Search for new light resonances decaying to jet pairs and produced in association with a photon in proton-proton collisions at √

A TLAS-CONF-2016-029 15 June 2016

ATLAS NOTE

ATLAS-CONF-2016-029

14th June 2016

Search for new light resonances decaying to jet pairs and produced in association with a photon in proton-proton collisions at √

s = 13 TeV with the ATLAS detector

The ATLAS Collaboration

Abstract

This note describes a search for new resonances decaying to pairs of jets in 3.2 fb

of proton-proton collisions with a centre-of-mass energy of

√ s = 13 TeV recorded during 2015

by the ATLAS detector at the Large Hadron Collider. The search requires the new resonance

would be produced in association with a high- p

photon, such as a photon radiated from the

colliding partons, in order to efficiently trigger on events containing light resonances. The

distribution of the invariant mass of the two leading jets is examined for local excesses above

a data-derived estimate of the smoothly falling background. No evidence of anomalous

phenomena is observed in the data, which are used to exclude effective cross-sections of

processes with Gaussian-shaped contributions to the observed dijet mass distribution and

regions of the parameter space of a lepto-phobic axial-vector Z

benchmark model. These

results extend the limits on light dijet resonances obtained at lower centre-of-mass energies.

1 Introduction

Searches for resonance peaks in the two-jet invariant mass distribution are an essential part of the physics program at the energy frontier. Many theoretical models predict resonances with significant couplings to quarks and gluons, including resonances which also couple to dark matter particles. From the experimental perspective, the search can be done with minimal model dependence and provides substantial gains in sensitivity with increasing of centre-of-mass energy.

These gains are especially important to searches for heavy hypothetical resonances, whose sensitivity is limited by the centre-of-mass energy and the fraction of that energy contained in the interacting partons.

In the Large Hadron Collider (LHC) era, the power to discover or exclude such hadronic resonances has been extended into the TeV range, though no evidence of statistically significant excesses has been seen [1–11].

Sensitivity to light resonances is controlled by more mundane factors, such as immense background rates that would swamp the trigger and data acquisition systems. Recording full events at these high rates demands minimum transverse momentum, p

T

, thresholds for the jets which creates a lower bound on the sensitivity at a mass of approximately M = 2 p

T

where p

T

is typically several hundred GeV.

Consequently, recent searches for light dijet resonances have poor sensitivity for masses well below 1 TeV.

No experiment at a hadron collider has placed new constraints using the dijet final state on resonance masses below 300 GeV in the past two decades. In terms of the coupling between quarks and the resonance, limits in this light-resonance region are weaker than limits in heavy-resonance regions [12].

In this note, we present a search using an alternative approach [13, 14] in which the trigger threshold limitations are avoided by examining data where the light resonance (denoted X ) is boosted in the transverse direction via recoil from high- p

initial-state radiation (ISR) of a photon; see Figure 1. Requiring a hard ISR object in the final state comes at the cost of reduced signal production rates, but allows highly-efficient triggering at much lower masses than typically possible when triggering directly on the resonance decay products. The search is performed in a range of dijet masses from 250 GeV to 1.5 TeV.

A complementary search, recording only partial event data in order to efficiently trigger on dijet events without requiring an ISR object, has been performed in parallel and also focuses on light resonances with dijet masses of 425 GeV–1.05 TeV. It is described separately in Ref. [15]. Another complementary search for resonances with masses of 600 GeV and above decaying to heavy-flavour jets is described in Ref. [16].

q

¯

q q

¯ q X

γ

Figure 1: Diagram for the production of a new resonance X recoiling against an ISR photon.

