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| CMS-TOP-19-008 ; CERN-EP-2020-152 | ||
| Measurement of the top quark Yukawa coupling from $\mathrm{t\bar{t}}$ kinematic distributions in the dilepton final state in proton-proton collisions at $\sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 15 September 2020 | ||
| Phys. Rev. D 102 (2020) 092013 | ||
| Abstract: A measurement of the Higgs boson Yukawa coupling to the top quark is presented using proton-proton collision data at $\sqrt{s} = $ 13 TeV, corresponding to an integrated luminosity of 137 fb$^{-1}$, recorded with the CMS detector. The coupling strength with respect to the standard model value, ${Y_{\mathrm{t}}} $, is determined from kinematic distributions in $\mathrm{t\bar{t}}$ final states containing ee, ${\mu}{\mu}$, or e${\mu}$ pairs. Variations of the Yukawa coupling strength lead to modified distributions for $\mathrm{t\bar{t}}$ production. 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} $, bounding ${Y_{\mathrm{t}}} < $ 1.54 at a 95% confidence level. | ||
| Links: e-print arXiv:2009.07123 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; CADI line (restricted) ; | ||
| Figures & Tables | Summary | Additional Figures | References | CMS Publications |
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| Figures | |
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Figure 1:
Sample Feynman diagrams for EW contributions to gluon-induced and quark-induced top quark pair production, where $\Gamma $ stands for neutral vector and scalar bosons. |
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Figure 1-a:
Sample Feynman diagram for EW contribution to quark-induced top quark pair production, where $\Gamma $ stands for neutral vector and scalar bosons. |
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Figure 1-b:
Sample Feynman diagram for EW contribution to gluon-induced top quark pair production, where $\Gamma $ stands for neutral vector and scalar bosons. |
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Figure 2:
Effect of the EW corrections on $\mathrm{t\bar{t}}$ differential kinematic distributions for different values of $ {Y_{\mathrm{t}}} $, after reweighting of simulated events. The effect is shown on the distribution of the invariant mass, ${M_{{\mathrm{t} {}\mathrm{\bar{t}}}}}$ (left), and the difference in rapidity between the top quark and antiquark, $\Delta y_{{\mathrm{t} {}\mathrm{\bar{t}}}}$ (right). |
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Figure 2-a:
Effect of the EW corrections on the distribution of the invariant mass, ${M_{{\mathrm{t} {}\mathrm{\bar{t}}}}}$, for different values of $ {Y_{\mathrm{t}}} $, after reweighting of simulated events. |
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Figure 2-b:
Effect of the EW corrections on the distribution of the difference in rapidity between the top quark and antiquark, $\Delta y_{{\mathrm{t} {}\mathrm{\bar{t}}}}$, for different values of $ {Y_{\mathrm{t}}} $, after reweighting of simulated events. |
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Figure 3:
The ratio of kinematic distributions with EW corrections (evaluated for various values of ${Y_{\mathrm{t}}}$) to the SM kinematic distribution (${Y_{\mathrm{t}}} =$ 1) is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The plots on the left show the information at the generator level, while the plots on the right are obtained from reconstructed events. The axis scale is kept the same for the sake of comparison. |
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Figure 3-a:
The ratio of the $ {M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$ distribution with EW corrections (evaluated for various values of ${Y_{\mathrm{t}}}$) to the SM kinematic distribution (${Y_{\mathrm{t}}} =$ 1) is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The plot shows the information at the generator level. The axis scale is kept the same for the sake of comparison. |
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Figure 3-b:
The ratio of the $ {M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$ distribution with EW corrections (evaluated for various values of ${Y_{\mathrm{t}}}$) to the SM kinematic distribution (${Y_{\mathrm{t}}} =$ 1) is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The plot is obtained from reconstructed events. The axis scale is kept the same for the sake of comparison. |
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Figure 3-c:
The ratio of the ${\Delta y_{{\mathrm{b}}\ell {\mathrm{b}}\ell}} $ distribution with EW corrections (evaluated for various values of ${Y_{\mathrm{t}}}$) to the SM kinematic distribution (${Y_{\mathrm{t}}} =$ 1) is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The plot shows the information at the generator level. The axis scale is kept the same for the sake of comparison. |
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Figure 3-d:
