Compact Muon Solenoid
LHC, CERN
Visit us: CMS Public Website, CMS Physics ;
Contact us: CMS Publications Committee
| CMS-HIG-19-015 ; CERN-EP-2021-038 | ||
| Measurements of Higgs boson production cross sections and couplings in the diphoton decay channel at $\sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 12 March 2021 | ||
| JHEP 07 (2021) 027 | ||
| Abstract: Measurements of Higgs boson production cross sections and couplings in events where the Higgs boson decays into a pair of photons are reported. Events are selected from a sample of proton-proton collisions at $\sqrt{s} = $ 13 TeV collected by the CMS detector at the LHC from 2016 to 2018, corresponding to an integrated luminosity of 137 fb$^{-1}$. Analysis categories enriched in Higgs boson events produced via gluon fusion, vector boson fusion, vector boson associated production, and production associated with top quarks are constructed. The total Higgs boson signal strength, relative to the standard model (SM) prediction, is measured to be 1.12 $\pm$ 0.09. Other properties of the Higgs boson are measured, including SM signal strength modifiers, production cross sections, and its couplings to other particles. These include the most precise measurements of gluon fusion and vector boson fusion Higgs boson production in several different kinematic regions, the first measurement of Higgs boson production in association with a top quark pair in five regions of the Higgs boson transverse momentum, and an upper limit on the rate of Higgs boson production in association with a single top quark. All results are found to be in agreement with the SM expectations. | ||
| Links: e-print arXiv:2103.06956 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; HepData record ; CADI line (restricted) ; | ||
| Figures & Tables | Summary | Additional Figures & Tables | References | CMS Publications |
|---|
| Figures | |
png pdf |
Figure 1:
Diagram showing the full set of STXS stage-1.2 bins, adapted from Ref. [10], defined for events with $ {{| y_\mathrm{H} |}} < $ 2.5. The solid boxes represent each STXS stage-1.2 bin. The units of ${{p_{\mathrm {T}}} ^\mathrm{H}}$, ${m_{\text {jj}}}$, ${{p_{\mathrm {T}}} ^{\mathrm{H} \text {jj}}}$, and ${{p_{\mathrm {T}}} ^{{\mathrm{V}}}}$ are in GeV. The shaded regions indicate the STXS bins that are divided at stage 1.2, but are not measured independently in this analysis. |
png pdf |
Figure 2:
Comparison of the dielectron invariant mass spectra in data (black points) and simulation (blue histogram), after applying energy scale corrections to data and energy smearing to the simulation, for ${\mathrm{Z} \to \mathrm{ee}}$ events with electrons reconstructed as photons. The statistical and systematic uncertainty on the simulation is shown by the pink band. The comparison is shown for events where both electrons are reconstructed in the ECAL barrel (left), and both in the ECAL endcaps (right). The lower panels show the ratio of the data to the MC simulation in black points, with the uncertainty on the ratio represented by the pink band. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 2-a:
Comparison of the dielectron invariant mass spectra in data (black points) and simulation (blue histogram), after applying energy scale corrections to data and energy smearing to the simulation, for ${\mathrm{Z} \to \mathrm{ee}}$ events with electrons reconstructed as photons. The statistical and systematic uncertainty on the simulation is shown by the pink band. The comparison is shown for events where both electrons are reconstructed in the ECAL barrel. The lower panel shows the ratio of the data to the MC simulation in black points, with the uncertainty on the ratio represented by the pink band. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 2-b:
Comparison of the dielectron invariant mass spectra in data (black points) and simulation (blue histogram), after applying energy scale corrections to data and energy smearing to the simulation, for ${\mathrm{Z} \to \mathrm{ee}}$ events with electrons reconstructed as photons. The statistical and systematic uncertainty on the simulation is shown by the pink band. The comparison is shown for events where both electrons are reconstructed in the ECAL endcaps. The lower panel shows the ratio of the data to the MC simulation in black points, with the uncertainty on the ratio represented by the pink band. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 3:
The left plot shows the distribution of the photon identification BDT score of the lowest scoring photon in diphoton pairs with 100 $ < {m_{\gamma \gamma}} < $ 180 GeV, for data events passing the preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background. The blue histogram corresponds to simulated Higgs boson signal events. The right plot shows the same distribution for ${\mathrm{Z} \to \mathrm{ee}}$ events in data and simulation, where the electrons are reconstructed as photons. The statistical and systematic uncertainty in simulation is also shown (pink band). Photons with an identification BDT score in the grey shaded region (below $-$0.9) are not considered in the analysis. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 3-a:
Distribution of the photon identification BDT score of the lowest scoring photon in diphoton pairs with 100 $ < {m_{\gamma \gamma}} < $ 180 GeV, for data events passing the preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background. The blue histogram corresponds to simulated Higgs boson signal events. Photons with an identification BDT score in the grey shaded region (below $-$0.9) are not considered in the analysis. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 3-b:
Distribution of the photon identification BDT score of the lowest scoring photon in diphoton pairs with 100 $ < {m_{\gamma \gamma}} < $ 180 GeV for ${\mathrm{Z} \to \mathrm{ee}}$ events in data and simulation, where the electrons are reconstructed as photons. The statistical and systematic uncertainty in simulation is also shown (pink band). "Photons" with an identification BDT score in the grey shaded region (below $-$0.9) are not considered in the analysis. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 4:
The left plot shows the validation of the ${\mathrm{H} \to \gamma \gamma}$ vertex identification algorithm on ${\mathrm{Z} \to \mu^{+} \mu^{-}}$ events, where the muon tracks are omitted when performing the event reconstruction. This allows the fraction of events with the correctly assigned vertex estimated with simulation to be compared with data, as a function of the ${p_{\mathrm {T}}}$ of the dimuon system, serving as a validation of the vertex identification BDT. Simulated events are weighted to match the distributions of pileup and distribution of vertices along the beam axis in data. The right plot demonstrates that the average vertex probability to be within 1 cm of the true vertex agrees with the true vertex efficiency in simulated events. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 4-a:
Validation of the ${\mathrm{H} \to \gamma \gamma}$ vertex identification algorithm on ${\mathrm{Z} \to \mu^{+} \mu^{-}}$ events, where the muon tracks are omitted when performing the event reconstruction. This allows the fraction of events with the correctly assigned vertex estimated with simulation to be compared with data, as a function of the ${p_{\mathrm {T}}}$ of the dimuon system, serving as a validation of the vertex identification BDT. Simulated events are weighted to match the distributions of pileup and distribution of vertices along the beam axis in data. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 4-b:
The plot demonstrates that the average vertex probability to be within 1 cm of the true vertex agrees with the true vertex efficiency in simulated events. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 5:
The most probable STXS class from the ggH BDT in ${\mathrm{Z} \to \mathrm{ee}}$ events where the electrons are reconstructed as photons is shown. The points show the predicted class for data, whilst the histogram shows predicted score for simulated Drell-Yan events, including statistical and systematic uncertainties (pink band). The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 6:
The left plot shows the distribution of the diphoton BDT score in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, for data events passing the preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background in red. The blue histogram corresponds to simulated Higgs boson signal events ($\times $100). The right plot shows the same distribution in ${\mathrm{Z} \to \mathrm{ee}}$ events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated Drell-Yan events, including statistical and systematic uncertainties (pink band). The regions shaded grey contain diphoton BDT scores below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 6-a:
Distribution of the diphoton BDT score in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, for data events passing the preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background in red. The blue histogram corresponds to simulated Higgs boson signal events ($\times $100). The regions shaded grey contain diphoton BDT scores below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 6-b:
Distribution of the diphoton BDT score in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, in ${\mathrm{Z} \to \mathrm{ee}}$ events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated Drell-Yan events, including statistical and systematic uncertainties (pink band). The regions shaded grey contain diphoton BDT scores below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 7:
The left plot shows the distribution of the dijet BDT output VBF probability in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, for data events passing the dijet preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background in red. The orange histogram corresponds to simulated VBF signal events, with the ggH events shown in blue (both $\times $100). The right plot shows the same distribution in ${\mathrm{Z} \to \mathrm{ee}}$ events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated Drell-Yan events, including statistical and systematic uncertainties (pink band). The regions shaded grey contain VBF probability values below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 7-a:
Distribution of the dijet BDT output VBF probability in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, for data events passing the dijet preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background in red. The orange histogram corresponds to simulated VBF signal events, with the ggH events shown in blue (both $\times $100). The regions shaded grey contain VBF probability values below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 7-b:
Distribution of the dijet BDT output VBF probability in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, in ${\mathrm{Z} \to \mathrm{ee}}$ events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated Drell-Yan events, including statistical and systematic uncertainties (pink band). The regions shaded grey contain VBF probability values below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 8:
The left plot shows the distribution of the VH hadronic BDT output score in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, for data events passing the preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background in red. The sum of all background distributions is scaled to the data. The orange histogram corresponds to simulated VH hadronic signal events. The right plot shows the same distribution in $ {\mathrm{Z} \to \mathrm{ee}} $+jets events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated Drell-Yan events, including statistical and systematic uncertainties (pink band). The regions shaded grey contain VH hadronic BDT scores below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 8-a:
Distribution of the VH hadronic BDT output score in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, for data events passing the preselection (black points), and for simulated background events (red band). Histograms are also shown for different components of the simulated background in red. The sum of all background distributions is scaled to the data. The orange histogram corresponds to simulated VH hadronic signal events. The regions shaded grey contain VH hadronic BDT scores below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 8-b:
Distribution of the VH hadronic BDT output score in events with ${m_{\gamma \gamma}}$ in the range 100-120 or 130-180 GeV, in $ {\mathrm{Z} \to \mathrm{ee}} $+jets events where the electrons are reconstructed as photons. The points show the score for data, the histogram shows the score for simulated Drell-Yan events, including statistical and systematic uncertainties (pink band). The regions shaded grey contain VH hadronic BDT scores below the lowest threshold used to define an analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 9:
Output scores for the three VH leptonic BDTs. The VH MET BDT is shown in the upper left, with the ZH leptonic BDT in the upper right, and the WH leptonic BDT below. In each case, the signal and background simulation are shown as histograms with the data as black points. Events are taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The statistical uncertainty in the data points is denoted as vertical bars and that on the background simulation by the pink band. The simulated signal and background distributions are normalised to the luminosity of the data. To increase its visibility, the signal is scaled by a factor of 500 for the VH MET BDT, with a factor of 50 applied for both ZH leptonic and WH leptonic BDTs. The regions shaded grey are not considered in the analysis. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 9-a:
Distribution of the output score for the VH MET BDT. The signal and background simulation are shown as histograms with the data as black points. Events are taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The statistical uncertainty in the data points is denoted as vertical bars and that on the background simulation by the pink band. The simulated signal and background distributions are normalised to the luminosity of the data. To increase its visibility, the signal is scaled by a factor of 500. The regions shaded grey are not considered in the analysis. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 9-b:
Distribution of the output score for the ZH leptonic BDT. The signal and background simulation are shown as histograms with the data as black points. Events are taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The statistical uncertainty in the data points is denoted as vertical bars and that on the background simulation by the pink band. The simulated signal and background distributions are normalised to the luminosity of the data. To increase its visibility, the signal is scaled by a factor of 50. The regions shaded grey are not considered in the analysis. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 9-c:
Distribution of the output score for the WH leptonic BDT. The signal and background simulation are shown as histograms with the data as black points. Events are taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The statistical uncertainty in the data points is denoted as vertical bars and that on the background simulation by the pink band. The simulated signal and background distributions are normalised to the luminosity of the data. To increase its visibility, the signal is scaled by a factor of 50. The regions shaded grey are not considered in the analysis. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 10:
Distributions of tHq BDT-bkg score (left) and the top DNN (right), which are used together to define the tHq leptonic analysis category. Events are taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The statistical uncertainty in the background estimation is represented by the pink band. The regions shaded grey contain BDT-bkg and top DNN scores below and above the respective thresholds for the tHq analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 10-a:
Distribution of the tHq BDT-bkg score, which is used to define the tHq leptonic analysis category. Events are taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The statistical uncertainty in the background estimation is represented by the pink band. The region shaded grey contains scores below the threshold for the tHq analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 10-b:
Distribution of the top DNN, which is used to define the tHq leptonic analysis category. Events are taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The statistical uncertainty in the background estimation is represented by the pink band. The region shaded grey contains scores above the threshold for the tHq analysis category. The full data set collected in 2016-2018 and the corresponding simulation are shown. |
png pdf |
Figure 11:
Distributions of BDT-bkg output used in the analysis categories targeting ttH production, for the leptonic (left) and the hadronic (right) channels. The upper two plots show events taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The lower two contain events from the ttZ control regions, described in the text. The grey region contains BDT-bkg scores below the lowest threshold for the ttH analysis categories. Total background uncertainties (statistical $\oplus $ systematic) are represented by the black (pink) shaded bands. |
png pdf |
Figure 11-a:
Distribution of BDT-bkg output used in the analysis categories targeting ttH production, for the leptonic channel. The plot shows events taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The grey region contains BDT-bkg scores below the lowest threshold for the ttH analysis categories. Total background uncertainties (statistical $\oplus $ systematic) are represented by the black (pink) shaded bands. |
png pdf |
Figure 11-b:
Distribution of BDT-bkg output used in the analysis categories targeting ttH production, for the hadronic channel. The plot shows events taken from the $ {m_{\gamma \gamma}} $ sidebands, satisfying either 100 $ < {m_{\gamma \gamma}} < $ 120 GeV or 130 $ < {m_{\gamma \gamma}} < $ 180 GeV. The grey region contains BDT-bkg scores below the lowest threshold for the ttH analysis categories. Total background uncertainties (statistical $\oplus $ systematic) are represented by the black (pink) shaded bands. |
png pdf |
Figure 11-c:
Distribution of BDT-bkg output used in the analysis categories targeting ttH production, for the leptonic channel. The plot contains events from the ttZ control regions, described in the text. The grey region contains BDT-bkg scores below the lowest threshold for the ttH analysis categories. Total background uncertainties (statistical $\oplus $ systematic) are represented by the black (pink) shaded bands. |
png pdf |
Figure 11-d:
Distribution of BDT-bkg output used in the analysis categories targeting ttH production, for the hadronic channel. The plot contains events from the ttZ control regions, described in the text. The grey region contains BDT-bkg scores below the lowest threshold for the ttH analysis categories. Total background uncertainties (statistical $\oplus $ systematic) are represented by the black (pink) shaded bands. |
png pdf |
Figure 12:
The shape of the parametric signal model for each year of simulated data, and for the sum of all years together, is shown. The open squares represent weighted simulation events and the blue line the corresponding model. Also shown is the ${\sigma _{\text {eff}}}$ value (half the width of the narrowest interval containing 68.3% of the ${m_{\gamma \gamma}}$ distribution) in the grey shaded area. The contribution of the signal model from each year of data taking is illustrated with the dotted lines. The models are shown for an analysis category targeting ggH 0J high ${{p_{\mathrm {T}}} ^\mathrm{H}}$ production (left), and for the weighted sum of all analysis categories (right). Here each analysis category is weighted by S/(S+B), where S and B are the numbers of expected signal and background events, respectively, in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. |
png pdf |
Figure 12-a:
The shape of the parametric signal model for each year of simulated data, and for the sum of all years together, is shown. The open squares represent weighted simulation events and the blue line the corresponding model. Also shown is the ${\sigma _{\text {eff}}}$ value (half the width of the narrowest interval containing 68.3% of the ${m_{\gamma \gamma}}$ distribution) in the grey shaded area. The contribution of the signal model from each year of data taking is illustrated with the dotted lines. The models are shown for an analysis category targeting ggH 0J high ${{p_{\mathrm {T}}} ^\mathrm{H}}$ production. |