2 ATLAS detector

The ATLAS experiment [17] at the LHC is a multi-purpose particle detector with a forward-backward symmetric cylindrical geometry with layers of tracking, calorimeter, and muon detectors over nearly the entire solid angle around the pp collision point. The directions1 and energies of high transverse momentum ( p

) particles are measured using silicon tracking detectors and straw tubes detecting transition radiation, finely segmented hadronic and electromagnetic calorimeters, and a muon spectrometer. The inner tracking detector (ID) covers the pseudorapidity range |η| < 2 . 5. It consists of silicon pixel, silicon micro- strip, and transition radiation tracking (TRT) detectors. Lead/liquid-argon (LAr) sampling calorimeters provide electromagnetic (EM) energy measurements with high granularity. A hadron (iron/scintillator- tile) calorimeter covers the central pseudorapidity range ( |η | < 1 . 7). The end-cap and forward regions are instrumented with LAr calorimeters for both EM and hadronic energy measurements up to |η | = 4 . 9. The first-level trigger is implemented in hardware and uses a subset of the detector information to reduce the accepted rate to 100 kHz. This hardware trigger is followed by a software-based trigger that reduces the rate of events recorded to 1 kHz.

3 Data

The data were collected in pp collisions at

√ s = 13 TeV during 2015. Collision events are recorded with a trigger requiring at least one photon candidate with an online p

threshold of 120 GeV passing "loose"

identification requirements based on the shower shapes in the EM calorimeter as well as on the energy leaking into the hadronic calorimeter from the EM calorimeter [18].

Only data satisfying beam, detector and data quality criteria are considered. The data used for the analysis correspond to an integrated luminosity of 3.2 fb

. The uncertainty in the integrated luminosity is ± 5%.

It is derived following a methodology similar to that detailed in Ref. [19] from a preliminary calibration of the luminosity scale using x – y beam-separation scans performed in August 2015.

4 Simulated samples

Samples of simulated events are used to characterise the hypothetical resonances as well as to study the kinematic distributions of background processes. However, these samples are not used to estim- ate the background contributions, except to validate the data-driven background estimate (described in Section 7).

Samples of backgrounds containing a photon with associated jets are simulated by Sherpa 2.1.1 [20], generated in several bins of photon p

from 35 GeV up to larger than 4 TeV. The matrix elements are calculated at leading-order (LO) with up to three partons for photon p

< 70 GeV or four partons for higher photon p

. These are merged with the Sherpa parton shower [21] using the ME+PS@LO

1

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

and the z -axis along the beam pipe. The x -axis points from the IP to the centre of the LHC ring, and the y -axis points

prescription [22]. The CT10 set of parton distribution functions (PDFs) [23] is used in conjunction with the dedicated parton shower tuning developed by the Sherpa authors.

As a benchmark signal, samples with a lepto-phobic Z

resonance are generated as in Refs. [10, 24]. This Z

has axial-vector couplings to quarks and to a fermion dark matter candidate. The coupling of the Z

to quarks, g

, is set to be universal in quark flavour. The mass of the dark matter fermion is set to a value much heavier than the Z

, such that the decay width to dark matter is zero. The total width Γ

is computed as the minimum width allowed given the coupling and mass m

; this width is 3 . 6–4 . 2% of the mass for m

= 250 GeV–1 . 5 TeV and g

= 0 . 3. Mixing of this benchmark model with the Standard Model Z boson is assumed to be negligible. A set of samples are generated with m

between 250 GeV and 1.5 TeV and with g

= 0 . 3 using the MadGraph5_aMC@NLO v2.2.3 [25] program with the NNPDF3.0 LO parton distribution function [26] in conjunction with PYTHIA 8.186 [27] and the A14 set of tuned parameters [28]. For efficient population of the kinematic phase space of the analysis, a photon with at least 100 GeV of transverse momentum is required in the generation phase.

5 Object Reconstruction

Photons are reconstructed from clusters of energy deposits in the electromagnetic calorimeter measured in projective towers. The photon energy is corrected by applying the energy scales measured with Z → e

e

decays. The trajectory of the photon is reconstructed using the longitudinal (shower depth) segmentation of the calorimeters and a constraint from the average collision point of the proton beams. Identification requirements are applied to reduce the contamination from π

or other neutral hadrons decaying to two photons. The photon identification is based on the profile of the energy deposits in the first and second layers of the electromagnetic calorimeter. Candidate photons are required to have p

> 130 GeV, to ensure the photon trigger is fully efficient. Photons used in the event selection must satisfy the "tight"

identification criteria defined in Ref. [29], be within |η | < 2 . 37 excluding the region 1 . 37 < |η | < 1 . 52, and be isolated as follows. The energy in the calorimeters in a cone of size ∆R = p

( ∆η )

+ ( ∆φ)

= 0 . 4 around the cluster barycentre excluding the energy associated with the photon cluster is required to be less than 2 . 45 GeV + 0 . 022 p

T

, where p

T

is the p

of the photon candidate. This cone energy is corrected for the leakage of the photon energy from the central core and for the effects of additional pp interactions occurring within the same bunch crossing (pile-up) [30].

