EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
CERN-PH-EP-2013-173
Submitted to: PRD
Search for a multi-Higgs-boson cascade in
W
+
W
−
b¯
b
events
with the ATLAS detector in
pp
collisions at
√
s
= 8
TeV
The ATLAS Collaboration
Abstract
A search is presented for new particles in an extension to the Standard Model that includes a heavy
Higgs boson (H
0), an intermediate charged Higgs boson pair (H
±), and a light Higgs boson (h
0). The
analysis searches for events involving the production of a single heavy neutral Higgs boson which
decays to the charged Higgs boson and a W boson, where the charged Higgs boson subsequently
decays into a W boson and the lightest neutral Higgs boson decaying to a bottom–antibottom-quark
pair. Such a cascade results in a W -boson pair and a bottom–antibottom-quark pair in the final state.
Events with exactly one lepton, missing transverse momentum, and at least four jets are selected
from a data sample corresponding to an integrated luminosity of 20.3 fb
−1, collected by the ATLAS
detector in proton–proton collisions at
√
s
= 8 TeV at the LHC. The data are found to be consistent
with Standard Model predictions, and 95% confidence-level upper limits are set on the product of
cross section and branching ratio. These limits range from 0.065 pb to 43 pb as a function of H
0and
H
±masses, with m
h0fixed at 125 GeV.
Search for a multi-Higgs-boson cascade in W
W
b¯
b events
with the ATLAS detector in pp collisions at
√
s = 8 TeV
The ATLAS Collaboration
A search is presented for new particles in an extension to the Standard Model that includes a heavy Higgs boson (H0), an intermediate charged Higgs boson pair (H±
), and a light Higgs boson (h0). The analysis searches for events involving the production of a single heavy neutral Higgs boson which decays to the charged Higgs boson and a W boson, where the charged Higgs boson subsequently decays into a W boson and the lightest neutral Higgs boson decaying to a bottom– antibottom-quark pair. Such a cascade results in a W -boson pair and a bottom–antibottom-quark pair in the final state. Events with exactly one lepton, missing transverse momentum, and at least four jets are selected from a data sample corresponding to an integrated luminosity of 20.3 fb−1, collected by the ATLAS detector in proton–proton collisions at√s = 8 TeV at the LHC. The data are found to be consistent with Standard Model predictions, and 95% confidence-level upper limits are set on the product of cross section and branching ratio. These limits range from 0.065 pb to 43 pb as a function of H0 and H±masses, with mh0 fixed at 125 GeV.
PACS numbers: 12.60.-i, 13.85.Rm, 14.80.-j
I. INTRODUCTION
Recently, a Higgs boson has been discovered by the ATLAS [1] and CMS [2] collaborations with a mass of approximately 125 GeV. This observation has been sup-ported by complementary evidence from the CDF and D0 collaborations [3]. The study of such a boson, responsi-ble for breaking electroweak symmetry in the Standard Model (SM), is one of the major objectives of experimen-tal high-energy physics. A viexperimen-tal question is whether this state is in fact the Higgs boson of the SM, or part of an extended Higgs sector (such as that of the minimal super-symmetric Standard Model, MSSM [4, 5]), a composite Higgs boson [6], or a completely different particle with Higgs-like couplings (such as a radion in warped extra dimensions [7, 8] or a dilaton [9]).
This Letter reports a search for particles in an exten-sion to the SM that includes heavier Higgs bosons in addition to a light neutral Higgs boson, h0, with mass
mh0 = 125 GeV. Rather than assuming a particular
the-oretical model, this analysis follows a simplified model approach by searching for a specific multi-Higgs-boson cascade topology [10]. Many beyond-the-SM Higgs mod-els introduce a second Higgs doublet. In addition to the h0, such models contain a heavy charged Higgs boson pair H± and a heavier neutral state H0. An additional
pseudoscalar particle, A, may also exist within the Two Higgs-Doublet Model (2HDM) [11] framework, but this analysis assumes it to be too heavy to participate in the cascade decay considered here.
This letter reports the first search at the LHC for new particles in the final state W±W∓b¯b, via the process
gg → H0 followed by the cascade, H0
→ W∓H±
→ W∓W±h0
→ W∓W±b¯b, as illustrated in Fig. 1. Other
production modes, such as associated production or vector-boson fusion lead to different final states and are not considered here. The W±W∓b¯b final state also
ap-pears in top-quark pair production. In this search, one
of the W bosons is assumed to decay to hadrons lead-ing to jets and the other one decays to an electron plus a neutrino (e+jets) or a muon plus a neutrino (µ+jets). The same final state has been used by CDF in a simi-lar search for Higgs-boson cascades [12]. Other related searches have been performed for charged Higgs bosons in top-quark decays t→ H+b [13–18]. Boosted decision
trees (BDTs) are used to distinguish the Higgs-boson cas-cade events from the predominantly t¯t background.
b ¯b W W g g H0 H± h0
FIG. 1: Diagram showing the Higgs-boson cascade gg → H0→ W∓
H±→ W∓W±h0→ W∓
W±b¯b.
II. ATLAS DETECTOR AND DATA SAMPLE
The ATLAS experiment [19] at the LHC is a multi-purpose particle physics detector with approximately forward-backward symmetric cylindrical geometry [20]. It consists of an inner tracking detector surrounded by a thin superconducting solenoid, electromagnetic and hadronic calorimeters, and a muon spectrometer incor-porating three large superconducting toroid magnet as-semblies.
The data used in this analysis were collected during 2012 from pp collisions at a centre-of-mass energy of 8 TeV using triggers designed to select high transverse mo-mentum (pT [20]) electrons or muons. The data sample
corresponds to an integrated luminosity of 20.3 fb−1.
III. SIGNAL AND BACKGROUND
SIMULATION
The production of H0 bosons via gluon fusion with
mH0 = 325–1025 GeV and subsequent decays H0 →
W∓H± with mH± = 225–925 GeV and H± → W±h0
with mh0 = 125 GeV, is modelled using the
MAD-GRAPH [21] Monte Carlo (MC) event generator with an effective vertex to model the fermion loop and a narrow natural width of 50 MeV. Additional radiation, hadronization, and showering are described by PYTHIA v6.4 [22]. Thirty-six different mass pairs are tested for the Higgs-boson cascade signal within the above mH±
and mH0 mass ranges.
The dominant SM background to this signature is top-quark pair production. This background is modelled using simulated events from the MC@NLO v4.01 [23] event generator with the CT10 [24] parton distribution functions (PDFs). The parton shower and the under-lying event simulation are performed with HERWIG v6.520 [25] and JIMMY v4.31 [26], respectively, using the AUET2 tune [27]. The t¯t cross section for pp col-lisions at a centre-of-mass energy of √s = 8 TeV is as-sumed to be σt¯t = 253+13−15 pb for a top-quark mass of
172.5 GeV. It has been calculated at next-to-next-to-leading order (NNLO) in QCD including resummation of next-to-next-to-leading-logarithmic soft gluon terms with Top++2.0 [28–33]. The PDF and αs
uncertain-ties are calculated using the PDF4LHC prescription [34] with the 68% confidence level (C.L.) of the MSTW2008 NNLO [35, 36], CT10 NNLO [24, 37] and NNPDF2.3 5f FFN [38] PDF sets, added in quadrature to ob-tain the normalization and factorization scale uncerob-tain- uncertain-ties. Additional t¯t samples used to estimate various systematic effects are generated with POWHEG [39– 41] interfaced to HERWIG/JIMMY, POWHEG inter-faced to PYTHIA, and AcerMC v3.8 [42] interinter-faced to PYTHIA. The t¯t modelling is also checked with samples generated by ALPGEN [43] interfaced with HERWIG. Other backgrounds are expected to originate from vectorboson production with associated jets (W -boson+jets and Z-boson/γ∗+jets), as well as single
top-quark, diboson (W W , W Z, ZZ), and multi-jet produc-tion. All background predictions, except that for multi-jet production, are obtained from simulated events.
