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ATLAS NOTEATLAS-CONF-2015-042

31st August 2015

Search for New Phenomena in Dijet Mass and AngularDistributions with the ATLAS Detector at

√s = 13 TeV

The ATLAS Collaboration

Abstract

This note describes a search for pairs of jets (dijets) produced by phenomena beyond theStandard Model in 80 pb−1 of proton-proton collisions with a centre-of-mass energy of√

s = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. We exam-ine the distribution of the invariant mass of the two leading jets for local excesses atop adata-driven estimate of the smoothly-falling distribution predicted by the Standard Model.We also compare the data to a Monte Carlo simulation of the Standard Model using thedistribution of an angular variable, χ, derived from the rapidity of the two jets. Both distri-butions lack evidence for anomalous phenomena. We exclude Quantum Black Holes withmasses below 6.8 TeV or 6.5 TeV in two benchmark scenarios. We also set 95% C.L. upperlimits on the cross section for new processes that would produce a Gaussian contribution tothe dijet mass distribution. We exclude Gaussian contributions with effective cross sectionsranging from approximately 0.4–2 pb below 2 TeV to 0.05–0.09 pb above 4 TeV.

© 2015 CERN for the benefit of the ATLAS Collaboration.Reproduction of this article or parts of it is allowed as specified in the CC-BY-3.0 license.

1 Introduction

When a particle collider increases its collision energy, it may cross beyond a threshold where new phe-nomena begin to produce observable effects. For example, the energy may become sufficiently high toreveal the substructure of the colliding particles, or to directly produce particles that could not be producedat lower energies. The Large Hadron Collider (LHC) at CERN has recently increased the centre-of-massenergy of its proton-proton collisions from

√s = 8 TeV to

√s = 13 TeV, opening a new energy regime

to observation.

In order to singly produce new particles in LHC collisions, the particles must interact with the constituentpartons within the proton. This in turn means that the new particles can also decay to partons. Often inmodels of beyond the Standard Model (BSM) phenomena, these decays dominate.

The partons shower and hadronize, creating collimated jets of particles carrying approximately the four-momenta of the original partons. The total production rates for two-jet (dijet) BSM signals can be large,allowing searches for anomalous dijet production to test for such signals with a relatively small datasample, even at masses that involve significant fractions of the total hadron collision energy.

Prior searches of dijet distributions at hadron colliders from the SPS, Tevatron, and the√

s = 7–8 TeVLHC [1–17] did not observe BSM phenomena. This note presents a search for BSM phenomena using80 pb−1 of collision data recorded by the ATLAS detector at the LHC. Analyses are performed on thedistributions of the dijet invariant mass, m j j , and of a variable derived from the angular separation of thetwo jets, χ, defined below.

In the Standard Model of particle physics, hadron collisions produce jet pairs primarily via 2→ 2 partonscattering processes governed by Quantum Chromodynamics (QCD). Far above the confinement scale ofQCD (≈ 1 GeV), jets emerge from collisions with large momenta, pT, transverse to the direction of theincident partons. Most dijet production, however, occurs at small angles θ∗ with respect to the directionof the incident partons in the parton-parton centre-of-mass frame1, due to t-channel poles in the crosssections for the dominant scattering processes. Many theories of BSM physics predict additional dijetproduction with a significant population of jets produced at large angles with respect to the beam (forreviews see Refs. [18, 19]). For the data analysed in this note, QCD predicts an m j j distribution that issmoothly falling, without a characteristic mass scale or other features. In contrast, new states decayingto two jets may introduce localized excesses in the mass distribution if the states have sufficiently narrowwidth. The search performed in this note exploits these differences in the χ and m j j distributions.

As is common, we define a rapidity y = 12 ln E+pz

E−pzfor each of the outgoing partons, where E is its energy

and pz is the component of its momentum along the beam pipe2. Each incoming parton carries a fraction(Bjorken x) of the momentum of its proton. A momentum imbalance between the two partons boosts thecentre-of-mass frame of the collision relative to the detector frame along the z direction. The boost fromthe laboratory to the centre-of-mass frame along the z direction is yB = 1

2 ln (x/x ′) = 12 (y1 + y2), where x

and x ′ are the fractions of the proton momentum carried by each parton and y1 and y2 are rapidities of theoutgoing partons in the detector frame. This boost is zero when both partons carry the same momentum

1 Since, experimentally, the two partons cannot be distinguished, θ∗ is always taken between 0 and π/2.2 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector

and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis pointsupwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. Thepseudorapidity is defined in terms of the polar angle θ as η = − ln tan(θ/2). It is equivalent to the rapidity for massless

particles. Angular distance is measured in units of ∆R ≡√

(∆η)2 + (∆φ)2.