Clusters without matching tracks are classified as unconverted photon candidates. A photon is considered as a converted photon candidate if it is matched to one track or a pair of tracks that pass a requirement on TRT hits [31]. Pairs of tracks must form a vertex in the ID which is consistent with originating from a massless particle. The position of this conversion vertex is used when computing the photon trajectory if tracks from the conversion have hits in the silicon detectors. A single-track photon candidate must include tracking measurements in the TRT and at least one measurement in the silicon detector after the innermost layer of the pixel detector.

The combination of the above requirements selects a sample of photons that is greater than 90% (80%) pure for unconverted (converted) candidates. The efficiency of the photon selection is roughly 95% for photons with p

> 130 GeV.

Jets are reconstructed using the anti- k

algorithm [32, 33] with a radius parameter R = 0 . 4 from clusters

of energy deposits in the calorimeters[34]. A correction used to calibrate jet energy measurements to the

scale of the constituent particles of the jet [35, 36] is then applied. Jets with 25 GeV < p

< 60 GeV and

|η | < 2 . 4 are required to originate from the primary interaction as determined by a jet vertex tagger [37].

The energies of selected jets are corrected for contributions from pile-up interactions [35].

Quality requirements are applied to photon candidates to reject events containing photons arising from instrumental problems or from non-collision background [31]. In addition, quality requirements are applied to remove events containing jets mis-construed from detector noise and out-of-time energy deposits in the calorimeter from cosmic rays or other non-collision sources [38]. Events are required to have a reconstructed primary vertex, defined as the highest sum p

T

vertex with at least two tracks.

6 Event Selection

The search uses a sample of events which contain at least one photon with p

> 130 GeV as well as at least two jets. Jets are required to have p

> 25 GeV and |η| < 2 . 8. In addition, half the difference in rapidity y of the leading two jets,

y

= y

− y

2

is required to satisfy | y

| < 0 . 8 to reduce the backgrounds from processes that yield an ISR photon and a non-resonant jet pair from QCD processes, which tend to have higher-rapidity separation. To suppress such jets surviving the photon isolation criterion, and to further suppress background from fragmentation photons where the photon is inside or near a jet, the selected photon is required to be separated from the closest jet by ∆R > 0 . 85. Figure 2 shows the m

distribution of events satisfying these criteria.

7 Background Estimation

To estimate the background contribution, a parametric function,

f ( z) = p

( 1 − z)

z

(1) where z ≡ m

/ √

s , is fit to the m

distribution shown in Figure 2 to obtain the parameters p

. The fit range is 203 GeV–1.493 TeV. The dijet searches of the CDF, CMS, and ATLAS experiments, such as those described in Refs. [1, 4, 5, 8, 10, 39], have found that expressions similar to Equation 1 successfully model dijet mass distributions observed at

√ s = 13 TeV and lower collision energies. This ansatz also describes the Sherpa simulation of Standard Model processes that yield a jet pair and ISR photon, described above.

A log-likelihood-ratio statistic employing Wilks’s theorem [40] was used to determine if the background

estimation would be significantly improved by an additional degree of freedom. With the current dataset,

Equation 1 was found to be sufficient, using the same criteria as Ref. [10]. The lower bound of the fit

range, 203 GeV, was chosen high enough to exclude kinematic bias from the p

requirement of the photon

trigger. The fit is performed on the binned data, with bins of widths varying proportionate to the detector

m

resolution. The resolution varies from approximately 6% at m

= 250 GeV to 2.7% at m

= 1 . 5 TeV.