The W/Z-boson+jets contribution is simulated using ALPGEN interfaced to HERWIG/JIMMY, and is nor-malized to NNLO theoretical cross sections [44, 45]. The contribution from single top-quark production is simu-lated using MC@NLO interfaced to HERWIG/JIMMY for the s-channel top-quark production and W t
produc-tion, and with AcerMC interfaced to PYTHIA for the t-channel, and normalized to approximate NNLO theo-retical cross sections [46–48]. Finally, diboson production is simulated with HERWIG and normalized to NLO the-oretical cross sections [49].
All generated events are passed through the detailed ATLAS detector simulation [50] based on GEANT4 [51], with the exception of the additional samples used to ac-count for systematic effects in t¯t production, for which a parameterized simulation [50] of the calorimeter response is used. The events are then processed with the same reconstruction software as the data. MC events are over-laid with additional minimum bias events generated with PYTHIA to simulate the effect of pile-up (additional pp interactions in either the same or closeby bunch cross-ings as the primary interaction); the number of overlaid proton–proton interactions is chosen to match the distri-bution of the number of additional interactions observed in the data.
Multi-jet production may mimic the presence of a lep-ton, but the contribution from these processes is found to be small. It is estimated from the data by the ma-trix method [52] in the µ+jets and e+jets channels. The matrix method is a technique to estimate the number of events with a fake, isolated lepton in the signal se-lection, and uses loose and tight isolation definitions for leptons. The tight isolation definitions are those used in this analysis, and tight leptons are a subset of the loose leptons. In a selection dominated by real leptons, the efficiency (real) of a loose lepton to also pass the tight
isolation requirements is measured. The rate (fake) of
loose leptons passing the tight requirements is measured in a multi-jet-dominated selection. These rates, realand
fake, are used to estimate the multi-jet contribution to
the analysis selection.
IV. EVENT SELECTION
This analysis relies on the measurement of jets, elec-trons, muons and the missing transverse momentum (Emiss
T ) [53]. Since this analysis investigates a final state
dominated by top-quark pair production, a selection sim-ilar to the top-quark cross-section measurement by the ATLAS collaboration [54] is used.
Jets are reconstructed using the anti-ktalgorithm [55]
with a radius parameter R = 0.4, and are calibrated at the energy cluster level [56] to compensate for differ-ing calorimeter response to hadronic and electromagnetic showers. A correction for pile-up is applied to the jet en-ergy [57]. Jets are required to have pT > 25 GeV and
|η| < 2.5. Jets from additional pp interactions are sup-pressed by requiring the jet vertex fraction (JVF) to be larger than 0.5 for jets with pT <50 GeV and|η| <2.4.
The JVF variable is defined as the transverse momen-tum weighted fraction of tracks associated with the jet that are compatible with originating from the primary vertex. The primary vertex is defined as the vertex
[GeV]
b b
m
0 20 40 60 80 100 120 140 160 180200
Fraction of events/20 GeV
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 ATLAS = 8 TeV s Simulation = 125 GeV 0 h m = 325 GeV ± H m = 525 GeV 0 H m = 125 GeV 0 h m = 525 GeV ± H m = 825 GeV 0 H m = 125 GeV 0 h m = 725 GeV ± H m = 1025 GeV 0 H m [GeV] W b b m 200 300 400 500 600 700 800 900 1000
Fraction of events/40 GeV
0 0.05 0.1 0.15 0.2 0.25 ATLAS = 8 TeV s Simulation [GeV] WW b b m 400 600 800 1000 1200 1400
Fraction of events/60 GeV
0 0.05 0.1 0.15 0.2 0.25 ATLAS = 8 TeV s Simulation
FIG. 2: Distributions of reconstructed masses in simulation for the three Higgs bosons in the cascade; the lightest Higgs boson, h0 (left, as mb¯b), the charged Higgs boson, H
±
(middle, as mb¯bW), and the heavy Higgs boson, H 0
(right, as mb¯bW W), shown
for three example mass hypotheses.
with the largest P p2
T of associated tracks. Jets are
b-tagged (identified as the product of a b-quark) using the MV1 tagger [58], which combines several tagging algo-rithms [59] using an artificial neural network. A 70% tag-ging efficiency is achieved in identifying b-jets with pT>
20 GeV and |η| < 2.5 in simulated t¯t events, while the light-jet rejection factor is 130. Additional corrections to the tagging efficiency and mistagging rate are derived from data and applied to all simulated samples [58, 60– 62].
Electrons are identified [63] as energy clusters in the electromagnetic calorimeter matched to reconstructed tracks in the inner detector. Selected electrons are re-quired to pass stringent selection requirements that pro-vide good discrimination between isolated electrons and jets. Isolation requirements are imposed in cones of calorimeter energy deposits (∆R(e, deposit) < 0.2) and inner-detector tracks (∆R(e, track) < 0.3) around the electrons direction where ∆R = p(∆η)2+ (∆φ)2. The
calorimeter isolation is corrected for leakage of the ergy of the electron into the isolation cone and for en-ergy deposits from pile-up events. Both the calorimeter and the inner detector isolation requirements are chosen to give 90% efficiency. Selected electrons are required to have transverse momentum pT>25 GeV and
pseudora-pidity in the range|η| < 2.47, excluding the calorimeter barrel/end-cap transition region 1.37 <|η| < 1.52.
Muons are reconstructed [64] using information from the muon spectrometer and the inner detector and are required to fulfil isolation requirements. Muons are re-quired to have transverse momentum pT >25 GeV and
|η| < 2.5. The isolation variable [65, 66] for muons is defined as Iµ = P ptrackT /p
µ
T, where the sum runs over
all tracks (except the one matched to the muon) that pass quality requirements and have ptrack
T >1 GeV and
∆R(µ, track) < 10 GeV/pµT. Muons with Iµ < 0.05 are
selected.
The transverse momentum of neutrinos is inferred from the magnitude of the missing transverse momentum in the event. The missing transverse momentum is
con-structed from the negative vector sum of the recon-structed jets, the topological calorimeter energy deposits outside of jets, and the muon momenta, all projected onto the transverse plane.
Overlapping objects are subject to a removal proce-dure. The jet closest to a selected electron is removed, if it is within ∆R(e, jet) < 0.2. Electrons with ∆R(e, jet) < 0.4 to any remaining jets and muons with ∆R(µ, jet) < 0.4 between the muon and nearest jet are removed since their likely origin is hadron decays.
Events are selected using single-lepton triggers with pT
thresholds of 24 GeV or 36 GeV for muons and 24 GeV or 60 GeV for electrons (the lower momentum triggers also apply isolation requirements). Events are required to have exactly one reconstructed isolated electron or muon matching the corresponding trigger object and a primary vertex reconstructed from at least five tracks, each with pT > 400 MeV. At least four jets with pT > 25 GeV
and|η| < 2.5 are required, of which at least two must be identified as b-jets. Additional requirements to reduce the multi-jet background are applied:
• in the e+jets channel: Emiss
T > 30 GeV and
mWT >30 GeV,
• in the µ+jets channel: Emiss
T > 20 GeV and
mW
T +ETmiss >60 GeV.