2

(x = x ′). Differences in two rapidities are invariant under Lorentz boosts along the z direction. Thereforethe following function of the rapidity difference y∗ = 1

2 (y1 − y2) between the two outgoing jets,

χ = e2 |y∗ | ∼1 + cos θ∗

1 − cos θ∗(1)

is the same in the detector frame as in the partonic centre-of-mass frame. In the centre-of-mass frame, thetwo partons have rapidity ±y∗.

The variable χ is constructed such that in the limit of massless parton scattering, and when only t-channelscattering contributes to the partonic cross section, the shape of the distribution of χ will be approximatelyindependent of the two-parton invariant mass. The shapes of the observed χ distributions are distortedfrom the χ distributions at parton-level by the non-uniform parton momentum distributions as a functionof x and x ′. Restricting the size of yB restricts the ranges of x and x ′ and reduces these distortions.

2 ATLAS Detector

The ATLAS experiment [20] at the LHC is a multi-purpose particle detector with a forward-backwardsymmetric cylindrical geometry with layers of tracking, calorimeter, and muon detectors over nearly theentire solid angle around the pp collision point. High-pT hadronic jets are measured using finely seg-mented hadronic and electromagnetic calorimeters. A steel/scintillator-tile calorimeter provides hadronicenergy measurements for the pseudorapidity range (|η | < 1.7). A lead/liquid-argon (LAr) calorimeterprovides electromagnetic (EM) energy measurements with higher granularity. The end-cap and forwardregions are instrumented with LAr calorimeters for both EM and hadronic energy measurements up to|η | = 4.9. A muon spectrometer surrounds the calorimeters. A first-level trigger is implemented in hard-ware and uses a subset of the detector information to reduce the accepted rate to 100 kHz. This is followedby a software-based trigger that reduces the average recorded collision rate to 1 kHz.

3 Data Selection

The analysis described in this note uses proton–proton collision data at 13 TeV centre-of-mass energyrecorded in August 2015. Collision events are recorded using a trigger requiring the presence of at leastone jet reconstructed in the software trigger with a pT of at least 360 GeV. The dataset does not includeearlier data due to an inefficiency in the triggering of very high energy objects.

Groups of contiguous calorimeter cells (topological clusters) are formed based on the significance of theenergy deposit over calorimeter noise [21]. These are clustered into jets using the anti-kt algorithm [22,23] with distance parameter R = 0.4. Jet four-momenta are computed summing over the four-momentaof the topological clusters that comprise the jet, treating each cluster as a four-vector with zero mass.These four-momenta are calibrated for the response to incident hadrons using the procedures described inRefs. [24, 25]. The agreement between data and simulation is further improved by the application of jet-wise calibration constants obtained at lower collision energies with in situ techniques [26] and validatedfor use at 13 TeV [27].

Events containing at least two jets are selected for offline analysis if the pT of the leading-pT jet is greaterthan 410 GeV and the pT of the subleading-pT jet is greater than 50 GeV. The requirement on leading jet

3

pT ensures a trigger efficiency of at least 99.5 % for collisions with |y∗ | < 1.7. Events are discarded fromthe search if either of the two leading jets, or a third jet with pT > 50 GeV, are poorly measured or have atopology compatible with non-collision background or calorimeter noise [28].

4 Simulated Collisions

For this search, events have been simulated for QCD processes with Pythia 8 [29] using the A14 [30]underlying event tune and the NNPDF2.3 LO [31] PDFs. Detector effects are simulated using Geant4within the ATLAS software infrastructure [32, 33]. The same software used to reconstruct data was usedfor the simulated events.