[TeV]

Reconstructed m

10

×

3 4 × 10

10

Events

10 10

10

10

|y*| < 0.8

Fit Range: 203 - 1493 GeV -value = 0.89

p

× 50 σ = 0.30), Z' (g

[GeV]

m jj

300 400 500 1000

Significance

− 2 0 2

ATLAS Preliminary

=13 TeV, 3.2 fb

s

Data

Background fit BumpHunter interval

= 300 GeV Z', m

Figure 2: The reconstructed dijet mass distribution (filled points) for events containing a photon with p

> 130 GeV and two jets with p

> 25 GeV and | y

| < 0 . 8 and satisfying the other selection criteria described in the text.

The solid line depicts the fit to Equation 1. Predictions for a lepto-phobic Z

of mass 300 GeV and coupling g

= 0 . 3 are shown above the fit, normalized to 50 times the predicted cross-section to render it visible. The vertical lines indicate the most discrepant interval identified by the BumpHunter algorithm. The lower panel shows the bin-by-bin significances of the data–fit differences, considering only statistical uncertainties.

8 Results

Figure 2 shows the result of the fit of the background model, Equation 1, to the data. The model agrees with the observed data with a p -value of 0.73, using a Poisson likelihood test statistic. The lower panel of the figure shows the significances of bin-by-bin differences between the data and the model. These Gaussian significances are calculated from the Poisson probability, considering only statistical uncertainties. The data has been overlaid with an example of the signal described in Section 4.

The statistical significance of any localised excess in the m

distribution is quantified using the Bump-

Hunter algorithm [41, 42]. The algorithm compares the binned m

distribution of the data to the fitted

background estimate, considering contiguous mass intervals in all possible locations, from intervals of

width of two bins to widths of half of the distribution. For each interval in the scan, it computes the

significance of any excess found. The algorithm identifies the interval 834 GeV–917 GeV, indicated by the

two vertical lines in Figure 2, as the most discrepant interval. The statistical significance of this outcome is

evaluated using the ensemble of possible outcomes across all intervals scanned by applying the algorithm

to many pseudo-data samples drawn randomly from the background fit. Without including systematic

uncertainties, the probability that fluctuations of the background model would produce an excess at least

as significant as the one observed in the data, anywhere in the distribution, is 0.89. Thus, there is no evidence of a localised contribution to the mass distribution from new phenomena.

A Bayesian method [5] is applied to the m

data and simulation of signals at a series of discrete masses to set 95% credibility-level (CL) upper limits on the cross-section times acceptance for the signals described above. The limits are obtained for a discrete set of points in the g

– m

plane. The method uses a constant prior for the signal cross-section and Gaussian priors for nuisance parameters corresponding to systematic uncertainties. The expected limits are calculated using pseudo-experiments generated from the maximum-likelihood values for parameters of the background-only model in Equation 1 using the systematic uncertainties in both the signal and background models. The limits on the coupling g

are obtained from the cross-section limits on nearby discrete model points using the fact that the signal cross-section scales with g

. The resulting limits are shown in Figure 3.

A similar procedure is used for a model in which the signal is assumed to have a Gaussian distribution with one of several widths, ranging from the detector mass resolution (for an intrinsically narrow resonance) to a width of 10% of the mean of the signal mass distribution; see Figure 4. This places 95% CL upper limits on the cross-section times acceptance (visible cross-section) for new processes producing a photon and a resonance jet pair. As the width increases, the expected signal contribution is distributed across more bins. Therefore wider signals are affected less than narrower signals by statistical fluctuations of the data in a single bin and have a reduced sensitivity compared to narrower signals.

In each set of limits, systematic uncertainties used for the signal samples include uncertainties on the acceptance due to uncertainties on the PDFs (1%), the jet energy resolution (2%), and the photon identification, energy scale and resolution (3%). The uncertainties on the jet energy scale are obtained, for the Z

signals, by varying four nuisance parameters accounting for contributions to the total jet energy scale uncertainty [43, 44]. For the Gaussian-shaped signals, the jet energy scale uncertainties are ≈ 1%, the relative change in mean mass observed in the Z

signals.

