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CMS-EXO-17-024 ; CERN-EP-2018-204
Search for low-mass resonances decaying into bottom quark-antiquark pairs in proton-proton collisions at $\sqrt{s} = $ 13 TeV
Phys. Rev. D 99 (2019) 012005
Abstract: A search for narrow, low-mass, scalar and pseudoscalar resonances decaying to bottom quark-antiquark pairs is presented. The search is based on events recorded in $\sqrt{s} = $ 13 TeV proton-proton collisions with the CMS detector at the LHC, collected in 2016, and corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The search selects events in which the resonance would be produced with high transverse momentum because of the presence of initial- or final-state radiation. In such events, the decay products of the resonance would be reconstructed as a single large-radius jet with high mass and two-prong substructure. A potential signal would be identified as a narrow excess in the jet invariant mass spectrum. No evidence for such a resonance is observed within the mass range from 50 to 350 GeV, and upper limits at 95% confidence level are set on the product of the cross section and branching fraction to a bottom quark-antiquark pair. These constitute the first constraints from the LHC on exotic bottom quark-antiquark resonances with masses below 325 GeV.
Figures & Tables Summary References CMS Publications
Figures

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Figure 1:
One-loop Feynman diagrams of processes exchanging a scalar $\phi $ (left) or pseudoscalar A (right) mediator, leading to a boosted double-b jet signature.

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Figure 1-a:
One-loop Feynman diagram of the process exchanging a scalar $\phi $ mediator, leading to a boosted double-b jet signature.

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Figure 1-b:
One-loop Feynman diagram of the process exchanging a pseudoscalar A mediator, leading to a boosted double-b jet signature.

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Figure 2:
The fitted pass-fail ratio $ {R_{\mathrm {p}/\mathrm {f}}} $ as a function of $ {p_{\mathrm {T}}} $ and $\rho $ for the AK8 selection (left) and the CA15 selection (right).

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Figure 2-a:
The fitted pass-fail ratio $ {R_{\mathrm {p}/\mathrm {f}}} $ as a function of $ {p_{\mathrm {T}}} $ and $\rho $ for the AK8 selection.

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Figure 2-b:
The fitted pass-fail ratio $ {R_{\mathrm {p}/\mathrm {f}}} $ as a function of $ {p_{\mathrm {T}}} $ and $\rho $ for the CA15 selection.

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Figure 3:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the AK8 selection for the failing (left) and passing (right) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The features at 166, 180, 201, 215, and 250 GeV in the $ {m_{\mathrm {SD}}} $ distribution are due to the $\rho $ boundaries, which define different $ {m_{\mathrm {SD}}} $ ranges for each $ {p_{\mathrm {T}}} $ category. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 3-a:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the AK8 selection for the failing region, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The features at 166, 180, 201, 215, and 250 GeV in the $ {m_{\mathrm {SD}}} $ distribution are due to the $\rho $ boundaries, which define different $ {m_{\mathrm {SD}}} $ ranges for each $ {p_{\mathrm {T}}} $ category. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 3-b:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the AK8 selection for the passing region, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The features at 166, 180, 201, 215, and 250 GeV in the $ {m_{\mathrm {SD}}} $ distribution are due to the $\rho $ boundaries, which define different $ {m_{\mathrm {SD}}} $ ranges for each $ {p_{\mathrm {T}}} $ category. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 4:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the CA15 selection for the failing (left) and passing (right) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The features at 285, 313, 341, 376, and 432 GeV in the $ {m_{\mathrm {SD}}} $ distribution are due to the $\rho $ boundaries, which define different $ {m_{\mathrm {SD}}} $ ranges for each $ {p_{\mathrm {T}}} $ category. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 4-a:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the CA15 selection for the failing regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The features at 285, 313, 341, 376, and 432 GeV in the $ {m_{\mathrm {SD}}} $ distribution are due to the $\rho $ boundaries, which define different $ {m_{\mathrm {SD}}} $ ranges for each $ {p_{\mathrm {T}}} $ category. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 4-b:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the CA15 selection for the passing regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The features at 285, 313, 341, 376, and 432 GeV in the $ {m_{\mathrm {SD}}} $ distribution are due to the $\rho $ boundaries, which define different $ {m_{\mathrm {SD}}} $ ranges for each $ {p_{\mathrm {T}}} $ category. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 5:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in each $ {p_{\mathrm {T}}} $ category for the AK8 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 5-a:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 400 $ < {p_{\mathrm {T}}} < $ 450 GeV category for the AK8 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 5-b:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 400 $ < {p_{\mathrm {T}}} < $ 450 GeV category for the AK8 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 5-c:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 450 $ < {p_{\mathrm {T}}} < $ 500 GeV category for the AK8 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 5-d:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 550 $ < {p_{\mathrm {T}}} < $ 600 GeV category for the AK8 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 5-e:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 675 $ < {p_{\mathrm {T}}} < $ 800 GeV category for the AK8 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 5-f:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 800 $ < {p_{\mathrm {T}}} < $ 1000 GeV category for the AK8 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 140 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 6:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in each $ {p_{\mathrm {T}}} $ category for the CA15 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 6-a:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 500 $ < {p_{\mathrm {T}}} < $ 550 GeV category for the CA15 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