Pythia 8 calculations use matrix elements which are leading order (LO) in the QCD coupling constantwith simulation of higher-order contributions partially included in the parton shower (PS) modeling. Py-thia 8 also includes modeling of hadronization effects. We reweight the distributions of events predictedby Pythia 8 to the next-to-leading-order (NLO) cross-section predictions of NLOJET++ [34–36] usingm j j - and χ-dependent correction factors,

k ( χ,m j j ) =σNLO( χ,m j j )NLOJET++

σLO+shower( χ,m j j )Pythia 8 .

Here σLO+shower is the cross-section obtained in Pythia 8 with hadronization corrections turned off. Thecorrection factors modify the shape of the χ distributions at the level of 15% at low values of χ and highvalues of m j j . The correction is 5% or less at the highest values of χ. The Pythia 8 predictions also omitelectroweak effects. We include these as additional m j j - and χ-dependent correction factors [37]. Thecorrection factors are unity at low m j j and differ from unity by up to 3% in the m j j > 3.4 TeV region.

5 Resonance Analysis

The search in the m j j distribution is performed using events with |y∗ | < 0.6 (χ < 3.3). The requirementon |y∗ | reduces the background to resonant BSM physics from QCD processes. To avoid kinematic biasfrom the selections described in Section 3, the search is confined to m j j > 1100 GeV.

Figure 1 shows the observed m j j distribution for the resonance analysis. The bin width varies with massand is chosen to approximate the m j j resolution as derived from the simulation of QCD processes. Thelargest value of m j j measured is 5.2 TeV. ATLAS, CMS, and CDF dijet searches [4, 6, 11, 12, 14] havefound that an ansatz of the form

f (z) = p1(1 − z)p2 zp3+p4 log z (2)

where z ≡ m j j/√

s, and pi are chosen by the fit, describes dijet mass distributions observed at lowercollision energies. The ansatz also describes leading and next-to-leading order simulations of QCD dijetproduction. The Standard Model background to the present analysis is estimated by a fit to the entireobserved m j j distribution with the same function. While providing data at lower m j j values, the obser-vations at lower collision energies involved larger statistics and wider ranges of mass than are availablein the present 13 TeV ATLAS data, and all four parameters were needed in order to obtain a satisfactorydescription of the data. Studies with simulation of 13 TeV QCD processes indicate that the ansatz with

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ATLAS Preliminary-1=13 TeV, 80 pbs

DataBackground fitBumpHunter intervalBlackMax, m = 4.0 TeVBlackMax, m = 5.0 TeV

Figure 1: The dijet mass distribution (filled points) for events in with |y∗ | < 0.6 and pT > 410 (50) GeV for theleading (subleading) jets fitted with a function described by Eq. 2 (solid line) discussed in the text. Predictions fromBlackMax for two Quantum Black Hole signals are shown above the fit, normalized to the predicted cross section.The vertical lines indicate the most discrepant interval identified by the BumpHunter algorithm. The bottom panelshows the bin-by-bin significance of the data-fit difference, considering statistical uncertainties only.

p4 set to zero will remain a good description of the m j j distribution until substantially more data are col-lected, and thus the log z term is removed from the fit. To avoid bias from a BSM process that contributesin a single, contiguous range of bins, any such range is automatically excluded from the fit if an excess inthose bins decreases the fit probability below 0.01.

The function in Eq. 2 is fit to this distribution with a probability of 0.45. The result is also shown in thefigure. The bottom panel of the figure shows the significances of bin by bin differences between the dataand the fit. These Gaussian significances are calculated from the Poisson probability. The significancetakes statistical uncertainties but no systematic uncertainties into account.

We search for statistical evidence of any localized excess in this distribution using the BumpHunteralgorithm [38, 39]. The algorithm operates on the binned m j j distribution, comparing the data with the

5

fitted background estimate in all possible mass intervals, up to half the mass range spanned by the data.For each interval in the scan, it computes the significance of any excess found. The algorithm identifiesthe interval 2.91–3.17 TeV, indicated by the two vertical lines in Figure 1, as the single most discrepantinterval. The significance of the outcome is evaluated using the ensemble of possible outcomes acrossall intervals scanned, by repeating the algorithm on pseudo-data drawn from the background fit. Beforeincluding systematic uncertainties, the probability (p-value) of observing a background fluctuation atleast as significant as the above, anywhere in the distribution, is 0.78. There is no evidence for a localizedcontribution to the distribution from BSM physics.