The uncertainty on the background prediction arising from statistical uncertainties on the values of

the parameters in Equation 1 is evaluated by fitting the parameters to pseudo-data drawn via Poisson

fluctuations around the nominal background model. The uncertainty in the prediction in each m

bin is

taken to be the standard deviation of the function value for all pseudo-experiments in that bin. To estimate

the uncertainty on the background prediction due to the choice of the background parameterization, a

parameterization with one additional degree of freedom, z

, is compared to the nominal background

model. The difference is taken as an uncertainty. The prediction of the m

distribution does not involve

simulated collisions and thus is not affected by theoretical or experimental uncertainties. The resulting

total background uncertainty is 2% or less for m

< 1 TeV.

[GeV]

m

300 400 500 600 700 800 900

q

g

0.05 0.1 0.15

0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55

>130 GeV)

γ

(P

γ Dijet +

= 13 TeV, 3.2 fb

s

Preliminary ATLAS

obs. limit exp. limit

Figure 3: The 95% CL upper limits obtained on coupling g

as a function of the resonance mass m

for the

lepto-phobic Z

model, as described in the text. Coupling values above the solid curve are excluded. The expected

limit is indicated by a dotted curve. The limits shown are interpolated between limits derived from simulation

at discrete points in the parameter space. The small markers indicate the simulated points. Ref. [15] provides

additional constraints that do not appear on this plot. For 450 GeV < m

< 950 GeV, it places an upper limit on

g

from 0.08–0.13, depending on m

.

[GeV]

m G

500 1000

BR [pb] × A × σ

− 3

10

− 2

10

− 1

10 1 10

ATLAS Preliminary

=13 TeV, 3.2 fb

s

> 130 GeV)

γ

(P

γ Dijet +

|y*| < 0.8

= 0.10 /m

σ

= 0.07 /m

σ

= Res.

/m

σ

Figure 4: The 95% CL upper limits obtained on cross-section times acceptance times branching ratio to a photon

and two jets, σ × A × BR, corrected for experimental inefficiencies, for a hypothetical signal with a cross-section

σ that produces a Gaussian contribution to the observed m

distribution, as a function of the mean mass of the

Gaussian distribution, m

. Limits are obtained for three different widths, from a width equal to the detector mass

resolution (“Res.”) to 10% of the mean of the Gaussian mass distribution. Signals with the given reconstructed

width are excluded for visible cross-sections above the corresponding curve.

9 Conclusion

No evidence of phenomena beyond the Standard Model was uncovered in this search using 3.2 fb

of proton-proton collisions at

√ s = 13 TeV recorded during 2015 by the ATLAS detector at the LHC. The dijet invariant mass distribution of selected events exhibits no significant local excesses atop a data-derived estimate of the smoothly falling distribution predicted by the Standard Model. The analysis excludes at 95% CL lepto-phobic axial-vector Z

bosons for g

above 0.26 at mass m

= 250 GeV and g

above 0.43 at m

= 950 GeV. It also sets 95% CL upper limits on the visible cross-section for new processes that would produce a photon and a Gaussian contribution to the dijet mass distribution. The limits on the visible cross-section range from approximately 100 fb at a mean mass of 250 GeV to 10–20 fb at 1.2 TeV.

These results extend the limits on light dijet resonances obtained at lower centre-of-mass energies.

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[GeV]

m

300 400 500 600 700 800 900

∈ × A

0 0.05 0.1 0.15

0.2 0.25 0.3 0.35 0.4 0.45 0.5

0.1 0.2 0.3

0.4

= 13 TeV s

Simulation,

Preliminary ATLAS

Figure 5: A summary of the signal acceptance (ratio of generated events passing kinematic selection to generated events with photon p

> 100 GeV) times efficiency for the various signal mass points and couplings considered.

The four sets of points correspond to different choices of coupling value g

.

Appendix: Additional Information for Re-interpretation

This section contains additional information for the convenience of reinterpreting these results in the context of models not considered here. Integrated data and Monte Carlo (MC) yields after each stage of the selection are presented in Table 1. Counts of the observed data and background predictions in each bin, taken from Figure 2 are given in Tables 2 and 3. The binning of the m

distribution is also defined in these tables. Table 7 provides the numeric values of the limits on Gaussian contributions from Figure 4.

