∆η(j1 , j2 )

•

•

•

mj1 ,j2•••

ηj1 × ηj2••

pTotalT••

Sum pT••pτT1 /pτT2

•

•

•

•

miss φ centrality
ET

•

•

•

m`,`,j1•m`1 ,`2•∆φ(`1 , `2 )•Sphericity

•

p`T1
pjT1
miss /p`2
ET
T

•
•
•
•

mT
min(∆η`1 `2 ,jets )•Cη1 ,η2 (η`1 ) · Cη1 ,η2 (η`2 )••Cη1 ,η2 (η` )Cη1 ,η2 (ηj3 )••Cη1 ,η2 (ητ1 )•Cη1 ,η2 (ητ2 )•Table 5. Discriminating variables used in the training of the BDT for each channel and category√
at s = 8 TeV. The more complex variables are described in the text. The filled circles indicate
which variables are used in each case.

centrality are shown for the τlep τhad and τhad τhad channels, and the distribution of the pT ofthe leading jet and the sphericity are shown for the τlep τlep channel. For all distributions,√the data are compared to the predicted SM backgrounds at s = 8 TeV. The corresponding
uncertainties are indicated by the shaded bands. All input distributions are well described,
giving confidence that the background models (from simulation and data) describe well the
relevant input variables of the BDT. Similarly, good agreement is found for the distributions√
at s = 7 TeV.

– 16 –JHEP04(2015)117

τlep τlepτlepτlep VBF

Events / 20 GeV

Events / 0.35

300

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fit

250

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake lepton
Uncert.

200
150

1000
τlepτlep Boosted

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fit

800

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake lepton
Uncert.

600
400

100
200

50
3

4

5

6

7

0

100

200

p 1 [GeV]

1 2

T

(b)

τlepτhad VBF

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fitEvents / 0.2

Events / 0.2

(a)
600

300
j

∆ η(j , j )Data
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.

500
400
300

2500

τlepτhad Boosted

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fitData
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.

2000
1500
1000

200
500

100
0
3

4

5

6

0

7

1

2

3

4

∆ η(j , j )∆ R (τ1, τ2)

1 2

400

(d)

τhadτhad VBF

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fit350

Events / 0.2

Events / 0.5

(c)

Data
50 x H (125)Z → ττ
OthersFake τ
Uncert.

300
250
200

900
800

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fitData
50 x H (125)Z → ττ
OthersFake τ
Uncert.

700
600
500
400

150

300

100

200

50

100

0
2

τhadτhad Boosted

3

4

5

6

0

7

1

1.5

∆ η(j , j )2∆ R (τ1, τ2)

1 2

(e)

(f)

Figure 2. Distributions of important BDT input variables for the three channels and the two√categories (VBF, left) and (boosted, right) for data collected at s = 8 TeV. The distributions
are shown for (a) the separation in pseudorapidity of the jets, ∆η(j1 , j2 ), and (b) the transverse
momentum of the leading jet pjT1 in the τlep τlep channel, for (c) ∆η(j1 , j2 ) and (d) ∆R(τ1 , τ2 ),the distance ∆R between the lepton and τhad , in the τlep τhad channel and for (e) ∆η(j1 , j2 ) and(f) ∆R(τ1 , τ2 ), the distance ∆R between the two τhad candidates, in the τhad τhad channel. The
contributions from a Standard Model Higgs boson with mH = 125 GeV are superimposed, multiplied
by a factor of 50. These figures use background predictions made without the global fit defined in
section 8. The error band includes statistical and pre-fit systematic uncertainties.

– 17 –JHEP04(2015)117

2

τlepτlep VBF

ATLAS

400

s = 8 TeV , 20.3 fb-1

Pre-fitEvents / 0.05

Events / 0.1

450

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake lepton
Uncert.

350
300
250
200

800

400

200

50

100

2

l1

1

0.2

0.4

l2

2

400
300

τlepτhad VBF

ATLAS

s = 8 TeV , 20.3 fb-1

Pre-fitData
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.

5000
4000
3000
2000

200

τlepτhad Boosted

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fitData
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.

1000

100
0
0

0.2

0.4

0.6

0
0

0.8
1
Cη ,η (η )
1

2

0.5

l

150

(d)

τhadτhad VBF

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fitEvents / 0.14

Events / 0.05

200

1
E missφ centrality
T

(c)
250

1

(b)
Events / 0.14

Events / 0.05

500

0.8

Sphericity

(a)
600

0.6

Data
50 x H (125)Z → ττ
OthersFake τ
Uncert.

1400
1200
1000
800

τhadτhad Boosted

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fitData
50 x H (125)Z → ττ
OthersFake τ
Uncert.

600

100

400
50
200
0
0

0.2

0.4

0.6

0
0

0.8
1
C η ,η (τ2)
1

0.5

1
φ centrality
E miss
T

2

(e)

(f)

Figure 3. Distributions of important BDT input variables for the three channels and the two√categories (VBF, left) and (boosted, right) for data collected at s = 8 TeV. The distributions areshown for (a) the product of the lepton centralities, Cη1 ,η2 (η`1 ) · Cη1 ,η2 (η`2 ), and (b) the sphericity
missin the τlep τlep channel, for (c) the centrality of the lepton, Cη1 ,η2 (η` ), and (d) the ET
φ centrality
in the τlep τhad channel, and for (e) the centrality of the subleading tau, Cη1 ,η2 (ητ2 ), and (f) themissET
φ centrality in the τhad τhad channel. The contributions from a Standard Model Higgs bosonwith mH = 125 GeV are superimposed, multiplied by a factor of 50. These figures use background
predictions made without the global fit defined in section 8. The error band includes statistical andpre-fit systematic uncertainties.

– 18 –JHEP04(2015)117

0
0

0.6
0.8
1
Cη ,η (η ) ⋅ Cη ,η (η )1Data
50 x H (125)Z → ττ
t t +single-top
OthersFake lepton
Uncert.

500

100

0.4

Pre-fit

600

300

0.2

ATLAS

s = 8 TeV, 20.3 fb-1

700

150

0
0

τlepτlep Boosted

6

Background estimation

6.1

Background from Z → τ τ production

A reliable modelling of the irreducible Z → τ τ background is an important ingredient of
the analysis. It has been shown in other ATLAS analyses that existing Z+jets Monte Carlosimulation needs to be reweighted to model data correctly [102–104]. Additionally, it is notpossible to select a sufficiently pure and signal-free Z → τ τ control sample from data tomodel the background in the signal region. Therefore this background is estimated using
embedded data, as described in section 3. This procedure was extensively validated using
both data and simulation. To validate the subtraction procedure of the muon cell energies
and tracks from data and the subsequent embedding of the corresponding information fromsimulation, the muons in Z → µµ events are replaced by simulated muons. The calorimeter
isolation energy in a cone of ∆R = 0.3 around the muons from data before and after
embedding is compared in figure 4(a). Good agreement is found, which indicates that no
deterioration (e.g. possible energy biases) in the muon environment is introduced. Anotherimportant test validates the embedding of more complex Z → τ τ events, which can only be
performed in the simulation. To achieve a meaningful validation, the same MC generator
with identical settings was used to simulate both the Z → µµ and Z → τ τ events. The
sample of embedded events is corrected for the bias due to the trigger, reconstruction andacceptance of the original muons. These corrections are determined from data as a functionof pµT and η(µ), and allow the acceptance of the original selection to be corrected. The tau
decay products are treated like any other objects obtained from the simulation, with one
8

For simplicity, leptons from heavy-quark decays are considered as fake leptons in the following.

– 19 –JHEP04(2015)117

The different final-state topologies of the three analysis channels have different backgroundcompositions which necessitate different strategies for the background estimation. In general, the number of expected background events and the associated kinematic distributions
are derived from a mixture of data-driven methods and simulation. The normalisationof several important background contributions is performed by comparing the simulated
samples of individual background sources to data in regions which only have a small or
negligible contamination from signal or other background events. The control regions usedin the analysis are summarised in table 6.
Common to all channels is the dominant Z → τ τ background, for which the kinematic
distributions are taken from data by employing the embedding technique, as describedin section 3. Background contributions from jets that are misidentified as hadronicallydecaying taus (fake backgrounds) are estimated by using either a fake-factor method orsamples of non-isolated τhad candidates. Likewise, samples of non-isolated leptons are used
to estimate fake-lepton contributions from jets or hadronically decaying taus and leptons
from other sources, such as heavy-quark decays.8
Contributions from various other physics processes with leptons and/or τhad candidates
in the final state are estimated using the simulation, normalised to the theoretical crosssections, as given in table 1. A more detailed discussion of the estimation of the various
background components in the different channels is given in the following.

Same sign τ decay products

Fake-enrichedmT > 70 GeV

Same sign τ decay productsmT < 40 GeV and mMMC
< 110 GeVττ

Invert b-jet veto and mT > 40 GeV

τlep τhadmMMC< 110 GeV or mMMC
> 150 GeVττττ

Fail VBF and Boosted selections

Pass preselection,

τhad τhad

Table 6. Summary and definition of the control regions used in the analysis. The requirements shown represent modifications to the signal region
requirements. All other selections are applied as for the corresponding signal regions. The variable mHPTO
is the invariant mass of the τ τ -systemττmiss,HPTO
obtained using the collinear approximation and the same objects as used in ET. Each control region listed is actually two control regions,corresponding to the VBF or boosted categories, with the exception of the rest category. The first three control regions listed are used in the global
fit defined in section 8.

Mass sideband

W -enriched

mHPTO< 100 GeVττ

Invert b-jet vetoZ → τ τ -enriched

Rest category

Top control region

80 < mvisτ τ < 100 GeV

Z → ``-enriched(same-flavour)τlep τlep

Process

JHEP04(2015)117– 20 –

0.3

Arbitrary Units

Arbitrary Units

0.35
Z→µµ
Data

0.25

Embedded Data

0.2

0.16

τlepτhad

0.14

MC

0.12

MC Stat. Error

0.1

Embedded MC
Emb. Uncertainty

0.08
0.15

ATLAS

0.06

0.1

0.04

µ

I (E T, 0.3) ⋅ p [GeV]
T

0

2

4

6

8

Emb. / MC

0.02

10

0
1.260
1.1
1
0.9
0.8
60

80

100

120

160

180

MMC [GeV]

80

100

120

140

160

180

[GeV]
mMMC
ττ

I (E T, 0.3) ⋅ p µ [GeV]
T

(a)

140

(b)

Figure 4. (a) The distribution of the calorimeter isolation energy I(ET , 0.3) · pµT within a cone ofradius ∆R = 0.3 around the muons in Z → µµ events from data, before and after the embeddingof simulated muons. (b) The distribution of the reconstructed invariant τ τ mass, mMMC
, in theτττlep τhad final state, for simulated Z → τ τ events, compared to the one obtained from simulated
Z → µµ events after tau embedding. The ratios of the values before and after the embedding
and between the embedded Z → µµ and Z → τ τ events are given in (a) and (b) respectively.
The errors in (a) and (b) on the ratios (points) represent the statistical uncertainties, while thesystematic uncertainties are indicated by the hatched bands in (b). The shaded bands represent thestatistical uncertainties from the Z → µµ data events in (a) and from the Z → τ τ simulation in (b).

important difference due to the absence of trigger simulation in this sample. Trigger effects
are parameterised from the simulation as a function of the tau decay product pT . Afterreplacing the muons with simulated taus, kinematic distributions of the embedded sample
can be directly compared to the fully simulated ones. As an example, the reconstructedinvariant mass, mMMC
, is shown in figure 4(b), for the τlep τhad final state. Good agreementττ
is found and the observed differences are covered by the systematic uncertainties. Similarly,
good agreement is found for other variables, such as the missing transverse momentum, thekinematic variables of the hadronically decaying tau lepton or of the associated jets in theevent. A direct comparison of the Z → τ τ background in data and the modelling using theembedding technique also shows good agreement. This can be seen in several kinematicquantity distributions, which are dominated by Z → τ τ events, shown in figure 2.
The normalisation of this background process is taken from the final fit described in
section 8. The normalisation is independent for the τlep τlep , τlep τhad , and τhad τhad analysis channels.
6.2

Background from misidentified leptons or hadronically decaying taus

For the τlep τlep channel, all background sources resulting from misidentified leptons aretreated together. In this approach, contributions from multijet and W +jets production,– 21 –JHEP04(2015)117

Emb. / Data

0.05
0
1.2
1.1
1
0.9
0.8

ATLAS Simulation
Preliminary

– 22 –JHEP04(2015)117

as well as the part of the tt̄ background resulting from decays to leptons and hadrons(tt̄ → `νb qqb) are included. A control sample is defined in data by inverting the isolation
requirements for one of the two leptons, while applying all other signal region requirements.
The contributions from other background channels (dileptonic tt̄ decays (tt̄ → `νb `νb),
Z → ee, Z → µµ, and diboson production) are obtained from the simulation and are
subtracted. From this control sample a template is created. The normalisation factor
is obtained by fitting the pT distribution of the subleading lepton at an early stage ofthe preselection.
For the τlep τhad channel, the fake-factor method is used to derive estimates for themultijet, W +jets, Z+jets, and semileptonic tt̄ background events that pass the τlep τhadselection due to a misidentified τhad candidate. The fake factor is defined as the ratio of
the number of jets identified as medium τhad candidates to the number satisfying the loose,but not the medium, criteria. Since the fake factor depends on the type of parton initiating
the jet and on the pT of the jet, it is determined as a function of pT separately for samples
enriched in quark- and gluon-initiated jets. In addition, the fake factor is found to be different for 1-track and 3-track candidates. Three different, quark-jet dominated samples areused separately for the W +jets, tt̄ and Z+jets background components. They are definedby selecting the high-mT region (mT > 70 GeV), by inverting the b-jet veto and by requiring two leptons with an invariant mass consistent with mZ (80 GeV < m`` < 100 GeV)
respectively. In addition, a multijet sample dominated by gluon-initiated jets is selectedby relaxing the lepton identification and requiring it to satisfy the loose identification criteria. The derived fake factors are found to vary from 0.124 (0.082) for pT = 20 GeV
to 0.088 (0.038) for pT = 150 GeV for 1-track (3-track) candidates in the VBF category.
The corresponding values for the boosted category are 0.146 (0.084) for pT = 20 GeV and
0.057 (0.033) for pT = 150 GeV. To obtain the fake-background estimate for the VBF andboosted signal regions, these factors are then applied, weighted by the expected relative
W +jets, Z+jets, multijet, and tt̄ fractions, to the events in regions defined by applying theselections of the corresponding signal region, except that the τhad candidate is required topass the loose and to fail the medium τhad identification. As an example, the good agreement between data and background estimates is shown in figure 5(a) for the reconstructedτ τ mass for events in the high-mT region, which is dominated by W +jets production.
For the τhad τhad channel, the multijet background is modelled using a template extracted from data that pass the VBF or boosted category selection, where, however, thetaus fail the isolation and opposite-sign charge requirements (the number-of-tracks requirement is not enforced). The normalisation of the multijet background is first determined by
performing a simultaneous fit of the multijet (modelled by the data sample just mentioned)
and Z → τ τ (modelled by embedding) templates after the preselection cuts. The fit is performed for the distribution of the difference in pseudorapidity between the two hadronic tau
candidates, ∆η(τhad , τhad ). The signal contribution is expected to be small in this category.
The agreement between data and the background estimate for this distribution is shownin figure 5(b) for the rest category defined in section 4. The preselection normalisation isused as a reference point and starting value for the global fit (see below) and is used forvalidation plots. The final normalisations of the two important background components,

Events / 0.15

Events / 20 GeV

0τlepτhad VBF

ATLAS

s = 8 TeV, 20.3 fb-1

W +jets
Control RegionData
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.

1200

τhadτhad Rest

ATLAS

s = 8 TeV, 20.3 fb-1

Pre-fitData
50 x H (125)Z → ττ
OthersFake τ
Uncert.

1000
800
600
400
200

100

200

300

0
0

0.5

1

mMMC
[GeV]
ττ

1.5
∆ η(τ,τ)(a)(b)

Figure 5. (a) The distribution of the reconstructed invariant τ τ mass, mMMC
, for events in theττ
W +jets control region, for the τlep τhad channel. (b) The separation in pseudorapidity of the τhadcandidates, ∆η(τhad , τhad ), for the τhad τhad channel in the rest control region. The expected SM
Higgs boson signal contribution is superimposed, multiplied by a factor 50. These figures use
background predictions made without the global fit defined in section 8. The error band includes
statistical and pre-fit systematic uncertainties.

from multijet and Z → τ τ events, are extracted from the final global fit, as described in
section 8, in which the ∆η(τhad , τhad ) distribution for the rest category is included.
6.3

Z → ee and Z → µµ background

The Drell-Yan Z/γ ∗ → ee and Z/γ ∗ → µµ background channels are important contributions to the final states with two same-flavour leptons. They also contribute to the otherchannels. As described below, a simulation based on Alpgen is used to estimate thesebackground sources. Correction factors are applied to account for differences between dataand simulation.
In the τlep τlep channel, the Alpgen simulation is normalised to the data in the Z-masscontrol region, 80 GeV < m`` < 100 GeV, for each category, and separately for Z → eeand Z → µµ events. The normalisation factors are determined from the final fit describedin section 8. The distribution of the reconstructed τ τ mass for events in this control regionis shown in figure 6(a).
In the τlep τhad channel, the Z → ee and Z → µµ background estimates are also basedon simulation. The corrections applied for a τhad candidate depend on whether it originatesfrom a lepton from the Z boson decay or from a jet. In the first case, corrections from data,
derived from dedicated tag-and-probe studies, are applied to account for the difference inthe rate of misidentified τhad candidates resulting from leptons [21, 105]. This is particularly
important for Z → ee events with a misidentified τhad candidate originating from a trueelectron. In the second case, the fake-factor method described in section 6.2 is applied.

– 23 –JHEP04(2015)117

240
220
200
180
160
140
120
100
80
60
40
20

ATLASs = 8 TeV, 20.3 fb-1

Data
50 x H (125)
Z → ee ,µµTop+diboson
Z → ττ
Fake lepton
Uncert.

400
300

Events / 0.2

Events / 20 GeV

τlepτlep VBF

500

ATLAS

s = 8 TeV, 20.3 fb-1

100

60

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.
Top
Control Region
Pre-fit

40
20

100

200

300

0
3

400

4

5

6
∆ η(j , j )

mMMC
[GeV]
ττ

1 2

(a)

(b)

Figure 6. (a) The distribution of the reconstructed invariant τ τ mass, mMMC
, for events inττ
the Z → `` control region, for the τlep τlep channel. (b) The distribution of the separation inpseudorapidity of the two leading jets, ∆η(j1 , j2 ), for events in the top control region, for theτlep τhad channel. This figure uses background predictions made without the global fit defined in
section 8. The error band includes statistical and pre-fit systematic uncertainties.

In the τhad τhad channel, the contribution of this background is very small and is takenfrom simulation.
6.4

W +jets background

Events with W bosons and jets constitute a background to all channels since leptonic W
decays can feed into all signatures when the true lepton is accompanied by a jet which
is falsely identified as a τhad or a lepton candidate. This process can also contribute via
semileptonic heavy quark decays that provide identified leptons.
As stated in section 6.2, for the τlep τlep and τlep τhad channels, the W +jets contributions
are determined with data-driven methods. For the τhad τhad channel, the W → τhad νbackground is estimated from simulation. A correction is applied to account for differencesin the τhad misidentification probability between data and simulation.
6.5

Background from top-quark production

Background contributions from tt̄ and single top-quark production, where leptons or
hadronically decaying taus appear in decays of top quarks, are estimated from simulation in the τlep τlep and τlep τhad channels. The normalisation is obtained from data control
regions defined by requiring a b-jet instead of a b-veto. In the τlep τhad channel, a large valueof the transverse mass mT is also required, to enhance the background from top-quark production and to suppress the signal contribution. This background is also found to be small
for the τhad τhad channel and it is estimated using simulation. The distribution of ∆η(j1 , j2 )for events in the top control region, for the τlep τhad channel, is shown in figure 6(b).

– 24 –JHEP04(2015)117

100

0τlepτhad VBF

80

Z → llControl Region
Pre-fit200

120

Channel

Backgroundτlep τlep

Top

0.99 ± 0.07

1.01 ± 0.05

Z → ee0.91 ± 0.16

0.98 ± 0.10

Z → µµ0.97 ± 0.13

0.96 ± 0.08

Top

0.84 ± 0.08

0.96 ± 0.04

τlep τhad

Scale factors (CR)
VBF
Boosted

6.6

Diboson background

The production of pairs of vector bosons (W + W − , ZZ and W ± Z), with subsequent decays
to leptons or jets, contributes especially to the background in the τlep τlep channel. For all
analysis channels, these contributions are estimated from simulation, normalised to the
NLO cross sections indicated in table 1.
6.7

Contributions from other Higgs boson decays

In the τlep τlep channel, a non-negligible contribution from H → W W → `ν`ν exists andthis process is considered as background. Its contribution is estimated for mH = 125 GeV
using simulation. The corresponding signal cross section is assumed to be the SM value
and is indicated in table 1.
6.8

Validation of background estimates

As described above, the normalisation for important background sources that are modelledwith simulation are determined by fitting to data in control regions. These normalisations
are compared in table 7 to predictions based on the theoretical cross sections for the 8 TeV
analysis. In most cases, the values obtained are compatible with unity within the statisticaluncertainties shown. For the top control region in the VBF category of the τlep τhad channel,
the value is also in agreement with unity if the experimental and theoretical systematic
uncertainties are included. The control-region normalisations are used for validation plots,
and they are used as starting values in the final global fit described in section 8. The global
fit does not change any of these normalisations by more than 2%.
It is important to verify that the BDT output distributions in data control regions arewell described after the various background determinations. Figure 7 shows distributions√
from important control regions for the s = 8 TeV dataset, i.e. the Z-enriched control
regions for the τlep τlep and τlep τhad channels, and the reconstructed τ τ invariant mass
sideband control region (defined as mMMC
< 100 GeV or mMMC
> 150 GeV) for theτττττhad τhad channel. The distributions are shown for both the VBF and the boosted categories.
All distributions are found to be well described, within the systematic uncertainties.