6 Angular Analysis

The search in χ distributions is performed using dijet events with |y∗ | < 1.7 (i.e. χ < 30.0) and |yB | <1.1. To avoid kinematic bias from the selections described in Section 3, the search is confined to m j j >

2500 GeV. Figure 2 shows the χ distributions of the data in the angular analysis in different m j j ranges.The highest m j j measured is 6.9 TeV. In the analysis, the Standard Model prediction in each m j j rangeis normalised to match the integral of the data in that range. The shapes of the χ distributions in thefigure are compared to data after normalising both to unit area. The theoretical uncertainties and the totaluncertainties are displayed as shaded bands around the Standard Model prediction.

The CLs-technique [40, 41] is used to test the compatibility of the χ distribution with the Standard Modelprediction and with a quantum black hole BSM signal (see below). The top panel in Figure 2 shows thedata in the m j j range used for this test. The data prefer the background-only hypothesis, with a CLs

statistic of 0.50 for the highest m j j range. The χ2 probability for the observed data given the StandardModel prediction is 0.57.

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χ1 2 3 4 5 6 7 8 10 20 30

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χ1/N

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Data SM= 6.5 TeV

thQBH, M Theoretical uncert.

Total uncertainties| < 1.1

B|y*| < 1.7, |y

ATLAS Preliminary­1 = 13 TeV, 80 pbs

Figure 2: Distributions of the dijet angular variable χ in different regions of the dijet invariant mass m j j for eventswith |y∗ | < 1.7, |yB | < 1.1 and pT > 410 (50) GeV for the leading (subleading) jets. Shown are the data(points), corrected Pythia 8 predictions (solid lines), and one prediction from the QBH generator for the QuantumBlack Hole model discussed in the text. The theoretical uncertainties and the total theoretical and experimentaluncertainties are displayed as shaded bands around the Standard Model prediction.

7

7 Signal Models

As the measured m j j and χ distributions do not deviate significantly from expectation, we use that datato constrain models that predict excesses in the distributions. While dijet resonances are predicted inmany models of BSM physics, in this initial 13 TeV result we focus on a particularly high-rate scenariowhere gravity can propagate in extra dimensions [19, 42–45] and thus low-entropy black holes can beproduced.

Models with extra dimensions, such as the Arkani-Hamed–Dimopoulous–Dvali (ADD) model [46, 47],solve the mass hierarchy problem of the Standard Model by lowering the fundamental scale of quantumgravity, MD to a few TeV. Consequently, the LHC could produce quantum black holes with massesat or above MD [48, 49]. A Quantum Black Hole produced near MD would evaporate faster than itthermalizes, decaying into a few particles rather than high-multiplicity final states [44, 45, 50]. Such asignal would appear as a local excess over the m j j distribution near the threshold mass, Mth, and wouldfall exponentially at higher masses. In this note, Quantum Black Hole production and decay to two jetsis simulated using both the QBH generator [51] and the BlackMax generator [50], assuming an ADDscenario with MD = Mth and n = 6, as in Ref. [14].

The two generators make different assumptions about the physics of black hole production and decay.Black holes decay thermally in BlackMax, while the decay products of the QBH generator are dictatedby particle conservation principles. Moreover, the QBH generator includes the effects of spin while theBlackMax generator does not.

The acceptance times efficiency in the resonance analysis for a Quantum Black Hole with mass 6.5 TeVis 54% for the QBH generator and 53% for the BlackMax generator. For the angular analysis, the corres-ponding acceptance times efficiency is 92% for the QBH generator and 91% for the BlackMax generator.For both Quantum Black Hole generators, the CTEQ6L1 [52] PDFs are used instead of NNPDF2.3 LOPDFs, to ensure good behavior at extreme values of Bjorken x.

Subsequent to parton-level calculations, the Quantum Black Hole models are simulated in an identicalmanner to QCD processes, using the same parameters for non-perturbative corrections.

Results are also provided on the cross section, σ, times acceptance, A, times branching ratio, BR, totwo jets of a hypothetical signal that produces a Gaussian contribution to the observed m j j distribution.For sufficiently narrow resonances, these results may be used to set limits on BSM models beyond thoseconsidered explicitly in this note. Such limits should be used when PDF and nonperturbative effectscan be safely truncated or neglected and, after applying the kinematic selection criteria of the resonanceanalysis, the distribution of m j j for a signal approaches a Gaussian distribution. The resulting limit willbe conservative at high masses with respect to the limits obtained with full benchmark templates. BSMmodels with an intrinsic width much smaller than 5% should be compared to the results with widthequal to the experimental resolution. For models with a larger width after detector effects, the limit thatbest matches their width should be used. More detailed instructions can be found in Appendix A ofRef. [14].