Selection Data Sherpa γ + j j MC m

= 300 GeV m

= 500 GeV

Pre-selection 1972534 1702760 1627 661

Photon p

> 130 GeV 783004 873246 1252 538

| y

| < 0 . 8 521380 559731 937 391

∆R > 0 . 85 492378 525987 880 355

m

> 200 GeV 96550 96568 642 312

Table 1: Event yields at each stage of the selection, for the observed data, the Sherpa simulation of γ + j j backgrounds (not used for the actual background prediction), and two samples of the Z

signals with g

= 0 . 3. The pre-selection consists of the trigger, event quality, and primary vertex requirements, as well as requiring at least two jets with

|η | < 2 . 8 and p

> 25 GeV and one tight isolated photon with p

> 10 GeV.

A summary of the acceptances times efficiencies, A × , is given in Figure 5 and Tables 4–6 for the various signals considered. Acceptance is defined as the fraction of generated events containing a photon

p >

m

[GeV] N(obs) N(exp), nominal N(exp), alternate

203–216 10832 10873 10856

216–229 9473 9326 9324

229–243 8429 8612 8618

243–257 7374 7383 7391

257–272 6777 6781 6790

272–287 5982 5813 5820

287–303 5307 5317 5322

303–319 4487 4559 4562

319–335 3970 3929 3930

335–352 3638 3598 3597

352–369 3139 3101 3099

369–387 2750 2831 2829

387–405 2392 2442 2438

405–424 2254 2223 2220

424–443 1936 1919 1915

443–462 1642 1663 1659

462–482 1520 1517 1514

482–502 1257 1315 1313

502–523 1172 1198 1196

523–544 1064 1039 1037

544–566 952 944 943

566–588 815 820 819

588–611 765 744 744

611–634 671 647 647

634–657 592 564 564

657–681 528 513 513

681–705 428 447 448

705–730 411 406 407

730–755 350 355 356

755–781 312 322 323

781–807 269 281 282

807–834 245 255 256

834–861 234 223 224

861–889 218 202 203

889–917 195 177 177

917–946 138 160 161

946–976 139 144 145

976–1006 139 126 127

Table 2: Data and integrated background counts for the combined event selection, including counts for data, the

nominal fit function and the alternate fit function with one additional degree of freedom. Table 3 contains this

information for higher masses.

m

[GeV] N(obs) N(exp), nominal N(exp), alternate

1006–1037 113 114 114

1037–1068 86 100 100

1068–1100 105 90 90

1100–1133 86 81 81

1133–1166 60 71 71

1166–1200 67 63 63

1200–1234 56 55 55

1234–1269 50 50 50

1269–1305 37 45 44

1305–1341 36 39 39

1341–1378 41 35 35

1378–1416 31 31 31

1416–1454 32 27 27

1454–1493 24 24 24

Table 3: Data and integrated background counts for the combined event selection, including counts for data, the nominal fit function and the alternate fit function with one additional degree of freedom. Table 2 contains this information for lower masses.

XX XX

XX XX XX X g

m

[GeV]

250 300 350 400 450 500 550 750 950

0.1 0.23 0.29 0.33 0.34

0.2 0.22 0.30 0.33 0.35 0.38

0.3 0.22 0.27 0.30 0.31 0.33 0.34 0.34 0.36 0.38

0.4 0.37

Table 4: A summary of the signal acceptance (ratio of generated events passing kinematic selection to generated events with photon p

> 100 GeV) for the various signal mass points and couplings considered.

XX XX

XX XX XX X g

m

[GeV]

250 300 350 400 450 500 550 750 950

0.1 0.82 0.84 0.82 0.83

0.2 0.82 0.83 0.83 0.80 0.80

0.3 0.83 0.84 0.82 0.82 0.82 0.82 0.83 0.81 0.80

0.4 0.80

Table 5: A summary of the signal efficiency with respected to events passing kinematic selection for the various signal mass points and couplings considered.