– 25 –JHEP04(2015)117

Table 7. The scale factors calculated in control regions (CR) for background normalisation. Only
the statistical uncertainties are given. The background contributions shown in validation plots use
the normalisation predicted from simulation multiplied by the corresponding scale factor. Finalnormalisations are taken from the global fit, described in section 8.

τlepτlep VBF

Events / 0.1

Events / 0.11

250

ATLAS

s = 8 TeV, 20.3 fb-1

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake lepton
Uncert.

200
150
100

700
600

τlepτlep Boosted

ATLAS

s = 8 TeV, 20.3 fb-1

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake lepton
Uncert.

500
400
300

Z → ττ
Control Region

Z → ττ
Control Region

200
50
100
-0.5

0

0.5

0
-1

1

-0.5

0

BDT output

τlepτhad VBF

ATLAS

s = 8 TeV, 20.3 fb-1

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.

400
300

3000

τlepτhad Boosted

ATLAS

s = 8 TeV, 20.3 fb-1

Data
50 x H (125)Z → ττ
t t +single-top
OthersFake τ
Uncert.

2500
2000
1500

Z → ττ
Control Region

200

Z → ττ
Control Region

1000

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-1

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1(d)τhadτhad VBF

Events / 0.2

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(c)
500

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(b)
Events / 0.13

Events / 0.17

(a)
500

0.5

BDT output

ATLAS

s = 8 TeV, 20.3 fb-1

300

Data
50 x H (125)Z → ττ
OthersFake τ
Uncert.

200

Mass Sideband
Control Region

400

900
800

τhadτhad Boosted

ATLAS

s = 8 TeV, 20.3 fb-1

Data
50 x H (125)Z → ττ
OthersFake τ
Uncert.

700
600
500
400

Mass Sideband
Control Region

300
200

100

100
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-1

-0.5

0

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-0.5

0

BDT output

(e)

0.5

1

BDT output(f)√Figure 7. Distributions of the BDT output for data collected at s = 8 TeV, compared to the
expected background contributions in important control regions. The distributions are shown for
the VBF (left) and boosted (right) categories (a,b) for the Z → τ τ -enriched control region in theτlep τlep channel, (c,d) for the Z → τ τ -enriched control region in the τlep τhad channel and (e,f) forthe τ τ invariant mass sideband control region in the τhad τhad channel. The contributions froma Standard Model Higgs boson with mH = 125 GeV are superimposed, multiplied by a factor of
50. These figures use background predictions made without the global fit defined in section 8. The
error band includes statistical and pre-fit systematic uncertainties.

– 26 –JHEP04(2015)117

0
-1

7

Systematic uncertainties

7.1

Experimental uncertainties

The major experimental systematic uncertainties result from uncertainties on efficiencies
for triggering, object reconstruction and identification, as well as from uncertainties on theenergy scale and resolution of jets, hadronically decaying taus and leptons. In general,
the effects resulting from lepton-related uncertainties are smaller than those from jets andtaus. They are not discussed in detail, however, their impact is included in table 8. In
addition, uncertainties on the luminosity affect the number of signal and background eventsfrom simulation.
• Luminosity: the uncertainty on the integrated luminosity is ±2.8% for the 8 TeV
dataset and ±1.8% for the 7 TeV dataset. It is determined from a calibration of
the luminosity scale derived from beam-separation scans performed in 2011 and 2012using the method described in ref. [106].
• Efficiencies: the efficiencies for triggering, reconstructing and identifying electrons,muons, and τhad candidates are measured in data using tag-and-probe techniques.
The uncertainties on the τhad identification efficiency are ±(2–3)% for 1-prong and±(3–5)% for 3-prong tau decays [39]. The b-jet tagging efficiency has been measured
from data using tt̄ events, where both top quarks decay to leptons, with a total
uncertainty of about ±2% for jets with transverse momenta up to 100 GeV [38, 107].
The MC samples used are corrected for differences in these efficiencies between dataand simulation and the associated uncertainties are propagated through the analysis.
• Energy scales: the uncertainties on the jet energy scale (JES) arise from several
sources. These include, among others, varied response due to the jet flavour composition (quark- versus gluon-initiated jets), pile-up, η intercalibration, and detector– 27 –JHEP04(2015)117

The numbers of expected signal and background events, the input variables to the BDT,
and thereby the BDT output and the final discrimination between signal and backgroundare affected by systematic uncertainties. They are discussed below, grouped into three
categories: experimental uncertainties, background modelling uncertainties, and theoreticaluncertainties. For all uncertainties, the effects on both the total signal and backgroundyields and on the shape of the BDT output distribution are evaluated. Table 8 gives asummary of the systematic uncertainties and their impact on the number of expected events√
for the signal and the total background for the analysis of the data taken at s = 8 TeV.
The dominant sources that affect the shape of the BDT output distribution are marked
in the table. All uncertainties are treated either as fully correlated or uncorrelated acrosschannels. The latter are also marked in table 8. The effects of the systematic uncertainties√
at s = 7 TeV are found to be similar and are not discussed here. The inclusion of theuncertainties in the profile likelihood global fit is described in section 8 and the effect ofthe most significant systematic uncertainties is presented in table 13.

response and modelling of in situ jet calibration [35, 36]. The impact of the JES uncertainty in this analysis is reduced because many of the background components are
estimated using data. The tau energy scale is obtained by fitting the reconstructedvisible mass for Z → τ τ events in data, which can be selected with a satisfactory
purity. It is measured with a precision of ±(2–4)% [108]. Since systematic uncertainties on the energy scales of all objects affect the reconstructed missing transverse
momentum, it is recalculated after each variation is applied. The scale uncertainty
miss due to the energy in calorimeter cells not associated with physics objects is
on ET
also taken into account.

7.2

Background modelling uncertainties

The most significant systematic uncertainties on the background estimation techniques, as
described in section 6, are detailed in the following for the three decay modes considered.
In the τlep τlep channel, systematic uncertainties on the shape and normalisation of
fake-lepton background sources are estimated by comparing samples of same-sign lepton
events that pass and fail the lepton isolation criteria. These uncertainties amount to±33% (±20%) at 8 TeV and ±10.5% (±13%) at 7 TeV for the boosted (VBF) category.
The extrapolation uncertainty for the Z → `` background is obtained by varying the m``window that defines the control region for this background, and amounts to about ±6%.
The corresponding extrapolation uncertainty for top-quark background sources is ±(3–6)%, obtained from the differences in event yields in the top-quark control regions whenusing different MC generators. Neither of these extrapolation uncertainties is significant
for the final result. The dominant uncertainties on the normalisation of the tt̄ background,obtained from the global fit, are the systematic uncertainties on the b-jet tagging efficiency
and the jet energy scale.
In the τlep τhad channel, an important systematic uncertainty on the background determination comes from the estimated fake background, for which several sources of systematic
uncertainty are considered. The statistical uncertainty on the effective fake factor is ±4.3%(±2.3%) in the 8 TeV VBF (boosted) category, and about ±22% (±11%) in the 7 TeV VBF(boosted) category. The dominant systematic uncertainty on the methodology itself arises– 28 –JHEP04(2015)117• Energy resolutions: systematic uncertainties on the energy resolution of taus, elecmiss affect the final discriminant. The effects resulting fromtrons, muons, jets, and ET
uncertainties on the tau energy resolution are small. The impact of changes in theamount of material (inactive material in the detector, e.g. support structures), in the
hadronic shower model and in the underlying-event tune were studied in the simulation. They result in systematic uncertainties below 1% on the tau energy resolution.
The jet energy resolution is determined by in situ measurements, as described inref. [109], and affects signal modelling and background components modelled by themiss is estimated by evaluating thesimulation. The uncertainty of the resolution on ET
miss terms. The largest impact results from the soft
energy resolution of each of the ET
term (see section 2), arising both from the MC modelling and the effects of pile-up.
It is evaluated using simulated Z(→ µµ)+jets events.

7.3

Theoretical uncertainties

Theoretical uncertainties are estimated for the signal and for all background contributions
modelled with the simulation. Since the major background contributions, from Z → τ τ– 29 –JHEP04(2015)117

from the composition of the combined fake background (W +jets, Z+jets, multijet, andtt̄ fractions), which is largely estimated based on simulated event samples as explained in
section 6.2. The uncertainty is estimated by varying each fractional contribution by ±50%,
which affects the effective fake factor by ±3% (±6%) and by ±10% (±15%) in the 8 TeV
and 7 TeV boosted (VBF) categories respectively. As a closure test, the method was also
applied in a region of data where the lepton and τhad candidate have the same charge, richin fake τhad candidates. Very good agreement was observed between data and the method’s
prediction, so that no additional in situ uncertainty was deemed necessary. In addition,
the uncertainties on the normalisation of the tt̄ background are important. As in the caseof the τlep τlep channel, the dominant contribution obtained from the global fit originatesfrom systematic uncertainties on the b-jet tagging efficiency and the jet energy scale, alongwith statistical uncertainties on the observed data in the respective control regions.
In the τhad τhad channel, the major background from multijet production is determinedusing a data-driven template method. The default multijet template, derived from a sample
in data where the τhad candidates fail the isolation and opposite-sign charge requirements, iscompared with an alternative template derived from a sample where the τhad candidates failjust the opposite-sign charge requirement. The normalisation of the alternative templateis fixed to that of the default template at preselection; the alternative multijet template ispropagated into the various categories and gives a different set of yields from the default
template. This difference, along with the difference in shape between the two templates,
constitutes the systematic uncertainty on the background estimate. This leads to an overall√
multijet yield variation of 10% (3%) in the VBF (boosted) category at s = 8 TeV and of√
10% (30%) in the VBF (boosted) category s = 7 TeV. However, there is a very strong
shape dependence, such that the uncertainties on the BDT output are much larger athigher output values.
For the embedding method used in all channels, the major systematic uncertainties are
related to the selection of Z → µµ events in data and to the subtraction of the muon energy
deposits in the calorimeters. The selection uncertainties are estimated by varying the muon
isolation criteria in the selection from the nominal value of I(pT , 0.2) < 0.2 (see section 4)
to tighter (I(pT , 0.4) < 0.06 and I(ET , 0.2) < 0.04) and looser (no isolation requirements)
values. The muon-related cell energies to be subtracted are varied within ±20% (±30%) for
the 8 TeV (7 TeV) data. In addition, systematic uncertainties on the corrections for trigger
and reconstruction efficiencies are taken into account. Due to the combination of singlelepton and dilepton triggers used, the uncertainties are largest for the τlep τlep channel. All
experimental systematic uncertainties relating to the embedded τ decay products (such as
tau energy scale or identification uncertainties) are applied normally. The combined effectof all uncertainties on the signal and background yields is included in table 8. Because
the Z → τ τ normalisation is determined in the final fit, the impact on the final result ismuch smaller.

±1.6
—
±9.2

±1.3
—

± 5.7

+4.5
−5.8

± 1.8
±2.3
±1.1

+11.3
−9.1

—
—
—
±0.2
< 0.1
< 0.1
< 0.1
± 0.3
—

± 2.1

+3.8
−4.3

± 1.2

+0.0
−1.2

+1.3
−1.7

+1.4
−2.1

+8.5
−9.1
+0.0
−0.2

±0.1
—
—

±2.8
—
—

τlep τlep
VBF
S
B

±5.7

+6.2
−8.0

± 5.9
±1.2
±0.4

+19.8
−15.3

—
—
—

+4.7
−4.9
+0.0
−0.1

±1.6
—

+1.4
−2.1

±2.8
—
—

±0.2
< 0.1
< 0.1
< 0.1
± 0.2
—

±0.7

+6.0
−6.5

±1.2

+3.7
−3.0
+0.0
−1.2

±1.6
—

+1.1
−1.5

±0.1
—
—

±5.7

+3.9
−3.6

±3.8
±2.7
±1.3

+9.7
−7.6

—
—
—

+9.5
−8.7
+0.8
−0.3

±2.8
—
±3.3
±1.8
< 0.1
±2.4

±0.2
< 0.1
< 0.1
< 0.1
± 0.2
—

±2.6
±1.5
—

±0.1
—
±1.2
±0.5
±0.2
±1.3
±1.0
±0.2

±5.7

+6.6
−6.1

±2.9
±1.3
±0.4

+19.3
−14.7

—
—
—

±2.8
—
±3.3
±1.8
±0.4
±2.4
±3.9
±0.4

±0.2
< 0.1
< 0.1
< 0.1
± 0.2
—

±2.6
±1.2
—

±0.1
—
±1.8
± 0.8
±0.2
±0.9
±0.4
< 0.1

± 5.7

+4.3
−4.0

±4.6
±2.4
±1.1

+10.7
−8.2

—
—
—

±0.5

+10.1
−8.0

±6.6
—
—
±2.9

+7.7
−8.8

±2.8

< 0.1
< 0.1
< 0.1
< 0.1
± 0.1
—

+20.3
−15.4

< 0.1
< 0.1
< 0.1
< 0.1
± 0.2
—

±5.7

+6.3
−5.8

±3.8
±1.2
±0.4

±0.6
±3.3
–

±0.1
< 0.1
±5.1
—
—
±2.5
±0.2
< 0.1
—
—
—

±0.1

+5.1
−6.2

±6.6
—
—
±2.9

+7.8
−8.9

±2.8

±5.2
±2.2
—

±0.1
< 0.1
±3.8
—
—
±2.5
±0.3
±0.2

τhad τhad
BoostedS
B

Table 8. Impact of systematic uncertainties on the total signal, S, (sum of all production modes) and on the sum of all background estimates,√
B, for each of the three channels and the two signal categories for the analysis of the data taken at s = 8 TeV. Each systematic uncertainty
is assumed to be correlated across the analysis channels, except those marked with a *. Uncertainties that affect the shape of the BDT-output
distribution in a non-negligible way are marked with a †. All values are given before the global fit. The notation UE/PS refers to the underlying
event and parton shower modelling.

Experimental
Luminosity
Tau trigger*
Tau identification
Lepton ident. and trigger*b-taggingτ energy scale†Jet energy scale and resolution†
missET
soft scale & resolution
Background Model
Modelling of fake backgrounds*†
Embedding†Z → `` normalisation*
Theoretical
Higher-order QCD corrections †UE/PSGenerator modelling
EW corrections
PDF †BR (H → τ τ )SourceRelative signal and background variations [%]τlep τlep
τlep τhadτlep τhad
τhad τhad
Boosted
VBF
Boosted
VBF
S
B
S
B
S
B
S
B

JHEP04(2015)117– 30 –

and misidentification of hadronically decaying τ leptons, are estimated using data-driven
methods, they are not affected by these uncertainties. Uncertainties on the signal crosssections are assigned from missing higher-order corrections, from uncertainties in the PDFs,
and from uncertainties in the modelling of the underlying event.

For Higgs boson production via ggF, the uncertainties on the cross sections due tomissing higher order QCD corrections are estimated by varying
the renormalisation andqfactorisation scales around the central values µR = µF = m2H + p2T in the NLO crosssection calculations of H + 1-jet and H + 2-jet production. In the calculation of the uncertainties, appropriate cuts on the Higgs pT (pH
T > 100 GeV ) and on the jet kinematics(∆η, pT ) are applied at parton level for the boosted and VBF categories respectively. The
resulting uncertainties on the ggF contributions are found to be about ±24% in the boosted
category and ±23% in the VBF category. The ggF contribution is dominant in the boosted
category, whereas it is only about 20% of the signal in the VBF category. Since the two categories are exclusive, their anti-correlation is taken into account following the prescription
in ref. [111].
In the present analysis, no explicit veto on jets is applied in the VBF selection, but
enough kinematical information is provided as input to the BDT so that the high BDToutput region corresponds to a more exclusive region, where the probability of finding
a third jet is reduced. Since the cross section for gluon-fusion events produced with athird jet is only known at LO, this could introduce a large uncertainty on the gluon-fusion
contamination in the highest (and most sensitive) BDT-output bins. The uncertainty
on the BDT shape of the ggF contribution is evaluated using the Mcfm Monte Carlo
program [98], which calculates H + 3 jets at LO. Scale variations induce changes of the
ggF contribution in the highest BDT bin of about ±30%. They are taken into account in
the final fit.
Uncertainties related to the simulation of the underlying event and parton shower are
estimated by comparing the acceptance from Powheg+Pythia to Powheg+Herwig forboth VBF and ggF Higgs boson production modes. Differences in the signal yields range
from ±1% to ±8% for the VBF and from ±1% to ±9% for ggF production, dependingon the channel and category. The BDT-score distribution of the Powheg+Pythia andPowheg+Herwig samples are compatible with each other within statistical uncertainties.
The PDF uncertainties are estimated by studying the change in the acceptance whenusing different PDF sets or varying the CT10 PDF set within its uncertainties. The
standard VBF Powheg sample and a MC@NLO [112] ggF sample, both generated with
the CT10 PDFs, are reweighted to the MSTW2008NLO [113], NNPDF [114] and the– 31 –JHEP04(2015)117

For VBF and VH Higgs boson production cross sections, the uncertainties due to missing higher-order QCD corrections are estimated by varying the factorisation and renormalisation scales by factors of two around the nominal scale mW , as prescribed by the LHC
Higgs Cross section Working Group [110]. The resulting uncertainties range from ±2% to±4%, depending on the process and the category-specific selection considered. In addition,
a 2% uncertainty related to the inclusion of the NLO EWK corrections (see section 3)
is assigned.

8

Signal extraction procedure

The BDT output in the six analysis categories provides the final discrimination between
signal and background for both the 7 and 8 TeV datasets. A maximum-likelihood fit isperformed on all categories simultaneously to extract the signal strength, µ, defined as
the ratio of the measured signal yield to the Standard Model expectation. The valueµ = 0 (µ = 1) corresponds to the absence (presence) of a Higgs boson signal with the SM
production cross section. The statistical analysis of the data employs a binned likelihood~ constructed as the product of Poisson probability terms, to estimate µ.
function L(µ, θ),
The impact of systematic uncertainties on the signal and background expectations is~ which are each parameterised by a Gaussian or logdescribed by nuisance parameters, θ,normal constraint. The expected numbers of signal and background events in each bin are~ The test statistic qµ is then constructed according to the profile likelihood
functions of θ.
ˆ~ˆ~ˆ where µ̂ and θ~ˆ are the parameters that maximise theratio: qµ = −2 ln[L(µ, θ)/L(µ̂,θ)],ˆˆ
likelihood, and θ~ are the nuisance parameter values that maximise the likelihood for agiven µ. This test statistic is used to measure the compatibility of the background-only
hypothesis with the observed data.
The likelihood is maximised on the BDT distributions in the signal regions, withinformation from control regions included to constrain background normalisations. The fit
includes the event yields from the Z → `` and top control regions in the τlep τlep channel,
and from the top control region of the τlep τhad channel; furthermore the ∆η(τhad , τhad )distribution in the rest control region of the τhad τhad channel is also included.
The Z → τ τ background is constrained primarily in the signal regions, due to the difference between the BDT distributions for Z → τ τ events and the signal. For the τhad τhadchannel, the Z → τ τ and multijet background rates are constrained by the simultaneous– 32 –JHEP04(2015)117

CT10 eigen-tunes parameterisation. The largest variation in acceptance for each category
is used as a constant PDF uncertainty; it varies between approximately ±4.5% and ±6%
for ggF production and between about ±0.8% and ±1.0% for VBF production. A shape
uncertainty is also included to cover any difference between the BDT score in the default
sample and the reweighted ones. The uncertainty on the total cross section for the VBF,VH and ggF production modes due to the PDFs is also considered.
Variations in the acceptance for different Monte Carlo generators are also included,
comparing Powheg+Herwig samples to MC@NLO+Herwig samples for ggF, and to
aMC@NLO+Herwig [115] samples for VBF. The generator modelling uncertainty isaround ±2% for ggF and ±4% for VBF productions modes.
Finally, an uncertainty on the decay branching ratio, BR(H → τ τ ), of ±5.7% [70]affects the signal rates.
The theoretical systematic uncertainties on the background predictions taken fromthe simulation are evaluated by applying the same procedures as used for the signal samples. Uncertainties resulting from the choice of QCD scales, PDF parameterisation andunderlying-event model are estimated. The results are reported in table 8.

– 33 –JHEP04(2015)117

fit of the two signal regions and the ∆η(τhad τhad ) distribution in the rest category control
region. The top and Z → `` background components for the τlep τlep and τlep τhad channels are also allowed to float freely, but are primarily constrained by the inclusion of therespective control regions.
As described in section 7, a large number of systematic uncertainties, taken into account via nuisance parameters, affect the final results. It is important to investigate thebehaviour of the global fit and in particular to investigate how far the nuisance parameters
are pulled away from their nominal values and how well their uncertainties are constrained.
Furthermore, it is important to understand which systematic uncertainties have the mostimpact on the final result. For this purpose a ranking of nuisance parameters is introduced.
For each parameter, the fit is performed again with the parameter fixed to its fitted value
shifted up or down by its fitted uncertainty, with all the other parameters allowed to vary.
The ranking obtained for those nuisance parameters contributing most to the uncertainty
on the signal strength is shown in figure 8 for the combined fit of the three channels at thetwo centre-of-mass energies. The parameters contributing most are those related to the jetenergy scale, the normalisation uncertainties for Z → τ τ and top-quark events, and thetau energy scale. The uncertainties on the jet energy scale are decomposed into several
uncorrelated components (among others: η intercalibration of different calorimeter regions,
jet energy response, and response to jets of different flavour). In addition, theoretical uncertainties on the branching ratio BR (H → τ τ ) are found to have a significant impact. In
general, good agreement is found between the pre-fit and post-fit values for these nuisanceparameters and neither large pulls nor large constraints are observed.
The distributions of the BDT discriminants for all channels and categories for the data
at 8 TeV are shown in figure 9, with background normalisations, signal normalisation, andnuisance parameters adjusted by the profile likelihood global fit.
The results for the numbers of fitted signal and background events, split into the various
contributions, are summarised in tables 9, 10 and 11 for the three channels separately, forthe dataset collected at 8 TeV centre-of-mass energy. In addition to the total number of
events, the expected number of events in each of the two highest BDT output bins is given.
The number of events observed in the data is also included. Within the uncertainties,
good agreement is observed between the data and the model predictions for the sum of
background components and a Standard Model Higgs boson with mH = 125 GeV.