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8 Systematic Uncertainties

In the resonance analysis, systematic uncertainties on the estimate of the background to the search arisefrom imperfect knowledge of the shape of the m j j distribution. To account for the statistical uncertaintyon the fitted parameters in Eq. 2, a large number of pseudo-experiments are performed, fitting pseudo-datadrawn via Poisson fluctuations around the nominal background model. The uncertainty on the backgroundprediction in each m j j bin is taken to be the root mean square of the function value in that bin for allpseudo-experiments. To account for the choice of function used in the fit, a parameterization with oneadditional degree of freedom, p4, is compared to the nominal fit. Fig. 3 shows these two contributions tothe uncertainty on the background prediction.

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Unce

rt.

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Figure 3: The dijet mass distribution (points) for events with |y∗ | < 0.6 and pT > 410 (50) GeV for the lead-ing (subleading) jets fitted with a function described by Eq. 2 (solid line). The light and dark cyan lines depictvariations of the background prediction from the statistical uncertainty on the fitted parameters and from the uncer-tainty due to the choice of function, as described in the text. The bottom panel depicts the relative uncertainty fromeach source.

In the angular analysis, theoretical uncertainties on simulations of the χ distributions of QCD processesare estimated as described in Ref. [17]. The resonance search does not estimate the background using

9

simulated collisions and thus it is not affected by uncertainties on simulations of QCD processes. Theeffect on the Pythia 8 QCD prediction of varying the PDFs is estimated using NLOJET++ with threedifferent PDF sets: CT10, MSTW2008 [53] and NNPDF23 [54]. As the choice of PDF largely affectsthe total cross section rather than the shape of the χ distributions, these uncertainties are negligible(< 1%). The uncertainty due to the choice of renormalization and factorization scales was estimatedusing NLOJET++ by varying each independently up and down by a factor two. The resulting uncertainty,taken as the envelope of the variations in the normalized χ distributions, depends on both m j j and χ,rising to 20% at the smallest χ values at high m j j values. The uncertainties due to limited statistics inthe simulation of the NLO corrections are less than 1%. The dominant experimental uncertainty on thepredictions of the χ distributions is the jet energy scale uncertainty. It is derived from 8 TeV data andcomplemented by additional uncertainties derived using 13 TeV data to account for differences in thecalibration and detector conditions [27]. The impact of this uncertainty is at most 9%.

The following systematic uncertainties are included in setting limits on the Quantum Black Hole models:statistical uncertainties, jet energy scale (up to 10%), and PDF and uncertainties due to higher-ordercorrections (1%). The impact of the uncertainty on the jet energy resolution is negligible. The uncertaintyon the integrated luminosity is ±9%. It is derived, following a methodology similar to that detailed inRef. [55], from a preliminary calibration of the luminosity scale using a pair of x-y beam-separation scansperformed in June 2015.

9 Limits

Starting from the m j j distribution obtained by the resonance analysis, a Bayesian method [12] is appliedto the data and QBH or BlackMax simulation at a series of discrete masses to set a 95% credibility-level upper limit on the cross section times acceptance for the two types of signals. The method uses aprior constant in signal strength and Gaussian priors for nuisance parameters corresponding to systematicuncertainties. The limit is interpolated between the discrete masses to create a curve continuous in blackhole mass.

Figure 4 shows the limit as a function of the Quantum Black Hole mass for the QBH and BlackMaxgenerators. From these limits, Quantum Black Holes in the n = 6, MD = Mth ADD scenario simulatedwith the QBH generator with Mth below 6.8 TeV are excluded at 95% credibility level. Signals pro-duced by the BlackMax generator are excluded below 6.5 TeV. These supercede the exclusions below5.66 TeV (5.62 TeV) on QBH (BlackMax) signals set by the ATLAS Collaboration using dijet events at√

s = 8 TeV [14]. A search performed by the CMS Collaboration for Quantum Black Holes yielded limitsin the range of 5.0–6.3 TeV, for n = 1–6 and different model assumptions [56].