png pdf |
Figure 12-b:
The shape of the parametric signal model for each year of simulated data, and for the sum of all years together, is shown. The open squares represent weighted simulation events and the blue line the corresponding model. Also shown is the ${\sigma _{\text {eff}}}$ value (half the width of the narrowest interval containing 68.3% of the ${m_{\gamma \gamma}}$ distribution) in the grey shaded area. The contribution of the signal model from each year of data taking is illustrated with the dotted lines. The models are shown for the weighted sum of all analysis categories. Here each analysis category is weighted by S/(S+B), where S and B are the numbers of expected signal and background events, respectively, in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. |
png pdf |
Figure 13:
The composition of the analysis categories in terms of a merged set of STXS bins is shown. The granularity of the STXS bin merging corresponds to the finest granularity used for the cross section measurements in this analysis. Analysis categories targeting a common STXS region are summed, where the signal compositions of the individual categories are weighted in the sum by the expected ratio of signal to signal-plus-background events. The colour scale corresponds to the fractional yield in each analysis category group (rows) accounted for by each STXS process (columns). Each row therefore sums to 100%. Entries with values less than 0.5% are not shown. Simulated events for each year in the period 2016-2018 are combined with appropriate weights corresponding to their relative integrated luminosity in data. The column labelled as "qqH rest" includes contributions from the qqH 0J, qqH 1J, qqH $ {m_{\text {jj}}} < $ 60 GeV and qqH 120 $ < {m_{\gamma \gamma}} < $ 350 GeV STXS bins. |
png pdf |
Figure 14:
Data points (black) and signal-plus-background model fit for the sum of all analysis categories is shown. Each analysis category is weighted by S/(S+B), where S and B are the numbers of expected signal and background events, respectively, in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. The one (green) standard deviation and two (yellow) standard deviation bands show the uncertainties in the background component of the fit. The solid red line shows the total signal-plus-background contribution, whereas the dashed red line shows the background component only. The lower panel shows the residuals after subtraction of this background component. |
png pdf |
Figure 15:
The best fit signal-plus-background model with data points (black) in the fit to signal strength modifiers of the four principal production modes. The model is shown separately for groups of analysis categories targeting the ggH (upper left), VBF (upper right), VH (lower left) and top quark associated (lower right) production modes. Here, the analysis categories in each group are summed after weighting by S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. The one standard deviation (green) and two standard deviation (yellow) bands show the uncertainties in the background component of the fit. The solid red line shows the total signal-plus-background contribution, whereas the dashed red line represents the background component only. The lower panel in each plot shows the residuals after subtraction of this background component. |
png pdf |
Figure 15-a:
The best fit signal-plus-background model with data points (black) in the fit to signal strength modifiers of the four principal production modes. The model is shown for groups of analysis categories targeting the ggH production modes. Here, the analysis categories in each group are summed after weighting by S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. The one standard deviation (green) and two standard deviation (yellow) bands show the uncertainties in the background component of the fit. The solid red line shows the total signal-plus-background contribution, whereas the dashed red line represents the background component only. The lower panel shows the residuals after subtraction of this background component. |
png pdf |
Figure 15-b:
The best fit signal-plus-background model with data points (black) in the fit to signal strength modifiers of the four principal production modes. The model is shown for groups of analysis categories targeting the VBF production modes. Here, the analysis categories in each group are summed after weighting by S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. The one standard deviation (green) and two standard deviation (yellow) bands show the uncertainties in the background component of the fit. The solid red line shows the total signal-plus-background contribution, whereas the dashed red line represents the background component only. The lower panel shows the residuals after subtraction of this background component. |
png pdf |
Figure 15-c:
The best fit signal-plus-background model with data points (black) in the fit to signal strength modifiers of the four principal production modes. The model is shown for groups of analysis categories targeting the VH production modes. Here, the analysis categories in each group are summed after weighting by S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. The one standard deviation (green) and two standard deviation (yellow) bands show the uncertainties in the background component of the fit. The solid red line shows the total signal-plus-background contribution, whereas the dashed red line represents the background component only. The lower panel shows the residuals after subtraction of this background component. |
png pdf |
Figure 15-d:
The best fit signal-plus-background model with data points (black) in the fit to signal strength modifiers of the four principal production modes. The model is shown for groups of analysis categories targeting the top quark associated production modes. Here, the analysis categories in each group are summed after weighting by S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ ${m_{\gamma \gamma}}$ window centred on ${m_\mathrm{H}}$. The one standard deviation (green) and two standard deviation (yellow) bands show the uncertainties in the background component of the fit. The solid red line shows the total signal-plus-background contribution, whereas the dashed red line represents the background component only. The lower panel shows the residuals after subtraction of this background component. |
png pdf |
Figure 16:
Observed results of the fit to signal strength modifiers of the four principal production modes. The contributions to the total uncertainty in each parameter from the theoretical systematic, experimental systematic, and statistical components are shown. The colour scheme is chosen to match the diagram presented in Fig. 1. The compatibility of this fit with respect to the SM prediction, expressed as a $p$-value, is approximately 50%. Also shown in black is the result of the fit to the inclusive signal strength modifier, which has a $p$-value of 17%. |
png pdf |
Figure 17:
A summary of the impact of the main sources of systematic uncertainty in the fit to signal strength modifiers of the four principal production modes. The observed (expected) impacts are shown by the solid (empty) bars. The colour scheme is chosen to match the diagram presented in Fig. 1. |
png pdf |
Figure 18:
Observed results of the maximal merging scheme STXS fit. The best fit cross sections are plotted together with the respective 68% CL intervals. The systematic components of the uncertainty in each parameter are shown by the coloured boxes. The hatched grey boxes demonstrate the theoretical uncertainties in the SM predictions. The lower panel shows the ratio of the fitted values to the SM predictions. Here the tH cross section ratio has a different scale, due to its high best fit value and uncertainty. The cross sections are constrained to be non-negative, as indicated by the hashed pattern below zero. The parameters whose best fit values are at zero are known to have 68% CL intervals which slightly under-cover; this is checked to be a small effect using pseudo-experiments. The colour scheme is chosen to match the diagram presented in Fig. 1. The compatibility of this fit with respect to the SM prediction, expressed as a $p$-value, is approximately 31%. |
png pdf |
Figure 19:
Observed correlations between the 17 parameters considered in the maximal merging STXS fit. The size of the correlations is indicated by the colour scale. |
png pdf |
Figure 20:
Observed results of the minimal merging scheme STXS fit. The best fit cross sections are plotted together with the respective 68% CL intervals. The systematic components of the uncertainty in each parameter are shown by the coloured boxes. The hatched grey boxes demonstrate the theoretical uncertainties in the SM predictions. The lower panel shows the ratio of the fitted values to the SM predictions. Here the tH cross section ratio has a different scale, due to its high best fit value and uncertainty. The cross sections are constrained to be non-negative, as indicated by the hashed pattern below zero. The parameters whose best fit values are at zero are known to have 68% CL intervals which slightly under-cover; this is checked to be a small effect using pseudo-experiments. The colour scheme is chosen to match the diagram presented in Fig. 1. The orange lines dashed with blue for the VBF-like parameters represent contributions from both the ggH and the qqH STXS bins. The compatibility of this fit with respect to the SM prediction, expressed as a $p$-value, is approximately 70%. |
png pdf |
Figure 21:
Observed correlations between the 27 parameters considered in the minimal merging STXS fit. The size of the correlations is indicated by the colour scale. |
png pdf |
Figure 22:
Observed two-dimensional likelihood scans performed in the $\kappa $-framework: $ {\kappa _{\mathrm{V}}} $-vs-$ {\kappa _\text {F}} $ in the resolved $\kappa $ model (upper) and $ {\kappa _\gamma} $-vs-$ {\kappa _\mathrm{g}} $ in the unresolved $\kappa $ model (lower). The 68 and 95% CL regions are given by the solid and dashed contours, respectively. The best fit and SM points are shown by the black cross and red diamond, respectively. The colour scale indicates the value of the test statistic. |
png pdf |
Figure 22-a:
Observed two-dimensional $ {\kappa _{\mathrm{V}}} $-vs-$ {\kappa _\text {F}} $ likelihood scan performed in the in the resolved $\kappa $ model. The 68 and 95% CL regions are given by the solid and dashed contours, respectively. The best fit and SM points are shown by the black cross and red diamond, respectively. The colour scale indicates the value of the test statistic. |
png pdf |
Figure 22-b:
Observed two-dimensional $ {\kappa _\gamma} $-vs-$ {\kappa _\mathrm{g}} $ likelihood scan performed in the in the unresolved $\kappa $ model. The 68 and 95% CL regions are given by the solid and dashed contours, respectively. The best fit and SM points are shown by the black cross and red diamond, respectively. The colour scale indicates the value of the test statistic. |
| Tables | |
png pdf |
Table 1:
Schema of the photon preselection requirements. The requirements depend both on whether a photon is in the barrel or endcap, and on its $ {R_\mathrm {9}}$ value. |
png pdf |
Table 2:
Definition of the ggH STXS bins. The product of the cross section and branching fraction ($\mathcal {B}$), evaluated at $ \sqrt {s}= $ 13 TeV and $ {m_\mathrm{H}} = $ 125 GeV, is given for each bin in the last column. The fraction of the total production mode cross section from each STXS bin is also shown. Events originating from ggZH production, in which the Z decays hadronically, are grouped with ggH in the STXS measurements and are shown as a separate column in the table. The bbH production mode, whose $\sigma _{\text {SM}}\mathcal {B}= $ 1.054 fb, is grouped together with the ggH 0J high ${{p_{\mathrm {T}}} ^\mathrm{H}}$ bin. Unless stated otherwise, the STXS bins are defined for $ {{| y_\mathrm{H} |}} < $ 2.5. Events with $ {{| y_\mathrm{H} |}} > $ 2.5 are mostly outside of the experimental acceptance and therefore have a negligible contribution to all analysis categories. |
png pdf |
Table 3:
The expected number of signal events for $ {m_\mathrm{H}} = $ 125 GeV in analysis categories targeting ggH production, excluding those targeting the VBF-like phase space, shown for an integrated luminosity of 137 fb$^{-1}$. The fraction of the total number of events arising from each production mode in each analysis category is provided, as is the fraction of events originating from the targeted STXS bin or bins. Entries with values less than 0.05% are not shown. Here qqH includes contributions from both VBF and hadronic VH production, whilst "Top" includes ttH and tH together. The $ {\sigma _{\text {eff}}} $, defined as the smallest interval containing 68.3% of the ${m_{\gamma \gamma}}$ distribution, is listed for each analysis category. The final column shows the expected ratio of signal to signal-plus-background, S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ window centred on $ {m_\mathrm{H}} $. |
png pdf |
Table 4:
Definition of the qqH STXS bins. The product of the cross section and branching fraction ($\mathcal {B}$), evaluated at $ \sqrt {s}= $ 13 TeV and $ {m_\mathrm{H}} = $ 125 GeV, is given for each bin in the last column. The fraction of the total production mode cross section from each STXS bin is also shown. Unless stated otherwise, the STXS bins are defined for $ {{| y_\mathrm{H} |}} < $ 2.5. Events with $ {{| y_\mathrm{H} |}} > $ 2.5 are mostly outside of the experimental acceptance and therefore have a negligible contribution to all analysis categories. |