png pdf
Figure 6-b:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 550 $ < {p_{\mathrm {T}}} < $ 600 GeV category for the CA15 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

png pdf
Figure 6-c:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 600 $ < {p_{\mathrm {T}}} < $ 675 GeV category for the CA15 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

png pdf
Figure 6-d:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 675 $ < {p_{\mathrm {T}}} < $ 800 GeV category for the CA15 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

png pdf
Figure 6-e:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions in the 800 $ < {p_{\mathrm {T}}} < $ 1000 GeV category for the CA15 selection in the passing regions. The fit is performed under the background-only hypothesis. A hypothetical $ {\mathrm {A}}({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal at a mass of 260 GeV is also indicated. The shaded blue band shows the systematic uncertainty in the total background prediction. The bottom panel shows the difference between the data and the nonresonant background prediction, divided by the statistical uncertainty in the data.

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Figure 7:
Upper limits at 95% CL on the product of the $\phi $ production cross section and the branching fraction to $ {{\mathrm {b}} {\overline {\mathrm {b}}}} $ (left) and on $ {g_{{\mathrm {q}}\phi}} $ (right), as a function of the resonance mass $m_{\phi}$. The blue dash-dotted line indicates the theoretical scalar production cross section assuming $ {g_{{\mathrm {q}}\phi}} = $ 1 as a chosen benchmark [5]. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections.

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Figure 7-a:
Upper limits at 95% CL on the product of the $\phi $ production cross section and the branching fraction to $ {{\mathrm {b}} {\overline {\mathrm {b}}}} $, as a function of the resonance mass $m_{\phi}$. The blue dash-dotted line indicates the theoretical scalar production cross section assuming $ {g_{{\mathrm {q}}\phi}} = $ 1 as a chosen benchmark [5]. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections.

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Figure 7-b:
Upper limits at 95% CL on $ {g_{{\mathrm {q}}\phi}} $, as a function of the resonance mass $m_{\phi}$. The blue dash-dotted line indicates the theoretical scalar production cross section assuming $ {g_{{\mathrm {q}}\phi}} = $ 1 as a chosen benchmark [5]. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections.

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Figure 8:
Upper limits at 95% CL on the product of the A production cross section and the branching fraction to $ {{\mathrm {b}} {\overline {\mathrm {b}}}} $ (left) and on $ {g_{{\mathrm {q}} {\mathrm {A}}}} $ (right), as a function of the resonance mass $m_{{\mathrm {A}}}$. The blue dash-dotted line indicates the theoretical pseudoscalar production cross section assuming $ {g_{{\mathrm {q}} {\mathrm {A}}}} = $ 1 as a chosen benchmark [5]. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections.