Starting from the χ distribution obtained by the angular analysis, the CLs technique is applied betweenthe Standard Model and the QBH or BlackMax simulation, using the asymptotic approximation [57] anda one-sided profile likelihood ratio, to set a 95% confidence-level upper limits on Quantum Black Holeproduction. The validity of the asymptotic approximation was confirmed using toy simulations. Thelimits are calculated in the most sensitive region, m j j > 3.4 TeV.

Figure 5 shows the limit from the angular analysis as a function of the Quantum Black Hole thresholdmass for the n = 6, MD = Mth ADD scenario simulated with the QBH and BlackMax generators. Theseresults exclude black holes simulated with the QBH generator with Mth below 6.5 TeV at 95% C.L. The

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Figure 4: Observed (filled circles) and expected 95% credibility-level upper limits (dotted line) on the cross section,σ, times acceptance, A, for Quantum Black Holes as a function of particle mass, obtained from the m j j distribution.The green and yellow bands represent the 68% and 95% contours of the expected limit. The dashed and dotted-dashed curves are the theoretical predictions of σ × A for the BlackMax and QBH generators. The observed(expected) mass limit occurs at the crossing of each σ× A curve with the observed (expected) 95% credibility-levelupper limit curve.

corresponding exclusion for predictions of the BlackMax Generator is 6.4 TeV. The results are consistentwith the resonance analysis.

Figure 6 shows limits on the Gaussian contributions to the observed m j j distribution obtained for fourdifferent widths, from a width equal to the detector mass resolution to 15% of the mean mass of theGaussian distribution. The mass resolution is 2% at a mass of 4 TeV. As the width increases, the localizedexcess becomes less distinct, and the limit weakens, accompanied by a decrease in the impact of statisticalfluctuations as the expected signal contribution is distributed across more bins. For intrinsically narrowresonances, which would contribute a Gaussian distribution of width equal to the detector mass resolution,we exclude effective cross sections ranging from approximately 2 pb below 2 TeV to 0.05 pb above4 TeV.

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Figure 5: Observed (filled circles) and expected 95% confidence-level upper limits (dotted line) on the cross section,σ, times acceptance, A for Quantum Black Holes as a function of particle mass, obtained from the χ distribution.The green and yellow bands represent the 68% and 95% contours of the expected limit. The dashed and dotted-dashed curves are the theoretical predictions of σ × A for the BlackMax and QBH generators. The observed(expected) mass limit occurs at the crossing of each σ× A curve with the observed (expected) 95% credibility-levelupper limit curve.

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Figure 6: The 95% credibility-level upper limits obtained in the resonance analysis on cross section, σ, timesacceptance, A, times branching ratio, BR, to two jets for a hypothetical signal that produces a Gaussian contributionto the observed m j j distribution, as a function of the mean mass of the Gaussian distribution, mG . Limits areobtained for four different widths, from a width equal to the detector mass resolution (“Res.”) to 15% of the meanmass of the Gaussian distribution.

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10 Conclusion

No evidence for phenomena beyond the Standard Model was uncovered in this search using dijets eventsin 80 pb−1 of proton-proton collisions with a centre-of-mass energy of

√s = 13 TeV recorded by the

ATLAS detector at the Large Hadron Collider. The dijet invariant mass distribution exhibits no significantlocal excesses atop a data-driven estimate of the smoothly-falling distribution predicted by the StandardModel. The distribution of the angular variable χ also agrees with a Monte Carlo simulation of theStandard Model. In an ADD scenario with n = 6 and MD = Mth, we exclude Quantum Black Holespredicted by the QBH generator with Mth below 6.8 TeV (6.5 TeV) at 95% C.L. using the resonance(angular) analysis. The exclusions for the BlackMax generator are 6.5 TeV (6.4 TeV). We also set 95%C.L. upper limits on the cross section for new processes that would produce a Gaussian contribution tothe dijet mass distribution. We exclude Gaussian contributions with effective cross sections ranging fromapproximately 0.4–5 pb below 2 TeV to 0.05–0.09 pb above 4 TeV.