png pdf |
Table 5:
The expected number of signal events for $ {m_\mathrm{H}} = $ 125 GeV in analysis categories targeting VBF-like phase space and VH production in which the vector boson decays hadronically, shown for an integrated luminosity of 137 fb$^{-1}$. The fraction of the total number of events arising from each production mode in each analysis category is provided, as is the fraction of events originating from the targeted STXS bin or bins. Entries with values less than 0.05% are not shown. Here ggH includes contributions from the ggZ (qqH and bbH production modes, whilst "Top" represents both ttH and tH production together. The $ {\sigma _{\text {eff}}} $, defined as the smallest interval containing 68.3% of the ${m_{\gamma \gamma}}$ distribution, is listed for each analysis category. The final column shows the expected ratio of signal to signal-plus-background, S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ window centred on $ {m_\mathrm{H}} $. |
png pdf |
Table 6:
Definition of the VH leptonic STXS bins. The product of the cross section and branching fraction ($\mathcal {B}$), evaluated at $ \sqrt {s}= $ 13 TeV and $ {m_\mathrm{H}} = $ 125 GeV, is given for each bin in the last column. The fraction of the total production mode cross section from each STXS bin is also shown. Unless stated otherwise, the STXS bins are defined for $ {{| y_\mathrm{H} |}} < $ 2.5. Events with $ {{| y_\mathrm{H} |}} > $ 2.5 are mostly outside of the experimental acceptance and therefore have a negligible contribution to all analysis categories. Only leptonic decays of the W and Z bosons are included in these definitions. |
png pdf |
Table 7:
The expected number of signal events for $ {m_\mathrm{H}} = $ 125 GeV in analysis categories targeting Higgs boson production in association with a leptonically decaying W or Z boson, shown for an integrated luminosity of 137 fb$^{-1}$. The fraction of the total number of events arising from each production mode in each analysis category is provided, as is the fraction of events originating from the targeted STXS bin or bins. Entries with values less than 0.05% are not shown. Here ggH includes contributions from the ggZ (qqH and bbH production modes, qqH incorporates both VBF and VH production with hadronic vector boson decays, and "Top" represents both ttH and tH production together. The $ {\sigma _{\text {eff}}} $, defined as the smallest interval containing 68.3% of the ${m_{\gamma \gamma}}$ distribution, is listed for each analysis category. The final column shows the expected ratio of signal to signal-plus-background, S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ window centred on $ {m_\mathrm{H}} $. |
png pdf |
Table 8:
Definition of the ttH, tH, and bbH STXS bins. The product of the cross section and branching fraction ($\mathcal {B}$), evaluated at $ \sqrt {s}= $ 13 TeV and $ {m_\mathrm{H}} = $ 125 GeV, is given for each bin in the last column. The fraction of the total production mode cross section from each STXS bin is also shown. Unless stated otherwise, the STXS bins are defined for $ {{| y_\mathrm{H} |}} < $ 2.5. Events with $ {{| y_\mathrm{H} |}} > $ 2.5 are mostly outside of the experimental acceptance and therefore have a negligible contribution to all analysis categories. |
png pdf |
Table 9:
The expected number of signal events for $ {m_\mathrm{H}} = $ 125 GeV in analysis categories targeting Higgs boson production in association with top quark, shown for an integrated luminosity of 137 fb$^{-1}$. The fraction of the total number of events arising from each production mode in each analysis category is provided, as is the fraction of events originating from the targeted STXS bin or bins. Entries with values less than 0.05% are not shown. Here ggH includes contributions from the ggZ (qqH and bbH production modes, whilst qqH incorporates both VBF and hadronic VH production. The $ {\sigma _{\text {eff}}} $, defined as the smallest interval containing 68.3% of the ${m_{\gamma \gamma}}$ distribution, is listed for each analysis category. The final column shows the expected ratio of signal to signal-plus-background, S/(S+B), where S and B are the numbers of expected signal and background events in a $ \pm $1$ {\sigma _{\text {eff}}} $ window centred on $ {m_\mathrm{H}} $. |
png pdf |
Table 10:
Description of the different categorisation regions, listed in descending order of priority in the first column. The second column shows each targeted STXS bin, or merged group of bins, together with the number of associated analysis categories. The last row contains the bins for which no analysis categories are constructed. |
png pdf |
Table 11:
A summary of the maximal and minimal parameter merging scenarios. The STXS bins that contribute to each parameter are listed. Furthermore, the bins that are constrained to their respective SM predictions in the fits are listed in the final row. |
png pdf |
Table 12:
Results of the maximal merging scheme STXS fit. The best fit cross sections are shown together with the respective 68% CL intervals. The uncertainty is decomposed into the systematic and statistical components. The expected uncertainties on the fitted parameters are given in brackets. Also listed are the SM predictions for the cross sections and the theoretical uncertainty in those predictions. |
png pdf |
Table 13:
Results of the minimal merging scheme STXS fit. The best fit cross sections are shown together with the respective 68% CL intervals. The uncertainty is decomposed into the systematic and statistical components. The expected uncertainties on the fitted parameters are given in brackets. Also listed are the SM predictions for the cross sections and the theoretical uncertainty in those predictions. |
| Summary |
|