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Figure 8-a:
Upper limits at 95% CL on the product of the A production cross section and the branching fraction to $ {{\mathrm {b}} {\overline {\mathrm {b}}}} $, as a function of the resonance mass $m_{{\mathrm {A}}}$. The blue dash-dotted line indicates the theoretical pseudoscalar production cross section assuming $ {g_{{\mathrm {q}} {\mathrm {A}}}} = $ 1 as a chosen benchmark [5]. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections.

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Figure 8-b:
Upper limits at 95% CL on $ {g_{{\mathrm {q}} {\mathrm {A}}}} $, as a function of the resonance mass $m_{{\mathrm {A}}}$. The blue dash-dotted line indicates the theoretical pseudoscalar production cross section assuming $ {g_{{\mathrm {q}} {\mathrm {A}}}} = $ 1 as a chosen benchmark [5]. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections.
Tables

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Table 1:
The selection efficiencies in percent for simulated $\phi ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal events with parton-level $ {H_{\mathrm {T}}} > $ 400 GeV, at different stages of the event selection, shown for different mass hypotheses and for AK8 and CA15 jets. The statistical uncertainties due to the simulated sample size are also shown.

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Table 2:
Summary of the systematic uncertainties affecting the signal, W and Z+jets processes. Instances where the uncertainty does not apply are indicated by a dash. The reported percentages reflect a one standard deviation effect on the product of acceptance and efficiency of each process. For the uncertainties related to the jet mass scale and resolution, which affect the mass distribution shapes, the reported percentages reflect a one standard deviation effect on the nominal jet mass.
Summary
A search for a low-mass resonance decaying into a bottom quark-antiquark pair and reconstructed as a single wide jet has been presented, using a data set of proton-proton collisions at $\sqrt{s} = $ 13 TeV corresponding to an integrated luminosity of 35.9 fb$^{-1}$. Dedicated substructure and double-b tagging techniques were employed to identify jets containing a resonance candidate over a smoothly falling soft-drop jet mass distribution in data. No significant excess above the standard model prediction was observed for signal masses between 50-350 GeV. Upper limits at 95% confidence level are set on the product of the resonance production cross section and the branching fraction to bottom quark-antiquark pairs, as well as on the coupling ${g_{\mathrm{q}\phi}} $ (${g_{\mathrm{q}\mathrm{A}}} $) of a scalar (pseudoscalar) boson decaying to quarks. The search excludes the production through gluon fusion of a scalar (pseudoscalar) decaying to $\mathrm{b\bar{b}}$ with a product of the cross section and branching fraction as low as 79 (86) pb at a resonance mass of 175 GeV, corresponding to an upper limit on ${g_{\mathrm{q}\phi}} $ (${g_{\mathrm{q}\mathrm{A}}} $) of 3.9 (2.5). This constitutes the first LHC constraint on exotic bottom quark-antiquark resonances below 325 GeV.
References
1 Abercrombie et al. Dark matter benchmark models for early LHC Run-2 searches: Report of the ATLAS/CMS dark matter forum 1507.00966
2 M. R. Buckley, D. Feld, and D. Goncalves Scalar simplified models for dark matter PRD 91 (2015) 015017 1410.6497