The transverse W-boson mass is defined as mWT =q2p`
TpνT(1− cos(φ`− φν)), where pT is the
transverse momentum, φ is the azimuthal angle, and ` and ν refer to the charged lepton and the neutrino, respectively. Different requirements are used for the muon and electron channels due to different levels of multi-jet background contamination. The signal pre-region (SPR) is defined to contain events that pass these requirements. Table I illustrates the expected yields of the background and the observed number of events in this region.
V. EVENT RECONSTRUCTION AND MULTIVARIATE ANALYSIS
A. Event Reconstruction
The Higgs-boson cascade event reconstruction begins with identification of the leptonically decaying W boson. It is assumed that the missing transverse momentum is due to the resulting neutrino. The neutrino pseudorapid-ity is set to the value which results in an invariant mass of the lepton and neutrino closest to the nominal W -boson mass [67]; in the case of degenerate solutions, the small-est magnitude of pseudorapidity is chosen. Next, the two b-tagged jets are used to reconstruct the lightest Higgs-boson candidate, h0; if there are more than two b-tagged
jets, the two jets with the highest b-tagging scores [58] are used. The hadronically decaying W boson is identified from the remaining jets as the pair with reconstructed dijet mass closest to the nominal W -boson mass. The charged Higgs-boson candidate H± is constructed from
the light h0 and the W -boson candidate which gives the
larger value of mH±. The heavy neutral Higgs-boson
candidate H0is then formed as b¯bW W . Fig. 2 illustrates
the reconstructed mass distributions for the h0, H±, and
H0in simulation for selected mass values.
Since the dominant background is top-quark pair pro-duction, the two b-quarks and two W bosons are com-bined in W b pairs to give top-quark candidates. The combination which minimizes the sum of the absolute value of their differences from the nominal top-quark mass [67] for both pairs is chosen. The invariant masses of the top-quark candidates are useful to discriminate t¯t events from the Higgs-boson signal. The masses (mt, m¯t)
of the two top-quark candidates and the absolute values of their differences (|mt− mt¯|) are calculated.
B. Multivariate Analysis
A multivariate analysis is performed to distinguish the Higgs-boson cascade from t¯t events. Several re-constructed kinematic quantities, including the invariant masses of the Higgs-boson candidates as described above, are used as inputs to a BDT classifier, provided in the TMVA [68] package. TMVA provides a ranking for the input variables, which is derived by counting how often an input variable is used to split decision tree nodes, and by weighting each split occurrence by the square of the gain in signal-to-background separation it has achieved and by the number of events in that node. Several com-binations of input variables are tested in training the BDTs. The inputs for the BDTs are optimized for the best expected cross-section limits while avoiding over-training, and the variable rankings of TMVA are used as heuristics in choosing the BDT inputs. Seven kinematic variables are chosen to achieve the best expected result across the entire signal mass grid:
• mb¯b, mb¯bW and mb¯bW W, as described above;
• ∆R(b, ¯b), the angular distance between the pair of b-tagged jets used to reconstruct the light Higgs-boson candidate;
• leptonic mt, the top-quark mass reconstructed
us-ing the leptonically decayus-ing W boson;
• hadronic mt, the top-quark mass reconstructed
us-ing the hadronically decayus-ing W boson; • |mt− m¯t|.
For cascades originating from a high-mass Higgs boson, the reconstructed top-quark masses along with mW W b¯b
are the highest-ranked input variables. For the low-mass Higgs-boson cascades, mb¯band ∆R(b, ¯b) have the highest
rank. Since the kinematics of the Higgs-boson cascade vary greatly with the masses of the heavy and interme-diate Higgs bosons, a different BDT is trained for each signal mass hypothesis.
Only MC events that pass the SPR requirements are used in the training of the BDTs. Each BDT is constructed as a forest with 750 decision trees, and is trained against simulated background event samples. The stochastic gradient boosting method [68] is used to improve classification accuracy and its robustness against statistical fluctuations. Each BDT is checked for over-training with a statistically independent test sample.
For each of the 36 signal mass points, a final thresh-old is chosen for its respective BDT output which gives the best expected sensitivity, measured using the same confidence-level calculations as applied to the data and described below. A counting experiment is then per-formed using events that pass those BDT output thresh-olds. In this way, the BDT thresholds divide the SPR into 36 non-orthogonal signal regions, one for each signal mass point.
VI. BACKGROUND VALIDATION IN
CONTROL REGIONS
The modelling of the SM backgrounds is validated in three background-dominated control regions. The con-trol regions retain the requirements of one lepton and at least four jets, and each region has additional require-ments. In control regions with fewer than two b-tagged jets, the two jets with the highest b-tagging scores are used to reconstruct the lightest Higgs boson, h0. The
following control regions are used:
• Control Region 1 (CR1): at least four jets, exactly one lepton and no b-tagged jets. This region vali-dates primarily the W -boson+jets modelling. This region is background-enriched relative to the hypo-thetical signal due to the b-tag veto.
[GeV] b b m 200 300 400 500 600 700 800 900 1000 Events 1 10 2 10 3 10 4 10 -1 L = 20.3 fb ∫ Data t t W+jets Other = 625 GeV ± H m = 925 GeV 0 H m Signal (0.05 pb) = 425 GeV ± H m = 525 GeV 0 H m Signal (1.00 pb) ATLAS s = 8 TeV [GeV] b b m 200 300 400 500 600 700 800 900 1000 (Data - SM) / SM-0.6-0.4 -0.20 0.2 0.4 0.6 Uncertainty [GeV] b b m 200 300 400 500 600 700 800 900 1000 Events 1 10 2 10 3 10 4 10 -1 L = 20.3 fb ∫ Data t t W+jets Other = 625 GeV ± H m = 925 GeV 0 H m Signal (0.05 pb) = 425 GeV ± H m = 525 GeV 0 H m Signal (1.00 pb) ATLAS s = 8 TeV [GeV] b b m 200 300 400 500 600 700 800 900 1000 (Data - SM) / SM-0.6 -0.4 -0.20 0.2 0.4 0.6 Uncertainty
FIG. 3: Distributions of mb¯b with uncertainties in the
con-trol regions CR1 (top) and CR2 (bottom). The data (black points) are compared to the background model (stacked his-togram). In control regions with fewer than two b-tagged jets, the two jets with the highest b-tagging scores are used. The final bin contains any overflow events. Two choices of signal hypotheses are also shown.
• Control Region 2 (CR2): at least four jets, ex-actly one lepton and exex-actly one b-tagged jet. This region validates primarily the modelling of the t¯t background. This background is fractionally larger, compared to a hypothetical signal, here than in the signal region due to the b-tagging cut, which pref-erentially selects the higher pT b-quarks from
top-quark decay. Although a potential signal would not be absent in this control region, the different levels of signal and t¯t contributions allow a test of t¯t modelling by comparing levels of agreement be-tween data and prediction in the signal and CR2 regions.
• Control Region 3 (CR3): at least four jets, ex-actly one lepton, at least two b-tagged jets, and mb¯b > 150 GeV. This region focuses primarily on validation the modelling of the t¯tbackground with kinematics similar to the hypothetical signal, but
TABLE I: Expected background contributions with their to-tal (systematic and statistical) uncertainties and the observed number of events with exactly one lepton and at least four jets, and in the SPR region, which additionally requires at least two b-tagged jets. In the table, contributions from pro-cesses with light-flavour (LF) u, d, s-quarks and heavy-flavour (HF) c, b-quarks are distinguished.