Impact = ∆µ/ σtot

-1

-0.5

0

0.5

1

η modelling of JES

BR(H → τ τ )Normalisation of Z → τ lepτ had

Flavour response of JES

Flavour composition of JES

Underlying event
Normalisation of Z → τ hadτ had
Normalisation of t/tt background forboosted category in τ lepτ had channel
Luminosity

ATLAS

Pull
-1

+1σ Post-fit Impact on µs = 7 TeV, 4.5 fb-1-1σ Post-fit Impact on µs = 8 TeV, 20.3 fb-4 -2-3 -2-1-1

00

1 12

23

43

Pull = (θ - θ0)/∆θ

Figure 8. Impact of systematic uncertainties on the fitted signal-strength parameter µ̂ for the
combined fit for all channels and both centre-of-mass energies. The systematic uncertainties arelisted in decreasing order of their impact on µ̂ on the y-axis. The hatched blue and red boxes show
the variations of µ̂ with respect to the total error on µ, σtot , referring to the top x-axis, whenfixing the corresponding individual nuisance parameter θ to its post-fit value θ̂ modified upwards
or downwards by its post-fit uncertainty, and repeating the fit. The filled circles, referring to thebottom x-axis, show the pulls of the fitted nuisance parameters, i.e. the deviations of the fitted
parameters θ̂ from their nominal values θ0 , normalised to their nominal uncertainties ∆θ. The
black lines show the post-fit uncertainties of the nuisance parameters, relative to their nominal
uncertainties, which are indicated by the yellow band. The jet energy scale uncertainties aredecomposed into uncorrelated components.

– 34 –JHEP04(2015)117

Tau energy scale response

103τlepτlep VBF
s = 8 TeV, 20.3 fb
ATLAS

Events / 0.11

Events / 0.11

104

Data
H (125) (µ=1.4)
H (125) (µ=1)
Z → ττ
OthersFake lepton
Uncert.

-1

102

-1

-0.5

0

0.5

1

BDT output

0τlepτhad VBF
s = 8 TeV, 20.3 fb
ATLAS

0.5
1
BDT output

Data
H (125) (µ=1.4)
H (125) (µ=1)
Z → ττ
OthersFake τ
Uncert.

-1

102

Data / Model

-0.5

103

1
-1
1.5
1
0.5
-1

-0.5

0

105
4

10

0.5

1

BDT output

-0.5

0

(b)
Events / 0.18

Data / Model
Events / 0.17

Data
H (125) (µ=1.4)
H (125) (µ=1)
Z → ττ
OthersFake lepton
Uncert.

-1

τlepτhad Boosted
s = 8 TeV, 20.3 fb
ATLAS

0.5
1
BDT output

Data
H (125) (µ=1.4)
H (125) (µ=1)
Z → ττ
OthersFake τ
Uncert.

-1

103
102

-1
1.5
1
0.5

-0.5

-1

-0.5

0

0.5

1

BDT output

0

(c)

0.5
1
BDT output

Data / Model

10

-1
1.5
1
0.5

-0.5

-1

-0.5

0

0.5

1

BDT output

0

(d)

0.5
1
BDT output

104
103

τhadτhad VBF
s = 8 TeV, 20.3 fb
ATLAS

Events / 0.4

Events / 0.4

7Data
H (125) (µ=1.4)
H (125) (µ=1)
Z → ττ
OthersFake τ
Uncert.

-1

102

106
105

τhadτhad Boosted
s = 8 TeV, 20.3 fb
ATLAS

Data
H (125) (µ=1.4)
H (125) (µ=1)
Z → ττ
OthersFake τ
Uncert.

-1

104
103
102

10

10

1

1

-1
1.5
1
0.5

-0.5

-1

-0.5

0

0.5

1

BDT output

0

(e)

0.5
1
BDT output

Data / Model

Data / Model

10

-1
1.5
1
0.5

-0.5

-1

-0.5

0

0.5

1

BDT output

0

(f)

0.5
1
BDT output√
Figure 9. Distributions of the BDT discriminants for the data taken at s = 8 TeV in the signal
regions of the VBF (left) and boosted (right) categories for the τlep τlep (top), τlep τhad (middle),and τhad τhad (bottom) channels. The Higgs boson signal (mH = 125 GeV) is shown stacked witha signal strength of µ = 1 (dashed line) and µ = 1.4 (solid line). The background predictions
are determined in the global fit (that gives µ = 1.4). The size of the statistical and systematic
normalisation uncertainties is indicated by the hashed band. The ratios of the data to the model(background plus Higgs boson contributions with µ = 1.4) are shown in the lower panels. The
dashed red and the solid black lines represent the changes in the model when µ = 1.0 or µ = 0 are
assumed respectively.

– 35 –JHEP04(2015)117

-1
1.5
1
0.5

(a)

Data / Models = 8 TeV, 20.3 fb
ATLAS

10

1

103

104

τlepτlep Boosted

102

10

104

105

Second to last bin
9.7 ± 1.0
1.2 ± 0.6
0.9 ± 0.4
3.0 ± 0.4

All bins
589 ± 2457 ± 12131 ± 19196 ± 172.9 ± 0.8
3.4 ± 0.4
< 0.1
< 0.1

BDT output bin

Z → ττ

Fake backgroundTop

OthersggF: H → W W (mH = 125 GeV)

VBF: H → W W

WH : H → WW

ZH : H → W W< 0.1
15.4 ± 1.8
3.5 ± 0.9

0.25 ± 0.07
0.14 ± 0.04
980 ± 2224 ± 61014

WH : H → ττZH : H → τ τ

Total backgroundTotal signal

Data

11

3.6 ± 1.0

5.6 ± 1.4

< 0.1

< 0.1

3.3 ± 0.9

0.35 ± 0.14

< 0.1

< 0.1

0.38 ± 0.08

0.11 ± 0.04

1.7 ± 0.6

0.89 ± 0.33

0.55 ± 0.35

1.99 ± 0.34

Last bin3095

33 ± 103080 ± 50

2.0 ± 0.5

3.8 ± 1.0

5.5 ± 1.5

21 ± 80.59 ± 0.07

0.90 ± 0.10

1.65 ± 0.18

7.7 ± 2.3

400 ± 40380 ± 50100 ± 40

2190 ± 80

All bins< 0.1
1.3 ± 0.5
0.49 ± 0.13
0.22 ± 0.06
0.113 ± 0.031
19.2 ± 2.1
2.1 ± 0.620

2.4 ± 0.9
0.95 ± 0.26
0.44 ± 0.12
0.21 ± 0.06
55 ± 44.0 ± 1.2
61

< 0.1

< 0.1

0.24 ± 0.08

2.6 ± 0.7

4.3 ± 1.0

0.6 ± 0.4

11.3 ± 1.3

Last bin

< 0.1

< 0.1

0.102 ± 0.017

0.43 ± 0.13

8.3 ± 1.6

9.8 ± 2.1

2.9 ± 1.3

33.7 ± 2.3

Second to last bin

BoostedTable 9. The predicted post-fit event yields in the τlep τlep channel for mH = 125 GeV for the total number of events and for the two highest bins√of the BDT distributions for the data taken at s = 8 TeV. The background normalisations, signal normalisation, and their uncertainties represent
the post-fit values (see text). The uncertainties on the total background and total signal represent the full statistical and systematic uncertainty,
while the uncertainties on the individual background components represent the full systematic uncertainty only.

16

< 0.1

2.7 ± 0.7

13.3 ± 4.0

VBF: H → τ τ

0.73 ± 0.26

9.8 ± 3.4

ggF: H → τ τ (mH = 125 GeV)

< 0.1

< 0.1

0.40 ± 0.06

0.12 ± 0.04

VBF

Process/Category

JHEP04(2015)117– 36 –

Second to last bin
8.2 ± 0.9
7.6 ± 0.9
0.3 ± 0.4
1.0 ± 0.7
1.0 ± 0.4

All bins
1680 ± 50
877 ± 2982 ± 1554 ± 26
63 ± 1116 ± 6

BDT output bin

Fake backgroundZ → ττ

Top

Z → ``(` → τhad )DibosonggF: H → τ τ (mH = 125 GeV)

5.5 ± 1.3

2760 ± 40
48 ± 12

Total background22

21

10.3 ± 2.5

10.7 ± 2.7

< 0.1

< 0.1

9.1 ± 2.2

1.2 ± 0.6

0.48 ± 0.20

0.30 ± 0.28

0.5 ± 0.4

4.2 ± 0.7

5.2 ± 0.7

Last bin12952

89 ± 26

12860 ± 110

4.6 ± 1.2

9.1 ± 2.3

16 ± 460 ± 20430 ± 40200 ± 50380 ± 50

6210 ± 170

5640 ± 160

All bins

2.9 ± 0.7
1.9 ± 0.5
0.93 ± 0.24
82 ± 616 ± 492

1.3 ± 0.4
0.77 ± 0.20
143 ± 614 ± 4170

10.1 ± 3.4

4.7 ± 1.6

8.6 ± 3.5

4.8 ± 1.5

41.1 ± 3.2

22.3 ± 1.8

Last bin

2.5 ± 0.6

9.2 ± 3.2

9.7 ± 2.2

13 ± 412 ± 457.5 ± 2.8

51.0 ± 2.5

Second to last bin

BoostedTable 10. The predicted post-fit event yields in the τlep τhad channel for mH = 125 GeV for the total number of events and for the two highest bins√of the BDT distributions for the data taken at s = 8 TeV. The background normalisations, signal normalisation, and their uncertainties represent
the post-fit values (see text). The uncertainties on the total background and total signal represent the full statistical and systematic uncertainty,
while the uncertainties on the individual background components represent the full systematic uncertainty only.

Data

2830

18.1 ± 2.3

0.16 ± 0.07

ZH : H → τ τ

Total signal< 0.1

0.6 ± 0.4

WH : H → ττ
< 0.1

31 ± 8

VBF: H → τ τ

4.5 ± 1.1

1.0 ± 0.4

VBF

Process/Category

JHEP04(2015)117– 37 –

Second to last bin
2.3 ± 0.9
0.67 ± 0.22

All bins
370 ± 18
37 ± 5475 ± 168.0 ± 2.7
12.0 ± 3.1

BDT output bin

Fake background

OthersZ → ττ

ggF: H → τ τ (mH = 125 GeV)

VBF: H → τ τ

20 ± 5

Total signal
63.9 ± 1.0

1.2 ± 1.0

< 0.1

< 0.1

3.4 ± 0.9

0.53 ± 0.20

0.6 ± 0.4

< 0.1

0.57 ± 0.29

Last bin3020

34 ± 102960 ± 50

2.4 ± 0.6

4.0 ± 1.1

6.3 ± 1.6

21 ± 82230 ± 70

89 ± 11645 ± 26

All bins

0.41 ± 0.11
0.23 ± 0.06
7.0 ± 1.8
2.7 ± 0.8
10

1.13 ± 0.30
143 ± 615 ± 4161

0.52 ± 0.13

1.6 ± 0.6

5.4 ± 1.6

0.92 ± 0.22

0.65 ± 0.33

Last bin

1.9 ± 0.5

2.8 ± 0.7

9.1 ± 3.3

93 ± 415.9 ± 2.0

35 ± 4

Second to last bin

BoostedTable 11. The predicted post-fit event yields in the τhad τhad channel for mH = 125 GeV for the total number of events and for the two highest bins√of the BDT distributions for the data taken at s = 8 TeV. The background normalisations, signal normalisation, and their uncertainties represent
the post-fit values (see text). The uncertainties on the total background and total signal represent the full statistical and systematic uncertainty,
while the uncertainties on the individual background components represent the full systematic uncertainty only.

5

2.5 ± 0.6883 ± 18

Total background892

3.6 ± 1.3

0.16 ± 0.04

ZH : H → τ τ

Data

< 0.1

0.25 ± 0.07

WH : H → ττ
< 0.1

1.8 ± 0.5

0.67 ± 0.23

0.6 ± 0.7

VBF

Process/Category

JHEP04(2015)117– 38 –

9

Results+0.32µ = 1.43 +0.27−0.26 (stat.) −0.25 (syst.) ± 0.09(theory syst.).

The systematic uncertainties are split into two groups: systematic uncertainties (syst.)
including all experimental effects as well as theoretical uncertainties on the signal region
acceptance, such as those due to the QCD scales, the PDF choice, and the underlying
event and parton shower; and, separately, theoretical uncertainties on the inclusive Higgs
boson production cross section and H → τ τ branching ratio (theory syst.). The results foreach individual channel and for each category as well as for their combination are shownin figure 10. They are based on the full dataset, however, separate combined results are
given for the two centre-of-mass energies.
The probability p0 of obtaining a result at least as signal-like as observed in the dataˆ~ˆ~ˆ
if no signal were present is calculated using the test statistic qµ=0 = −2 ln(L(0, θ)/L(µ̂,θ))
in the asymptotic approximation [117]. For mH = 125.36 GeV, the observed p0 value is
2.7 × 10−6 , which corresponds to a deviation from the background-only hypothesis of 4.5σ.
This can be compared to an expected significance of 3.4σ. This provides evidence at thelevel of 4.5σ for the decay of the Higgs boson into tau leptons. Table 12 shows the expected
and observed significances for the signal strength measured in each channel separately.
Figure 11 shows the expected and observed number of events, in bins of log 10 (S/B),
for all signal region bins. Here, S/B is the signal-to-background ratio calculated assumingµ = 1.4 for each BDT bin in the signal regions. The expected signal yield for both µ = 1
and the best-fit value µ = 1.4 for mH = 125 GeV is shown on top of the background
prediction from the best-fit values. The background expectation where the signal-strengthparameter is fixed to µ = 0 is also shown for comparison.
To visualise the compatibility of this excess of events above background predictions
with the SM Higgs boson at mH = 125 GeV, a weighted distribution of events as a functionof mMMCis shown in figure 12. The events are weighted by a factor of ln(1 + S/B), whichττenhances the events compatible with the signal hypothesis. The excess of events in thismass distribution is consistent with the expectation for a Standard Model Higgs boson with
mH = 125 GeV. The distributions for the predicted excess in data over the backgroundare also shown for alternative SM Higgs boson mass hypotheses of mH = 110 GeV andmH = 150 GeV. The data favour a Higgs boson mass of mH = 125 GeV and are lessconsistent with the other masses considered.

– 39 –JHEP04(2015)117

As explained in the previous section, the observed signal strength is determined from a
global maximum likelihood fit to the BDT output distributions in data, with nuisanceparameters that are either free or constrained. The results are extracted for each channel
and for each category individually as well as for combinations of categories and for theoverall combination.
At the value of the Higgs boson mass obtained from the combination of the ATLAS
H → γγ and H → ZZ ∗ measurements [116], mH = 125.36 GeV, the signal strength obtained from the combined H → τ τ analysis is:Channel and Category

Observed Significance (σ)τlep τlep VBF

1.15

1.88

τlep τlep Boosted

0.57

1.72

τlep τlep Total

1.25

2.40

τlep τhad VBF

2.11

2.23

τlep τhad Boosted

1.11

1.01

τlep τhad Total

2.33

2.33

τhad τhad VBF

1.70

2.23

τhad τhad Boosted

0.82

2.56

τhad τhad Total

1.99

3.25

Combined

3.43

4.54

Table 12. The expected and observed significances of the signal in each channel and category forthe combined 7 and 8 TeV datasets.

Source of Uncertainty

Uncertainty on µ

Signal region statistics (data)

+0.27
−0.26

Jet energy scale± 0.13

Tau energy scale± 0.07

Tau identification± 0.06

Background normalisation± 0.12

Background estimate stat.

± 0.10BR (H → τ τ )± 0.08

Parton shower/Underlying event± 0.04PDF± 0.03

Total sys.

+0.33
−0.26

Total

+0.43
−0.37

Table 13. Important sources of uncertainty on the measured signal-strength parameter µ. The
contributions are given as absolute uncertainties on the best-fit value of µ = 1.43. Various subcomponents are combined assuming no correlations.

As discussed in section 8, the dominant uncertainties on the measurement of the signalstrength parameters include statistical uncertainties on the data from the signal regions,
uncertainties on the jet and tau energy scales, uncertainties on the normalisation of the
Z → τ τ and tt̄ background components as well as theoretical uncertainties. The contributions of each of these significant sources to the uncertainty of the measured signal strength
are summarised in table 13.

– 40 –JHEP04(2015)117

Expected Significance (σ)

σ(statistical)

ATLAS

σ(syst. excl. theory)

mH = 125.36 GeVσ(theory)

Total uncertainty± 1σ on µ

+ 0.3
- 0.3

H → ττ

+ 0.3µ = 1.4 +-0.4
0.4 - 0.2

Boosted+ 0.5µ = 2.1+-0.9
0.8 - 0.5

VBF

+ 0.3
µ = 1.2 +-0.4
0.4 - 0.3

+ 0.1
- 0.1

+ 0.8
7 TeV (Combined) µ = 0.9 +-1.1
1.1 - 0.8

8 TeV (Combined) µ = 1.5 +-0.5
0.4

+ 0.7
- 0.7

µ = 2.0+1.0 + 0.6-0.9 - 0.5

Boostedµ = 3.0+2.0 + 1.4-1.7 - 1.3

VBF

+ 0.8
µ = 1.7 +-1.0
0.9 - 0.8

H → τlepτhadµ = 1.0 +-0.5
0.5 - 0.3

+ 0.1
- 0.1

+ 0.4
- 0.3
+ 0.4
+ 0.1
- 0.1

+1.0 + 0.6-0.9 - 0.6

Boostedµ = 0.9VBF+ 0.5µ = 1.0 +-0.6
0.5 - 0.4
+ 0.5
- 0.5

+ 0.8
H → τhadτhad µ = 2.0 +-0.9
0.7 - 0.5
+ 0.1
- 0.1

+2.0 + 1.0-1.6 - 0.9

Boostedµ = 3.6VBF+ 0.6µ = 1.4 +-0.9
0.7 - 0.5

0s = 7 TeV, 4.5 fb-1
s = 8 TeV, 20.3 fb-1

2

4

Signal strength (µ)

Figure 10. The best-fit value for the signal strength µ in the individual channels and their√√
combination for the full ATLAS datasets at s = 7 TeV and s = 8 TeV. The total ±1σ uncertainty is indicated by the shaded green band, with the individual contributions from the statisticaluncertainty (top, black), the experimental systematic uncertainty (middle, blue), and the theory
uncertainty (bottom, red) on the signal cross section (from QCD scale, PDF, and branching ratios)shown by the error bars and printed in the central column.

The normalisation uncertainties on the Z → τ τ embedded sample are correlated acrossthe categories in each respective channel. The global fit also constrains the normalisation
for Z → τ τ more strongly than for the Z → `` and top-quark background components, as
the low BDT-score region is dominated by Z → τ τ events.
The measurement of the overall signal strength discussed above does not give direct
information on the relative contributions of the different production mechanisms. Therefore, the signal strengths of different production processes contributing to the H → τ τ
decay mode are determined, exploiting the sensitivity offered by the use of the event categories in the analyses of the three channels. The data are fitted separating the vectorboson-mediated VBF and V H processes from gluon-mediated ggF processes. Two signal
τ and µτ τ
strength parameters, µτggF
VBF+VH , which scale the SM-predicted rates to those ob-– 41 –JHEP04(2015)117

H → τlepτlep

+ 0.3
- 0.3

Events / bin

104

Data
Background (µ=1.4)
Background (µ=0)

310H (125)→ττ ( µ=1.4)
H (125)→ττ ( µ=1)

102
H→ττ
ATLAS
s = 8 TeV, 20.3 fb-1

1
-4

s = 7 TeV, 4.5 fb-1

-3

-2

-1

0

1

log10(S / B)
Figure 11. Event yields as a function of log10 (S/B), where S (signal yield) and B (backgroundyield) are taken from the BDT output bin of each event, assuming a signal strength µ = 1.4.
Events in all categories are included. The predicted background is obtained from the global fit(with µ = 1.4), and signal yields are shown for mH = 125 GeV at µ = 1 and µ = 1.4 (the best-fit
value). The background-only distribution (dashed line) is obtained from the global fit, with µ fixedat zero.

served, are introduced. The two-dimensional 68% and 95% confidence level (CL) contours
τ and µτ τin the plane of µτggF
VBF+VH [84] are shown in figure 13 for mH = 125.36 GeV. The
best-fit values areτµτggF= 2.0 ± 0.8(stat.) +1.2
−0.8 (syst.) ± 0.3(theory syst.)

and
+0.31
τ
µτVBF+VH= 1.24 +0.49−0.45 (stat.) −0.29 (syst.) ± 0.08(theory syst.),in agreement with the predictions from the Standard Model. The two results are strongly
anti-correlated (correlation coefficient of −48%). The observed (expected) significances ofτ and µτ τ
the µτggF
VBF+VH signal strengths are 1.74σ (0.95σ) and 2.25σ (1.72σ) respectively.
A total cross section times branching ratio for H → τ τ with mH = 125 GeV can also
be measured. The central value is obtained from the product of the measured µ and thepredicted cross section used to define it. The uncertainties are similarly obtained by scaling
the uncertainties on µ by the predicted cross section, noting that theoretical uncertainties
on the inclusive cross section cancel between µ and the predicted cross section and thus
are not included for the production processes under consideration. These include the– 42 –JHEP04(2015)11710

s = 7 TeV, 4.5 fb-1
s = 8 TeV, 20.3 fb-1ln(1+S/B) w. Events / 10 GeV

60

Data
H (125) (µ=1.0)
Z → ττ
Others
Fakes
Uncert.

40
20

ATLAS

80

H→ ττ VBF+Boosted

60

s = 7 TeV, 4.5 fb-1
s = 8 TeV, 20.3 fb

-1

20

0

0

20

10

H (125) (µ =1.0)
H (110) (µ =1.0)
H (150) (µ =1.0)

0
50

100

150

200
m MMC
[GeV]
ττ

Data
H (125) (µ=1.4)
Z → ττ
Others
Fakes
Uncert.