Measurements of Higgs boson properties with the Higgs boson decaying into a pair of photons are reported. Events with two photons are selected from a sample of proton-proton collisions at a centre-of-mass energy $\sqrt{s}= $ 13 TeV collected with the CMS detector at the LHC from 2016 to 2018, corresponding to an integrated luminosity of 137 fb$^{-1}$. Analysis categories enriched in events produced via gluon fusion, vector boson fusion, vector boson associated production, production associated with two top quarks, and production associated with one top quark are constructed. A range of production and coupling properties of the Higgs boson are measured. The total Higgs boson signal strength, relative to the standard model (SM) prediction, is measured to be 1.12 $\pm$ 0.09. A simultaneous measurement of the signal strengths of the four principal Higgs boson production mechanisms is performed and found to be compatible with the SM prediction with a $p$-value of 50%. Two different measurements are performed within the simplified template cross section framework, in which 17 and 27 independent kinematic regions are measured simultaneously, with corresponding $p$-values with respect to the SM of 31 and 70%, respectively. Many of these kinematic regions are measured for the first time, including a simultaneous measurement of Higgs boson production in association with two top quarks in five different regions of the Higgs boson transverse momentum ${p_{\mathrm{T}}^{\mathrm{H}}}$. Furthermore, several additional measurements are the most precise made in a single channel to date. These include cross sections of vector boson fusion in different kinematic regions, gluon fusion in association with jets, and the region of gluon fusion production with ${p_{\mathrm{T}}^{\mathrm{H}}} > $ 200 GeV, which is particularly sensitive to physics beyond the SM. The gluon fusion cross section with ${p_{\mathrm{T}}^{\mathrm{H}}} > $ 200 GeV is found to be consistent with the SM, with a measured value of 0.9$_{-0.3}^{+0.4}$ relative to the SM prediction. An upper limit on the rate of Higgs boson production in association with a single top quark is also presented. The observed (expected) limit at 95% confidence level is found to be 14 (8) times the SM prediction. All other results, such as measurements of the Higgs boson's couplings to vector bosons and to fermions, are also in agreement with the SM expectations. |
| Additional Figures | |
png pdf |
Additional Figure 1:
Schematic to show the maximal merging scheme. The parameters of interest are defined by the solid boxes. |
png pdf |
Additional Figure 2:
Schematic to show the minimal merging scheme. The parameters of interest are defined by the solid boxes. The orange and blue boxes correspond to the VBF-like parameters which include contributions from both the ggH and qqH STXS bins. |
png pdf |
Additional Figure 3:
Observed correlations between the signal strength modifiers of the four principal production modes. The size of the correlations is indicated by the colour scale. |
png pdf |
Additional Figure 4:
Observed results of the STXS stage 0 fit. The best fit cross sections are plotted along with the respective 68% confidence intervals. The systematic components of the uncertainty in each parameter are shown by the coloured boxes. The hatched grey boxes demonstrate the theoretical uncertainties in the SM predictions. The lower panel shows the ratio of the fitted values to the SM predictions. Here the tH cross section ratio has a different scale, due to its high best fit value and uncertainty. The cross sections are constrained to be non-negative, as indicated by the hashed pattern below zero. The colour scheme is chosen to match the diagram presented in Fig. 1. The compatibility of this fit with respect to the SM prediction, expressed as a $p$-value, is approximately 61%. |
png pdf |
Additional Figure 5:
Observed correlations between the parameters in the STXS stage 0 fit. The size of the correlations is indicated by the colour scale. |
png pdf |
Additional Figure 6:
Observed two-dimensional likelihood scans for pairs of parameters in the maximal merging STXS fit with the largest correlations: ggH VBF-like vs qqH VBF-like (upper) and tH vs ttH (lower). The 68 and 95% CL regions are given by the solid and dashed contours, respectively. The best fit and SM points are shown by the black cross and red diamond, respectively. The parameters are plotted as a ratio with respect to their SM prediction. |
png pdf |
Additional Figure 6-a:
Observed two-dimensional likelihood scans for pairs of parameters in the maximal merging STXS fit with the largest correlations: ggH VBF-like vs qqH VBF-like (upper) and tH vs ttH (lower). The 68 and 95% CL regions are given by the solid and dashed contours, respectively. The best fit and SM points are shown by the black cross and red diamond, respectively. The parameters are plotted as a ratio with respect to their SM prediction. |
png pdf |
Additional Figure 6-b:
Observed two-dimensional likelihood scans for pairs of parameters in the maximal merging STXS fit with the largest correlations: ggH VBF-like vs qqH VBF-like (upper) and tH vs ttH (lower). The 68 and 95% CL regions are given by the solid and dashed contours, respectively. The best fit and SM points are shown by the black cross and red diamond, respectively. The parameters are plotted as a ratio with respect to their SM prediction. |
png pdf |
Additional Figure 7:
One-dimensional likelihood scans in $ {\kappa _\text {F}} $, in the resolved $\kappa $ model where the value of $ \kappa $ is profiled in the fit. The expected and observed scans are shown in red and black, respectively. |
png pdf |
Additional Figure 8:
Visualisations of a candidate single top-associated production event in data. The event is selected in the tHq leptonic analysis category and is characterised by two photon candidates with a diphoton invariant mass of 125.52 GeV, shown by the green blocks. The top quark decays into a W boson and a b quark. The long red line depicts the muon from the decay of the W boson and the red cone depicts the b-tagged jet originating from the b quark. The jet produced from the additional quark is shown as the orange cone. |
png pdf |
Additional Figure 8-a:
Visualisations of a candidate single top-associated production event in data. The event is selected in the tHq leptonic analysis category and is characterised by two photon candidates with a diphoton invariant mass of 125.52 GeV, shown by the green blocks. The top quark decays into a W boson and a b quark. The long red line depicts the muon from the decay of the W boson and the red cone depicts the b-tagged jet originating from the b quark. The jet produced from the additional quark is shown as the orange cone. |
png pdf |
Additional Figure 8-b:
Visualisations of a candidate single top-associated production event in data. The event is selected in the tHq leptonic analysis category and is characterised by two photon candidates with a diphoton invariant mass of 125.52 GeV, shown by the green blocks. The top quark decays into a W boson and a b quark. The long red line depicts the muon from the decay of the W boson and the red cone depicts the b-tagged jet originating from the b quark. The jet produced from the additional quark is shown as the orange cone. |
| Additional Tables | |
png pdf |
Additional Table 1:
Results of the STXS stage 0 fit. The best fit cross sections are shown together with the respective 68% CL intervals. The uncertainty is decomposed into the systematic and statistical components. The expected uncertainties on the fitted parameters, computed assuming the SM predicted cross section values, are given in brackets. Also listed are the SM predictions for the cross sections and the theoretical uncertainty in those predictions. |