Source e/µ + ≥ 4 jets SPR Yields
t¯t 36.0+3.7−3.8·10 4 14.0+2.1−2.0·10 4 W -boson + jets LF 16.0+8.2−8.3·10 4 6.0+4.2−4.1·10 2 W -boson + jets HF 8.6+4.4−4.4·10 4 4.6+2.5−2.4·10 3 Z-boson + jets LF 26.0+6.3−6.4·10 3 11.0+8.3−7.7·10 1 Z-boson + jets HF 4.9+1.1−1.0·10 3 6.7+1.7−1.6·10 2 Single top-quark 16.0+2.0−2.1·10 3 46.0+7.6−7.3·10 2 W W, W Z, ZZ 26.0+5.4−5.5·10 2 6.9+1.9−2.0·10 1 Fake leptons 1.8+1.8−1.8·10 4 8.6+8.6−8.6·10 2 Total 68.0+14.0 −18.0·104 15.1+2.2−2.4·104 Observed 664876 151123
is background-enriched due to the mb¯b >150 GeV
requirement.
Figs. 3 and 4 illustrate the modelling of the Higgs-boson mass reconstruction in CR1, CR2 and CR3. The data and simulation agree within total uncertainties over the entire phase space. This is important, as the BDT may utilize any part of this phase space to build a pow-erful discriminant. In addition, the BDT output in each of the three control regions is compared to the predicted output and found to agree within statistical and system-atic uncertainties.
VII. SYSTEMATIC UNCERTAINTIES
Several sources of systematic uncertainties are relevant to this analysis.
Instrumental systematic uncertainties are related to the reconstruction of physics objects. For jets, system-atic uncertainties on the jet energy scale, energy resolu-tion, and reconstruction efficiency are included. For lep-tons, the systematic uncertainties from the momentum or energy scale and resolution, trigger efficiency, recon-struction, and identification efficiency are incorporated. Systematic uncertainties related to the performances of the b-tagging and JVF requirements are also included.
Due to the presence of multiple (≥4) jets and the dominant t¯t background (roughly 90% in the signal re-gion), significant systematic uncertainties are associated with jets and the modelling of the t¯t background. Ta-ble II lists the impact of these uncertainties on the back-ground estimates and signal efficiency for an example
[GeV] b b m 200 300 400 500 600 700 800 900 1000 Events 1 10 2 10 3 10 4 10 -1 L = 20.3 fb ∫ Data t t W+jets Other = 625 GeV ± H m = 925 GeV 0 H m Signal (0.05 pb) = 425 GeV ± H m = 525 GeV 0 H m Signal (1.00 pb) ATLAS s = 8 TeV [GeV] b b m 200 300 400 500 600 700 800 900 1000 (Data - SM) / SM-0.6-0.4 -0.20 0.2 0.4 0.6 Uncertainty [GeV] WW b b m 0 200 400 600 800 1000 1200 1400 1600 1800 Events 1 10 2 10 3 10 4 10 -1 L = 20.3 fb ∫ Data t t W+jets Other = 625 GeV ± H m = 925 GeV 0 H m Signal (0.05 pb) = 425 GeV ± H m = 525 GeV 0 H m Signal (1.00 pb) ATLAS s = 8 TeV [GeV] WW b b m 0 200 400 600 800 1000 1200 1400 1600 1800 (Data - SM) / SM-0.6 -0.4 -0.20 0.2 0.4 0.6 Uncertainty
FIG. 4: Distributions of mb¯b(top) and mb¯bW W(bottom) with
uncertainties in the control region CR3. The data (black points) are compared to the background model (stacked his-togram). The final bin contains any overflow events. Two choices of signal hypotheses are also shown.
nal region given by the BDT threshold for a signal with mH0, mH±= 425, 225 GeV.
Several sources of uncertainty on the jet energy scale calibration are considered, such as uncertainties due to pile-up and the light-quark and gluon composition. These sources are added in quadrature and listed as one systematic uncertainty in Table II. As a further uncer-tainty, the jet energy is smeared to cover any disagree-ments in the jet energy resolution measured in data and in simulated event samples. A jet reconstruction ef-ficiency [69] systematic uncertainty is applied by ran-domly discarding a fraction of low-pT jets in the
simu-lated events. The jet b-tagging efficiencies are evaluated in data and MC [58]. The difference is corrected with a scale factor, the uncertainty of which is treated as a sys-tematic uncertainty. A small discrepancy in the efficiency of the JVF requirement has been observed between data and MC simulation. The JVF requirement is varied to cover this observed discrepancy, and the resulting change in the expected background is taken as a systematic un-certainty.
Uncertainty Background Signal
Yields (%) Efficiency (%)
mH0= 425 GeV
mH±= 225 GeV
Jet vertex fraction ± 1.6 ± 2.1
b-tagging eff. ± 8.8 ± 14
Jet energy scale ± 3.9 ± 7
Jet energy res. ± 1.1 ± 11
Jet reco. eff. ± <1.0 ± <1.0
µ momentum ± <1.0 ± <1.0
e energy ± <1.0 ± <1.0
Lepton trigger eff. ± <1.0 ± 1.8
Lepton ident. eff. ± 1.5 ± 2.1
Lepton reco. eff. ± <1.0 ± <1.0
W -boson+jets shape ± <1.0 -Quark/gluon radiation ± <1.0 ± 2.8 t¯t modelling ± 2.7 -Bg. normalization ± 5.5 -Luminosity ± 2.8 ± 2.8 Total uncertainty ± 12 ± 20
TABLE II: Details of the systematic uncertainties relative to the total expected background and the signal efficiency in the signal region for a Higgs-boson cascade signal with mH0, mH±
= 425, 225 GeV. The signal region for this mass point is defined as the events that pass the BDT threshold for this mass sample. The positive and negative relative shifts have been averaged for compactness.
Systematic uncertainties associated with leptons are found to have a small effect, typically less than 1% rel-ative to background estimates and signal efficiency. For muons, the uncertainty in the momentum scale and res-olution is accounted for. For electrons, the uncertainties in the energy scale and resolution are included. For both leptons, uncertainties on the trigger, identification, and reconstruction efficiencies are incorporated.
The uncertainty due to the modelling of initial- and final-state quark and gluon radiation (ISR/FSR) is esti-mated using t¯t events produced with the AcerMC gen-erator interfaced with PYTHIA, where the parameters controlling ISR/FSR are varied in a range suggested by the data in the analysis of Ref. [70]. For the signal, events generated with varied ISR/FSR parameters in PYTHIA are compared to the nominal simulation; the differences in background yields and signal efficiency estimates are taken as a systematic uncertainty.
The systematic uncertainty due to the modelling of t¯t production is estimated by comparing results ob-tained with MC@NLO, POWHEG, and ALPGEN sig-nal samples. An uncertainty due to the theoretical t¯t cross section [71] is applied to the overall t¯t normaliza-tion. Since this is the dominant background the effect on the total background uncertainty is substantial (about 5% relative to the background estimate); the total nor-malization uncertainty on the background is 5.5%.
Since non-t¯t processes account for less than 10% of the background in the signal region, systematic uncertainties
associated with them are found to have a small impact on the overall background uncertainty. The systematic uncertainty related to the modelling of W -boson+jets is determined by varying the parameterization of the renor-malization and factorization scales in ALPGEN. As de-fault, both scales are set to (m2
W + (p
W
T)
2) and this is
varied by factors of two and by changing the form to (m2
W +
P
jetsp2T). This systematic uncertainty is found
to be small (<1%). An overall uncertainty of 4% is ap-plied to the W -boson + jets estimate due to uncertainties in the the cross section, with an additional 24% per jet added in quadrature due to the uncertainty in Berends scaling [72]. This results in a 48% uncertainty for events with four jets, contributing to the overal 5.5% uncer-tainty on the background normalization.