3 P. Harris, V. V. Khoze, M. Spannowsky, and C. Williams Constraining dark sectors at colliders: Beyond the effective theory approach PRD 91 (2015) 055009 1411.0535
4 U. Haisch and E. Re Simplified dark matter top-quark interactions at the LHC JHEP 06 (2015) 078 1503.00691
5 G. Busoni et al. Recommendations on presenting LHC searches for missing transverse energy signals using simplified $ s $-channel models of dark matter 1603.04156
6 CMS Collaboration Search for narrow resonances in dijet final states at $ \sqrt{s}= $ 8 TeV with the novel CMS technique of data scouting PRL 117 (2016) 031802 CMS-EXO-14-005
1604.08907
7 CMS Collaboration Search for dijet resonances in proton-proton collisions at $ \sqrt{s} = $ 13 TeV and constraints on dark matter and other models PLB 769 (2017) 520 CMS-EXO-16-032
1611.03568
8 CMS Collaboration Search for narrow and broad dijet resonances in proton-proton collisions at $ \sqrt{s}= $ 13 TeV and constraints on dark matter mediators and other new particles JHEP 08 (2018) 130 CMS-EXO-16-056
1806.00843
9 ATLAS Collaboration Search for low-mass dijet resonances using trigger-level jets with the ATLAS detector in $ pp $ collisions at $ \sqrt{s}= $ 13 TeV PRL 121 (2018) 081801 1804.03496
10 CMS Collaboration Search for narrow resonances in the b-tagged dijet mass spectrum in proton-proton collisions at $ \sqrt{s} = $ 8 TeV PRL 120 (2018) 201801 CMS-EXO-16-057
1802.06149
11 ATLAS Collaboration Search for resonances in the mass distribution of jet pairs with one or two jets identified as $ b $-jets in proton-proton collisions at $ \sqrt{s}= $ 13 TeV with the ATLAS detector PRD 98 (2018) 032016 1805.09299
12 CMS Collaboration Search for low mass vector resonances decaying to quark-antiquark pairs in proton-proton collisions at $ \sqrt{s}=13\text{}\text{}\mathrm{TeV} $ PRL 119 (2017) 111802 CMS-EXO-16-030
1705.10532
13 CMS Collaboration Search for low mass vector resonances decaying into quark-antiquark pairs in proton-proton collisions at $ \sqrt{s}=13\text{}\text{}\mathrm{TeV} $ JHEP 01 (2018) 097 CMS-EXO-17-001
1710.00159
14 ATLAS Collaboration Search for light resonances decaying to boosted quark pairs and produced in association with a photon or a jet in proton-proton collisions at $ \sqrt{s}= $ 13 TeV with the ATLAS detector Submitted to PLB 1801.08769
15 CMS Collaboration Inclusive search for a highly boosted Higgs boson decaying to a bottom quark-antiquark pair PRL 120 (2018) 071802 CMS-HIG-17-010
1709.05543
16 D. Liu, J. Liu, C. E. M. Wagner, and X.-P. Wang Bottom-quark forward-backward asymmetry, dark matter and the LHC PRD 97 (2018) 055021 1712.05802
17 M. Cacciari, G. P. Salam, and G. Soyez The anti-$ {k_{\mathrm{T}}} $ jet clustering algorithm JHEP 04 (2008) 063 0802.1189
18 Y. L. Dokshitzer, G. D. Leder, S. Moretti, and B. R. Webber Better jet clustering algorithms JHEP 08 (1997) 001 hep-ph/9707323
19 M. Wobisch and T. Wengler Hadronization corrections to jet cross-sections in deep inelastic scattering in Proceedings of the Workshop on Monte Carlo Generators for HERA Physics, Hamburg, Germany, p. 270 1998 hep-ph/9907280
20 J. M. Butterworth, A. R. Davison, M. Rubin, and G. P. Salam Jet substructure as a new Higgs search channel at the LHC PRL 100 (2008) 242001 0802.2470
21 I. Moult, L. Necib, and J. Thaler New angles on energy correlation functions JHEP 12 (2016) 153 1609.07483
22 CMS Collaboration Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV JINST 13 (2018) P05011 CMS-BTV-16-002
1712.07158
23 CMS Collaboration The CMS trigger system JINST 12 (2017) P01020 CMS-TRG-12-001