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Appendix

Figures 7-12 show the m j j distributions and the pT distributions for the leading and subleading jets inevents selected by the resonance analysis or the angular analysis. The figures also show the Pythia 8simulation of QCD processes overlaid. The shaded band indicates the experimental uncertainty on thejet energy scale calibration. The NLO and electroweak correction factors, described in the text, are notapplied to the simulation in these figures.

Figure 13 displays the highest mass dijet event found by the resonance analysis. Figure 14 displays thehighest mass dijet event found by the angular analysis.

[GeV]jjm

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Figure 7: The observed m j j distribution obtained with the resonance analysis selection of events with |y∗ | < 0.6and pT > 410 (50) GeV for the leading (subleading) jets. The distribution predicted by Pythia 8 simulation ofQCD processes is overlaid. The NLO and electroweak correction factors, described in the text, are not appliedto the simulation in this figure. The shaded band indicates the experimental uncertainty on the jet energy scalecalibration. Theoretical uncertainties are not depicted.

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Figure 8: The observed m j j distribution obtained in the angular analysis selection of events with |y∗ | < 1.7,|yB | < 1.1 and pT > 410 (50) GeV for the leading (subleading) jets. The distribution predicted by Pythia 8simulation of QCD processes is overlaid. The NLO and electroweak correction factors, described in the text, arenot applied to the simulation in this figure. The shaded band indicates the experimental uncertainty on the jet energyscale calibration. Theoretical uncertainties are not depicted.

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Figure 9: The observed pT distribution of the leading jet, obtained with the resonance analysis selection of eventswith |y∗ | < 0.6 and pT > 50 GeV for the subleading jet. The distribution predicted by Pythia 8 simulation ofQCD processes is overlaid. The NLO and electroweak correction factors, described in the text, are not appliedto the simulation in this figure. The shaded band indicates the experimental uncertainty on the jet energy scalecalibration. Theoretical uncertainties are not depicted.

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Figure 10: The observed pT distribution of the leading jet, obtained with the angular analysis selection of eventswith |y∗ | < 1.7, |yB | < 1.1, and pT > 50 GeV for the subleading jet. The distribution predicted by Pythia 8simulation of QCD processes is overlaid. The NLO and electroweak correction factors, described in the text, arenot applied to the simulation in this figure. The shaded band indicates the experimental uncertainty on the jet energyscale calibration. Theoretical uncertainties are not depicted.

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Figure 11: The observed pT distribution of the subleading jet, obtained with the resonance analysis selection ofevents with |y∗ | < 0.6 and pT > 410 GeV for the leading jet. The distribution predicted by Pythia 8 simulationof QCD processes is overlaid. The NLO and electroweak correction factors, described in the text, are not appliedto the simulation in this figure. The shaded band indicates the experimental uncertainty on the jet energy scalecalibration. Theoretical uncertainties are not depicted.

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[GeV]T

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Figure 12: The observed pT distribution of the subleading jet, obtained with the angular analysis selection of eventswith |y∗ | < 1.7, |yB | < 1.1, and pT > 410 GeV for leading jet. The distribution predicted by Pythia 8 simulationof QCD processes is overlaid. The NLO and electroweak correction factors, described in the text, are not appliedto the simulation in this figure. The shaded band indicates the experimental uncertainty on the jet energy scalecalibration. Theoretical uncertainties are not shown.

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Figure 13: The highest-mass, central dijet event passing the dijet mass analysis selection collected in August 2015(Event 531676916, Run 276731) : the two central high-pT jets have an invariant mass of 5.2 TeV, the highest-pTjet has a pT of 2.5 TeV, the subleading jet has a pT of 2.4 TeV and the third jet has a pT of 0.34 GeV. The missingtransverse momentum and the scalar sum of the transverse momenta of all objects in this event are 0.05 TeV and5.7 TeV, respectively. The scalar sum of the jet pT is 5.2 TeV. Only tracks with pT > 2 GeV are displayed.

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Figure 14: The highest-mass, central dijet event passing the dijet angular analysis selection collected in August 2015(Event 876578955, Run 276731) : the two central high-pT jets have an invariant mass of 6.9 TeV, the highest-pT jethas a pT of 1.3 TeV, and the subleading jet has a pT of 1.2 TeV. The missing transverse momentum and the scalarsum of the transverse momenta of all objects in this event are 0.1 TeV and 2.8 TeV, respectively. Only tracks withpT > 2 GeV are displayed.

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