The ratio of the ${\Delta y_{{\mathrm{b}}\ell {\mathrm{b}}\ell}} $ distribution with EW corrections (evaluated for various values of ${Y_{\mathrm{t}}}$) to the SM kinematic distribution (${Y_{\mathrm{t}}} =$ 1) is shown, demonstrating the sensitivity of these distributions to the Yukawa coupling. The plot is obtained from reconstructed events. The axis scale is kept the same for the sake of comparison. |
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Figure 4:
Data-to-simulation comparisons for the jet multiplicity (upper left), ${{p_{\mathrm {T}}} ^\text {miss}}$ (upper right), lepton ${p_{\mathrm {T}}}$ (lower left), and b jet ${p_{\mathrm {T}}}$ (lower right). The uncertainty bands are derived by varying each uncertainty source up and down by one standard deviation (as described in Section 4) and summing the effects in quadrature. The signal simulation is divided into the following categories: events with correctly identified leptons and jets in which jets are correctly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct jets), events with correctly identified leptons and jets in which jets are incorrectly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ swapped jets), events with correctly identified leptons where the two b jets originating from top decays are not identified correctly (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong jets), and lastly events where the identified leptons are not those from W boson decay vertices (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong leptons). The lower panels show the ratio of data to the simulated events in each bin, with total uncertainty bands drawn around the nominal expected bin content. |
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Figure 4-a:
Data-to-simulation comparison for the jet multiplicity. The uncertainty bands are derived by varying each uncertainty source up and down by one standard deviation (as described in Section 4) and summing the effects in quadrature. The signal simulation is divided into the following categories: events with correctly identified leptons and jets in which jets are correctly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct jets), events with correctly identified leptons and jets in which jets are incorrectly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ swapped jets), events with correctly identified leptons where the two b jets originating from top decays are not identified correctly (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong jets), and lastly events where the identified leptons are not those from W boson decay vertices (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong leptons). The lower panel shows the ratio of data to the simulated events in each bin, with total uncertainty bands drawn around the nominal expected bin content. |
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Figure 4-b:
Data-to-simulation comparison for ${{p_{\mathrm {T}}} ^\text {miss}}$. The uncertainty bands are derived by varying each uncertainty source up and down by one standard deviation (as described in Section 4) and summing the effects in quadrature. The signal simulation is divided into the following categories: events with correctly identified leptons and jets in which jets are correctly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct jets), events with correctly identified leptons and jets in which jets are incorrectly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ swapped jets), events with correctly identified leptons where the two b jets originating from top decays are not identified correctly (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong jets), and lastly events where the identified leptons are not those from W boson decay vertices (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong leptons). The lower panel shows the ratio of data to the simulated events in each bin, with total uncertainty bands drawn around the nominal expected bin content. |
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Figure 4-c:
Data-to-simulation comparison for the lepton ${p_{\mathrm {T}}}$. The uncertainty bands are derived by varying each uncertainty source up and down by one standard deviation (as described in Section 4) and summing the effects in quadrature. The signal simulation is divided into the following categories: events with correctly identified leptons and jets in which jets are correctly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct jets), events with correctly identified leptons and jets in which jets are incorrectly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ swapped jets), events with correctly identified leptons where the two b jets originating from top decays are not identified correctly (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong jets), and lastly events where the identified leptons are not those from W boson decay vertices (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong leptons). The lower panel shows the ratio of data to the simulated events in each bin, with total uncertainty bands drawn around the nominal expected bin content. |