40

20

Weighted (Data-Bkg.)

ln(1+S/B) w. Events / 10 GeV

H→ ττ VBF+Boosted

10

(a)

H (125) (µ =1.4)
H (110) (µ =1.6)
H (150) (µ =6.2)

0
50

100

150

200
m MMC
[GeV]
ττ

(b)

Figure 12.
Distributions of the reconstructed invariant τ τ mass, mMMC
, where events areττweighted by ln(1 + S/B) for all channels. These weights are determined by the signal (S) andbackground (B) predictions for each BDT bin. The bottom panel in each plot shows the difference
between weighted data events and weighted background events (black points), compared to theweighted signal yields. The background predictions are obtained from the global fit with themH = 125 GeV signal hypothesis (signal strength µ = 1.4). The mH = 125 GeV signal is plottedwith a solid red line, and, for comparison, signals for mH = 110 GeV (blue) and mH = 150 GeV(green) are also shown. The signal normalisations are taken from fits to data with the corresponding
signal mass hypotheses, and the fitted µ values are given in the figure. The signal strengths areshown for the Standard Model expectations (µ = 1) in (a), while in (b) the best-fit values are used.

uncertainties on the inclusive cross section due to the QCD scale and the PDF choice as wellas the uncertainty on the branching ratio H → τ τ ; however, theoretical uncertainties on theacceptance of the signal regions from the QCD scale and PDF choice are retained, alongwith the uncertainties due to underlying event and parton shower, and the electroweak
correction on VBF production. Table 14 gives the measured values for the total crosssection at 7 and at 8 TeV, as well as the measured values at 8 TeV for gluon fusion
production and for VBF and V H production separately.

10

Cross-check with cut-based analysis

The search for the SM Higgs boson presented above is cross-checked for the dataset collected√
at s = 8 TeV in an analysis where cuts on kinematic variables are applied. This searchuses improved definitions of event categories and an improved fit model with respect to√results previously published for the s = 7 TeV dataset [21]. To allow a straightforward
comparison of results, the multivariate and cut-based analyses have common components.
The two analyses are performed for the same three channels, τlep τlep , τlep τhad and τhad τhad ,they use the same preselection and share the same strategy for the estimation of backgroundcontributions and systematic uncertainties. As in the multivariate analysis, the irreducible– 43 –JHEP04(2015)117

Weighted (Data-Bkg.)

ATLAS

80

VBF+VH

µττ

5
H→ττ

Best fits = 8 TeV, 20.3 fb-1

4
3

95% C.L.

s = 7 TeV, 4.5 fb-1

68% C.L.

ATLAS

SM prediction

2
1
0
-1

0

1

2

3

4

5

6

7
µττ

ggF

τ
τ
Figure 13. Likelihood contours for the combination of all channels in the (µτggF, µτVBF+VH) plane.
The signal strength µ is the ratio of the measured signal yield to the Standard Model expectation,for each production mode. The 68% and 95% CL contours are shown as dashed and solid lines
respectively, for mH = 125.36 GeV. The SM expectation is shown by a filled plus symbol, and thebest fit to the data is shown as a star.

Measured σ×BR [pb]Predicted σ×BR [pb]

7 TeV

+0.9
1.0 +0.9−0.8 (stat.)−0.8 (syst.)

1.09 ± 0.118 TeV

2.1 ± 0.4(stat.)+0.5−0.4 (syst.)

1.39 ± 0.14

Gluon fusion, 8 TeV

1.7 ± 1.1(stat.)+1.5−1.1 (syst.)

1.22 ± 0.14

VBF+V H, 8 TeV

0.26 ± 0.09(stat.)+0.06−0.05 (syst.)

0.17 ± 0.01

Table 14. Measured and predicted total cross section times branching ratio for H → τ τ with
mH = 125 GeV, at 7 TeV and at 8 TeV for all production modes, as well as for gluon fusion andfor VBF and V H production separately, at 8 TeV only. The theoretical predictions are obtained as
described in section 3.

– 44 –JHEP04(2015)117mH = 125.36 GeV

– 45 –JHEP04(2015)117

Z → τ τ background is estimated using the embedding procedure and the reducible ones
are estimated using similar data-driven methods, as described in section 6. Finally, thesame statistical methods are used to extract the results, although these are applied todifferent discriminating variables. While the multivariate analysis performs a fit to the
BDT output distribution, the cut-based analysis relies on a fit to the τ τ invariant mass
distribution. The τ τ invariant mass is calculated using the missing mass calculator, as
described in section 4.3. The analysis is not designed to be sensitive to a specific value ofthe Higgs boson mass mH . The use of the mass as the discriminating variable is motivated
not only by its power to separate the irreducible Z → τ τ background from signal, but also
by its sensitivity to the mass of the signal itself.
In the cut-based analysis, a categorisation is performed similar to that in the multivariate analysis, i.e. VBF and boosted categories are defined. To increase the separation power,
subcategories are introduced for the τlep τhad and τhad τhad channels. These subcategories
target events produced via the same production mode, but select different phase-space
regions with different signal-to-background ratios. With this strategy the most sensitive
subcategories have a small number of events, but a high signal-to-background ratio. Although the combined sensitivity is dominated by the few highly sensitive subcategories, theothers are important not just to increase the sensitivity but also to constrain the various
background components.
An overview of the defined categories in the three channels is given in table 15. In
all channels, the event categorisation is designed by splitting events first according to
the production mode, either VBF-like or boosted ggF-like, and second, for the τlep τhadand τhad τhad channels, by signal-to-background ratio. The events accepted in the VBF
categories pass a common selection that requires the presence of the two forward jets
distinctive of VBF production. In the τlep τhad channel, tight and loose VBF subcategories
are defined, via cuts on the mass of the dijet system, mjj , and pH
T , the transverse momentumof the Higgs boson candidate. In the τhad τhad channel, the variables used to select themost sensitive categories for both production modes are pH
T and the separation ∆R(τ1 , τ2 )between the two τhad candidates. In the VBF-like events, correlations between the invariant
mass of the selected jets mjj and ∆ηjj of the jets characteristic of VBF production are
also used. The subcategory with the highest purity is the VBF high-pH
T subcategory, whereH
tight cuts on pT and ∆R(τ1 , τ2 ) reject almost all non-resonant background sources. The
other two VBF-like subcategories are distinguished by a different signal-to-background ratio
due to a tighter selection applied to the forward jets. For the τhad τhad channel, boosted
subcategories are also defined. The division is based on the same cuts on pH
T and ∆R(τ1 , τ2 )H
as used in the VBF high-pT category. Events with low transverse momentum are not usedin any category because in such events the signal cannot be effectively distinguished frombackground channels. The proportion of the signal yield produced via VBF in the VBFlike subcategories is found to be 80% in the τlep τlep channel, between 67% and 85% in theτlep τhad channel and between 58% and 78% in the τhad τhad channel.
The final results are derived from the combined fit of the mτ τ distributions observedin the various subcategories. The number of fitted signal and background events in eachchannel and category is given in table 16. The combined mass distribution for the threeChannel

VBF category selection criteria
At least two jets with pjT1 > 40 GeV and pjT2 > 30 GeV|∆ηj1 ,j2 | > 3.0

τlep τlep

mj1 ,j2 > 400 GeV
b-jet veto for jets with pT > 25 GeV
Jet veto: no additional jet with pT > 25 GeV within |η| < 2.4
At least two jets with pjT1 > 40 GeV and pjT2 > 30 GeV
miss > 20 GeV
ET

T

T

T

T

T

T

b-jet veto for jets with pT > 30 GeV
τlep τhadmin(η(j1 ) , η(j2 ) ) < η(`) , η(τhad ) < max(η(j1 ) , η(j2 ) )VBF tight

VBF loose

mj1 ,j2 > 500 GeV

Non tight VBF

pH
T > 100 GeV
pτThad > 30 GeV
mvis > 40 GeV
At least two jets with pjT1 > 50 GeV and pjT2 > 30 GeV|∆η(τ1 , τ2 )| < 1.5|∆ηj1 ,j2 | > 2.6 and mj1 ,j2 > 250 GeV
τhad τhadmin(η(j1 ) , η(j2 ) ) < η(τ1 ) , η(τ2 ) < max(η(j1 ) , η(j2 ) )VBF high pH
T

VBF low pH
T , tight

VBF low pH
T , loose∆R(τ1 , τ2 ) < 1.5 and∆R(τ1 , τ2 ) > 1.5 or∆R(τ1 , τ2 ) > 1.5 orpH
T > 140 GeV

pH
T < 140 GeV

pH
T < 140 GeV

mj1 ,j2 [GeV] > (−250 ·|∆ηj1 ,j2 | + 1550)

mj1 ,j2 [GeV] < (−250 ·|∆ηj1 ,j2 | + 1550)

ChannelBoosted category selection criteria
Exclude events passing the VBF selectionτlep τleppH
T > 100 GeV
b-jet veto for jets with pT > 25 GeV
Exclude events passing the VBF selection
miss > 20 GeVETτlep τhadpH
T > 100 GeV
pT (τhad ) > 30 GeV
b-jet veto for jets with pT > 30 GeV
Exclude events passing the VBF selection∆η(τ1 , τ2 ) < 1.5

τhad τhadpH
T > 100 GeVBoosted high pH
T

Boosted low pH
T∆R(τ1 , τ2 ) < 1.5 and∆R(τ1 , τ2 ) > 1.5 orpH
T > 140 GeV

pH
T < 140 GeV

Table 15. Summary of the selection criteria used to define the VBF and boosted subcategories in
the cut-based analysis for the three analysis channels. The labels (1) and (2) refer to the leading(highest pT ) and subleading final-state objects (leptons, τhad , jets). The variables are defined in
the text.

– 46 –JHEP04(2015)117|∆ηj1 ,j2 | > 3.0 and η(j1 ) · η(j2 ) < 0,
mj1 ,j2 > 300 GeV
j1
j2
τhad
Total
`
miss
~
p
= |~
p + p~+ p~ + p~ + E| < 30 GeVτlep τlep
Total signal
Total backgroundDataτlep τhad
SignalBackground
Data

SignalBackground
Data

Boosted38 ± 133400 ± 64
3428
Boosted52 ± 174399 ± 73
4435
Boostedhigh pHlow pHT
T
17 ± 620 ± 71155 ± 28 2130 ± 41
1204
2121

√
Table 16. The measured signal and background yields of the cut-based analysis at s = 8 TeV inthe τlep τlep , τlep τhad and τhad τhad channels for mH = 125 GeV. The normalisations and uncertainties
are taken from the global fit. The uncertainties on the predicted yields reflect the full statisticaland systematic uncertainties.

channels is shown in figure 14, where events are weighted by ln(1 + S/B), based on thesignal and background content of their channel and category. An excess of events above
the expected SM background is visible in the mass region around 125 GeV.
The signal strengths extracted in the three analysis channels and their combination
are given in table 17. This cut-based analysis also provides evidence for H → τ τ decays,
giving a combined signal strength of+0.41µCut−based = 1.43 +0.36−0.35 (stat.) −0.33 (syst.) ± 0.10(theory syst.)

for mH = 125.36 GeV. For comparison, the results obtained in the multivariate analysis√
for the dataset at s = 8 TeV are also included in table 17. Good agreement between the
results of the two analyses is found for the individual channels as well as for their combination. To further quantify the level of agreement, the correlation ρ and the uncertainties on
the differences between the µ values obtained, i.e. ∆µ ± δ(∆µ), were evaluated using theso-called jackknife technique [118, 119]. Using this method, the correlation between the µvalues obtained in the two analyses is found to be between 0.55 and 0.75 for each of thethree analysis channels. The results of the analyses are found to be fully compatible, withdeviations ∆µ/δ(∆µ) below 1 for all analysis channels as well as for the combined result.
The probability p0 of obtaining a result at least as signal-like as observed if no signal
were present is shown as a function of the mass in figure 15 for the cut-based analysis for√the combined dataset at s = 8 TeV. The observed p0 values show a shallow minimum
around 125 GeV, corresponding to a significance of 3.2σ. The expected significance forthe cut-based analysis is superimposed on the figure and reaches a significance of 2.5σ at
mH = 125.36 GeV. The corresponding significance values for the multivariate analysis for– 47 –JHEP04(2015)117

τhad τhad

VBF
11 ± 4130 ± 7152
Tight VBF
Loose VBF
8.8 ± 317 ± 652 ± 4398 ± 1762407
VBF high pH
VBF
low pH
T
T
tight
loose
5.7 ± 1.9
5.2 ± 1.9 3.7 ± 1.3
59 ± 486 ± 5156 ± 765
94
157

ATLASH→ ττ Cut-based analysis

Data
H (125) (µ=1.4)
Z → ττ
Others
Fakes
Uncert.

30
20

s = 8 TeV, 20.3 fb-1

10

Weighted (Data-Bkg.)

02

H (125) (µ =1.4)
H (110) (µ =1.3)
H (150) (µ =1.9)

0
50

100

150

200
m MMC
[GeV]
ττ

Figure 14. Distribution of the reconstructed invariant τ τ mass, mMMC
, for the sum of all channels
ττ√in the cut-based analysis for the data taken at s = 8 TeV. The events are weighted by a factor
of ln(1 + S/B) based on the signal (S) and background (B) yields in each category. The bottom
panel shows the difference between weighted data events and weighted background events (black
points), compared to the weighted signal yields. The background predictions are obtained from theglobal fit with the mH = 125 GeV signal hypothesis (signal strength µ = 1.4). The mH = 125 GeV
signal is plotted as a solid red line, and, for comparison, signals for mH = 110 GeV (blue) andmH = 150 GeV (green) are also shown. The signal normalisations are taken from fits to data withthe corresponding signal mass hypotheses and the fitted µ values are given in the figure.

Fitted µ values√sMultivariate
analysisCut-based
analysisτlep τlep

8 TeV

1.9+1.0−0.9

3.2+1.4−1.3

τlep τhad

8 TeV

1.1+0.6−0.5

0.7+0.7−0.6

τhad τhad

8 TeV

1.8+0.9−0.7

1.6+0.9−0.7

All channels

8 TeV

1.53+0.47−0.41

1.43+0.55−0.49√
Table 17. Fitted values of the signal strength for the different channels at s = 8 TeV for themultivariate and cut-based analyses, measured at mH =125.36 GeV. The results for the combinationsof all channels are also given. The total uncertainties (statistical and systematic) are quoted.

– 48 –JHEP04(2015)117

ln(1+S/B) w. Events / 10 GeV

40

Local p0

s = 8 TeV, 20.3 fb-1

ATLAS

10
1

MVA Observed
CBA Observed
MVA Expected for mH = 125 GeV
CBA Expected for mH = 125 GeV

H→ττ

0σ
1σ

10-1

2σ
-2

10

3σ

10-3

4σ

-5

10

10-6
100

110

120

130

140

150

mH [GeV]Figure 15. Observed (solid red) and expected (dashed red) p0 values as a function of mH for the√
combination of all channels in the cut-based analysis (CBA) for the data taken at s = 8 TeV. The
expected p0 values are given for the background-only hypothesis. The corresponding observed andexpected p0 values for the multivariate analysis (MVA) are indicated for mH = 125 GeV by a fulland open star respectively. The axis labels on the right hand side and the dotted lines display thesignificance in units of Gaussian standard deviations.

√the dataset at s = 8 TeV are found to be 4.5σ (observed) and 3.3σ (expected). They arealso indicated in the figure.
Given the mass sensitivity of the cut-based analysis, a two-dimensional likelihood fit
for the signal strength µ and the mass mH is performed. The mass points are tested insteps of 5 GeV in the range between 100 GeV and 150 GeV. The best fit value is foundat µ = 1.4 and mH = 125 GeV. The result is shown in the (mH , µ) plane in figure 16
together with the 68% and 95% CL contours. This result indicates that the observation iscompatible with the decay of a Standard Model Higgs boson with a mass of 125 GeV.

11

Conclusions

Evidence for decays of the recently discovered Higgs boson into pairs of tau leptons ispresented. The analysis is based on the full set of proton-proton collision data recordedby the ATLAS experiment at the LHC during Run 1. The data correspond to integrated√√
luminosities of 4.5 fb−1 and 20.3 fb−1 at centre-of-mass energies of s = 7 TeV and s =8 TeV respectively. All combinations of leptonic and hadronic tau decay channels areincluded and event categories selecting both the vector boson fusion and highly boosted τ τsignatures are considered in a multivariate analysis. An excess of events over the expectedbackground from other Standard Model processes is found with an observed (expected)
significance of 4.5 (3.4) standard deviations. This excess is consistent with resulting from– 49 –JHEP04(2015)117

10-4

µ

5

H→ττ Cut-Based Analysis

4.5

s = 8 TeV, 20.3 fb-1

4

95% C.L.
68% C.L.
95% C.L.
(exp. m =125.36GeV µ=1.43)
H

68% C.L.
(exp. m =125.36GeV µ=1.43)

3.5 ATLAS
3

HBest fit

2.5
2
1
0.5
0
100

110

120

130

140

150

mH [GeV]Figure 16. The results of the two-dimensional likelihood fit in the (mH , µ) plane for the cut-based√
analysis for the data taken at s = 8 TeV. The signal strength µ is the ratio of the measured signal
yield to the Standard Model expectation. The 68% and 95% CL contours are shown as dashed andsolid red lines respectively. The best-fit value is indicated as a red cross. The dashed and solid bluelines correspond to the expected 68% and 95% CL contours for mH = 125.36 GeV and µ = 1.43.

H → τ τ decays with mH = 125.36 GeV. The measured signal strength, normalised to theStandard Model expectation, is+0.32µ = 1.43 +0.27−0.26 (stat.) −0.25 (syst.) ± 0.09(theory syst.).

This value is consistent with the predicted Yukawa coupling strength of the Higgs bosonin the Standard Model.
The results of the multivariate analysis are cross-checked for the data collected at√
s = 8 TeV using a cut-based analysis. The results confirm the findings of the multivariate
analysis, and an excess with a compatible signal strength is found. A two-dimensional fit of
the signal strength µ and mH in the cut-based analysis indicates that the observed excess
is compatible with the τ τ decay of the Higgs boson with a mass of 125 GeV.

Acknowledgments
We thank CERN for the very successful operation of the LHC, as well as the support staff
from our institutions without whom ATLAS could not be operated efficiently.
We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and
FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST
and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR,– 50 –JHEP04(2015)117

1.5

Open Access. This article is distributed under the terms of the Creative Commons
Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction inany medium, provided the original author(s) and source are credited.