The systematic uncertainty due to single top-quark, diboson, and Z-boson+jets production is evaluated by varying their cross sections within their uncertainties as described in Ref. [52]. Since these contributions are small, the systematics associated with them are found to be negligible (<1%).
Finally, the luminosity uncertainty, measured using techniques similar to those described in Ref. [73], is 2.8%.
VIII. RESULTS
The yields in the signal regions are given in Table III. The observed yields are found to be consistent with SM background expectations, within uncertainties. The BDT outputs for three example signal mass points are illustrated in Fig. 5.
The 95% confidence-level production cross-section up-per limits for the various signal hypotheses are obtained using the CLs frequentist method [74], with the profile likelihood ratio of the number of events that pass the BDT threshold as the test statistic [75] as implemented in Ref. [76]. Systematic uncertainties are treated as nui-sance parameters and the calculation uses the asymptotic approximation [75]. Table III presents the signal efficien-cies, the total expected background and observed event counts for each signal case, as well as the expected and observed limits with the local p-values. The p-values are defined as the probabilities under the background-only hypothesis to observe these data or data which are more signal-like. The p-values have a maximum possible value of 0.5, which is the case when n < b, where b is the num-ber of events expected from the background model and nis the number of events observed in the data.
Since the signal regions are correlated, background-only pseudo-experiments are used to estimate the ex-pected distribution of the p-values in all the signal re-gions, accounting for the correlations. The observed dis-tribution of p-values is found to be consistent with the expectation from pseudo-experiments. The expected and observed limits as a function of the H0 and H± masses
are illustrated in Fig. 6. The limits are the weakest in low Higgs-boson mass regions due to the poorer
= 1025, 225 GeV ± H , m 0 H Trained for m BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Events 1 10 2 10 3 10 4 10 5 10 -1 L = 20.3 fb ∫ Data t t W+jets Other BDT threshold = 225 GeV ± H m = 1025 GeV 0 H m Signal (1.00 pb) ATLAS s = 8 TeV = 1025, 225 GeV ± H , m 0 H Trained for m BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 (Data - SM) / SM-0.6-0.4 -0.20 0.2 0.4 0.6 Uncertainty = 625, 325 GeV ± H , m 0 H Trained for m BDT output -1 -0.95 -0.9 -0.85 -0.8 -0.75 -0.7 -0.65 -0.6 Events 1 10 2 10 3 10 4 10 -1 L = 20.3 fb ∫ Data t t W+jets Other BDT threshold = 325 GeV ± H m = 625 GeV 0 H m Signal (1.00 pb) ATLAS s = 8 TeV = 625, 325 GeV ± H , m 0 H Trained for m BDT output -1 -0.95 -0.9 -0.85 -0.8 -0.75 -0.7 -0.65 -0.6 (Data - SM) / SM-0.6 -0.4 -0.20 0.2 0.4 0.6 Uncertainty = 1025, 625 GeV ± H , m 0 H Trained for m BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Events 1 10 2 10 3 10 4 10 5 10 -1 L = 20.3 fb ∫ Data t t W+jets Other BDT threshold = 625 GeV ± H m = 1025 GeV 0 H m Signal (1.00 pb) ATLAS s = 8 TeV = 1025, 625 GeV ± H , m 0 H Trained for m BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 (Data - SM) / SM-0.6 -0.4 -0.20 0.2 0.4 0.6 Uncertainty
FIG. 5: Distribituions of the BDT output in the signal regions for three example signal mass points, mH0, mH±= 1025, 225
GeV (top), mH0, mH± = 625, 325 GeV (middle), mH0, mH±
= 1025, 625 GeV (bottom). Signal histograms have been scaled to a production cross section of 1 pb. BDT thresholds are shown as dashed lines for each mass point. The back-ground model is shown as the coloured stacked histogram. The final bin contains any overflow events.
tion between t¯t and signal events.
In order to facilitate the comparison of these results with those obtained by other experiments, the observed cross-section limits are compared to the predictions for
Mass [GeV] 0 H 400 500 600 700 800 900 1000 Mass [GeV] ± H 300 400 500 600 700 800 900 Expected Limits [pb] -1 10 1 10 -1 Ldt = 20.3 fb
∫
ATLAS = 8 TeV s ± W ± W b b → ± W ± W 0 h → ± H ± W → 0 H Mass [GeV] 0 H 400 500 600 700 800 900 1000 Mass [GeV] ± H 300 400 500 600 700 800 900 95% C.L. Upper Limits [pb] -1 10 1 10 -1 Ldt = 20.3 fb∫
ATLAS = 8 TeV s ± W ± W b b → ± W ± W 0 h → ± H ± W → 0 H Mass [GeV] 0 H 400 500 600 700 800 900 1000 Mass [GeV] ± H 300 400 500 600 700 800 900 0)H → (gg σ 95% C.L. Upper Limits/ -1 10 1 10 -1 Ldt = 20.3 fb∫
ATLAS = 8 TeV s ± W ± W b b → ± W ± W 0 h → ± H ± W → 0 HFIG. 6: The expected (top) and observed (middle) 95% C.L. upper limits on the cross section for gg → H0 → W∓
H±→ W±W∓h0→ W±
W∓b¯b as a function of mH0 and mH±. The
ratio (bottom) of the observed 95% C.L. upper limits on the cross section to the theoretical cross section for a heavy Higgs boson produced via gluon-gluon fusion at the SM rate.
a heavy Higgs boson with SM-like gg-fusion production (Fig. 6). The theoretical production cross section of a heavy SM-like Higgs boson (only gluon fusion is con-sidered) is calculated in the complex-pole scheme us-ing the dFG [77] program, to next-to-next-to-leadus-ing order (NNLO) in QCD. Next-to-leading order (NLO) electroweak (EW) corrections are also applied, as well as QCD soft-gluon resummations up to next-to-next-to-leading log (NNLL).Using this benchmark, the
cross-section upper limits observed are greater than the theo-retical cross sections of the heavy Higgs boson, H0, for
all mass points tested. Therefore, the current limits are not stringent enough to exclude models with SM-like pro-duction rates even with 100% branching ratios for both H0 → H±W± and H± → h0W± and SM values for
BR(h0
→ b¯b). The limits are most stringent in the high H0and H±mass regions, where the ratio of the limits to
the theoretical cross section is nearly unity. This search produces tighter bounds than those obtained by the CDF collaboration [12].
Additionally, the results of this search are interpret-ted in the context of a heavy CP-even Higgs boson of a type-II 2-Higgs-Doublet Model [78] produced via gluon fusion. This model has seven free parameters: the mass of the CP-even Higgs bosons (mh0 and mH0), the mass of
the CP-odd Higgs boson (mA), the mass of the charged
scalar (mH±), the mixing angle between the CP-even
Higgs bosons (α), the ratio of the vacuum expectation values of the two Higgs doublets (tan β), and the Z2
-symmetry soft-breaking-term coefficient of the Higgs po-tential (M2
12). The parameter space of the type-II 2HDM
is sampled for given values of mH0 and mH± and
as-suming mh0 = 125 GeV and sin(β − α) ≥ 0.99. The
latter assumptions are made in order to maintain a SM-like Higgs boson with properties similar to those ob-served at the LHC. The gluon-fusion production cross section is calculated with SusHi [79] at NNLO precision in QCD corrections, and the branching ratio of the cas-cade H0
→ W∓H±
→ W+W−h
→ W+W−b¯b with
2HDMC [80]. Only parameter space points that satisfy theory constraints are considered. The theory constraints include Higgs-potential stability, tree-level unitarity for Higgs-boson scattering [81], and the perturbative nature of the quartic Higgs-boson couplings, as these are imple-mented in 2HDMC. The type-II 2HDM phase space is scanned with a million random points per (mH0, mH±)
pair. The majority of the spanned phase space violates the theoretical constraints mentioned above. The points with the lowest cross section times branching fraction σ×BF(excluded)/σ×BF(theory) which satisfy the above constraints are shown in Table IV, where σ is the cross section and BF is the branching fraction. None are ex-cluded by the limits presented here.