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Figure 4-d:
Data-to-simulation comparison for the b jet ${p_{\mathrm {T}}}$. The uncertainty bands are derived by varying each uncertainty source up and down by one standard deviation (as described in Section 4) and summing the effects in quadrature. The signal simulation is divided into the following categories: events with correctly identified leptons and jets in which jets are correctly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ correct jets), events with correctly identified leptons and jets in which jets are incorrectly assigned (${\mathrm{t} {}\mathrm{\bar{t}}}$ swapped jets), events with correctly identified leptons where the two b jets originating from top decays are not identified correctly (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong jets), and lastly events where the identified leptons are not those from W boson decay vertices (${\mathrm{t} {}\mathrm{\bar{t}}}$ wrong leptons). The lower panel shows the ratio of data to the simulated events in each bin, with total uncertainty bands drawn around the nominal expected bin content. |
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Figure 5:
The pre-fit agreement between data and MC simulation in the final kinematic binning. The solid lines divide the three data-taking periods, while the dashed lines divide the two ${{| \Delta y_{{\mathrm{b}}\ell {\mathrm{b}}\ell} |}}$ bins in each data-taking period, with ${M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$ bin ranges displayed on the $x$ axis. The lower panel shows the ratio of data to the simulated events in each bin, with total uncertainty bands drawn around the nominal expected bin content, obtained by summing the contributions of all uncertainty sources in quadrature. |
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Figure 6:
The EW correction rate modifier $R_\mathrm {EW}^\text {bin}$ in two separate ($ {M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$, ${\Delta y_{{\mathrm{b}}\ell {\mathrm{b}}\ell}} $) bins from simulated 2017 data, demonstrating the quadratic dependence on ${Y_{\mathrm{t}}}$. All bins have an increasing or decreasing quadratic yield function, with the steepest dependence on ${Y_{\mathrm{t}}}$ found at lower values of ${M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$. |
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Figure 6-a:
The EW correction rate modifier $R_\mathrm {EW}^\text {bin}$ in bin ($ {M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}} \in$ [100, 210] GeV, $|{\Delta y_{{\mathrm{b}}\ell {\mathrm{b}}\ell}}| < $ 1.0) bins from simulated 2017 data, demonstrating the quadratic dependence on ${Y_{\mathrm{t}}}$. All bins have an increasing or decreasing quadratic yield function, with the steepest dependence on ${Y_{\mathrm{t}}}$ found at lower values of ${M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$. |
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Figure 6-b:
The EW correction rate modifier $R_\mathrm {EW}^\text {bin}$ in bin ($ {M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}} \in$ [440, 3000] GeV, $|{\Delta y_{{\mathrm{b}}\ell {\mathrm{b}}\ell}}| < $ 1.0) bins from simulated 2017 data, demonstrating the quadratic dependence on ${Y_{\mathrm{t}}}$. All bins have an increasing or decreasing quadratic yield function, with the steepest dependence on ${Y_{\mathrm{t}}}$ found at lower values of ${M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$. |
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Figure 7:
The effect of the Yukawa parameter ${Y_{\mathrm{t}}}$ on reconstructed event yield in the final binned distributions. The variation of ${Y_{\mathrm{t}}}$ induces a shape distortion in the kinematic distributions. The marginal effect relative to the standard model expectation ${Y_{\mathrm{t}}} =$ 1 is visualized in the lower panel. |
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Figure 8:
The result of a profile likelihood scan, performed by fixing the value of $ {Y_{\mathrm{t}}} $ at values over the interval [0, 3] and taking the ratio of $-2\ln(\mathcal {L}({Y_{\mathrm{t}}}))$ to the best fit value $-2\ln(\mathcal {L}(\hat{\mathrm{t}}))$. The expected curves from fits to simulated Asimov data are shown produced for the SM value $ {Y_{\mathrm{t}}} =$ 1.0 (dashed) and for the final best fit value of $ {Y_{\mathrm{t}}} =$ 1.16 (dotted). |
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Figure 9:
The comparison 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 separate the three data-taking periods, while the dashed lines indicate the boundaries of the two ${{| \Delta y_{{\mathrm{b}}\ell {\mathrm{b}}\ell} |}}$ bins in each data-taking period, with ${M_{{\mathrm{b}}{\mathrm{b}}{\ell}{\ell}}}$ bin ranges displayed on the $x$ axis. The lower panel shows the ratio of data to the simulated events in each bin, with total post-fit uncertainty bands drawn around the nominal expected bin content. |