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G. Aad85 , B. Abbott113 , J. Abdallah152 , S. Abdel Khalek117 , O. Abdinov11 , R. Aben107 ,B. Abi114 , M. Abolins90 , O.S. AbouZeid159 , H. Abramowicz154 , H. Abreu153 , R. Abreu30 ,Y. Abulaiti147a,147b , B.S. Acharya165a,165b,a , L. Adamczyk38a , D.L. Adams25 , J. Adelman108 ,S. Adomeit100 , T. Adye131 , T. Agatonovic-Jovin13a , J.A. Aguilar-Saavedra126a,126f ,M. Agustoni17 , S.P. Ahlen22 , F. Ahmadov65,b , G. Aielli134a,134b , H. Akerstedt147a,147b ,T.P.A. Åkesson81 , G. Akimoto156 , A.V. Akimov96 , G.L. Alberghi20a,20b , J. Albert170 ,S. Albrand55 , M.J. Alconada Verzini71 , M. Aleksa30 , I.N. Aleksandrov65 , C. Alexa26a ,G. Alexander154 , G. Alexandre49 , T. Alexopoulos10 , M. Alhroob113 , G. Alimonti91a , L. Alio85 ,J. Alison31 , B.M.M. Allbrooke18 , L.J. Allison72 , P.P. Allport74 , A. Aloisio104a,104b , A. Alonso36 ,F. Alonso71 , C. Alpigiani76 , A. Altheimer35 , B. Alvarez Gonzalez90 , D. Álvarez Piqueras168 ,M.G. Alviggi104a,104b , K. Amako66 , Y. Amaral Coutinho24a , C. Amelung23 , D. Amidei89 ,S.P. Amor Dos Santos126a,126c , A. Amorim126a,126b , S. Amoroso48 , N. Amram154 , G. Amundsen23 ,C. Anastopoulos140 , L.S. Ancu49 , N. Andari30 , T. Andeen35 , C.F. Anders58b , G. Anders30 ,K.J. Anderson31 , A. Andreazza91a,91b , V. Andrei58a , X.S. Anduaga71 , S. Angelidakis9 ,I. Angelozzi107 , P. Anger44 , A. Angerami35 , F. Anghinolfi30 , A.V. Anisenkov109,c , N. Anjos12 ,A. Annovi47 , M. Antonelli47 , A. Antonov98 , J. Antos145b , F. Anulli133a , M. Aoki66 ,L. Aperio Bella18 , G. Arabidze90 , Y. Arai66 , J.P. Araque126a , A.T.H. Arce45 , F.A. Arduh71 ,J-F. Arguin95 , S. Argyropoulos42 , M. Arik19a , A.J. Armbruster30 , O. Arnaez30 , V. Arnal82 ,H. Arnold48 , M. Arratia28 , O. Arslan21 , A. Artamonov97 , G. Artoni23 , S. Asai156 , N. Asbah42 ,A. Ashkenazi154 , B. Åsman147a,147b , L. Asquith150 , K. Assamagan25 , R. Astalos145a ,M. Atkinson166 , N.B. Atlay142 , B. Auerbach6 , K. Augsten128 , M. Aurousseau146b , G. Avolio30 ,B. Axen15 , G. Azuelos95,d , Y. Azuma156 , M.A. Baak30 , A.E. Baas58a , C. Bacci135a,135b ,H. Bachacou137 , K. Bachas155 , M. Backes30 , M. Backhaus30 , E. Badescu26a , P. Bagiacchi133a,133b ,P. Bagnaia133a,133b , Y. Bai33a , T. Bain35 , J.T. Baines131 , O.K. Baker177 , P. Balek129 , F. Balli84 ,E. Banas39 , Sw. Banerjee174 , A.A.E. Bannoura176 , H.S. Bansil18 , L. Barak173 , S.P. Baranov96 ,E.L. Barberio88 , D. Barberis50a,50b , M. Barbero85 , T. Barillari101 , M. Barisonzi176 , T. Barklow144 ,N. Barlow28 , S.L. Barnes84 , B.M. Barnett131 , R.M. Barnett15 , Z. Barnovska5 , A. Baroncelli135a ,G. Barone49 , A.J. Barr120 , F. Barreiro82 , J. Barreiro Guimarães da Costa57 , R. Bartoldus144 ,A.E. Barton72 , P. Bartos145a , V. Bartsch150 , A. Bassalat117 , A. Basye166 , R.L. Bates53 ,S.J. Batista159 , J.R. Batley28 , M. Battaglia138 , M. Battistin30 , F. Bauer137 , H.S. Bawa144,e ,J.B. Beacham111 , M.D. Beattie72 , T. Beau80 , P.H. Beauchemin162 , R. Beccherle124a,124b ,P. Bechtle21 , H.P. Beck17,f , K. Becker120 , S. Becker100 , M. Beckingham171 , C. Becot117 ,A.J. Beddall19c , A. Beddall19c , S. Bedikian177 , V.A. Bednyakov65 , C.P. Bee149 , L.J. Beemster107 ,T.A. Beermann176 , M. Begel25 , K. Behr120 , C. Belanger-Champagne87 , P.J. Bell49 , W.H. Bell49 ,G. Bella154 , L. Bellagamba20a , A. Bellerive29 , M. Bellomo86 , K. Belotskiy98 , O. Beltramello30 ,O. Benary154 , D. Benchekroun136a , K. Bendtz147a,147b , N. Benekos166 , Y. Benhammou154 ,E. Benhar Noccioli49 , J.A. Benitez Garcia160b , D.P. Benjamin45 , J.R. Bensinger23 ,S. Bentvelsen107 , D. Berge107 , E. Bergeaas Kuutmann167 , N. Berger5 , F. Berghaus170 ,J. Beringer15 , C. Bernard22 , N.R. Bernard86 , C. Bernius110 , F.U. Bernlochner21 , T. Berry77 ,P. Berta129 , C. Bertella83 , G. Bertoli147a,147b , F. Bertolucci124a,124b , C. Bertsche113 ,D. Bertsche113 , M.I. Besana91a , G.J. Besjes106 , O. Bessidskaia Bylund147a,147b , M. Bessner42 ,N. Besson137 , C. Betancourt48 , S. Bethke101 , A.J. Bevan76 , W. Bhimji46 , R.M. Bianchi125 ,L. Bianchini23 , M. Bianco30 , O. Biebel100 , S.P. Bieniek78 , K. Bierwagen54 , M. Biglietti135a ,J. Bilbao De Mendizabal49 , H. Bilokon47 , M. Bindi54 , S. Binet117 , A. Bingul19c , C. Bini133a,133b ,C.W. Black151 , J.E. Black144 , K.M. Black22 , D. Blackburn139 , R.E. Blair6 , J.-B. Blanchard137 ,T. Blazek145a , I. Bloch42 , C. Blocker23 , W. Blum83,∗ , U. Blumenschein54 , G.J. Bobbink107 ,V.S. Bobrovnikov109,c , S.S. Bocchetta81 , A. Bocci45 , C. Bock100 , C.R. Boddy120 , M. Boehler48 ,T.T. Boek176 , J.A. Bogaerts30 , A.G. Bogdanchikov109 , A. Bogouch92,∗ , C. Bohm147a ,V. Boisvert77 , T. Bold38a , V. Boldea26a , A.S. Boldyrev99 , M. Bomben80 , M. Bona76 ,M. Boonekamp137 , A. Borisov130 , G. Borissov72 , S. Borroni42 , J. Bortfeldt100 , V. Bortolotto60a ,K. Bos107 , D. Boscherini20a , M. Bosman12 , H. Boterenbrood107 , J. Boudreau125 , J. Bouffard2 ,– 59 –JHEP04(2015)117

E.V. Bouhova-Thacker72 , D. Boumediene34 , C. Bourdarios117 , N. Bousson114 , S. Boutouil136d ,A. Boveia31 , J. Boyd30 , I.R. Boyko65 , I. Bozic13a , J. Bracinik18 , A. Brandt8 , G. Brandt15 ,O. Brandt58a , U. Bratzler157 , B. Brau86 , J.E. Brau116 , H.M. Braun176,∗ , S.F. Brazzale165a,165c ,B. Brelier159 , K. Brendlinger122 , A.J. Brennan88 , R. Brenner167 , S. Bressler173 , K. Bristow146c ,T.M. Bristow46 , D. Britton53 , F.M. Brochu28 , I. Brock21 , R. Brock90 , J. Bronner101 ,G. Brooijmans35 , T. Brooks77 , W.K. Brooks32b , J. Brosamer15 , E. Brost116 , J. Brown55 ,P.A. Bruckman de Renstrom39 , D. Bruncko145b , R. Bruneliere48 , S. Brunet61 , A. Bruni20a ,G. Bruni20a , M. Bruschi20a , L. Bryngemark81 , T. Buanes14 , Q. Buat143 , F. Bucci49 ,P. Buchholz142 , A.G. Buckley53 , S.I. Buda26a , I.A. Budagov65 , F. Buehrer48 , L. Bugge119 ,M.K. Bugge119 , O. Bulekov98 , A.C. Bundock74 , H. Burckhart30 , S. Burdin74 , B. Burghgrave108 ,S. Burke131 , I. Burmeister43 , E. Busato34 , D. Büscher48 , V. Büscher83 , P. Bussey53 ,C.P. Buszello167 , B. Butler57 , J.M. Butler22 , A.I. Butt3 , C.M. Buttar53 , J.M. Butterworth78 ,P. Butti107 , W. Buttinger28 , A. Buzatu53 , M. Byszewski10 , S. Cabrera Urbán168 ,D. Caforio20a,20b , O. Cakir4a , P. Calafiura15 , A. Calandri137 , G. Calderini80 , P. Calfayan100 ,L.P. Caloba24a , D. Calvet34 , S. Calvet34 , R. Camacho Toro49 , S. Camarda42 , D. Cameron119 ,L.M. Caminada15 , R. Caminal Armadans12 , S. Campana30 , M. Campanelli78 , A. Campoverde149 ,V. Canale104a,104b , A. Canepa160a , M. Cano Bret76 , J. Cantero82 , R. Cantrill126a , T. Cao40 ,M.D.M. Capeans Garrido30 , I. Caprini26a , M. Caprini26a , M. Capua37a,37b , R. Caputo83 ,R. Cardarelli134a , T. Carli30 , G. Carlino104a , L. Carminati91a,91b , S. Caron106 , E. Carquin32a ,G.D. Carrillo-Montoya146c , J.R. Carter28 , J. Carvalho126a,126c , D. Casadei78 , M.P. Casado12 ,M. Casolino12 , E. Castaneda-Miranda146b , A. Castelli107 , V. Castillo Gimenez168 , N.F. Castro126a ,P. Catastini57 , A. Catinaccio30 , J.R. Catmore119 , A. Cattai30 , G. Cattani134a,134b , J. Caudron83 ,V. Cavaliere166 , D. Cavalli91a , M. Cavalli-Sforza12 , V. Cavasinni124a,124b , F. Ceradini135a,135b ,B.C. Cerio45 , K. Cerny129 , A.S. Cerqueira24b , A. Cerri150 , L. Cerrito76 , F. Cerutti15 , M. Cerv30 ,A. Cervelli17 , S.A. Cetin19b , A. Chafaq136a , D. Chakraborty108 , I. Chalupkova129 , P. Chang166 ,B. Chapleau87 , J.D. Chapman28 , D. Charfeddine117 , D.G. Charlton18 , C.C. Chau159 ,C.A. Chavez Barajas150 , S. Cheatham153 , A. Chegwidden90 , S. Chekanov6 , S.V. Chekulaev160a ,G.A. Chelkov65,g , M.A. Chelstowska89 , C. Chen64 , H. Chen25 , K. Chen149 , L. Chen33d,h ,S. Chen33c , X. Chen33f , Y. Chen67 , H.C. Cheng89 , Y. Cheng31 , A. Cheplakov65 ,E. Cheremushkina130 , R. Cherkaoui El Moursli136e , V. Chernyatin25,∗ , E. Cheu7 , L. Chevalier137 ,V. Chiarella47 , G. Chiefari104a,104b , J.T. Childers6 , A. Chilingarov72 , G. Chiodini73a ,A.S. Chisholm18 , R.T. Chislett78 , A. Chitan26a , M.V. Chizhov65 , S. Chouridou9 , B.K.B. Chow100 ,D. Chromek-Burckhart30 , M.L. Chu152 , J. Chudoba127 , J.J. Chwastowski39 , L. Chytka115 ,G. Ciapetti133a,133b , A.K. Ciftci4a , R. Ciftci4a , D. Cinca53 , V. Cindro75 , A. Ciocio15 ,Z.H. Citron173 , M. Citterio91a , M. Ciubancan26a , A. Clark49 , P.J. Clark46 , R.N. Clarke15 ,W. Cleland125 , J.C. Clemens85 , C. Clement147a,147b , Y. Coadou85 , M. Cobal165a,165c ,A. Coccaro139 , J. Cochran64 , L. Coffey23 , J.G. Cogan144 , B. Cole35 , S. Cole108 , A.P. Colijn107 ,J. Collot55 , T. Colombo58c , G. Compostella101 , P. Conde Muiño126a,126b , E. Coniavitis48 ,S.H. Connell146b , I.A. Connelly77 , S.M. Consonni91a,91b , V. Consorti48 , S. Constantinescu26a ,C. Conta121a,121b , G. Conti30 , F. Conventi104a,i , M. Cooke15 , B.D. Cooper78 ,A.M. Cooper-Sarkar120 , N.J. Cooper-Smith77 , K. Copic15 , T. Cornelissen176 , M. Corradi20a ,F. Corriveau87,j , A. Corso-Radu164 , A. Cortes-Gonzalez12 , G. Cortiana101 , G. Costa91a ,M.J. Costa168 , D. Costanzo140 , D. Côté8 , G. Cottin28 , G. Cowan77 , B.E. Cox84 , K. Cranmer110 ,G. Cree29 , S. Crépé-Renaudin55 , F. Crescioli80 , W.A. Cribbs147a,147b , M. Crispin Ortuzar120 ,M. Cristinziani21 , V. Croft106 , G. Crosetti37a,37b , T. Cuhadar Donszelmann140 , J. Cummings177 ,M. Curatolo47 , C. Cuthbert151 , H. Czirr142 , P. Czodrowski3 , S. D’Auria53 , M. D’Onofrio74 ,M.J. Da Cunha Sargedas De Sousa126a,126b , C. Da Via84 , W. Dabrowski38a , A. Dafinca120 ,T. Dai89 , O. Dale14 , F. Dallaire95 , C. Dallapiccola86 , M. Dam36 , A.C. Daniells18 ,M. Danninger169 , M. Dano Hoffmann137 , V. Dao48 , G. Darbo50a , S. Darmora8 , J. Dassoulas74 ,A. Dattagupta61 , W. Davey21 , C. David170 , T. Davidek129 , E. Davies120,k , M. Davies154 ,O. Davignon80 , A.R. Davison78 , P. Davison78 , Y. Davygora58a , E. Dawe143 , I. Dawson140 ,R.K. Daya-Ishmukhametova86 , K. De8 , R. de Asmundis104a , S. De Castro20a,20b , S. De Cecco80 ,– 60 –JHEP04(2015)117

N. De Groot106 , P. de Jong107 , H. De la Torre82 , F. De Lorenzi64 , L. De Nooij107 , D. De Pedis133a ,A. De Salvo133a , U. De Sanctis150 , A. De Santo150 , J.B. De Vivie De Regie117 , W.J. Dearnaley72 ,R. Debbe25 , C. Debenedetti138 , B. Dechenaux55 , D.V. Dedovich65 , I. Deigaard107 , J. Del Peso82 ,T. Del Prete124a,124b , F. Deliot137 , C.M. Delitzsch49 , M. Deliyergiyev75 , A. Dell’Acqua30 ,L. Dell’Asta22 , M. Dell’Orso124a,124b , M. Della Pietra104a,i , D. della Volpe49 , M. Delmastro5 ,P.A. Delsart55 , C. Deluca107 , D.A. DeMarco159 , S. Demers177 , M. Demichev65 , A. Demilly80 ,S.P. Denisov130 , D. Derendarz39 , J.E. Derkaoui136d , F. Derue80 , P. Dervan74 , K. Desch21 ,C. Deterre42 , P.O. Deviveiros30 , A. Dewhurst131 , S. Dhaliwal107 , A. Di Ciaccio134a,134b ,L. Di Ciaccio5 , A. Di Domenico133a,133b , C. Di Donato104a,104b , A. Di Girolamo30 ,B. Di Girolamo30 , A. Di Mattia153 , B. Di Micco135a,135b , R. Di Nardo47 , A. Di Simone48 ,R. Di Sipio20a,20b , D. Di Valentino29 , F.A. Dias46 , M.A. Diaz32a , E.B. Diehl89 , J. Dietrich16 ,T.A. Dietzsch58a , S. Diglio85 , A. Dimitrievska13a , J. Dingfelder21 , P. Dita26a , S. Dita26a ,F. Dittus30 , F. Djama85 , T. Djobava51b , J.I. Djuvsland58a , M.A.B. do Vale24c , D. Dobos30 ,C. Doglioni49 , T. Doherty53 , T. Dohmae156 , J. Dolejsi129 , Z. Dolezal129 , B.A. Dolgoshein98,∗ ,M. Donadelli24d , S. Donati124a,124b , P. Dondero121a,121b , J. Donini34 , J. Dopke131 , A. Doria104a ,M.T. Dova71 , A.T. Doyle53 , E. Drechsler54 , M. Dris10 , J. Dubbert89 , S. Dube15 , E. Dubreuil34 ,E. Duchovni173 , G. Duckeck100 , O.A. Ducu26a , D. Duda176 , A. Dudarev30 , F. Dudziak64 ,L. Duflot117 , L. Duguid77 , M. Dührssen30 , M. Dunford58a , H. Duran Yildiz4a , M. Düren52 ,A. Durglishvili51b , D. Duschinger44 , M. Dwuznik38a , M. Dyndal38a , J. Ebke100 , W. Edson2 ,N.C. Edwards46 , W. Ehrenfeld21 , T. Eifert30 , G. Eigen14 , K. Einsweiler15 , T. Ekelof167 ,M. El Kacimi136c , M. Ellert167 , S. Elles5 , F. Ellinghaus83 , A.A. Elliot170 , N. Ellis30 ,J. Elmsheuser100 , M. Elsing30 , D. Emeliyanov131 , Y. Enari156 , O.C. Endner83 , M. Endo118 ,R. Engelmann149 , J. Erdmann43 , A. Ereditato17 , D. Eriksson147a , G. Ernis176 , J. Ernst2 ,M. Ernst25 , J. Ernwein137 , S. Errede166 , E. Ertel83 , M. Escalier117 , H. Esch43 , C. Escobar125 ,B. Esposito47 , A.I. Etienvre137 , E. Etzion154 , H. Evans61 , A. Ezhilov123 , L. Fabbri20a,20b ,G. Facini31 , R.M. Fakhrutdinov130 , S. Falciano133a , R.J. Falla78 , J. Faltova129 , Y. Fang33a ,M. Fanti91a,91b , A. Farbin8 , A. Farilla135a , T. Farooque12 , S. Farrell15 , S.M. Farrington171 ,P. Farthouat30 , F. Fassi136e , P. Fassnacht30 , D. Fassouliotis9 , A. Favareto50a,50b , L. Fayard117 ,P. Federic145a , O.L. Fedin123,l , W. Fedorko169 , S. Feigl30 , L. Feligioni85 , C. Feng33d , E.J. Feng6 ,H. Feng89 , A.B. Fenyuk130 , P. Fernandez Martinez168 , S. Fernandez Perez30 , S. Ferrag53 ,J. Ferrando53 , A. Ferrari167 , P. Ferrari107 , R. Ferrari121a , D.E. Ferreira de Lima53 , A. Ferrer168 ,D. Ferrere49 , C. Ferretti89 , A. Ferretto Parodi50a,50b , M. Fiascaris31 , F. Fiedler83 , A. Filipčič75 ,M. Filipuzzi42 , F. Filthaut106 , M. Fincke-Keeler170 , K.D. Finelli151 , M.C.N. Fiolhais126a,126c ,L. Fiorini168 , A. Firan40 , A. Fischer2 , J. Fischer176 , W.C. Fisher90 , E.A. Fitzgerald23 , M. Flechl48 ,I. Fleck142 , P. Fleischmann89 , S. Fleischmann176 , G.T. Fletcher140 , G. Fletcher76 , T. Flick176 ,A. Floderus81 , L.R. Flores Castillo60a , M.J. Flowerdew101 , A. Formica137 , A. Forti84 ,D. Fournier117 , H. Fox72 , S. Fracchia12 , P. Francavilla80 , M. Franchini20a,20b , S. Franchino30 ,D. Francis30 , L. Franconi119 , M. Franklin57 , M. Fraternali121a,121b , S.T. French28 , C. Friedrich42 ,F. Friedrich44 , D. Froidevaux30 , J.A. Frost120 , C. Fukunaga157 , E. Fullana Torregrosa83 ,B.G. Fulsom144 , J. Fuster168 , C. Gabaldon55 , O. Gabizon176 , A. Gabrielli20a,20b ,A. Gabrielli133a,133b , S. Gadatsch107 , S. Gadomski49 , G. Gagliardi50a,50b , P. Gagnon61 ,C. Galea106 , B. Galhardo126a,126c , E.J. Gallas120 , B.J. Gallop131 , P. Gallus128 , G. Galster36 ,K.K. Gan111 , J. Gao33b , Y.S. Gao144,e , F.M. Garay Walls46 , F. Garberson177 , C. Garcı́a168 ,J.E. Garcı́a Navarro168 , M. Garcia-Sciveres15 , R.W. Gardner31 , N. Garelli144 , V. Garonne30 ,C. Gatti47 , G. Gaudio121a , B. Gaur142 , L. Gauthier95 , P. Gauzzi133a,133b , I.L. Gavrilenko96 ,C. Gay169 , G. Gaycken21 , E.N. Gazis10 , P. Ge33d , Z. Gecse169 , C.N.P. Gee131 , D.A.A. Geerts107 ,Ch. Geich-Gimbel21 , K. Gellerstedt147a,147b , C. Gemme50a , A. Gemmell53 , M.H. Genest55 ,S. Gentile133a,133b , M. George54 , S. George77 , D. Gerbaudo164 , A. Gershon154 , H. Ghazlane136b ,N. Ghodbane34 , B. Giacobbe20a , S. Giagu133a,133b , V. Giangiobbe12 , P. Giannetti124a,124b ,F. Gianotti30 , B. Gibbard25 , S.M. Gibson77 , M. Gilchriese15 , T.P.S. Gillam28 , D. Gillberg30 ,G. Gilles34 , D.M. Gingrich3,d , N. Giokaris9 , M.P. Giordani165a,165c , R. Giordano104a,104b ,F.M. Giorgi20a , F.M. Giorgi16 , P.F. Giraud137 , D. Giugni91a , C. Giuliani48 , M. Giulini58b ,– 61 –JHEP04(2015)117