In conclusion, the first LHC search for a topology in which a heavy Higgs boson decays via a cascade of lighter charged and neutral Higgs bosons has been performed by the ATLAS experiment using data corresponding to an integrated luminosity of 20.3 fb−1 in pp collisions at
√s= 8 TeV. No significant excess of events above the ex-pectation from the SM background was found and limits on the production cross section have been set.
TABLE III: Expected background and observed yield, with expected and observed cross-section upper limits for each signal hypothesis in their respective signal regions. For the expected cross-section limits, the uncertainties describe a range which contains the limits in 68% and 95% of simulated experiments, respectively. Also shown is the p-value for the background-only hypothesis.
Masses [GeV] Yields Efficiency (%) Limits [pb] at 95% C.L. Backgr.-only
mH0 mh± t¯t Total Bkgd. Obs. Signal Expected Obs. p-value
325 225 8.4+1.0−1.0·103 8.9 +1.0 −1.3·103 9244 0.96 +0.32 −0.32 11 +5+12 −3−5 12.8 0.36 425 225 9.8+1.2−1.2·10 4 10.3+1.2−1.5·10 4 103738 2.9+0.8−0.8 41 +18+40 −12−19 40.2 0.49 425 325 9.4+1.1−1.1·10 4 9.8+1.1−1.4·10 4 99770 2.9+0.7−0.7 40 +17+40 −11−18 39 0.49 525 225 11.4+1.6−1.5·10 4 12.3+1.6−1.9·10 4 124802 3.8+0.8−0.8 42 +17+41 −12−19 42.8 0.49 525 325 11.5+1.6−1.6 ·10 4 12.6+1.7−1.9·10 4 127702 4.6+1.0−1.0 35 +15+34 −10−16 51.7 0.49 525 425 41.0+6.3−6.0 ·10 2 44.0+6.9−7.1·10 2 4342 0.31+0.1−0.1 23 +11+28 −7−11 22.6 0.49 625 225 20.3+2.9−3.0 ·10 3 23.0+3.4−4.0·10 3 22907 1.6+0.4−0.4 21 +8+20 −6−9 19.6 0.5 625 325 10.0+1.5−1.3 ·10 3 10.8+1.7−1.7·10 3 11064 1.5+0.3−0.4 11 +5+11 −3−5 11 0.49 625 425 20.5+3.4−3.0 ·10 2 24.4+4.1−4.9·10 2 2294 0.85+0.27−0.22 4.8 +2.1+5.2 −1.4−2.2 4.27 0.5 625 525 22.0+3.4−3.7 ·10 2 25.3+4.4−5.0·10 2 2564 1.0+0.3−0.2 4.3 +1.8+4.5 −1.2−2.0 4.22 0.5 725 225 31.8+5.2−5.2 ·10 2 37.7+6.9−7.6·10 2 3710 2.4+0.6−0.6 2.6 +1.1+2.6 −0.7−1.2 2.42 0.5 725 325 36.0+5.2−5.7 ·10 2 41.0+7.0−7.8·10 2 3980 2.7+0.6−0.6 2.1 +0.9+2.2 −0.6−1.0 1.99 0.5 725 425 24.9+4.3−3.9 ·10 2 29.6+5.7−6.2·10 2 2828 2.8+0.7−0.6 1.7 +0.7+1.8 −0.5−0.8 1.49 0.5 725 525 13.4+2.1−1.9 ·10 2 16.3+3.3−3.5·10 2 1538 2.8+0.7−0.6 0.84 +0.40+1.00 −0.25−0.40 0.718 0.5 725 625 23.6+3.6−3.5 ·10 2 28.7+5.3−6.1·10 2 2702 3.5+0.9−0.9 1.2 +0.6+1.4 −0.4−0.6 1.06 0.5 825 225 7.1+0.92−1.3 ·10 2 8.9+1.4−2.4·10 2 830 1.4+0.4−0.4 0.91 +0.42+1.00 −0.27−0.43 0.794 0.5 825 325 10.8+1.5−1.7 ·10 2 13.0+2.4−2.8·10 2 1237 2.4+0.6−0.6 0.82 +0.36+0.89 −0.23−0.38 0.717 0.5 825 425 10.5+1.9−1.6 ·10 2 12.7+2.7−2.5·10 2 1186 2.3+0.6−0.5 0.92 +0.41+1.00 −0.26−0.42 0.8 0.5 825 525 8.0+1.6−1.3·10 2 9.9+2.4−2.8·10 2 901 2.9+0.7−0.7 0.55 +0.25+0.62 −0.16−0.26 0.457 0.5 825 625 5.9+0.8−1.0·10 2 7.7+1.6−1.8·10 2 696 2.5+0.7−0.7 0.36 +0.18+0.45 −0.11−0.18 0.282 0.5 825 725 5.1+0.8 −0.7·102 6.6+1.6−1.3·102 628 1.6+0.5−0.4 0.56+0.28+0.71−0.17−0.27 0.484 0.5 925 225 5.7+0.9 −0.8·102 7.0+1.3−1.4·102 641 2.1+0.5−0.5 0.51+0.22+0.55−0.14−0.24 0.441 0.5 925 325 7.4+1.1 −1.2·102 9.3+1.4−1.9·102 876 2.7+0.7−0.6 0.58+0.27+0.69−0.17−0.27 0.528 0.5 925 425 6.6+1.0 −1.0·102 8.2+1.6−1.7·102 796 3.1+0.7−0.7 0.40+0.18+0.46−0.12−0.19 0.38 0.5 925 525 6.0+1.0 −1.1·102 8.1+1.8−1.9·102 787 3.3+0.9−0.8 0.37+0.17+0.43−0.11−0.18 0.345 0.5 925 625 1.8+0.4 −0.3·102 2.4+0.6−0.6·102 185 2.4+0.6−0.6 0.17+0.08+0.20−0.05−0.08 0.123 0.5 925 725 2.8+0.7 −0.4·102 3.8+1.0−0.9·102 359 2.7+0.7−0.7 0.30+0.14+0.34−0.09−0.14 0.272 0.5 925 825 4.7+0.7−0.7·102 6.0 +1.3 −1.2·102 537 3.6 +1.0 −0.9 0.22 +0.11+0.28 −0.07−0.11 0.172 0.5 1025 225 2.9+0.5−0.7·102 3.7 +1.1 −1.2·102 306 1.9 +0.5 −0.5 0.23 +0.11+0.28 −0.07−0.11 0.15 0.5 1025 325 7.1+1.0−1.2·102 9.4 +2.0 −2.2·102 839 3.3 +0.8 −0.8 0.37 +0.17+0.41 −0.11−0.17 0.292 0.5 1025 425 5.4+0.8−0.9·102 7.1 +1.5 −1.7·102 691 3.3 +0.8 −0.8 0.33 +0.15+0.37 −0.09−0.15 0.308 0.5 1025 525 2.4+0.5−0.6·102 3.5 +1.6 −1.1·102 297 3 +0.8 −0.7 0.19 +0.09+0.22 −0.05−0.09 0.147 0.5 1025 625 4.3+0.7−0.9·10 2 5.7+1.6−1.4·10 2 477 3.6+1.0−0.9 0.19 +0.10+0.25 −0.06−0.09 0.132 0.5 1025 725 1.4+0.2−0.3·10 2 2.0+0.5−0.6·10 2 162 1.8+0.5−0.4 0.15 +0.08+0.19 −0.05−0.07 0.0939 0.5 1025 825 2.1+0.3−0.5·10 2 3.0+0.7−1. ·10 2 241 2.6+0.6−0.6 0.14 +0.07+0.18 −0.04−0.07 0.0887 0.5 1025 925 9.4+1.2−1.7·10 13.7 +4.7 −4.4 ·10 110 1.9 +0.5 −0.5 0.10 +0.06+0.15 −0.03−0.05 0.0653 0.5
TABLE IV: Interpretation of the results in some type-II 2HDM parameter space choices. For each value of mH0, mH±, where
at least one valid point is found, sample points in the space of the parameters (tan(β), sin(β − α), mA, and M212) which satisfy
potential stability, unitarity and perturbativity constraints and give the smallest ratio of excluded to predicted cross section are shown.