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Figure 10:
Templates are shown for the uncertainties associated with the final-state radiation in PYTHIA (upper left), the jet energy corrections (upper right), the factorization scale (lower left), and the renormalization scale (lower right). Along with the intrinsic uncertainty in the EW corrections, these are the limiting 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, although they are treated separately in the fit. |
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Figure 10-a:
Templates are shown for the uncertainties associated with the final-state radiation in PYTHIA. Along with the intrinsic uncertainty in the EW corrections, these are the limiting 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, although they are treated separately in the fit. |
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Figure 10-b:
Templates are shown for the uncertainties associated with the jet energy corrections. Along with the intrinsic uncertainty in the EW corrections, these are the limiting 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, although they are treated separately in the fit. |
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Figure 10-c:
Templates are shown for the uncertainties associated with the factorization scale. Along with the intrinsic uncertainty in the EW corrections, these are the limiting 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, although they are treated separately in the fit. |
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Figure 10-d:
Templates are shown for the uncertainties associated with the renormalization scale. Along with the intrinsic uncertainty in the EW corrections, these are the limiting 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, although they are treated separately in the fit. |
| Tables | |
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Table 1:
Simulated signal, background, and data event yields for each of the three years and their combination. 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 collected by the CMS experiment. Data at a center-of-mass energy of 13 TeV is analyzed from the LHC Run 2, collected in 2016-18 and corresponding to an integrated luminosity of 137 fb$^{-1}$. The resulting best fit value of the top quark Yukawa coupling relative to the standard model is given by ${Y_{\mathrm{t}}} = $ 1.16 $^{+0.24}_{-0.35}$. 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. [9] and [11], this measurement avoids dependence on other Yukawa coupling values through additional branching assumptions, making it a compelling independent 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 ${Y_{\mathrm{t}}} < $ 1.7 at a 95% confidence level [12] while this measurement achieves an approximate result of ${Y_{\mathrm{t}}} < $ 1.54. |
| Additional Figures | |
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Additional Figure 1:
Nuisance parameter post-fit constraints and impacts are shown for the 30 uncertainties in the fit with the largest impact on the best fit value of ${Y_{{\mathrm {t}}}}$. This information is also provided for a fit using an Asimov dataset generated with $ {Y_{{\mathrm {t}}}} =$ 1 (expected), for the sake of comparison with the final fit result on data (observed). Impacts are calculated by repeating the fit with individual nuisance parameters held fixed and varied up and down by one standard deviation according to the their post-fit uncertainty, then recording the resulting effect on the best fit value of ${Y_{{\mathrm {t}}}}$. Note that some uncertainty sources are split into a correlated nuisance parameter and an uncorrelated parameter unique to each data-taking year, as indicated by the paranthetical expressions in the parameter names. This is done when the uncertainty in question has a partial correlation between years, or in some cases where the modelling was changed after 2016. In the case of partial correlations, this allows us to separately consider a correlated and uncorrelated effect from each nuisance parameter, in approximation. Uncertainties related to the jet energy corrections (JEC) come from several components, including the flavor dependence of the jet responses (FlavorQCD), corrections to initial and final state radiations (RelativeFSR), variations of JEC in different data taking periods (TimeEtaPt), variations of the single particle response in ECAL (SinglePionECAL), residual differences between samples used to derive the JEC (RelativeSample), a constant scale uncertainty for the biases of methods to study the jet energy response (AbsoluteMPFBias), together with differences between those methods in the calibration fits (RelativeBal). The word relative stands for relative $\eta $-dependent corrections, calibrating different detector regions relative to $ | \eta | < $ 1.3 using dijet events. More details can be found in Ref. [44]. |
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