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| CMS-PAS-TOP-19-008 | ||
| Measurement of the top quark Yukawa coupling from $\mathrm{t}\bar{\mathrm{t}}$ kinematic distributions in the dilepton final state at $\sqrt{s}= $ 13 TeV | ||
| CMS Collaboration | ||
| May 2020 | ||
| Abstract: An indirect measurement of the Higgs Yukawa coupling to the top quark is presented using pp collision at $\sqrt{s}= $ 13 TeV with an integrated luminosity of 137 fb$^{-1}$ recorded by the CMS detector. The coupling strength with respect to the standard model value, $Y_\mathrm{t}$, is determined from kinematic distributions in $\mathrm{t\bar{t}}$ production final states containing ee, $\mu\mu$, or e$\mu$ pairs. Sensitivity to the Yukawa coupling originates from altered distributions of $\mathrm{t\bar{t}}$ production in the presence of virtual Higgs boson exchange. In particular the distributions of the mass of the $\mathrm{t\bar{t}}$ system and the rapidity difference of the top quark and antiquark are sensitive to the value of $Y_\mathrm{t}$. The measurement yields a best-fit value of $Y_\mathrm{t}=$ 1.16$^{+0.24}_{-0.35}$ and a 95% confidence interval of $Y_\mathrm{t}\in[0,1.62]$. | ||
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Links:
CDS record (PDF) ;
CADI line (restricted) ;
These preliminary results are superseded in this paper, PRD 102 (2020) 092013. The superseded preliminary plots can be found here. |
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| Figures | |
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Figure 1:
Sample diagrams for weak contributions to gluon-induced and quark-induced top quark pair production, where $\Gamma $ stands for neutral gauge bosons, Higgs boson and pseudo-Goldstone bosons. |
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Figure 2:
Effect of the weak corrections on ${\mathrm{t} {}\mathrm{\bar{t}}}$ differential kinematic distributions for different values of $ {Y_\mathrm {t}} $, after reweighting of simulated events. |
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Figure 2-a:
Effect of the weak corrections on ${\mathrm{t} {}\mathrm{\bar{t}}}$ differential kinematic distributions for different values of $ {Y_\mathrm {t}} $, after reweighting of simulated events. |
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Figure 2-b:
Effect of the weak corrections on ${\mathrm{t} {}\mathrm{\bar{t}}}$ differential kinematic distributions for different values of $ {Y_\mathrm {t}} $, after reweighting of simulated events. |
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Figure 3:
The ratio of reconstructed kinematic distributions with weak corrections (evaluated for various values of ${Y_\mathrm {t}}$) to the SM kinematic distribution is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The upper figures show the information at generator level, while the lower figures are obtained from reconstructed events. |
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Figure 3-a:
The ratio of reconstructed kinematic distributions with weak corrections (evaluated for various values of ${Y_\mathrm {t}}$) to the SM kinematic distribution is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The upper figures show the information at generator level, while the lower figures are obtained from reconstructed events. |
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Figure 3-b:
The ratio of reconstructed kinematic distributions with weak corrections (evaluated for various values of ${Y_\mathrm {t}}$) to the SM kinematic distribution is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The upper figures show the information at generator level, while the lower figures are obtained from reconstructed events. |
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Figure 3-c:
The ratio of reconstructed kinematic distributions with weak corrections (evaluated for various values of ${Y_\mathrm {t}}$) to the SM kinematic distribution is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The upper figures show the information at generator level, while the lower figures are obtained from reconstructed events. |
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Figure 3-d:
The ratio of reconstructed kinematic distributions with weak corrections (evaluated for various values of ${Y_\mathrm {t}}$) to the SM kinematic distribution is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The upper figures show the information at generator level, while the lower figures are obtained from reconstructed events. |