1609.02366
24 CMS Collaboration The CMS experiment at the CERN LHC JINST 3 (2008) S08004 CMS-00-001
25 GEANT4 Collaboration GEANT4--a simulation toolkit NIMA 506 (2003) 250
26 J. Alwall et al. The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations JHEP 07 (2014) 079 1405.0301
27 O. Mattelaer and E. Vryonidou Dark matter production through loop-induced processes at the LHC: the $ s $-channel mediator case EPJC 75 (2015) 436 1508.00564
28 S. P. Jones, M. Kerner, and G. Luisoni Next-to-Leading-Order QCD Corrections to Higgs Boson Plus Jet Production with Full Top-Quark Mass Dependence PRL 120 (2018) 162001 1802.00349
29 J. Alwall et al. Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions EPJC 53 (2008) 473 0706.2569
30 P. Nason A new method for combining NLO QCD with shower Monte Carlo algorithms JHEP 11 (2004) 040 hep-ph/0409146
31 S. Frixione, P. Nason, and C. Oleari Matching NLO QCD computations with parton shower simulations: the POWHEG method JHEP 11 (2007) 070 0709.2092
32 S. Alioli, P. Nason, C. Oleari, and E. Re A general framework for implementing NLO calculations in shower monte carlo programs: the POWHEG BOX JHEP 06 (2010) 043 1002.2581
33 G. Luisoni, P. Nason, C. Oleari, and F. Tramontano $ \mathrm{H}\mathrm{W}^{\pm} $/$ \mathrm{H}\mathrm{Z} $ + 0 and 1 jet at NLO with the POWHEG BOX interfaced to GoSam and their merging within MiNLO JHEP 10 (2013) 083 1306.2542
34 D. de Florian, G. Ferrera, M. Grazzini, and D. Tommasini Higgs boson production at the LHC: transverse momentum resummation effects in the $ \mathrm{H}\to 2\gamma $, $ \mathrm{H}\to\mathrm{W}\mathrm{W}\to \ell\nu\ell\nu $ and $ \mathrm{H}\to\mathrm{Z}\mathrm{Z}\to 4\ell $ decay modes JHEP 06 (2012) 132 1203.6321
35 M. Grazzini and H. Sargsyan Heavy-quark mass effects in Higgs boson production at the LHC JHEP 09 (2013) 129 1306.4581
36 E. Bagnaschi, G. Degrassi, P. Slavich, and A. Vicini Higgs production via gluon fusion in the POWHEG approach in the SM and in the MSSM JHEP 02 (2012) 088 1111.2854
37 E. Bagnaschi and A. Vicini The Higgs transverse momentum distribution in gluon fusion as a multiscale problem JHEP 01 (2016) 056 1505.00735
38 T. Sjostrand et al. An introduction to PYTHIA 8.2 CPC 191 (2015) 159 1410.3012
39 CMS Collaboration Event generator tunes obtained from underlying event and multiparton scattering measurements EPJC 76 (2016) 155 CMS-GEN-14-001
1512.00815
40 J. M. Campbell and R. K. Ellis MCFM for the Tevatron and the LHC NPPS 205-206 (2010) 10 1007.3492
41 M. Czakon, P. Fiedler, and A. Mitov Total top quark pair-production cross section at hadron colliders through $ \mathcal{O}(\alpha_s^4) $ PRL 110 (2013) 252004 1303.6254
42 S. Kallweit et al. NLO electroweak automation and precise predictions for $ \mathrm{W} $+multijet production at the LHC JHEP 04 (2015) 012 1412.5157
43 S. Kallweit et al. NLO QCD+EW predictions for V + jets including off-shell vector-boson decays and multijet merging JHEP 04 (2016) 021 1511.08692
44 S. Kallweit et al. NLO QCD+EW automation and precise predictions for V+multijet production in Proceedings, 50th Rencontres de Moriond, QCD and high energy interactions, p. 121 2015 1505.05704
45 J. M. Lindert et al. Precise predictions for $ \mathrm{V} $+jets dark matter backgrounds EPJC 77 (2017) 829 1705.04664
46 NNPDF Collaboration Parton distributions for the LHC run II JHEP 04 (2015) 040 1410.8849
47 CMS Collaboration Particle-flow reconstruction and global event description with the CMS detector JINST 12 (2017) P10003 CMS-PRF-14-001