B.K. Gjelsten119 , S. Gkaitatzis155 , I. Gkialas155 , E.L. Gkougkousis117 , L.K. Gladilin99 ,C. Glasman82 , J. Glatzer30 , P.C.F. Glaysher46 , A. Glazov42 , G.L. Glonti62 , M. Goblirsch-Kolb101 ,J.R. Goddard76 , J. Godlewski30 , S. Goldfarb89 , T. Golling49 , D. Golubkov130 ,A. Gomes126a,126b,126d , L.S. Gomez Fajardo42 , R. Gonçalo126a ,J. Goncalves Pinto Firmino Da Costa137 , L. Gonella21 , S. González de la Hoz168 ,G. Gonzalez Parra12 , S. Gonzalez-Sevilla49 , L. Goossens30 , P.A. Gorbounov97 , H.A. Gordon25 ,I. Gorelov105 , B. Gorini30 , E. Gorini73a,73b , A. Gorišek75 , E. Gornicki39 , A.T. Goshaw45 ,C. Gössling43 , M.I. Gostkin65 , M. Gouighri136a , D. Goujdami136c , M.P. Goulette49 ,A.G. Goussiou139 , C. Goy5 , H.M.X. Grabas138 , L. Graber54 , I. Grabowska-Bold38a ,P. Grafström20a,20b , K-J. Grahn42 , J. Gramling49 , E. Gramstad119 , S. Grancagnolo16 ,V. Grassi149 , V. Gratchev123 , H.M. Gray30 , E. Graziani135a , O.G. Grebenyuk123 ,Z.D. Greenwood79,m , K. Gregersen78 , I.M. Gregor42 , P. Grenier144 , J. Griffiths8 , A.A. Grillo138 ,K. Grimm72 , S. Grinstein12,n , Ph. Gris34 , Y.V. Grishkevich99 , J.-F. Grivaz117 , J.P. Grohs44 ,A. Grohsjean42 , E. Gross173 , J. Grosse-Knetter54 , G.C. Grossi134a,134b , Z.J. Grout150 , L. Guan33b ,J. Guenther128 , F. Guescini49 , D. Guest177 , O. Gueta154 , C. Guicheney34 , E. Guido50a,50b ,T. Guillemin117 , S. Guindon2 , U. Gul53 , C. Gumpert44 , J. Guo35 , S. Gupta120 , P. Gutierrez113 ,N.G. Gutierrez Ortiz53 , C. Gutschow78 , N. Guttman154 , C. Guyot137 , C. Gwenlan120 ,C.B. Gwilliam74 , A. Haas110 , C. Haber15 , H.K. Hadavand8 , N. Haddad136e , P. Haefner21 ,S. Hageböck21 , Z. Hajduk39 , H. Hakobyan178 , M. Haleem42 , J. Haley114 , D. Hall120 ,G. Halladjian90 , G.D. Hallewell85 , K. Hamacher176 , P. Hamal115 , K. Hamano170 , M. Hamer54 ,A. Hamilton146a , S. Hamilton162 , G.N. Hamity146c , P.G. Hamnett42 , L. Han33b , K. Hanagaki118 ,K. Hanawa156 , M. Hance15 , P. Hanke58a , R. Hanna137 , J.B. Hansen36 , J.D. Hansen36 ,P.H. Hansen36 , K. Hara161 , A.S. Hard174 , T. Harenberg176 , F. Hariri117 , S. Harkusha92 ,R.D. Harrington46 , P.F. Harrison171 , F. Hartjes107 , M. Hasegawa67 , S. Hasegawa103 ,Y. Hasegawa141 , A. Hasib113 , S. Hassani137 , S. Haug17 , M. Hauschild30 , R. Hauser90 ,M. Havranek127 , C.M. Hawkes18 , R.J. Hawkings30 , A.D. Hawkins81 , T. Hayashi161 , D. Hayden90 ,C.P. Hays120 , J.M. Hays76 , H.S. Hayward74 , S.J. Haywood131 , S.J. Head18 , T. Heck83 ,V. Hedberg81 , L. Heelan8 , S. Heim122 , T. Heim176 , B. Heinemann15 , L. Heinrich110 , J. Hejbal127 ,L. Helary22 , C. Heller100 , M. Heller30 , S. Hellman147a,147b , D. Hellmich21 , C. Helsens30 ,J. Henderson120 , R.C.W. Henderson72 , Y. Heng174 , C. Hengler42 , A. Henrichs177 ,A.M. Henriques Correia30 , S. Henrot-Versille117 , G.H. Herbert16 , Y. Hernández Jiménez168 ,R. Herrberg-Schubert16 , G. Herten48 , R. Hertenberger100 , L. Hervas30 , G.G. Hesketh78 ,N.P. Hessey107 , R. Hickling76 , E. Higón-Rodriguez168 , E. Hill170 , J.C. Hill28 , K.H. Hiller42 ,S.J. Hillier18 , I. Hinchliffe15 , E. Hines122 , R.R. Hinman15 , M. Hirose158 , D. Hirschbuehl176 ,J. Hobbs149 , N. Hod107 , M.C. Hodgkinson140 , P. Hodgson140 , A. Hoecker30 , M.R. Hoeferkamp105 ,F. Hoenig100 , D. Hoffmann85 , M. Hohlfeld83 , T.R. Holmes15 , T.M. Hong122 ,L. Hooft van Huysduynen110 , W.H. Hopkins116 , Y. Horii103 , A.J. Horton143 , J-Y. Hostachy55 ,S. Hou152 , A. Hoummada136a , J. Howard120 , J. Howarth42 , M. Hrabovsky115 , I. Hristova16 ,J. Hrivnac117 , T. Hryn’ova5 , A. Hrynevich93 , C. Hsu146c , P.J. Hsu152,o , S.-C. Hsu139 , D. Hu35 ,X. Hu89 , Y. Huang42 , Z. Hubacek30 , F. Hubaut85 , F. Huegging21 , T.B. Huffman120 ,E.W. Hughes35 , G. Hughes72 , M. Huhtinen30 , T.A. Hülsing83 , M. Hurwitz15 , N. Huseynov65,b ,J. Huston90 , J. Huth57 , G. Iacobucci49 , G. Iakovidis10 , I. Ibragimov142 , L. Iconomidou-Fayard117 ,E. Ideal177 , Z. Idrissi136e , P. Iengo104a , O. Igonkina107 , T. Iizawa172 , Y. Ikegami66 ,K. Ikematsu142 , M. Ikeno66 , Y. Ilchenko31,p , D. Iliadis155 , N. Ilic159 , Y. Inamaru67 , T. Ince101 ,P. Ioannou9 , M. Iodice135a , K. Iordanidou9 , V. Ippolito57 , A. Irles Quiles168 , C. Isaksson167 ,M. Ishino68 , M. Ishitsuka158 , R. Ishmukhametov111 , C. Issever120 , S. Istin19a ,J.M. Iturbe Ponce84 , R. Iuppa134a,134b , J. Ivarsson81 , W. Iwanski39 , H. Iwasaki66 , J.M. Izen41 ,V. Izzo104a , B. Jackson122 , M. Jackson74 , P. Jackson1 , M.R. Jaekel30 , V. Jain2 , K. Jakobs48 ,S. Jakobsen30 , T. Jakoubek127 , J. Jakubek128 , D.O. Jamin152 , D.K. Jana79 , E. Jansen78 ,H. Jansen30 , J. Janssen21 , M. Janus171 , G. Jarlskog81 , N. Javadov65,b , T. Javůrek48 , L. Jeanty15 ,J. Jejelava51a,q , G.-Y. Jeng151 , D. Jennens88 , P. Jenni48,r , J. Jentzsch43 , C. Jeske171 , S. Jézéquel5 ,H. Ji174 , J. Jia149 , Y. Jiang33b , M. Jimenez Belenguer42 , S. Jin33a , A. Jinaru26a , O. Jinnouchi158 ,– 62 –JHEP04(2015)117

M.D. Joergensen36 , P. Johansson140 , K.A. Johns7 , K. Jon-And147a,147b , G. Jones171 ,R.W.L. Jones72 , T.J. Jones74 , J. Jongmanns58a , P.M. Jorge126a,126b , K.D. Joshi84 , J. Jovicevic148 ,X. Ju174 , C.A. Jung43 , P. Jussel62 , A. Juste Rozas12,n , M. Kaci168 , A. Kaczmarska39 , M. Kado117 ,H. Kagan111 , M. Kagan144 , E. Kajomovitz45 , C.W. Kalderon120 , S. Kama40 ,A. Kamenshchikov130 , N. Kanaya156 , M. Kaneda30 , S. Kaneti28 , V.A. Kantserov98 , J. Kanzaki66 ,B. Kaplan110 , A. Kapliy31 , D. Kar53 , K. Karakostas10 , A. Karamaoun3 , N. Karastathis10 ,M.J. Kareem54 , M. Karnevskiy83 , S.N. Karpov65 , Z.M. Karpova65 , K. Karthik110 ,V. Kartvelishvili72 , A.N. Karyukhin130 , L. Kashif174 , G. Kasieczka58b , R.D. Kass111 ,A. Kastanas14 , Y. Kataoka156 , A. Katre49 , J. Katzy42 , V. Kaushik7 , K. Kawagoe70 ,T. Kawamoto156 , G. Kawamura54 , S. Kazama156 , V.F. Kazanin109 , M.Y. Kazarinov65 ,R. Keeler170 , R. Kehoe40 , M. Keil54 , J.S. Keller42 , J.J. Kempster77 , H. Keoshkerian5 ,O. Kepka127 , B.P. Kerševan75 , S. Kersten176 , K. Kessoku156 , J. Keung159 , R.A. Keyes87 ,F. Khalil-zada11 , H. Khandanyan147a,147b , A. Khanov114 , A. Kharlamov109 , A. Khodinov98 ,A. Khomich58a , T.J. Khoo28 , G. Khoriauli21 , V. Khovanskiy97 , E. Khramov65 , J. Khubua51b ,H.Y. Kim8 , H. Kim147a,147b , S.H. Kim161 , N. Kimura155 , O. Kind16 , B.T. King74 , M. King168 ,
R.S.B. King120 , S.B. King169 , J. Kirk131 , A.E. Kiryunin101 , T. Kishimoto67 , D. Kisielewska38a ,F. Kiss48 , K. Kiuchi161 , E. Kladiva145b , M. Klein74 , U. Klein74 , K. Kleinknecht83 ,P. Klimek147a,147b , A. Klimentov25 , R. Klingenberg43 , J.A. Klinger84 , T. Klioutchnikova30 ,P.F. Klok106 , E.-E. Kluge58a , P. Kluit107 , S. Kluth101 , E. Kneringer62 , E.B.F.G. Knoops85 ,A. Knue53 , D. Kobayashi158 , T. Kobayashi156 , M. Kobel44 , M. Kocian144 , P. Kodys129 ,T. Koffas29 , E. Koffeman107 , L.A. Kogan120 , S. Kohlmann176 , Z. Kohout128 , T. Kohriki66 ,T. Koi144 , H. Kolanoski16 , I. Koletsou5 , J. Koll90 , A.A. Komar96,∗ , Y. Komori156 , T. Kondo66 ,N. Kondrashova42 , K. Köneke48 , A.C. König106 , S. König83 , T. Kono66,s , R. Konoplich110,t ,N. Konstantinidis78 , R. Kopeliansky153 , S. Koperny38a , L. Köpke83 , A.K. Kopp48 , K. Korcyl39 ,K. Kordas155 , A. Korn78 , A.A. Korol109,c , I. Korolkov12 , E.V. Korolkova140 , V.A. Korotkov130 ,O. Kortner101 , S. Kortner101 , V.V. Kostyukhin21 , V.M. Kotov65 , A. Kotwal45 ,A. Kourkoumeli-Charalampidi155 , C. Kourkoumelis9 , V. Kouskoura25 , A. Koutsman160a ,R. Kowalewski170 , T.Z. Kowalski38a , W. Kozanecki137 , A.S. Kozhin130 , V.A. Kramarenko99 ,G. Kramberger75 , D. Krasnopevtsev98 , A. Krasznahorkay30 , J.K. Kraus21 , A. Kravchenko25 ,S. Kreiss110 , M. Kretz58c , J. Kretzschmar74 , K. Kreutzfeldt52 , P. Krieger159 , K. Krizka31 ,K. Kroeninger43 , H. Kroha101 , J. Kroll122 , J. Kroseberg21 , J. Krstic13a , U. Kruchonak65 ,H. Krüger21 , N. Krumnack64 , Z.V. Krumshteyn65 , A. Kruse174 , M.C. Kruse45 , M. Kruskal22 ,T. Kubota88 , H. Kucuk78 , S. Kuday4c , S. Kuehn48 , A. Kugel58c , F. Kuger175 , A. Kuhl138 ,T. Kuhl42 , V. Kukhtin65 , Y. Kulchitsky92 , S. Kuleshov32b , M. Kuna133a,133b , T. Kunigo68 ,A. Kupco127 , H. Kurashige67 , Y.A. Kurochkin92 , R. Kurumida67 , V. Kus127 , E.S. Kuwertz148 ,M. Kuze158 , J. Kvita115 , D. Kyriazopoulos140 , A. La Rosa49 , L. La Rotonda37a,37b , C. Lacasta168 ,F. Lacava133a,133b , J. Lacey29 , H. Lacker16 , D. Lacour80 , V.R. Lacuesta168 , E. Ladygin65 ,R. Lafaye5 , B. Laforge80 , T. Lagouri177 , S. Lai48 , H. Laier58a , L. Lambourne78 , S. Lammers61 ,C.L. Lampen7 , W. Lampl7 , E. Lançon137 , U. Landgraf48 , M.P.J. Landon76 , V.S. Lang58a ,A.J. Lankford164 , F. Lanni25 , K. Lantzsch30 , S. Laplace80 , C. Lapoire21 , J.F. Laporte137 ,T. Lari91a , F. Lasagni Manghi20a,20b , M. Lassnig30 , P. Laurelli47 , W. Lavrijsen15 , A.T. Law138 ,P. Laycock74 , O. Le Dortz80 , E. Le Guirriec85 , E. Le Menedeu12 , T. LeCompte6 ,F. Ledroit-Guillon55 , C.A. Lee146b , H. Lee107 , S.C. Lee152 , L. Lee1 , G. Lefebvre80 , M. Lefebvre170 ,F. Legger100 , C. Leggett15 , A. Lehan74 , G. Lehmann Miotto30 , X. Lei7 , W.A. Leight29 ,A. Leisos155 , A.G. Leister177 , M.A.L. Leite24d , R. Leitner129 , D. Lellouch173 , B. Lemmer54 ,K.J.C. Leney78 , T. Lenz21 , G. Lenzen176 , B. Lenzi30 , R. Leone7 , S. Leone124a,124b ,C. Leonidopoulos46 , S. Leontsinis10 , C. Leroy95 , C.G. Lester28 , C.M. Lester122 , M. Levchenko123 ,J. Levêque5 , D. Levin89 , L.J. Levinson173 , M. Levy18 , A. Lewis120 , A.M. Leyko21 , M. Leyton41 ,B. Li33b,u , B. Li85 , H. Li149 , H.L. Li31 , L. Li45 , L. Li33e , S. Li45 , Y. Li33c,v , Z. Liang138 , H. Liao34 ,B. Liberti134a , P. Lichard30 , K. Lie166 , J. Liebal21 , W. Liebig14 , C. Limbach21 , A. Limosani151 ,S.C. Lin152,w , T.H. Lin83 , F. Linde107 , B.E. Lindquist149 , J.T. Linnemann90 , E. Lipeles122 ,A. Lipniacka14 , M. Lisovyi42 , T.M. Liss166 , D. Lissauer25 , A. Lister169 , A.M. Litke138 , B. Liu152 ,– 63 –JHEP04(2015)117

D. Liu152 , J. Liu85 , J.B. Liu33b , K. Liu33b,x , L. Liu89 , M. Liu45 , M. Liu33b , Y. Liu33b ,M. Livan121a,121b , A. Lleres55 , J. Llorente Merino82 , S.L. Lloyd76 , F. Lo Sterzo152 ,E. Lobodzinska42 , P. Loch7 , W.S. Lockman138 , F.K. Loebinger84 , A.E. Loevschall-Jensen36 ,A. Loginov177 , T. Lohse16 , K. Lohwasser42 , M. Lokajicek127 , B.A. Long22 , J.D. Long89 ,R.E. Long72 , K.A. Looper111 , L. Lopes126a , D. Lopez Mateos57 , B. Lopez Paredes140 ,I. Lopez Paz12 , J. Lorenz100 , N. Lorenzo Martinez61 , M. Losada163 , P. Loscutoff15 , X. Lou33a ,A. Lounis117 , J. Love6 , P.A. Love72 , A.J. Lowe144,e , F. Lu33a , N. Lu89 , H.J. Lubatti139 ,C. Luci133a,133b , A. Lucotte55 , F. Luehring61 , W. Lukas62 , L. Luminari133a , O. Lundberg147a,147b ,B. Lund-Jensen148 , M. Lungwitz83 , D. Lynn25 , R. Lysak127 , E. Lytken81 , H. Ma25 , L.L. Ma33d ,G. Maccarrone47 , A. Macchiolo101 , J. Machado Miguens126a,126b , D. Macina30 , D. Madaffari85 ,R. Madar48 , H.J. Maddocks72 , W.F. Mader44 , A. Madsen167 , M. Maeno8 , T. Maeno25 ,A. Maevskiy99 , E. Magradze54 , K. Mahboubi48 , J. Mahlstedt107 , S. Mahmoud74 , C. Maiani137 ,C. Maidantchik24a , A.A. Maier101 , A. Maio126a,126b,126d , S. Majewski116 , Y. Makida66 ,N. Makovec117 , P. Mal137,y , B. Malaescu80 , Pa. Malecki39 , V.P. Maleev123 , F. Malek55 ,U. Mallik63 , D. Malon6 , C. Malone144 , S. Maltezos10 , V.M. Malyshev109 , S. Malyukov30 ,J. Mamuzic13b , B. Mandelli30 , L. Mandelli91a , I. Mandić75 , R. Mandrysch63 , J. Maneira126a,126b ,A. Manfredini101 , L. Manhaes de Andrade Filho24b , J. Manjarres Ramos160b , A. Mann100 ,P.M. Manning138 , A. Manousakis-Katsikakis9 , B. Mansoulie137 , R. Mantifel87 , M. Mantoani54 ,L. Mapelli30 , L. March146c , J.F. Marchand29 , G. Marchiori80 , M. Marcisovsky127 , C.P. Marino170 ,M. Marjanovic13a , F. Marroquim24a , S.P. Marsden84 , Z. Marshall15 , L.F. Marti17 ,S. Marti-Garcia168 , B. Martin30 , B. Martin90 , T.A. Martin171 , V.J. Martin46 ,B. Martin dit Latour14 , H. Martinez137 , M. Martinez12,n , S. Martin-Haugh131 , A.C. Martyniuk78 ,M. Marx139 , F. Marzano133a , A. Marzin30 , L. Masetti83 , T. Mashimo156 , R. Mashinistov96 ,J. Masik84 , A.L. Maslennikov109,c , I. Massa20a,20b , L. Massa20a,20b , N. Massol5 ,P. Mastrandrea149 , A. Mastroberardino37a,37b , T. Masubuchi156 , P. Mättig176 , J. Mattmann83 ,J. Maurer26a , S.J. Maxfield74 , D.A. Maximov109,c , R. Mazini152 , S.M. Mazza91a,91b ,L. Mazzaferro134a,134b , G. Mc Goldrick159 , S.P. Mc Kee89 , A. McCarn89 , R.L. McCarthy149 ,T.G. McCarthy29 , N.A. McCubbin131 , K.W. McFarlane56,∗ , J.A. Mcfayden78 , G. Mchedlidze54 ,S.J. McMahon131 , R.A. McPherson170,j , J. Mechnich107 , M. Medinnis42 , S. Meehan31 ,S. Mehlhase100 , A. Mehta74 , K. Meier58a , C. Meineck100 , B. Meirose41 , C. Melachrinos31 ,B.R. Mellado Garcia146c , F. Meloni17 , A. Mengarelli20a,20b , S. Menke101 , E. Meoni162 ,K.M. Mercurio57 , S. Mergelmeyer21 , N. Meric137 , P. Mermod49 , L. Merola104a,104b , C. Meroni91a ,F.S. Merritt31 , H. Merritt111 , A. Messina30,z , J. Metcalfe25 , A.S. Mete164 , C. Meyer83 ,C. Meyer122 , J-P. Meyer137 , J. Meyer30 , R.P. Middleton131 , S. Migas74 , S. Miglioranzi165a,165c ,L. Mijović21 , G. Mikenberg173 , M. Mikestikova127 , M. Mikuž75 , A. Milic30 , D.W. Miller31 ,C. Mills46 , A. Milov173 , D.A. Milstead147a,147b , A.A. Minaenko130 , Y. Minami156 ,I.A. Minashvili65 , A.I. Mincer110 , B. Mindur38a , M. Mineev65 , Y. Ming174 , L.M. Mir12 ,G. Mirabelli133a , T. Mitani172 , J. Mitrevski100 , V.A. Mitsou168 , A. Miucci49 , P.S. Miyagawa140 ,J.U. Mjörnmark81 , T. Moa147a,147b , K. Mochizuki85 , S. Mohapatra35 , W. Mohr48 ,S. Molander147a,147b , R. Moles-Valls168 , K. Mönig42 , C. Monini55 , J. Monk36 , E. Monnier85 ,J. Montejo Berlingen12 , F. Monticelli71 , S. Monzani133a,133b , R.W. Moore3 , N. Morange63 ,D. Moreno163 , M. Moreno Llácer54 , P. Morettini50a , M. Morgenstern44 , M. Morii57 ,M. Morinaga156 , V. Morisbak119 , S. Moritz83 , A.K. Morley148 , G. Mornacchi30 , J.D. Morris76 ,A. Morton42 , L. Morvaj103 , H.G. Moser101 , M. Mosidze51b , J. Moss111 , K. Motohashi158 ,R. Mount144 , E. Mountricha25 , S.V. Mouraviev96,∗ , E.J.W. Moyse86 , S. Muanza85 , R.D. Mudd18 ,F. Mueller58a , J. Mueller125 , K. Mueller21 , T. Mueller28 , D. Muenstermann49 , P. Mullen53 ,Y. Munwes154 , J.A. Murillo Quijada18 , W.J. Murray171,131 , H. Musheghyan54 , E. Musto153 ,A.G. Myagkov130,aa , M. Myska128 , O. Nackenhorst54 , J. Nadal54 , K. Nagai120 , R. Nagai158 ,Y. Nagai85 , K. Nagano66 , A. Nagarkar111 , Y. Nagasaka59 , K. Nagata161 , M. Nagel101 ,A.M. Nairz30 , Y. Nakahama30 , K. Nakamura66 , T. Nakamura156 , I. Nakano112 ,H. Namasivayam41 , G. Nanava21 , R.F. Naranjo Garcia42 , R. Narayan58b , T. Nattermann21 ,T. Naumann42 , G. Navarro163 , R. Nayyar7 , H.A. Neal89 , P.Yu. Nechaeva96 , T.J. Neep84 ,– 64 –JHEP04(2015)117