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Figure 4:
Data to MC simulation comparison is shown for jet multiplicity, ${{p_{\mathrm {T}}} ^\text {miss}}$, lepton ${p_{\mathrm {T}}}$, and b jet ${p_{\mathrm {T}}}$. Uncertainty bands are derived by varying each known uncertainty source up and down across the full data-taking run, and summing the effects in quadrature. Here the signal simulation is divided into the following categories: correctly reconstructed events (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct reco), events with correctly reconstructed leptons and b jets but incorrect pairing of b jets and leptons (${\mathrm{t} {}\mathrm{\bar{t}}}$ b jets swapped), events with incorrectly reconstructed b jets or leptons including non-dilepton ${\mathrm{t} {}\mathrm{\bar{t}}}$ decays (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong reco), and a separate category for incorrectly reconstructed dilepton events which have a $\tau $ lepton in the final state (${\mathrm{t} {}\mathrm{\bar{t}}}$ $\tau $). |
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Figure 4-a:
Data to MC simulation comparison is shown for jet multiplicity, ${{p_{\mathrm {T}}} ^\text {miss}}$, lepton ${p_{\mathrm {T}}}$, and b jet ${p_{\mathrm {T}}}$. Uncertainty bands are derived by varying each known uncertainty source up and down across the full data-taking run, and summing the effects in quadrature. Here the signal simulation is divided into the following categories: correctly reconstructed events (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct reco), events with correctly reconstructed leptons and b jets but incorrect pairing of b jets and leptons (${\mathrm{t} {}\mathrm{\bar{t}}}$ b jets swapped), events with incorrectly reconstructed b jets or leptons including non-dilepton ${\mathrm{t} {}\mathrm{\bar{t}}}$ decays (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong reco), and a separate category for incorrectly reconstructed dilepton events which have a $\tau $ lepton in the final state (${\mathrm{t} {}\mathrm{\bar{t}}}$ $\tau $). |
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Figure 4-b:
Data to MC simulation comparison is shown for jet multiplicity, ${{p_{\mathrm {T}}} ^\text {miss}}$, lepton ${p_{\mathrm {T}}}$, and b jet ${p_{\mathrm {T}}}$. Uncertainty bands are derived by varying each known uncertainty source up and down across the full data-taking run, and summing the effects in quadrature. Here the signal simulation is divided into the following categories: correctly reconstructed events (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct reco), events with correctly reconstructed leptons and b jets but incorrect pairing of b jets and leptons (${\mathrm{t} {}\mathrm{\bar{t}}}$ b jets swapped), events with incorrectly reconstructed b jets or leptons including non-dilepton ${\mathrm{t} {}\mathrm{\bar{t}}}$ decays (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong reco), and a separate category for incorrectly reconstructed dilepton events which have a $\tau $ lepton in the final state (${\mathrm{t} {}\mathrm{\bar{t}}}$ $\tau $). |
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Figure 4-c:
Data to MC simulation comparison is shown for jet multiplicity, ${{p_{\mathrm {T}}} ^\text {miss}}$, lepton ${p_{\mathrm {T}}}$, and b jet ${p_{\mathrm {T}}}$. Uncertainty bands are derived by varying each known uncertainty source up and down across the full data-taking run, and summing the effects in quadrature. Here the signal simulation is divided into the following categories: correctly reconstructed events (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct reco), events with correctly reconstructed leptons and b jets but incorrect pairing of b jets and leptons (${\mathrm{t} {}\mathrm{\bar{t}}}$ b jets swapped), events with incorrectly reconstructed b jets or leptons including non-dilepton ${\mathrm{t} {}\mathrm{\bar{t}}}$ decays (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong reco), and a separate category for incorrectly reconstructed dilepton events which have a $\tau $ lepton in the final state (${\mathrm{t} {}\mathrm{\bar{t}}}$ $\tau $). |
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Figure 4-d:
Data to MC simulation comparison is shown for jet multiplicity, ${{p_{\mathrm {T}}} ^\text {miss}}$, lepton ${p_{\mathrm {T}}}$, and b jet ${p_{\mathrm {T}}}$. Uncertainty bands are derived by varying each known uncertainty source up and down across the full data-taking run, and summing the effects in quadrature. Here the signal simulation is divided into the following categories: correctly reconstructed events (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct reco), events with correctly reconstructed leptons and b jets but incorrect pairing of b jets and leptons (${\mathrm{t} {}\mathrm{\bar{t}}}$ b jets swapped), events with incorrectly reconstructed b jets or leptons including non-dilepton ${\mathrm{t} {}\mathrm{\bar{t}}}$ decays (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong reco), and a separate category for incorrectly reconstructed dilepton events which have a $\tau $ lepton in the final state (${\mathrm{t} {}\mathrm{\bar{t}}}$ $\tau $). |
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Figure 5:
Binned data and simulated events prior to performing the fit. The solid lines divide the three datataking periods, while the dashed lines divide the two ${|\Delta y|_\mathrm {b\ell}}$ bins in each datataking period, with ${M_\mathrm {b\ell}}$ bin ranges displayed on the $x$ axis. |
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Figure 6:
The weak correction rate modifier $R_\mathrm {W}^\mathrm {bin}$ in two separate [$ {M_\mathrm {b\ell}}$, ${\Delta y_\mathrm {b\ell}} $] bins from 2017 data, demonstrating the quadratic dependence on ${Y_\mathrm {t}}$. All bins will have an increasing or decreasing quadratic yield function, with the steepest dependence on ${Y_\mathrm {t}}$ found at lower values of ${M_\mathrm {b\ell}}$. |
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Figure 6-a:
The weak correction rate modifier $R_\mathrm {W}^\mathrm {bin}$ in two separate [$ {M_\mathrm {b\ell}}$, ${\Delta y_\mathrm {b\ell}} $] bins from 2017 data, demonstrating the quadratic dependence on ${Y_\mathrm {t}}$. All bins will have an increasing or decreasing quadratic yield function, with the steepest dependence on ${Y_\mathrm {t}}$ found at lower values of ${M_\mathrm {b\ell}}$. |
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Figure 6-b:
The weak correction rate modifier $R_\mathrm {W}^\mathrm {bin}$ in two separate [$ {M_\mathrm {b\ell}}$, ${\Delta y_\mathrm {b\ell}} $] bins from 2017 data, demonstrating the quadratic dependence on ${Y_\mathrm {t}}$. All bins will have an increasing or decreasing quadratic yield function, with the steepest dependence on ${Y_\mathrm {t}}$ found at lower values of ${M_\mathrm {b\ell}}$. |
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Figure 7:
The effect of the Yukawa parameter ${Y_\mathrm {t}}$ on reconstructed events in the final binning. The POI induces a shape distortion on the kinematic distributions. |
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Figure 8:
The result of a likelihood scan, performed by fixing the value of $ {Y_\mathrm {t}} $ at values over the interval [0, 3]. Expected curves from fits on simulated data are shown produced at the SM value $ {Y_\mathrm {t}} =$ 1.0 (red, dashed) and at the final best-fit value of $ {Y_\mathrm {t}} =$ 1.16 (blue, dashed). |
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Figure 9:
The agreement between data and MC simulation at the best fit value of $ {Y_\mathrm {t}} =$ 1.16 after performing the likelihood maximization, with shaded bands displaying the post-fit uncertainty. The solid lines divide the three datataking periods, while the dashed lines divide the two ${|\Delta y|_\mathrm {b\ell}}$ bins in each datataking period, with ${M_\mathrm {b\ell}}$ bin ranges displayed on the x axis. |
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Figure 10:
Shape templates are shown for the uncertainties associated with the final-state radiation in PYTHIA8, the jet energy corrections, the factorization scale, and the renormalization scale. Along with the intrinsic uncertainty included on the weak corrections, these are seen to be the dominant uncertainties in the fit. The shaded bars represent the raw template information, while the lines show the shapes after smoothing and symmetrization procedures have been applied. In the fit, the jet energy corrections are split into 26 different components, but for brevity only the total uncertainty is shown here. Variation between years is minimal for each of these uncertainties, though they are treated separately in the fit. |
png pdf |
Figure 10-a:
Shape templates are shown for the uncertainties associated with the final-state radiation in PYTHIA8, the jet energy corrections, the factorization scale, and the renormalization scale. Along with the intrinsic uncertainty included on the weak corrections, these are seen to be the dominant uncertainties in the fit. The shaded bars represent the raw template information, while the lines show the shapes after smoothing and symmetrization procedures have been applied. In the fit, the jet energy corrections are split into 26 different components, but for brevity only the total uncertainty is shown here. Variation between years is minimal for each of these uncertainties, though they are treated separately in the fit. |
png pdf |
Figure 10-b:
Shape templates are shown for the uncertainties associated with the final-state radiation in PYTHIA8, the jet energy corrections, the factorization scale, and the renormalization scale. Along with the intrinsic uncertainty included on the weak corrections, these are seen to be the dominant uncertainties in the fit. The shaded bars represent the raw template information, while the lines show the shapes after smoothing and symmetrization procedures have been applied. In the fit, the jet energy corrections are split into 26 different components, but for brevity only the total uncertainty is shown here. Variation between years is minimal for each of these uncertainties, though they are treated separately in the fit. |
png pdf |
Figure 10-c:
Shape templates are shown for the uncertainties associated with the final-state radiation in PYTHIA8, the jet energy corrections, the factorization scale, and the renormalization scale. Along with the intrinsic uncertainty included on the weak corrections, these are seen to be the dominant uncertainties in the fit. The shaded bars represent the raw template information, while the lines show the shapes after smoothing and symmetrization procedures have been applied. In the fit, the jet energy corrections are split into 26 different components, but for brevity only the total uncertainty is shown here. Variation between years is minimal for each of these uncertainties, though they are treated separately in the fit. |
png pdf |
Figure 10-d:
Shape templates are shown for the uncertainties associated with the final-state radiation in PYTHIA8, the jet energy corrections, the factorization scale, and the renormalization scale. Along with the intrinsic uncertainty included on the weak corrections, these are seen to be the dominant uncertainties in the fit. The shaded bars represent the raw template information, while the lines show the shapes after smoothing and symmetrization procedures have been applied. In the fit, the jet energy corrections are split into 26 different components, but for brevity only the total uncertainty is shown here. Variation between years is minimal for each of these uncertainties, though they are treated separately in the fit. |
| Tables | |
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Table 1:
MC simulation and data event yields for each of the three years and their combination. Drell-Yan decays are included in V + jets samples, where V stands for a W or Z vector boson. The rightmost column shows the fraction of each component relative to the total simulated sample yield across the full data set. The statistical uncertainty in the simulated event counts is given. |
| Summary |
| A measurement of the Higgs Yukawa coupling to the top quark is presented, based on data from proton-proton collisions at the CMS experiment, deriving a best fit value of ${Y_\mathrm{t}} =$ 1.16$^{+0.24}_{-0.35}$ and a 95% confidence interval (CI) of ${Y_\mathrm{t}} \in\,{[0, \,1.62]} $. Data at a center-of-mass energy 13 TeV is analyzed from the full LHC Run 2, collected from 2016-2018, yielding an integrated luminosity of 137 fb$^{-1}$. This measurement uses the effects of virtual Higgs boson exchange on $\mathrm{t\bar{t}}$ kinematic properties to extract information about the coupling from kinematic distributions. Although the sensitivity is lower compared to constraints obtained from studying processes involving Higgs boson production in Refs. [7] and [9], this measurement avoids dependence on other Yukawa coupling values through additional branching assumptions, making it a compelling orthogonal measurement. This measurement also achieves a slightly higher precision than the only other ${Y_\mathrm{t}} $ measurement that does not make additional branching fraction assumptions, performed in the search for production of four top quarks. The four top quark search places a 95% CI of ${Y_\mathrm{t}} < $ 1.7 [10] while this measurement achieves a 95% CI of ${Y_\mathrm{t}} < $ 1.62. |
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