XX XX

XX XX XX X g

m

[GeV]

250 300 350 400 450 500 550 750 950

0.1 0.19 0.24 0.27 0.28

0.2 0.18 0.25 0.27 0.28 0.30

0.3 0.18 0.22 0.25 0.26 0.28 0.28 0.28 0.30 0.30

0.4 0.29

m

Limit [pb] Limit [pb] Limit [pb]

[GeV] ( σ / m = res.) ( σ / m = 7%.) ( σ / m = 10%)

250 0.085 0.13 -

300 0.092 0.15 0.22

350 0.11 0.12 0.13

400 0.055 0.076 0.095

450 0.057 0.068 0.075

500 0.033 0.052 0.07

550 0.054 0.075 0.1

600 0.062 0.1 0.13

650 0.062 0.086 0.099

700 0.028 0.044 0.052

750 0.022 0.03 0.04

800 0.018 0.03 0.039

900 0.029 0.032 0.036

1000 0.017 0.024 0.029

1200 0.011 0.016 0.021

Table 7: The 95% CL upper limits on cross-section times acceptance times branching ratio to a photon and two jets,

σ × A × BR, for a hypothetical signal with a cross-section σ that produces a Gaussian contribution to the observed

m

distribution, as a function of the mean mass of the Gaussian distribution, m

. Limits are obtained for three

different widths, from a width equal to the detector mass resolution (“res.”) to 10% of the mean of the Gaussian

mass distribution.

[TeV]

Reconstructed m

10

×

3 4 × 10

10

Events

10 10

10

10

|y*| < 0.8

Fit Range: 203 - 1493 GeV -value = 0.89

p

[GeV]

m jj

300 400 500 1000

Significance

− 2 0 2

ATLAS Preliminary

=13 TeV, 3.2 fb

s

Data

Background fit BumpHunter interval

Figure 6: The reconstructed dijet mass distribution (filled points) for events containing a photon with p

> 130 GeV and two jets with p

> 25 GeV and |y

| < 0 . 8 and satisfying the other selection criteria described in the text. This version of Figure 2 omits the overlaid signal. The solid line depicts the fit to Equation 1. The vertical lines indicate the most discrepant interval identified by the BumpHunter algorithm. The lower panel shows the bin-by-bin significances of the data–fit differences, considering only statistical uncertainties.

Appendix: Additional Plots

This appendix contains figures with additional detail on the analysis results, intended for conference

speakers. Figure 6 is an alternate version of Figure 2 where no signal has been overlaid. Figures 7 and

8 summarize the results of the BumpHunter algorithm for all mass intervals considered. Figures 9 and

10 illustrate the relative background uncertainty as function of dijet mass. Figure 11 shows the limits

on visible cross-section of the lepto-phobic axial-vector Z

for discrete values of coupling g

. Figure 12

shows the limits on the coupling g

of the Z

model as a function of the resonance mass m

, the equivalent

of Figure 3 while directly comparing to the limits obtained in Ref. [15].

[GeV]

m jj

300 400 1000

p-value

− 2

× 10 4

− 2

× 10 5

− 1

10

− 1

× 10 2

− 1

× 10 3

− 1

× 10 4

− 1

× 10 5

ATLAS Preliminary

=13 TeV, 3.2 fb

s

Figure 7: Local p -value for all intervals examined by BumpHunter. For each interval, a line is drawn with horizontal

extent indicating the mass range covered and vertical position indicating the local p -value of the interval.

BumpHunter test statistic

2 4 6 8 10 12 14 16

Pseudo-experiments

1 10 10 2

10 3

Pseudo-experiments Value in Data

ATLAS Preliminary

=13 TeV, 3.2 fb

s

-value = 0.89 p

Figure 8: Distribution of the BumpHunter test statistic [42], the negative logarithm of the minimum p -value found,

for an ensemble of background-only pseudo-experiments drawn from the nominal background prediction. The

statistic for the observed m

distribution is indicated by the arrow.

[GeV]

m

10

×

3 4 × 10

10

Events

10 10

10

10

[GeV]

m jj

300 400 500 1000

Rel. Uncert. ^{0.1 −}

0 0.1

|y*| < 0.8

Fit Range: 203 - 1493 GeV -value = 0.89

p

Data Fit

Statistical uncertainty on fit Function choice

=13 TeV, 3.2 fb

s

ATLAS Preliminary

Figure 9: The reconstructed dijet mass distribution (filled points) for events containing a photon with p

> 130 GeV

and two jets with p

> 25 GeV and |y

| < 0 . 8 and satisfying the other selection criteria described in the text. The

solid line drawn through the points indicates the fit to Equation 1. The dashed curve shows the relative uncertainty

on the background prediction due to the statistical uncertainty on the fit parameters. The dotted curve shows the

relative uncertainty due to the choice of the background parameterization. These are more easily visible in the lower

panel.