mH0 mH± tan(β) sin(β − α) mA M212 σ(H0) BF(H0→ h0W+W−) Excl/Pred
[GeV] [GeV] [GeV] [TeV2] [pb]
325 225 15 0.99 303 6.9 ·10−3 28 0.222 2.1 425 225 20 0.99 439 8.9 ·10−3 2 0.404 41 425 325 10 0.99 486 1.8 ·10−2 10 0.288 14 525 325 10 0.99 384 2.7 ·10−2 3 0.436 39 525 425 10 0.99 384 2.7 ·10−2 5 0.136 34 625 325 10 0.99 549 3.9 ·10−2 1 0.501 20 625 425 10 0.99 693 3.9 ·10−2 2 0.607 4.1 625 525 10 0.99 693 3.9 ·10−2 3 0.219 7.7 725 325 1 0.99 675 5.9 ·10−2 0.3 0.009 664 725 425 10 0.99 731 5.2 ·10−2 1 0.643 3.5 725 525 10 0.99 731 5.2 ·10−2 1 0.659 1.1 725 625 10 0.99 396 5.2 ·10−2 1 0.002 440 825 525 1 0.99 788 1.3 ·10−1 0.3 0.024 76 825 625 1 0.99 788 1.3 ·10−1 0.3 0.021 41 825 725 10 0.999 807 6.8 ·10−2 1 0.168 4.1 925 725 1 0.999 921 2.4 ·10−1 0.2 0.003 530 1025 825 1 0.999 920 3.4 ·10−1 0.1 0.003 243
IX. ACKNOWLEDGEMENTS
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; BMWF 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, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET, ERC and NSRF, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Germany; GSRT and NSRF, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; BRF
and RCN, Norway; MNiSW and NCN, Poland; GRICES and FCT, Portugal; MNE/IFA, Romania; MES of Rus-sia and ROSATOM, RusRus-sian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MIZˇS, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Can-tons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Lever-hulme Trust, United Kingdom; DOE and NSF, United States of America.
The crucial computing support from all WLCG part-ners is acknowledged gratefully, in particular from CERN and the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Tai-wan), RAL (UK) and BNL (USA) and in the Tier-2 fa-cilities worldwide.
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The ATLAS Collaboration
G. Aad48, T. Abajyan21, B. Abbott112, J. Abdallah12, S. Abdel Khalek116, O. Abdinov11, R. Aben106, B. Abi113,
M. Abolins89, O.S. AbouZeid159, H. Abramowicz154, H. Abreu137, Y. Abulaiti147a,147b, B.S. Acharya165a,165b,a,
L. Adamczyk38a, D.L. Adams25, T.N. Addy56, J. Adelman177, S. Adomeit99, T. Adye130, S. Aefsky23,
T. Agatonovic-Jovin13b, J.A. Aguilar-Saavedra125b,b, M. Agustoni17, S.P. Ahlen22, A. Ahmad149, F. Ahmadov64,c,
M. Ahsan41, G. Aielli134a,134b, T.P.A. ˚Akesson80, G. Akimoto156, A.V. Akimov95, M.A. Alam76, J. Albert170,
S. Albrand55, M.J. Alconada Verzini70, M. Aleksa30, I.N. Aleksandrov64, F. Alessandria90a, C. Alexa26a,
G. Alexander154, G. Alexandre49, T. Alexopoulos10, M. Alhroob165a,165c, M. Aliev16, G. Alimonti90a, L. Alio84,
J. Alison31, B.M.M. Allbrooke18, L.J. Allison71, P.P. Allport73, S.E. Allwood-Spiers53, J. Almond83,
A. Aloisio103a,103b, R. Alon173, A. Alonso36, F. Alonso70, A. Altheimer35, B. Alvarez Gonzalez89,
M.G. Alviggi103a,103b, K. Amako65, Y. Amaral Coutinho24a, C. Amelung23, V.V. Ammosov129,∗,
S.P. Amor Dos Santos125a, A. Amorim125a,d, S. Amoroso48, N. Amram154, G. Amundsen23, C. Anastopoulos30,
L.S. Ancu17, N. Andari30, T. Andeen35, C.F. Anders58b, G. Anders58a, K.J. Anderson31, A. Andreazza90a,90b,
V. Andrei58a, X.S. Anduaga70, S. Angelidakis9, P. Anger44, A. Angerami35, F. Anghinolfi30, A.V. Anisenkov108,
N. Anjos125a, A. Annovi47, A. Antonaki9, M. Antonelli47, A. Antonov97, J. Antos145b, F. Anulli133a, M. Aoki102,
L. Aperio Bella18, R. Apolle119,e, G. Arabidze89, I. Aracena144, Y. Arai65, A.T.H. Arce45, S. Arfaoui149,
J-F. Arguin94, S. Argyropoulos42, E. Arik19a,∗, M. Arik19a, A.J. Armbruster88, O. Arnaez82, V. Arnal81,
O. Arslan21, A. Artamonov96, G. Artoni23, S. Asai156, N. Asbah94, S. Ask28, B. ˚Asman147a,147b, L. Asquith6,
K. Assamagan25, R. Astalos145a, A. Astbury170, M. Atkinson166, N.B. Atlay142, B. Auerbach6, E. Auge116,
A.M. Bach15, H. Bachacou137, K. Bachas155, M. Backes30, M. Backhaus21, J. Backus Mayes144, E. Badescu26a,
P. Bagiacchi133a,133b, P. Bagnaia133a,133b, Y. Bai33a, D.C. Bailey159, T. Bain35, J.T. Baines130, O.K. Baker177,
S. Baker77, P. Balek128, F. Balli137, E. Banas39, Sw. Banerjee174, D. Banfi30, A. Bangert151, V. Bansal170,
H.S. Bansil18, L. Barak173, S.P. Baranov95, T. Barber48, E.L. Barberio87, D. Barberis50a,50b, M. Barbero84,
T. Barillari100, M. Barisonzi176, T. Barklow144, N. Barlow28, B.M. Barnett130, R.M. Barnett15, A. Baroncelli135a,
G. Barone49, A.J. Barr119, F. Barreiro81, J. Barreiro Guimar˜aes da Costa57, R. Bartoldus144, A.E. Barton71,
P. Bartos145a, V. Bartsch150, A. Bassalat116, A. Basye166, R.L. Bates53, L. Batkova145a, J.R. Batley28,
M. Battistin30, F. Bauer137, H.S. Bawa144,g, T. Beau79, P.H. Beauchemin162, R. Beccherle50a, P. Bechtle21,
H.P. Beck17, K. Becker176, S. Becker99, M. Beckingham139, A.J. Beddall19c, A. Beddall19c, S. Bedikian177,
V.A. Bednyakov64, C.P. Bee84, L.J. Beemster106, T.A. Beermann176, M. Begel25, K. Behr119,
C. Belanger-Champagne86, P.J. Bell49, W.H. Bell49, G. Bella154, L. Bellagamba20a, A. Bellerive29, M. Bellomo30,