1706.04965
48 M. Cacciari, G. P. Salam, and G. Soyez Fastjet user manual EPJC 72 (2012) 1896 1111.6097
49 D. Bertolini, P. Harris, M. Low, and N. Tran Pileup Per Particle Identification JHEP 10 (2014) 059 1407.6013
50 CMS Collaboration Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV JINST 12 (2017) P02014 CMS-JME-13-004
1607.03663
51 D. Krohn, J. Thaler, and L.-T. Wang Jet trimming JHEP 02 (2010) 084 0912.1342
52 CMS Collaboration Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at $ \sqrt{s}= $ 8 TeV JINST 10 (2015) P06005 CMS-EGM-13-001
1502.02701
53 CMS Collaboration Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at $ \sqrt{s}= $ 13 TeV JINST 13 (2018) P06015 CMS-MUO-16-001
1804.04528
54 A. J. Larkoski, S. Marzani, G. Soyez, and J. Thaler Soft drop JHEP 05 (2014) 146 1402.2657
55 M. Dasgupta, A. Fregoso, S. Marzani, and G. P. Salam Towards an understanding of jet substructure JHEP 09 (2013) 029 1307.0007
56 CMS Collaboration Jet algorithms performance in 13 TeV data CMS-PAS-JME-16-003 CMS-PAS-JME-16-003
57 J. Dolen et al. Thinking outside the ROCs: Designing decorrelated taggers (DDT) for jet substructure JHEP 05 (2016) 156 1603.00027
58 A. J. Larkoski, G. P. Salam, and J. Thaler Energy correlation functions for jet substructure JHEP 06 (2013) 108 1305.0007
59 J. Thaler and K. Van Tilburg Identifying boosted objects with N-subjettiness JHEP 03 (2011) 015 1011.2268
60 R. A. Fisher On the interpretation of $ \chi^{2} $ from contingency tables, and the calculation of P J. Royal Stat. Soc. 85 (1922) 87
61 CMS Collaboration Search for new physics in final states with an energetic jet or a hadronically decaying $ \mathrm{W} $ or $ \mathrm{Z} $ boson and transverse momentum imbalance at $ \sqrt{s} = $ 13 TeV PRD 97 (2018) 092005 CMS-EXO-16-048
1712.02345
62 A. Denner, S. Dittmaier, T. Kasprzik, and A. Muck Electroweak corrections to $ \mathrm{W} $+jet hadroproduction including leptonic $ \mathrm{W} $-boson decays JHEP 08 (2009) 075 0906.1656
63 A. Denner, S. Dittmaier, T. Kasprzik, and A. Muck Electroweak corrections to dilepton+jet production at hadron colliders JHEP 06 (2011) 069 1103.0914
64 A. Denner, S. Dittmaier, T. Kasprzik, and A. Maeck Electroweak corrections to monojet production at the LHC EPJC 73 (2013) 2297 1211.5078
65 J. H. Kuhn, A. Kulesza, S. Pozzorini, and M. Schulze Electroweak corrections to hadronic photon production at large transverse momenta JHEP 03 (2006) 059 hep-ph/0508253
66 CMS Collaboration Determination of jet energy calibration and transverse momentum resolution in CMS JINST 6 (2011) 11002 CMS-JME-10-011
1107.4277
67 CMS Collaboration CMS luminosity measurements for the 2016 data taking period CMS-PAS-LUM-17-001 CMS-PAS-LUM-17-001
68 ATLAS and CMS Collaborations Procedure for the LHC Higgs boson search combination in Summer 2011 CMS-NOTE-2011-005
69 A. L. Read Presentation of search results: the CL$ _s $ technique JPG 28 (2002) 2693
70 T. Junk Confidence level computation for combining searches with small statistics NIMA 434 (1999) 435 hep-ex/9902006
71 CMS Collaboration Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV EPJC 75 (2015) 212 CMS-HIG-14-009
1412.8662
72 G. Cowan, K. Cranmer, E. Gross, and O. Vitells Asymptotic formulae for likelihood-based tests of new physics EPJC 71 (2011) 1554 1007.1727
73 L. Demortier P values and nuisance parameters in Statistical issues for LHC physics. Proceedings, Workshop, PHYSTAT-LHC, Geneva, Switzerland, June 27-29, 2007, p. 23 2008
Compact Muon Solenoid
LHC, CERN