10

×

3 4 × 10

10

Events

10 10

10

10

[GeV]

mjj

300 400 500 600 700 800 900 1000

Significance

−2 0 2

[GeV]

m

300 400 500 600 1000

Significance

−2 0 2

Nominal

Best Fit

ATLAS Preliminary

=13 TeV, 3.2 fb

s

Data Nominal fit Best fit

Figure 10: The reconstructed dijet mass distribution (filled points) for events containing a photon with p

> 130 GeV and two jets with p

> 25 GeV and | y

| < 0 . 8 and satisfying the other selection criteria described in the text.

The dark solid line depicts the fit to Equation 1 used for BumpHunter. The lighter (cyan) solid line depicts the best fit to a superposition of Equation 1 and an additional Z

signal with mass of 300 GeV and g

= 0 . 3 and arbitrary normalization, along with the full set of systematic uncertainties considered when computing the limits.

The fit has determined the normalization of the signal and the values of the nuisance parameters representing the

systematic uncertainties. The middle panel shows the bin-by-bin significances of the data–fit differences for the

nominal fit, considering only statistical uncertainties. The lower panel shows the bin-by-bin significances of the

data–fit differences for the best fit, considering only statistical uncertainties.

[GeV]

m

200 300 400 500 600

BR [pb] × A × σ

−3

10

−2

10

−1

10 1

ATLAS Preliminary

= 0.10) Z' (gq

Observed 95% CL upper limit Expected 95% CL upper limit 68% and 95% bands

=13 TeV, 3.2 fb-1

s

|y*| < 0.8

[GeV]

m

200 400 600 800

BR [pb] × A × σ

−3

10

−2

10

−1

10 1

ATLAS Preliminary

= 0.20) Z' (gq

Observed 95% CL upper limit Expected 95% CL upper limit 68% and 95% bands

=13 TeV, 3.2 fb-1

s

|y*| < 0.8

[GeV]

m

200 400 600 800 1000

BR [pb] × A × σ

−3

10

−2

10

−1

10 1

ATLAS Preliminary

= 0.30) Z' (gq

Observed 95% CL upper limit Expected 95% CL upper limit 68% and 95% bands

=13 TeV, 3.2 fb-1

s

|y*| < 0.8

Figure 11: The 95% CL upper limits obtained on the visible cross-section, corrected for experimental inefficiencies,

as a function of the resonance mass m

for the lepto-phobic Z

model with three choices of coupling values, g

, as

discussed in the main text. The black points and curves indicate the observed limit. The dotted curves (and colored

bands) indicate the limit one would expect to obtain when the observed data agree with the background prediction

(or fluctuate to a value one or two times higher or lower than the uncertainty on the prediction). The blue dashed

curves indicate the visible cross-section predicted in the model for each choice of coupling values.

[GeV]

m

200 300 400 500 600 700 800 900 1000

q

g

0.05 0.1 0.15

0.2 0.25 0.3 0.35 0.4 0.45

= 13 TeV; 3.2-3.4 fb

s

Preliminary ATLAS

obs. limit, Dijet + γ exp. limit, Dijet + γ obs. limit, TLA exp. limit, TLA

|y*| < 0.8

|y*| < 0.3 |y*| < 0.6

Figure 12: The 95% CL upper limits obtained from the present search (solid red curve) and the Trigger-Level

Analysis (TLA) of Ref. [15] (solid black curve) on coupling g

as a function of the resonance mass m

for the

lepto-phobic Z

model, as described in the text. Coupling values above the solid curves are excluded by each

analysis. The expected limit is indicated by a dotted version of each curve. The limits shown are interpolated

between limits derived from simulation at discrete points in the parameter space. The limits from Ref. [15] are

obtained with one of two selections, | y

| < 0 . 3 and | y

| < 0 . 6, each addressing a separate range of masses m

.