A. Belloni57, O.L. Beloborodova108,h, K. Belotskiy97, 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, K. Benslama131, S. Bentvelsen106, D. Berge30, E. Bergeaas Kuutmann16,
N. Berger5, F. Berghaus170, E. Berglund106, J. Beringer15, C. Bernard22, P. Bernat77, R. Bernhard48, C. Bernius78,
F.U. Bernlochner170, T. Berry76, P. Berta128, C. Bertella84, F. Bertolucci123a,123b, M.I. Besana90a, G.J. Besjes105,
O. Bessidskaia147a,147b, N. Besson137, S. Bethke100, W. Bhimji46, R.M. Bianchi124, L. Bianchini23, M. Bianco30,
O. Biebel99, S.P. Bieniek77, K. Bierwagen54, J. Biesiada15, M. Biglietti135a, J. Bilbao De Mendizabal49,
H. Bilokon47, M. Bindi20a,20b, S. Binet116, A. Bingul19c, C. Bini133a,133b, B. Bittner100, C.W. Black151,
J.E. Black144, K.M. Black22, D. Blackburn139, R.E. Blair6, J.-B. Blanchard137, T. Blazek145a, I. Bloch42,
C. Blocker23, J. Blocki39, W. Blum82,∗, U. Blumenschein54, G.J. Bobbink106, V.S. Bobrovnikov108, S.S. Bocchetta80,
A. Bocci45, C.R. Boddy119, M. Boehler48, J. Boek176, T.T. Boek176, N. Boelaert36, J.A. Bogaerts30,
A.G. Bogdanchikov108, A. Bogouch91,∗, C. Bohm147a, J. Bohm126, V. Boisvert76, T. Bold38a, V. Boldea26a,
A.S. Boldyrev98, N.M. Bolnet137, M. Bomben79, M. Bona75, M. Boonekamp137, S. Bordoni79, C. Borer17,
A. Borisov129, G. Borissov71, M. Borri83, S. Borroni42, J. Bortfeldt99, V. Bortolotto135a,135b, K. Bos106,
D. Boscherini20a, M. Bosman12, H. Boterenbrood106, J. Bouchami94, J. Boudreau124, E.V. Bouhova-Thacker71,
D. Boumediene34, C. Bourdarios116, N. Bousson84, S. Boutouil136d, A. Boveia31, J. Boyd30, I.R. Boyko64,
I. Bozovic-Jelisavcic13b, J. Bracinik18, P. Branchini135a, A. Brandt8, G. Brandt15, O. Brandt54, U. Bratzler157,
B. Brau85, J.E. Brau115, H.M. Braun176,∗, S.F. Brazzale165a,165c, B. Brelier159, K. Brendlinger121, R. Brenner167,
S. Bressler173, T.M. Bristow46, D. Britton53, F.M. Brochu28, I. Brock21, R. Brock89, F. Broggi90a, C. Bromberg89,
J. Bronner100, G. Brooijmans35, T. Brooks76, W.K. Brooks32b, J. Brosamer15, E. Brost115, G. Brown83, J. Brown55,
P.A. Bruckman de Renstrom39, D. Bruncko145b, R. Bruneliere48, S. Brunet60, A. Bruni20a, G. Bruni20a,
M. Bruschi20a, L. Bryngemark80, T. Buanes14, Q. Buat55, F. Bucci49, P. Buchholz142, R.M. Buckingham119,
A.G. Buckley46, S.I. Buda26a, I.A. Budagov64, B. Budick109, F. Buehrer48, L. Bugge118, M.K. Bugge118,
O. Bulekov97, A.C. Bundock73, M. Bunse43, H. Burckhart30, S. Burdin73, T. Burgess14, B. Burghgrave107,
S. Burke130, I. Burmeister43, E. Busato34, V. B¨uscher82, P. Bussey53, C.P. Buszello167, B. Butler57, J.M. Butler22,
A.I. Butt3, C.M. Buttar53, J.M. Butterworth77, W. Buttinger28, A. Buzatu53, M. Byszewski10, S. Cabrera Urb´an168,
D. Caforio20a,20b, O. Cakir4a, P. Calafiura15, G. Calderini79, P. Calfayan99, R. Calkins107, L.P. Caloba24a,
R. Caloi133a,133b, D. Calvet34, S. Calvet34, R. Camacho Toro49, P. Camarri134a,134b, D. Cameron118,
L.M. Caminada15, R. Caminal Armadans12, S. Campana30, M. Campanelli77, V. Canale103a,103b, F. Canelli31,
A. Canepa160a, J. Cantero81, R. Cantrill76, T. Cao40, M.D.M. Capeans Garrido30, I. Caprini26a, M. Caprini26a,
M. Capua37a,37b, R. Caputo82, R. Cardarelli134a, T. Carli30, G. Carlino103a, L. Carminati90a,90b, S. Caron105,
E. Carquin32a, G.D. Carrillo-Montoya146c, A.A. Carter75, J.R. Carter28, J. Carvalho125a,i, D. Casadei77,
M.P. Casado12, C. Caso50a,50b,∗, E. Castaneda-Miranda146b, A. Castelli106, V. Castillo Gimenez168, N.F. Castro125a,
P. Catastini57, A. Catinaccio30, J.R. Catmore71, A. Cattai30, G. Cattani134a,134b, S. Caughron89, V. Cavaliere166,
D. Cavalli90a, M. Cavalli-Sforza12, V. Cavasinni123a,123b, F. Ceradini135a,135b, B. Cerio45, K. Cerny128,
A.S. Cerqueira24b, A. Cerri150, L. Cerrito75, F. Cerutti15, A. Cervelli17, S.A. Cetin19b, A. Chafaq136a,
D. Chakraborty107, I. Chalupkova128, K. Chan3, P. Chang166, B. Chapleau86, J.D. Chapman28, D. Charfeddine116,
D.G. Charlton18, V. Chavda83, C.A. Chavez Barajas30, S. Cheatham86, S. Chekanov6, S.V. Chekulaev160a,
G.A. Chelkov64, M.A. Chelstowska88, C. Chen63, H. Chen25, K. Chen149, L. Chen33d, S. Chen33c, X. Chen174,
Y. Chen35, Y. Cheng31, A. Cheplakov64, R. Cherkaoui El Moursli136e, V. Chernyatin25,∗, E. Cheu7, L. Chevalier137,
V. Chiarella47, G. Chiefari103a,103b, J.T. Childers30, A. Chilingarov71, G. Chiodini72a, A.S. Chisholm18,
R.T. Chislett77, A. Chitan26a, M.V. Chizhov64, S. Chouridou9, B.K.B. Chow99, I.A. Christidi77,
D. Chromek-Burckhart30, M.L. Chu152, J. Chudoba126, G. Ciapetti133a,133b, A.K. Ciftci4a, R. Ciftci4a, D. Cinca62,
V. Cindro74, A. Ciocio15, M. Cirilli88, P. Cirkovic13b, Z.H. Citron173, M. Citterio90a, M. Ciubancan26a, A. Clark49,
P.J. Clark46, R.N. Clarke15, J.C. Clemens84, B. Clement55, C. Clement147a,147b, Y. Coadou84, M. Cobal165a,165c,
A. Coccaro139, J. Cochran63, S. Coelli90a, L. Coffey23, J.G. Cogan144, J. Coggeshall166, J. Colas5, B. Cole35,