P.D. Nef144 , A. Negri121a,121b , G. Negri30 , M. Negrini20a , S. Nektarijevic49 , C. Nellist117 ,A. Nelson164 , T.K. Nelson144 , S. Nemecek127 , P. Nemethy110 , A.A. Nepomuceno24a , M. Nessi30,ab ,M.S. Neubauer166 , M. Neumann176 , R.M. Neves110 , P. Nevski25 , P.R. Newman18 , D.H. Nguyen6 ,R.B. Nickerson120 , R. Nicolaidou137 , B. Nicquevert30 , J. Nielsen138 , N. Nikiforou35 ,A. Nikiforov16 , V. Nikolaenko130,aa , I. Nikolic-Audit80 , K. Nikolics49 , K. Nikolopoulos18 ,P. Nilsson25 , Y. Ninomiya156 , A. Nisati133a , R. Nisius101 , T. Nobe158 , M. Nomachi118 ,I. Nomidis29 , S. Norberg113 , M. Nordberg30 , O. Novgorodova44 , S. Nowak101 , M. Nozaki66 ,L. Nozka115 , K. Ntekas10 , G. Nunes Hanninger88 , T. Nunnemann100 , E. Nurse78 , F. Nuti88 ,B.J. O’Brien46 , F. O’grady7 , D.C. O’Neil143 , V. O’Shea53 , F.G. Oakham29,d , H. Oberlack101 ,T. Obermann21 , J. Ocariz80 , A. Ochi67 , I. Ochoa78 , S. Oda70 , S. Odaka66 , H. Ogren61 , A. Oh84 ,S.H. Oh45 , C.C. Ohm15 , H. Ohman167 , H. Oide30 , W. Okamura118 , H. Okawa161 , Y. Okumura31 ,T. Okuyama156 , A. Olariu26a , A.G. Olchevski65 , S.A. Olivares Pino46 , D. Oliveira Damazio25 ,E. Oliver Garcia168 , A. Olszewski39 , J. Olszowska39 , A. Onofre126a,126e , P.U.E. Onyisi31,p ,C.J. Oram160a , M.J. Oreglia31 , Y. Oren154 , D. Orestano135a,135b , N. Orlando73a,73b ,C. Oropeza Barrera53 , R.S. Orr159 , B. Osculati50a,50b , R. Ospanov122 , G. Otero y Garzon27 ,H. Otono70 , M. Ouchrif136d , E.A. Ouellette170 , F. Ould-Saada119 , A. Ouraou137 ,K.P. Oussoren107 , Q. Ouyang33a , A. Ovcharova15 , M. Owen84 , V.E. Ozcan19a , N. Ozturk8 ,K. Pachal120 , A. Pacheco Pages12 , C. Padilla Aranda12 , M. Pagáčová48 , S. Pagan Griso15 ,E. Paganis140 , C. Pahl101 , F. Paige25 , P. Pais86 , K. Pajchel119 , G. Palacino160b , S. Palestini30 ,M. Palka38b , D. Pallin34 , A. Palma126a,126b , J.D. Palmer18 , Y.B. Pan174 , E. Panagiotopoulou10 ,J.G. Panduro Vazquez77 , P. Pani107 , N. Panikashvili89 , S. Panitkin25 , D. Pantea26a ,L. Paolozzi134a,134b , Th.D. Papadopoulou10 , K. Papageorgiou155 , A. Paramonov6 ,D. Paredes Hernandez155 , M.A. Parker28 , F. Parodi50a,50b , J.A. Parsons35 , U. Parzefall48 ,E. Pasqualucci133a , S. Passaggio50a , A. Passeri135a , F. Pastore135a,135b,∗ , Fr. Pastore77 ,G. Pásztor29 , S. Pataraia176 , N.D. Patel151 , J.R. Pater84 , S. Patricelli104a,104b , T. Pauly30 ,J. Pearce170 , L.E. Pedersen36 , M. Pedersen119 , S. Pedraza Lopez168 , R. Pedro126a,126b ,S.V. Peleganchuk109 , D. Pelikan167 , H. Peng33b , B. Penning31 , J. Penwell61 , D.V. Perepelitsa25 ,E. Perez Codina160a , M.T. Pérez Garcı́a-Estañ168 , L. Perini91a,91b , H. Pernegger30 ,S. Perrella104a,104b , R. Peschke42 , V.D. Peshekhonov65 , K. Peters30 , R.F.Y. Peters84 ,B.A. Petersen30 , T.C. Petersen36 , E. Petit42 , A. Petridis147a,147b , C. Petridou155 , E. Petrolo133a ,F. Petrucci135a,135b , N.E. Pettersson158 , R. Pezoa32b , P.W. Phillips131 , G. Piacquadio144 ,E. Pianori171 , A. Picazio49 , E. Piccaro76 , M. Piccinini20a,20b , M.A. Pickering120 , R. Piegaia27 ,D.T. Pignotti111 , J.E. Pilcher31 , A.D. Pilkington78 , J. Pina126a,126b,126d , M. Pinamonti165a,165c,ac ,A. Pinder120 , J.L. Pinfold3 , A. Pingel36 , B. Pinto126a , S. Pires80 , M. Pitt173 , C. Pizio91a,91b ,L. Plazak145a , M.-A. Pleier25 , V. Pleskot129 , E. Plotnikova65 , P. Plucinski147a,147b , D. Pluth64 ,S. Poddar58a , F. Podlyski34 , R. Poettgen83 , L. Poggioli117 , D. Pohl21 , M. Pohl49 , G. Polesello121a ,A. Policicchio37a,37b , R. Polifka159 , A. Polini20a , C.S. Pollard53 , V. Polychronakos25 ,K. Pommès30 , L. Pontecorvo133a , B.G. Pope90 , G.A. Popeneciu26b , D.S. Popovic13a ,A. Poppleton30 , S. Pospisil128 , K. Potamianos15 , I.N. Potrap65 , C.J. Potter150 , C.T. Potter116 ,G. Poulard30 , J. Poveda30 , V. Pozdnyakov65 , P. Pralavorio85 , A. Pranko15 , S. Prasad30 , S. Prell64 ,D. Price84 , J. Price74 , L.E. Price6 , D. Prieur125 , M. Primavera73a , S. Prince87 , M. Proissl46 ,K. Prokofiev60c , F. Prokoshin32b , E. Protopapadaki137 , S. Protopopescu25 , J. Proudfoot6 ,M. Przybycien38a , H. Przysiezniak5 , E. Ptacek116 , D. Puddu135a,135b , E. Pueschel86 , D. Puldon149 ,M. Purohit25,ad , P. Puzo117 , J. Qian89 , G. Qin53 , Y. Qin84 , A. Quadt54 , D.R. Quarrie15 ,W.B. Quayle165a,165b , M. Queitsch-Maitland84 , D. Quilty53 , A. Qureshi160b , V. Radeka25 ,V. Radescu42 , S.K. Radhakrishnan149 , P. Radloff116 , P. Rados88 , F. Ragusa91a,91b , G. Rahal179 ,S. Rajagopalan25 , M. Rammensee30 , C. Rangel-Smith167 , K. Rao164 , F. Rauscher100 , S. Rave83 ,T.C. Rave48 , T. Ravenscroft53 , M. Raymond30 , A.L. Read119 , N.P. Readioff74 ,D.M. Rebuzzi121a,121b , A. Redelbach175 , G. Redlinger25 , R. Reece138 , K. Reeves41 , L. Rehnisch16 ,H. Reisin27 , M. Relich164 , C. Rembser30 , H. Ren33a , Z.L. Ren152 , A. Renaud117 , M. Rescigno133a ,S. Resconi91a , O.L. Rezanova109,c , P. Reznicek129 , R. Rezvani95 , R. Richter101 , E. Richter-Was38b ,M. Ridel80 , P. Rieck16 , J. Rieger54 , M. Rijssenbeek149 , A. Rimoldi121a,121b , L. Rinaldi20a ,– 65 –JHEP04(2015)117

E. Ritsch62 , I. Riu12 , F. Rizatdinova114 , E. Rizvi76 , S.H. Robertson87,j ,A. Robichaud-Veronneau87 , D. Robinson28 , J.E.M. Robinson84 , A. Robson53 , C. Roda124a,124b ,L. Rodrigues30 , S. Roe30 , O. Røhne119 , S. Rolli162 , A. Romaniouk98 , M. Romano20a,20b ,E. Romero Adam168 , N. Rompotis139 , M. Ronzani48 , L. Roos80 , E. Ros168 , S. Rosati133a ,K. Rosbach49 , M. Rose77 , P. Rose138 , P.L. Rosendahl14 , O. Rosenthal142 , V. Rossetti147a,147b ,E. Rossi104a,104b , L.P. Rossi50a , R. Rosten139 , M. Rotaru26a , I. Roth173 , J. Rothberg139 ,D. Rousseau117 , C.R. Royon137 , A. Rozanov85 , Y. Rozen153 , X. Ruan146c , F. Rubbo12 ,I. Rubinskiy42 , V.I. Rud99 , C. Rudolph44 , M.S. Rudolph159 , F. Rühr48 , A. Ruiz-Martinez30 ,Z. Rurikova48 , N.A. Rusakovich65 , A. Ruschke100 , H.L. Russell139 , J.P. Rutherfoord7 ,N. Ruthmann48 , Y.F. Ryabov123 , M. Rybar129 , G. Rybkin117 , N.C. Ryder120 , A.F. Saavedra151 ,G. Sabato107 , S. Sacerdoti27 , A. Saddique3 , H.F-W. Sadrozinski138 , R. Sadykov65 ,F. Safai Tehrani133a , H. Sakamoto156 , Y. Sakurai172 , G. Salamanna135a,135b , A. Salamon134a ,M. Saleem113 , D. Salek107 , P.H. Sales De Bruin139 , D. Salihagic101 , A. Salnikov144 , J. Salt168 ,D. Salvatore37a,37b , F. Salvatore150 , A. Salvucci106 , A. Salzburger30 , D. Sammel48 ,D. Sampsonidis155 , A. Sanchez104a,104b , J. Sánchez168 , V. Sanchez Martinez168 , H. Sandaker14 ,R.L. Sandbach76 , H.G. Sander83 , M.P. Sanders100 , M. Sandhoff176 , T. Sandoval28 , C. Sandoval163 ,R. Sandstroem101 , D.P.C. Sankey131 , A. Sansoni47 , C. Santoni34 , R. Santonico134a,134b ,H. Santos126a , I. Santoyo Castillo150 , K. Sapp125 , A. Sapronov65 , J.G. Saraiva126a,126d ,B. Sarrazin21 , G. Sartisohn176 , O. Sasaki66 , Y. Sasaki156 , K. Sato161 , G. Sauvage5,∗ , E. Sauvan5 ,P. Savard159,d , D.O. Savu30 , C. Sawyer120 , L. Sawyer79,m , D.H. Saxon53 , J. Saxon31 , C. Sbarra20a ,A. Sbrizzi20a,20b , T. Scanlon78 , D.A. Scannicchio164 , M. Scarcella151 , V. Scarfone37a,37b ,J. Schaarschmidt173 , P. Schacht101 , D. Schaefer30 , R. Schaefer42 , S. Schaepe21 , S. Schaetzel58b ,U. Schäfer83 , A.C. Schaffer117 , D. Schaile100 , R.D. Schamberger149 , V. Scharf58a ,V.A. Schegelsky123 , D. Scheirich129 , M. Schernau164 , C. Schiavi50a,50b , J. Schieck100 , C. Schillo48 ,M. Schioppa37a,37b , S. Schlenker30 , E. Schmidt48 , K. Schmieden30 , C. Schmitt83 , S. Schmitt58b ,B. Schneider17 , Y.J. Schnellbach74 , U. Schnoor44 , L. Schoeffel137 , A. Schoening58b ,B.D. Schoenrock90 , A.L.S. Schorlemmer54 , M. Schott83 , D. Schouten160a , J. Schovancova25 ,S. Schramm159 , M. Schreyer175 , C. Schroeder83 , N. Schuh83 , M.J. Schultens21 ,H.-C. Schultz-Coulon58a , H. Schulz16 , M. Schumacher48 , B.A. Schumm138 , Ph. Schune137 ,C. Schwanenberger84 , A. Schwartzman144 , T.A. Schwarz89 , Ph. Schwegler101 , Ph. Schwemling137 ,R. Schwienhorst90 , J. Schwindling137 , T. Schwindt21 , M. Schwoerer5 , F.G. Sciacca17 , E. Scifo117 ,G. Sciolla23 , F. Scuri124a,124b , F. Scutti21 , J. Searcy89 , G. Sedov42 , E. Sedykh123 , P. Seema21 ,S.C. Seidel105 , A. Seiden138 , F. Seifert128 , J.M. Seixas24a , G. Sekhniaidze104a , S.J. Sekula40 ,K.E. Selbach46 , D.M. Seliverstov123,∗ , G. Sellers74 , N. Semprini-Cesari20a,20b , C. Serfon30 ,L. Serin117 , L. Serkin54 , T. Serre85 , R. Seuster160a , H. Severini113 , T. Sfiligoj75 , F. Sforza101 ,A. Sfyrla30 , E. Shabalina54 , M. Shamim116 , L.Y. Shan33a , R. Shang166 , J.T. Shank22 ,M. Shapiro15 , P.B. Shatalov97 , K. Shaw165a,165b , A. Shcherbakova147a,147b , C.Y. Shehu150 ,P. Sherwood78 , L. Shi152,ae , S. Shimizu67 , C.O. Shimmin164 , M. Shimojima102 , M. Shiyakova65 ,A. Shmeleva96 , D. Shoaleh Saadi95 , M.J. Shochet31 , S. Shojaii91a,91b , D. Short120 , S. Shrestha111 ,E. Shulga98 , M.A. Shupe7 , S. Shushkevich42 , P. Sicho127 , O. Sidiropoulou155 , D. Sidorov114 ,A. Sidoti133a , F. Siegert44 , Dj. Sijacki13a , J. Silva126a,126d , Y. Silver154 , D. Silverstein144 ,S.B. Silverstein147a , V. Simak128 , O. Simard5 , Lj. Simic13a , S. Simion117 , E. Simioni83 ,B. Simmons78 , D. Simon34 , R. Simoniello91a,91b , P. Sinervo159 , N.B. Sinev116 , G. Siragusa175 ,A. Sircar79 , A.N. Sisakyan65,∗ , S.Yu. Sivoklokov99 , J. Sjölin147a,147b , T.B. Sjursen14 ,H.P. Skottowe57 , P. Skubic113 , M. Slater18 , T. Slavicek128 , M. Slawinska107 , K. Sliwa162 ,V. Smakhtin173 , B.H. Smart46 , L. Smestad14 , S.Yu. Smirnov98 , Y. Smirnov98 , L.N. Smirnova99,af ,O. Smirnova81 , K.M. Smith53 , M. Smith35 , M. Smizanska72 , K. Smolek128 , A.A. Snesarev96 ,G. Snidero76 , S. Snyder25 , R. Sobie170,j , F. Socher44 , A. Soffer154 , D.A. Soh152,ae , C.A. Solans30 ,M. Solar128 , J. Solc128 , E.Yu. Soldatov98 , U. Soldevila168 , A.A. Solodkov130 , A. Soloshenko65 ,O.V. Solovyanov130 , V. Solovyev123 , P. Sommer48 , H.Y. Song33b , N. Soni1 , A. Sood15 ,A. Sopczak128 , B. Sopko128 , V. Sopko128 , V. Sorin12 , M. Sosebee8 , R. Soualah165a,165c ,P. Soueid95 , A.M. Soukharev109,c , D. South42 , S. Spagnolo73a,73b , F. Spanò77 , W.R. Spearman57 ,– 66 –JHEP04(2015)117

F. Spettel101 , R. Spighi20a , G. Spigo30 , L.A. Spiller88 , M. Spousta129 , T. Spreitzer159 ,R.D. St. Denis53,∗ , S. Staerz44 , J. Stahlman122 , R. Stamen58a , S. Stamm16 , E. Stanecka39 ,C. Stanescu135a , M. Stanescu-Bellu42 , M.M. Stanitzki42 , S. Stapnes119 , E.A. Starchenko130 ,J. Stark55 , P. Staroba127 , P. Starovoitov42 , R. Staszewski39 , P. Stavina145a,∗ , P. Steinberg25 ,B. Stelzer143 , H.J. Stelzer30 , O. Stelzer-Chilton160a , H. Stenzel52 , S. Stern101 , G.A. Stewart53 ,J.A. Stillings21 , M.C. Stockton87 , M. Stoebe87 , G. Stoicea26a , P. Stolte54 , S. Stonjek101 ,A.R. Stradling8 , A. Straessner44 , M.E. Stramaglia17 , J. Strandberg148 , S. Strandberg147a,147b ,A. Strandlie119 , E. Strauss144 , M. Strauss113 , P. Strizenec145b , R. Ströhmer175 , D.M. Strom116 ,R. Stroynowski40 , A. Strubig106 , S.A. Stucci17 , B. Stugu14 , N.A. Styles42 , D. Su144 , J. Su125 ,R. Subramaniam79 , A. Succurro12 , Y. Sugaya118 , C. Suhr108 , M. Suk128 , V.V. Sulin96 ,S. Sultansoy4d , T. Sumida68 , S. Sun57 , X. Sun33a , J.E. Sundermann48 , K. Suruliz150 ,G. Susinno37a,37b , M.R. Sutton150 , Y. Suzuki66 , M. Svatos127 , S. Swedish169 , M. Swiatlowski144 ,I. Sykora145a , T. Sykora129 , D. Ta90 , C. Taccini135a,135b , K. Tackmann42 , J. Taenzer159 ,A. Taffard164 , R. Tafirout160a , N. Taiblum154 , H. Takai25 , R. Takashima69 , H. Takeda67 ,T. Takeshita141 , Y. Takubo66 , M. Talby85 , A.A. Talyshev109,c , J.Y.C. Tam175 , K.G. Tan88 ,J. Tanaka156 , R. Tanaka117 , S. Tanaka132 , S. Tanaka66 , A.J. Tanasijczuk143 , B.B. Tannenwald111 ,N. Tannoury21 , S. Tapprogge83 , S. Tarem153 , F. Tarrade29 , G.F. Tartarelli91a , P. Tas129 ,M. Tasevsky127 , T. Tashiro68 , E. Tassi37a,37b , A. Tavares Delgado126a,126b , Y. Tayalati136d ,F.E. Taylor94 , G.N. Taylor88 , W. Taylor160b , F.A. Teischinger30 , M. Teixeira Dias Castanheira76 ,P. Teixeira-Dias77 , K.K. Temming48 , H. Ten Kate30 , P.K. Teng152 , J.J. Teoh118 , F. Tepel176 ,S. Terada66 , K. Terashi156 , J. Terron82 , S. Terzo101 , M. Testa47 , R.J. Teuscher159,j ,J. Therhaag21 , T. Theveneaux-Pelzer34 , J.P. Thomas18 , J. Thomas-Wilsker77 , E.N. Thompson35 ,P.D. Thompson18 , R.J. Thompson84 , A.S. Thompson53 , L.A. Thomsen36 , E. Thomson122 ,M. Thomson28 , W.M. Thong88 , R.P. Thun89,∗ , F. Tian35 , M.J. Tibbetts15 , V.O. Tikhomirov96,ag ,Yu.A. Tikhonov109,c , S. Timoshenko98 , E. Tiouchichine85 , P. Tipton177 , S. Tisserant85 ,T. Todorov5,∗ , S. Todorova-Nova129 , J. Tojo70 , S. Tokár145a , K. Tokushuku66 , K. Tollefson90 ,E. Tolley57 , L. Tomlinson84 , M. Tomoto103 , L. Tompkins31 , K. Toms105 , N.D. Topilin65 ,E. Torrence116 , H. Torres143 , E. Torró Pastor168 , J. Toth85,ah , F. Touchard85 , D.R. Tovey140 ,H.L. Tran117 , T. Trefzger175 , L. Tremblet30 , A. Tricoli30 , I.M. Trigger160a , S. Trincaz-Duvoid80 ,M.F. Tripiana12 , W. Trischuk159 , B. Trocmé55 , C. Troncon91a , M. Trottier-McDonald15 ,M. Trovatelli135a,135b , P. True90 , M. Trzebinski39 , A. Trzupek39 , C. Tsarouchas30 ,J.C-L. Tseng120 , P.V. Tsiareshka92 , D. Tsionou137 , G. Tsipolitis10 , N. Tsirintanis9 ,S. Tsiskaridze12 , V. Tsiskaridze48 , E.G. Tskhadadze51a , I.I. Tsukerman97 , V. Tsulaia15 ,S. Tsuno66 , D. Tsybychev149 , A. Tudorache26a , V. Tudorache26a , A.N. Tuna122 ,S.A. Tupputi20a,20b , S. Turchikhin99,af , D. Turecek128 , I. Turk Cakir4c , R. Turra91a,91b ,A.J. Turvey40 , P.M. Tuts35 , A. Tykhonov49 , M. Tylmad147a,147b , M. Tyndel131 , I. Ueda156 ,R. Ueno29 , M. Ughetto85 , M. Ugland14 , M. Uhlenbrock21 , F. Ukegawa161 , G. Unal30 , A. Undrus25 ,G. Unel164 , F.C. Ungaro48 , Y. Unno66 , C. Unverdorben100 , J. Urban145b , D. Urbaniec35 ,P. Urquijo88 , G. Usai8 , A. Usanova62 , L. Vacavant85 , V. Vacek128 , B. Vachon87 , N. Valencic107 ,S. Valentinetti20a,20b , A. Valero168 , L. Valery34 , S. Valkar129 , E. Valladolid Gallego168 ,S. Vallecorsa49 , J.A. Valls Ferrer168 , W. Van Den Wollenberg107 , P.C. Van Der Deijl107 ,R. van der Geer107 , H. van der Graaf107 , R. Van Der Leeuw107 , D. van der Ster30 , N. van Eldik30 ,P. van Gemmeren6 , J. Van Nieuwkoop143 , I. van Vulpen107 , M.C. van Woerden30 ,M. Vanadia133a,133b , W. Vandelli30 , R. Vanguri122 , A. Vaniachine6 , P. Vankov42 , F. Vannucci80 ,G. Vardanyan178 , R. Vari133a , E.W. Varnes7 , T. Varol86 , D. Varouchas80 , A. Vartapetian8 ,K.E. Varvell151 , F. Vazeille34 , T. Vazquez Schroeder54 , J. Veatch7 , F. Veloso126a,126c , T. Velz21 ,S. Veneziano133a , A. Ventura73a,73b , D. Ventura86 , M. Venturi170 , N. Venturi159 , A. Venturini23 ,V. Vercesi121a , M. Verducci133a,133b , W. Verkerke107 , J.C. Vermeulen107 , A. Vest44 ,M.C. Vetterli143,d , O. Viazlo81 , I. Vichou166 , T. Vickey146c,ai , O.E. Vickey Boeriu146c ,G.H.A. Viehhauser120 , S. Viel169 , R. Vigne30 , M. Villa20a,20b , M. Villaplana Perez91a,91b ,E. Vilucchi47 , M.G. Vincter29 , V.B. Vinogradov65 , J. Virzi15 , I. Vivarelli150 , F. Vives Vaque3 ,S. Vlachos10 , D. Vladoiu100 , M. Vlasak128 , A. Vogel21 , M. Vogel32a , P. Vokac128 , G. Volpi124a,124b ,1

