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| CMS-PAS-EXO-17-024 | ||
| Search for low mass resonances decaying into bottom quark-antiquark pairs in pp collisions at $\sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| July 2018 | ||
| Abstract: A search for narrow scalar resonances decaying to bottom quark-antiquark pairs is presented. The search is based on events collected in $\sqrt{s}= $ 13 TeV proton-proton collisions with the CMS detector at the CERN LHC. The data sample, collected in 2016, corresponds to an integrated luminosity of 35.9 fb$^{-1}$. The resonance is produced with high transverse momentum due to initial state radiation, such that the decay products of the resonance are reconstructed as a single large-radius jet with high mass and two-pronged substructure. The signal is identified as a narrow excess in the jet invariant mass spectrum. No evidence for such a resonance is observed within the resonance mass range from 50 to 350 GeV. Upper limits at the 95% confidence level are set on the product of the cross section and branching fraction to a bottom quark-antiquark pair, constituting the first constraint from the LHC in this resonance mass range. | ||
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Links:
CDS record (PDF) ;
inSPIRE record ;
CADI line (restricted) ;
These preliminary results are superseded in this paper, PRD 99 (2019) 012005. The superseded preliminary plots can be found here. |
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| Figures | |
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Figure 1:
One-loop diagrams of processes exchanging a scalar ($\mathrm{h}i $) or pseudoscalar ($A$) mediator, leading to a boosted double b-jet signature. |
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Figure 1-a:
One-loop diagrams of processes exchanging a scalar ($\mathrm{h}i $) or pseudoscalar ($A$) mediator, leading to a boosted double b-jet signature. |
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Figure 1-b:
One-loop diagrams of processes exchanging a scalar ($\mathrm{h}i $) or pseudoscalar ($A$) mediator, leading to a boosted double b-jet signature. |
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Figure 2:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the AK8 selection for the failing (top) and passing (bottom) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. 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 bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 2-a:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the AK8 selection for the failing (top) and passing (bottom) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. 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 bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 2-b:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the AK8 selection for the failing (top) and passing (bottom) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. 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 bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 3:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the CA15 selection for the failing (top) and passing (bottom) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. 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 bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 3-a:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the CA15 selection for the failing (top) and passing (bottom) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. 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 bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 3-b:
The observed and fitted background $ {m_{\mathrm {SD}}} $ distributions for the CA15 selection for the failing (top) and passing (bottom) regions, combining all the $ {p_{\mathrm {T}}} $ categories. The background fit is performed under the background-only hypothesis. 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 bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 4:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 4-a:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 4-b:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 4-c:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 4-d:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 4-e:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 4-f:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
png pdf |
Figure 5:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
png pdf |
Figure 5-a:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
png pdf |
Figure 5-b:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
png pdf |
Figure 5-c:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
png pdf |
Figure 5-d:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
png pdf |
Figure 5-e:
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. The QCD multijet background in the passing region is predicted using the failing region and the pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$. The bottom panel shows the difference between the data and the background prediction, divided by the statistical uncertainty on the data. |
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Figure 6:
The fitted pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$ as function of $ {p_{\mathrm {T}}} $ and $\rho $ for both the AK8 selection (top) and the CA15 selection (bottom). |
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Figure 6-a:
The fitted pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$ as function of $ {p_{\mathrm {T}}} $ and $\rho $ for both the AK8 selection (top) and the CA15 selection (bottom). |
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Figure 6-b:
The fitted pass-fail ratio $R_{\mathrm {p}/\mathrm {f}}$ as function of $ {p_{\mathrm {T}}} $ and $\rho $ for both the AK8 selection (top) and the CA15 selection (bottom). |
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Figure 7:
95% CL upper limits on the $\mathrm{h}i ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ production cross section times branching fraction (top) and on $ {g_{{\rm q}\mathrm{h}i}} $ (bottom) as a function of resonance mass. The blue dash-dotted line indicates the theoretical scalar production cross section assuming $ {g_{{\rm q}\mathrm{h}i}} =$ 1 as a chosen benchmark. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections. |
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Figure 7-a:
95% CL upper limits on the $\mathrm{h}i ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ production cross section times branching fraction (top) and on $ {g_{{\rm q}\mathrm{h}i}} $ (bottom) as a function of resonance mass. The blue dash-dotted line indicates the theoretical scalar production cross section assuming $ {g_{{\rm q}\mathrm{h}i}} =$ 1 as a chosen benchmark. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections. |
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Figure 7-b:
95% CL upper limits on the $\mathrm{h}i ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ production cross section times branching fraction (top) and on $ {g_{{\rm q}\mathrm{h}i}} $ (bottom) as a function of resonance mass. The blue dash-dotted line indicates the theoretical scalar production cross section assuming $ {g_{{\rm q}\mathrm{h}i}} =$ 1 as a chosen benchmark. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections. |
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Figure 8:
95% CL upper limits on the $A({{\mathrm {b}} {\overline {\mathrm {b}}}})$ production cross section times branching fraction (top) and on $ {g_{{\rm q}A}} $ (bottom) as a function of resonance mass. The blue dash-dotted line indicates the theoretical pseudoscalar production cross section assuming $ {g_{{\rm q}A}} =$ 1 as a chosen benchmark. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections. |
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Figure 8-a:
95% CL upper limits on the $A({{\mathrm {b}} {\overline {\mathrm {b}}}})$ production cross section times branching fraction (top) and on $ {g_{{\rm q}A}} $ (bottom) as a function of resonance mass. The blue dash-dotted line indicates the theoretical pseudoscalar production cross section assuming $ {g_{{\rm q}A}} =$ 1 as a chosen benchmark. The vertical line at 175 GeV corresponds to the transition between the AK8 and CA15 jet selections. |
png pdf |
Figure 8-b:
95% CL upper limits on the $A({{\mathrm {b}} {\overline {\mathrm {b}}}})$ production cross section times branching fraction (top) and on $ {g_{{\rm q}A}} $ (bottom) as a function of resonance mass. The blue dash-dotted line indicates the theoretical pseudoscalar production cross section assuming $ {g_{{\rm q}A}} =$ 1 as a chosen benchmark. 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 efficiency in percentages for simulated $\mathrm{h}i ({{\mathrm {b}} {\overline {\mathrm {b}}}})$ signal events with parton-level $ {H_{\mathrm {T}}} > $ 400 GeV at different stages of the event selection, shown for each mass hypothesis and for AK8 and CA15 jets. The statistical uncertainties due to the MC 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 "--". The reported percentages reflect a one standard deviation effect on the acceptance times efficiency of the different processes. 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 resonance decaying into a bottom quark-antiquark pair and reconstructed as a single wide jet has been presented, using a dataset of proton-proton collisions at $\sqrt{s} = $ 13 TeV corresponding to an integrated luminosity of 35.9 fb$^{-1}$. Novel 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, and 95% confidence level upper limits are set on the resonance production cross section times branching fraction to bottom quark-antiquark pairs, as well as the coupling ${g_{{\rm q}\mathrm{h}i}} $ (${g_{{\rm q}A}} $) of a scalar (pseudoscalar) boson coupling to quarks. The search excludes the production through gluon fusion of a scalar (psuedoscalar) decaying to $\mathrm{b\bar{b}}$ with a cross section times branching ratio as low as 79 pb (86 pb) at a resonance mass of 175 GeV, corresponding to an upper limit on ${g_{{\rm q}\mathrm{h}i}} $ (${g_{{\rm q}A}} $) of 3.9 (2.5). This constitutes the first LHC constraint on such resonances in this mass range. |
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Compact Muon Solenoid LHC, CERN |
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