Department of Physics, University of Adelaide, Adelaide, Australia
Physics Department, SUNY Albany, Albany NY, United States of America
3
Department of Physics, University of Alberta, Edmonton AB, Canada
4 (a)Department of Physics, Ankara University, Ankara; (b) Department of Physics, Gazi University,
Ankara; (c) Istanbul Aydin University, Istanbul; (d) Division of Physics, TOBB University of
Economics and Technology, Ankara, Turkey
5
LAPP, CNRS/IN2P3 and Université de Savoie, Annecy-le-Vieux, France
6
High Energy Physics Division, Argonne National Laboratory, Argonne IL, United States of America
7
Department of Physics, University of Arizona, Tucson AZ, United States of America
8
Department of Physics, The University of Texas at Arlington, Arlington TX, United States ofAmerica9
Physics Department, University of Athens, Athens, Greece
10
Physics Department, National Technical University of Athens, Zografou, Greece
11
Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan
12
Institut de Fı́sica d’Altes Energies and Departament de Fı́sica de la Universitat Autònoma deBarcelona, Barcelona, Spain2– 67 –JHEP04(2015)117

M. Volpi88 , H. von der Schmitt101 , H. von Radziewski48 , E. von Toerne21 , V. Vorobel129 ,K. Vorobev98 , M. Vos168 , R. Voss30 , J.H. Vossebeld74 , N. Vranjes137 , M. Vranjes Milosavljevic13a ,V. Vrba127 , M. Vreeswijk107 , T. Vu Anh48 , R. Vuillermet30 , I. Vukotic31 , Z. Vykydal128 ,P. Wagner21 , W. Wagner176 , H. Wahlberg71 , S. Wahrmund44 , J. Wakabayashi103 , J. Walder72 ,R. Walker100 , W. Walkowiak142 , R. Wall177 , P. Waller74 , B. Walsh177 , C. Wang33c , C. Wang45 ,F. Wang174 , H. Wang15 , H. Wang40 , J. Wang42 , J. Wang33a , K. Wang87 , R. Wang105 ,S.M. Wang152 , T. Wang21 , X. Wang177 , C. Wanotayaroj116 , A. Warburton87 , C.P. Ward28 ,D.R. Wardrope78 , M. Warsinsky48 , A. Washbrook46 , C. Wasicki42 , P.M. Watkins18 ,A.T. Watson18 , I.J. Watson151 , M.F. Watson18 , G. Watts139 , S. Watts84 , B.M. Waugh78 ,S. Webb84 , M.S. Weber17 , S.W. Weber175 , J.S. Webster31 , A.R. Weidberg120 , B. Weinert61 ,J. Weingarten54 , C. Weiser48 , H. Weits107 , P.S. Wells30 , T. Wenaus25 , D. Wendland16 ,Z. Weng152,ae , T. Wengler30 , S. Wenig30 , N. Wermes21 , M. Werner48 , P. Werner30 , M. Wessels58a ,J. Wetter162 , K. Whalen29 , A. White8 , M.J. White1 , R. White32b , S. White124a,124b ,D. Whiteson164 , D. Wicke176 , F.J. Wickens131 , W. Wiedenmann174 , M. Wielers131 ,P. Wienemann21 , C. Wiglesworth36 , L.A.M. Wiik-Fuchs21 , P.A. Wijeratne78 , A. Wildauer101 ,M.A. Wildt42,aj , H.G. Wilkens30 , H.H. Williams122 , S. Williams28 , C. Willis90 , S. Willocq86 ,A. Wilson89 , J.A. Wilson18 , I. Wingerter-Seez5 , F. Winklmeier116 , B.T. Winter21 , M. Wittgen144 ,J. Wittkowski100 , S.J. Wollstadt83 , M.W. Wolter39 , H. Wolters126a,126c , B.K. Wosiek39 ,J. Wotschack30 , M.J. Woudstra84 , K.W. Wozniak39 , M. Wright53 , M. Wu55 , S.L. Wu174 , X. Wu49 ,Y. Wu89 , T.R. Wyatt84 , B.M. Wynne46 , S. Xella36 , M. Xiao137 , D. Xu33a , L. Xu33b,ak ,B. Yabsley151 , S. Yacoob146b,al , R. Yakabe67 , M. Yamada66 , H. Yamaguchi156 , Y. Yamaguchi118 ,A. Yamamoto66 , S. Yamamoto156 , T. Yamamura156 , T. Yamanaka156 , K. Yamauchi103 ,Y. Yamazaki67 , Z. Yan22 , H. Yang33e , H. Yang174 , Y. Yang111 , S. Yanush93 , L. Yao33a ,W-M. Yao15 , Y. Yasu66 , E. Yatsenko42 , K.H. Yau Wong21 , J. Ye40 , S. Ye25 , I. Yeletskikh65 ,A.L. Yen57 , E. Yildirim42 , M. Yilmaz4b , K. Yorita172 , R. Yoshida6 , K. Yoshihara156 , C. Young144 ,C.J.S. Young30 , S. Youssef22 , D.R. Yu15 , J. Yu8 , J.M. Yu89 , J. Yu114 , L. Yuan67 , A. Yurkewicz108 ,I. Yusuff28,am , B. Zabinski39 , R. Zaidan63 , A.M. Zaitsev130,aa , A. Zaman149 , S. Zambito23 ,L. Zanello133a,133b , D. Zanzi88 , C. Zeitnitz176 , M. Zeman128 , A. Zemla38a , K. Zengel23 ,O. Zenin130 , T. Ženiš145a , D. Zerwas117 , G. Zevi della Porta57 , D. Zhang89 , F. Zhang174 ,H. Zhang90 , J. Zhang6 , L. Zhang152 , R. Zhang33b , X. Zhang33d , Z. Zhang117 , X. Zhao40 ,Y. Zhao33d , Z. Zhao33b , A. Zhemchugov65 , J. Zhong120 , B. Zhou89 , C. Zhou45 , L. Zhou35 ,L. Zhou40 , N. Zhou164 , C.G. Zhu33d , H. Zhu33a , J. Zhu89 , Y. Zhu33b , X. Zhuang33a , K. Zhukov96 ,A. Zibell175 , D. Zieminska61 , N.I. Zimine65 , C. Zimmermann83 , R. Zimmermann21 ,S. Zimmermann21 , S. Zimmermann48 , Z. Zinonos54 , M. Ziolkowski142 , G. Zobernig174 ,A. Zoccoli20a,20b , M. zur Nedden16 , G. Zurzolo104a,104b , L. Zwalinski30

13 (a)– 68 –JHEP04(2015)117

Institute of Physics, University of Belgrade, Belgrade; (b) Vinca Institute of Nuclear Sciences,
University of Belgrade, Belgrade, Serbia
14
Department for Physics and Technology, University of Bergen, Bergen, Norway
15
Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley
CA, United States of America
16
Department of Physics, Humboldt University, Berlin, Germany
17
Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics,
University of Bern, Bern, Switzerland
18
School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom
19 (a)
Department of Physics, Bogazici University, Istanbul; (b) Department of Physics, Dogus
University, Istanbul; (c) Department of Physics Engineering, Gaziantep University, Gaziantep,
Turkey20 (a)INFN Sezione di Bologna; (b) Dipartimento di Fisica e Astronomia, Università di Bologna,
Bologna, Italy
21
Physikalisches Institut, University of Bonn, Bonn, Germany
22
Department of Physics, Boston University, Boston MA, United States of America
23
Department of Physics, Brandeis University, Waltham MA, United States of America
24 (a)
Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (b) Electrical Circuits
Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora; (c) Federal University of Sao
Joao del Rei (UFSJ), Sao Joao del Rei; (d) Instituto de Fisica, Universidade de Sao Paulo, Sao
Paulo, Brazil
25
Physics Department, Brookhaven National Laboratory, Upton NY, United States of America
26 (a)
National Institute of Physics and Nuclear Engineering, Bucharest; (b) National Institute for
Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj
Napoca; (c) University Politehnica Bucharest, Bucharest; (d) West University in Timisoara,
Timisoara, Romania
27
Departamento de Fı́sica, Universidad de Buenos Aires, Buenos Aires, Argentina
28
Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
29
Department of Physics, Carleton University, Ottawa ON, Canada
30
CERN, Geneva, Switzerland
31
Enrico Fermi Institute, University of Chicago, Chicago IL, United States of America
32 (a)
Departamento de Fı́sica, Pontificia Universidad Católica de Chile, Santiago; (b) Departamento
de Fı́sica, Universidad Técnica Federico Santa Marı́a, Valparaı́so, Chile
33 (a)
Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; (b) Department ofModern Physics, University of Science and Technology of China, Anhui; (c) Department of Physics,
Nanjing University, Jiangsu; (d) School of Physics, Shandong University, Shandong; (e) Physics
Department, Shanghai Jiao Tong University, Shanghai; (f ) Physics Department, Tsinghua
University, Beijing 100084, China
34
Laboratoire de Physique Corpusculaire, Clermont Université and Université Blaise Pascal and
CNRS/IN2P3, Clermont-Ferrand, France
35
Nevis Laboratory, Columbia University, Irvington NY, United States of America
36
Niels Bohr Institute, University of Copenhagen, Kobenhavn, Denmark
37 (a)INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b) Dipartimento di
Fisica, Università della Calabria, Rende, Italy
38 (a)AGH University of Science and Technology, Faculty of Physics and Applied Computer Science,
Krakow; (b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland
39
The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Krakow,
Poland40
Physics Department, Southern Methodist University, Dallas TX, United States of America
41
Physics Department, University of Texas at Dallas, Richardson TX, United States of America
42
DESY, Hamburg and Zeuthen, Germany
43
Institut für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany

44Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany
Department of Physics, Duke University, Durham NC, United States of America
46
SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
47
INFN Laboratori Nazionali di Frascati, Frascati, Italy
48
Fakultät für Mathematik und Physik, Albert-Ludwigs-Universität, Freiburg, Germany
49
Section de Physique, Université de Genève, Geneva, Switzerland
50 (a)INFN Sezione di Genova; (b) Dipartimento di Fisica, Università di Genova, Genova, Italy
51 (a)
E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b)High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia
52
II Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany
53
SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom
54
II Physikalisches Institut, Georg-August-Universität, Göttingen, Germany
55
Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS/IN2P3,
Grenoble, France
56
Department of Physics, Hampton University, Hampton VA, United States of America
57
Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, United Statesof America
58 (a)
Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (b)Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (c) ZITI Institut für
technische Informatik, Ruprecht-Karls-Universität Heidelberg, Mannheim, Germany
59
Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan
60 (a)
Department of Physics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong; (b)Department of Physics, The University of Hong Kong, Hong Kong; (c) Department of Physics, The
Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
61
Department of Physics, Indiana University, Bloomington IN, United States of America
62
Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria
63
University of Iowa, Iowa City IA, United States of America
64
Department of Physics and Astronomy, Iowa State University, Ames IA, United States of America
65
Joint Institute for Nuclear Research, JINR Dubna, Dubna, Russia
66
KEK, High Energy Accelerator Research Organization, Tsukuba, Japan
67
Graduate School of Science, Kobe University, Kobe, Japan
68
Faculty of Science, Kyoto University, Kyoto, Japan
69
Kyoto University of Education, Kyoto, Japan70
Department of Physics, Kyushu University, Fukuoka, Japan
71
Instituto de Fı́sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina
72
Physics Department, Lancaster University, Lancaster, United Kingdom
73 (a)INFN Sezione di Lecce; (b) Dipartimento di Matematica e Fisica, Università del Salento, Lecce,
Italy
74
Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom
75
Department of Physics, Jožef Stefan Institute and University of Ljubljana, Ljubljana, Slovenia
76
School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom
77
Department of Physics, Royal Holloway University of London, Surrey, United Kingdom
78
Department of Physics and Astronomy, University College London, London, United Kingdom
79
Louisiana Tech University, Ruston LA, United States of America
80
Laboratoire de Physique Nucléaire et de Hautes Energies, UPMC and Université Paris-Diderot and
CNRS/IN2P3, Paris, France
81
Fysiska institutionen, Lunds universitet, Lund, Sweden
82
Departamento de Fisica Teorica C-15, Universidad Autonoma de Madrid, Madrid, Spain
83
Institut für Physik, Universität Mainz, Mainz, Germany
84
School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
85
CPPM, Aix-Marseille Université and CNRS/IN2P3, Marseille, France
86
Department of Physics, University of Massachusetts, Amherst MA, United States of America
45

JHEP04(2015)117– 69 –

87

Department of Physics, McGill University, Montreal QC, Canada
School of Physics, University of Melbourne, Victoria, Australia
89
Department of Physics, The University of Michigan, Ann Arbor MI, United States of America
90
Department of Physics and Astronomy, Michigan State University, East Lansing MI, United Statesof America
91 (a)INFN Sezione di Milano; (b) Dipartimento di Fisica, Università di Milano, Milano, Italy
92
B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Republic of
Belarus93
National Scientific and Educational Centre for Particle and High Energy Physics, Minsk, Republicof Belarus
94
Department of Physics, Massachusetts Institute of Technology, Cambridge MA, United States ofAmerica
95
Group of Particle Physics, University of Montreal, Montreal QC, Canada
96
P.N. Lebedev Institute of Physics, Academy of Sciences, Moscow, Russia
97
Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia
98
National Research Nuclear University MEPhI, Moscow, Russia
99
D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow,
Russia100
Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany
101
Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany
102
Nagasaki Institute of Applied Science, Nagasaki, Japan103
Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan
104 (a)INFN Sezione di Napoli; (b) Dipartimento di Fisica, Università di Napoli, Napoli, Italy
105
Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United Statesof America
106
Institute for Mathematics, Astrophysics and Particle Physics, Radboud University
Nijmegen/Nikhef, Nijmegen, Netherlands
107
Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam,
Netherlands
108
Department of Physics, Northern Illinois University, DeKalb IL, United States of America
109
Budker Institute of Nuclear Physics, SB RAS, Novosibirsk, Russia
110
Department of Physics, New York University, New York NY, United States of America
111
Ohio State University, Columbus OH, United States of America
112
Faculty of Science, Okayama University, Okayama, Japan
113
Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK,
United States of America
114
Department of Physics, Oklahoma State University, Stillwater OK, United States of America
115
Palacký University, RCPTM, Olomouc, Czech Republic
116
Center for High Energy Physics, University of Oregon, Eugene OR, United States of America
117
LAL, Université Paris-Sud and CNRS/IN2P3, Orsay, France
118
Graduate School of Science, Osaka University, Osaka, Japan
119
Department of Physics, University of Oslo, Oslo, Norway
120
Department of Physics, Oxford University, Oxford, United Kingdom
121 (a)INFN Sezione di Pavia; (b) Dipartimento di Fisica, Università di Pavia, Pavia, Italy
122
Department of Physics, University of Pennsylvania, Philadelphia PA, United States of America
123
Petersburg Nuclear Physics Institute, Gatchina, Russia
124 (a)INFN Sezione di Pisa; (b) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy
125
Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, United States ofAmerica
126 (a)Laboratorio de Instrumentacao e Fisica Experimental de Particulas - LIP, Lisboa; (b) Faculdadede Ciências, Universidade de Lisboa, Lisboa; (c) Department of Physics, University of Coimbra,
Coimbra; (d) Centro de Fı́sica Nuclear da Universidade de Lisboa, Lisboa; (e) Departamento de
88

JHEP04(2015)117– 70 –

– 71 –JHEP04(2015)117

Fisica, Universidade do Minho, Braga; (f ) Departamento de Fisica Teorica y del Cosmos and
CAFPE, Universidad de Granada, Granada (Spain); (g) Dep Fisica and CEFITEC of Faculdade deCiencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
127
Institute of Physics, Academy of Sciences of the Czech Republic, Praha, Czech Republic
128
Czech Technical University in Prague, Praha, Czech Republic
129
Faculty of Mathematics and Physics, Charles University in Prague, Praha, Czech Republic
130State Research Center Institute for High Energy Physics, Protvino, Russia
131
Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom
132
Ritsumeikan University, Kusatsu, Shiga, Japan133 (a)INFN Sezione di Roma; (b) Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy
134 (a)INFN Sezione di Roma Tor Vergata; (b) Dipartimento di Fisica, Università di Roma Tor
Vergata, Roma, Italy
135 (a)INFN Sezione di Roma Tre; (b) Dipartimento di Matematica e Fisica, Università Roma Tre,
Roma, Italy
136 (a)Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies Université Hassan II, Casablanca; (b) Centre National de l’Energie des Sciences Techniques
Nucleaires, Rabat; (c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech;(d)Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda; (e) Faculté dessciences, Université Mohammed V-Agdal, Rabat, Morocco137
DSM/IRFU (Institut de Recherches sur les Lois Fondamentales de l’Univers), CEA Saclay(Commissariat à l’Energie Atomique et aux Energies Alternatives), Gif-sur-Yvette, France
138
Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA,
United States of America
139
Department of Physics, University of Washington, Seattle WA, United States of America
140
Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
141
Department of Physics, Shinshu University, Nagano, Japan142
Fachbereich Physik, Universität Siegen, Siegen, Germany
143
Department of Physics, Simon Fraser University, Burnaby BC, Canada
144
SLAC National Accelerator Laboratory, Stanford CA, United States of America
145 (a)Faculty of Mathematics, Physics & Informatics, Comenius University, Bratislava; (b)Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of
Sciences, Kosice, Slovak Republic
146 (a)Department of Physics, University of Cape Town, Cape Town; (b) Department of Physics,
University of Johannesburg, Johannesburg; (c) School of Physics, University of the Witwatersrand,
Johannesburg, South Africa
147 (a)Department of Physics, Stockholm University; (b) The Oskar Klein Centre, Stockholm, Sweden
148
Physics Department, Royal Institute of Technology, Stockholm, Sweden
149
Departments of Physics & Astronomy and Chemistry, Stony Brook University, Stony Brook NY,
United States of America
150
Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom
151
School of Physics, University of Sydney, Sydney, Australia
152
Institute of Physics, Academia Sinica, Taipei, Taiwan
153
Department of Physics, Technion: Israel Institute of Technology, Haifa, Israel
154
Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv,
Israel155
Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
156
International Center for Elementary Particle Physics and Department of Physics, The University ofTokyo, Tokyo, Japan
157
Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan
158
Department of Physics, Tokyo Institute of Technology, Tokyo, Japan
159
Department of Physics, University of Toronto, Toronto ON, Canada
160 (a)TRIUMF, Vancouver BC; (b) Department of Physics and Astronomy, York University, Toronto
ON, Canada

161

Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan
Department of Physics and Astronomy, Tufts University, Medford MA, United States of America
163
Centro de Investigaciones, Universidad Antonio Narino, Bogota, Colombia
164
Department of Physics and Astronomy, University of California Irvine, Irvine CA, United States ofAmerica165 (a)INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; (b) ICTP, Trieste; (c) Dipartimento
di Chimica, Fisica e Ambiente, Università di Udine, Udine, Italy
166
Department of Physics, University of Illinois, Urbana IL, United States of America
167
Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden
168
Instituto de Fı́sica Corpuscular (IFIC) and Departamento de Fı́sica Atómica, Molecular y Nuclear
and Departamento de Ingenierı́a Electrónica and Instituto de Microelectrónica de Barcelona(IMB-CNM), University of Valencia and CSIC, Valencia, Spain
169
Department of Physics, University of British Columbia, Vancouver BC, Canada
170
Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada
171
Department of Physics, University of Warwick, Coventry, United Kingdom
172
Waseda University, Tokyo, Japan173
Department of Particle Physics, The Weizmann Institute of Science, Rehovot, Israel
174
Department of Physics, University of Wisconsin, Madison WI, United States of America
175
Fakultät für Physik und Astronomie, Julius-Maximilians-Universität, Würzburg, Germany
176
Fachbereich C Physik, Bergische Universität Wuppertal, Wuppertal, Germany
177
Department of Physics, Yale University, New Haven CT, United States of America
178
Yerevan Physics Institute, Yerevan, Armenia
179
Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules(IN2P3), Villeurbanne, France
162

Also at Department of Physics, King’s College London, London, United Kingdom
Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, AzerbaijancAlso at Novosibirsk State University, Novosibirsk, RussiadAlso at TRIUMF, Vancouver BC, CanadaeAlso at Department of Physics, California State University, Fresno CA, United States of AmericafAlso at Department of Physics, University of Fribourg, Fribourg, Switzerlandg
Also at Tomsk State University, Tomsk, RussiahAlso at CPPM, Aix-Marseille Université and CNRS/IN2P3, Marseille, Francei
Also at Università di Napoli Parthenope, Napoli, Italyj
Also at Institute of Particle Physics (IPP), CanadakAlso at Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United KingdomlAlso at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg,
Russiam
Also at Louisiana Tech University, Ruston LA, United States of AmericanAlso at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spaino
Also at Department of Physics, National Tsing Hua University, TaiwanpAlso at Department of Physics, The University of Texas at Austin, Austin TX, United States ofAmericaq
Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgiar
Also at CERN, Geneva, Switzerlands
Also at Ochadai Academic Production, Ochanomizu University, Tokyo, Japant
Also at Manhattan College, New York NY, United States of AmericauAlso at Institute of Physics, Academia Sinica, Taipei, Taiwanv
Also at LAL, Université Paris-Sud and CNRS/IN2P3, Orsay, Francew
Also at Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, Taipei, TaiwanxAlso at Laboratoire de Physique Nucléaire et de Hautes Energies, UPMC and Université
Paris-Diderot and CNRS/IN2P3, Paris, Franceb– 72 –JHEP04(2015)117a

y– 73 –JHEP04(2015)117

Also at School of Physical Sciences, National Institute of Science Education and Research,
Bhubaneswar, Indiaz
Also at Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italyaa
Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russiaab
Also at section de Physique, Université de Genève, Geneva, Switzerlandac
Also at International School for Advanced Studies (SISSA), Trieste, Italyad
Also at Department of Physics and Astronomy, University of South Carolina, Columbia SC, UnitedStates of AmericaaeAlso at School of Physics and Engineering, Sun Yat-sen University, Guangzhou, Chinaaf
Also at Faculty of Physics, M.V.Lomonosov Moscow State University, Moscow, Russiaag
Also at National Research Nuclear University MEPhI, Moscow, RussiaahAlso at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest,
Hungaryai
Also at Department of Physics, Oxford University, Oxford, United Kingdom
ajAlso at Institut für Experimentalphysik, Universität Hamburg, Hamburg, GermanyakAlso at Department of Physics, The University of Michigan, Ann Arbor MI, United States ofAmericaal
Also at Discipline of Physics, University of KwaZulu-Natal, Durban, South AfricaamAlso at University of Malaya, Department of Physics, Kuala Lumpur, Malaysia∗
Deceased