| References | ||||
| 1 | ATLAS Collaboration | Observation of a new particle in the search for the standard model Higgs boson with the ATLAS detector at the LHC | PLB 716 (2012) 1 | 1207.7214 |
| 2 | CMS Collaboration | Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC | PLB 716 (2012) 30 | CMS-HIG-12-028 1207.7235 |
| 3 | CMS Collaboration | Observation of a new boson with mass near 125 GeV in pp collisions at $ \sqrt{s} = $ 7 and 8 TeV | JHEP 06 (2013) 081 | CMS-HIG-12-036 1303.4571 |
| 4 | CMS Collaboration | Observation of $ \mathrm{t\bar{t}}\mathrm{H} $ production | PRL 120 (2018) 231801 | CMS-HIG-17-035 1804.02610 |
| 5 | ATLAS Collaboration | Observation of Higgs boson production in association with a top quark pair at the LHC with the ATLAS detector | PLB 784 (2018) 173 | 1806.00425 |
| 6 | CMS Collaboration | Observation of Higgs boson decay to bottom quarks | PRL 121 (2018) 121801 | CMS-HIG-18-016 1808.08242 |
| 7 | ATLAS Collaboration | Observation of $ \mathrm{H} \rightarrow \mathrm{b\bar{b}} $ decays and VH production with the ATLAS detector | PLB 786 (2018) 59 | 1808.08238 |
| 8 | CMS Collaboration | Combined measurements of Higgs boson couplings in proton--proton collisions at $ \sqrt{s}= $ 13 TeV | EPJC 79 (2019) 421 | CMS-HIG-17-031 1809.10733 |
| 9 | ATLAS Collaboration | Combined measurements of Higgs boson production and decay using up to 80 fb$ ^{-1} $ of proton-proton collision data at $ \sqrt{s}= $ 13 TeV collected with the ATLAS experiment | PRD 101 (2020) 012002 | 1909.02845 |
| 10 | LHC Higgs Cross Section Working Group | Handbook of LHC Higgs cross sections: 4. deciphering the nature of the Higgs sector | CERN (2016) | 1610.07922 |
| 11 | CMS Collaboration | Observation of the diphoton decay of the Higgs boson and measurement of its properties | EPJC 74 (2014) 3076 | CMS-HIG-13-001 1407.0558 |
| 12 | CMS Collaboration | Measurements of Higgs boson properties in the diphoton decay channel in proton-proton collisions at $ \sqrt{s} = $ 13 TeV | JHEP 11 (2018) 185 | CMS-HIG-16-040 1804.02716 |
| 13 | M. Cepeda et al. | Report from Working Group 2: Higgs Physics at the HL-LHC and HE-LHC | in Proceedings of the HL/HE-LHC Workshop, A. Dainese et al., eds., volume 7, 2019, CERN Yellow Report | 1902.00134 |
| 14 | LHC Higgs Cross Section Working Group | Handbook of LHC Higgs cross sections: 3. Higgs properties | CERN (2013) | 1307.1347 |
| 15 | CMS Collaboration | HEPDATA record for this analysis | DOI | |
| 16 | CMS Collaboration | The CMS trigger system | JINST 12 (2017) P01020 | CMS-TRG-12-001 1609.02366 |
| 17 | CMS Collaboration | The CMS high level trigger | EPJC 46 (2006) 605 | hep-ex/0512077 |
| 18 | CMS Collaboration | Particle-flow reconstruction and global event description with the CMS detector | JINST 12 (2017) P10003 | CMS-PRF-14-001 1706.04965 |
| 19 | M. Cacciari, G. P. Salam, and G. Soyez | The anti-$ {k_{\mathrm{T}}} $ jet clustering algorithm | JHEP 04 (2008) 063 | 0802.1189 |
| 20 | M. Cacciari, G. P. Salam, and G. Soyez | FastJet user manual | EPJC 72 (2012) 1896 | 1111.6097 |
| 21 | 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 |
| 22 | CMS Collaboration | Performance of missing transverse momentum reconstruction in proton-proton collisions at $ \sqrt{s} = $ 13 TeV using the CMS detector | JINST 14 (2019) P07004 | CMS-JME-17-001 1903.06078 |
| 23 | CMS Collaboration | The CMS experiment at the CERN LHC | JINST 3 (2008) S08004 | CMS-00-001 |
| 24 | CMS Collaboration | Measurements of $ \mathrm{t\bar{t}}\mathrm{H} $ production and the CP structure of the Yukawa interaction between the Higgs boson and top quark in the diphoton decay channel | PRL 125 (2020) 061801 | CMS-HIG-19-013 2003.10866 |
| 25 | ATLAS Collaboration | Measurements of Higgs boson properties in the diphoton decay channel with 36 fb$ ^{-1} $ of pp collision data at $ \sqrt{s} = $ 13 TeV with the ATLAS detector | PRD 98 (2018) 052005 | 1802.04146 |
| 26 | ATLAS Collaboration | Higgs boson production cross-section measurements and their EFT interpretation in the $ 4\ell $ decay channel at $ \sqrt{s}= $ 13 TeV with the ATLAS detector | EPJC 80 (2020) 957 | 2004.03447 |
| 27 | ATLAS Collaboration | Measurements of gluon-gluon fusion and vector-boson fusion Higgs boson production cross-sections in the $ \mathrm{H} \to \mathrm{W}\mathrm{W}^{\ast} \to \mathrm{e}\nu\mu\nu $ decay channel in pp collisions at $ \sqrt{s}= $ 13 TeV with the ATLAS detector | PLB 789 (2019) 508 | 1808.09054 |
| 28 | ATLAS Collaboration | Cross-section measurements of the Higgs boson decaying into a pair of $ \tau $-leptons in proton-proton collisions at $ \sqrt{s}= $ 13 TeV with the ATLAS detector | PRD 99 (2019) 072001 | 1811.08856 |
| 29 | CMS Collaboration | Measurements of properties of the Higgs boson decaying into the four-lepton final state in pp collisions at $ \sqrt{s}= $ 13 TeV | JHEP 11 (2017) 047 | CMS-HIG-16-041 1706.09936 |
| 30 | CMS Collaboration | Measurements of properties of the Higgs boson decaying to a W boson pair in pp collisions at $ \sqrt{s}= $ 13 TeV | PLB 791 (2019) 96 | CMS-HIG-16-042 1806.05246 |
| 31 | CMS Collaboration | Observation of the Higgs boson decay to a pair of $ \tau $ leptons with the CMS detector | PLB 779 (2018) 283 | CMS-HIG-16-043 1708.00373 |
| 32 | N. Berger et al. | Simplified template cross sections -- stage 1.1 | LHC Higgs Cross Section Working Group Report LHCHXSWG-2019-003, DESY-19-070 | 1906.02754 |
| 33 | ATLAS Collaboration | Measurements of $ \mathrm{W}\mathrm{H} $ and $ \mathrm{Z}\mathrm{H} $ production in the $ \mathrm{H} \rightarrow \mathrm{b\bar{b}} $ decay channel in $ pp $ collisions at 13 TeV with the ATLAS detector | EPJC 81 (2021) 178 | 2007.02873 |
| 34 | CMS Collaboration | Measurements of production cross sections of the Higgs boson in the four-lepton final state in proton-proton collisions at $ \sqrt{s} = $ 13 TeV | Submitted to EPJC | CMS-HIG-19-001 2103.04956 |
| 35 | T. Chen and C. Guestrin | XGBoost: A scalable tree boosting system | in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016 | |
| 36 | H. Voss, A. Hocker, J. Stelzer, and F. Tegenfeldt | TMVA, the toolkit for multivariate data analysis with ROOT | in XIth International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT), 2007 | physics/0703039 |
| 37 | M. Abadi et al. | Tensorflow: A system for large-scale machine learning | in Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation, USENIX Association | |
| 38 | CMS Collaboration | CMS luminosity measurements for the 2016 data taking period | CMS-PAS-LUM-17-001 | CMS-PAS-LUM-17-001 |
| 39 | CMS Collaboration | CMS luminosity measurement for the 2017 data-taking period at $ \sqrt{s} = $ 13 TeV | CMS-PAS-LUM-17-004 | CMS-PAS-LUM-17-004 |
| 40 | CMS Collaboration | CMS luminosity measurement for the 2018 data-taking period at $ \sqrt{s} = $ 13 TeV | CMS-PAS-LUM-18-002 | CMS-PAS-LUM-18-002 |
| 41 | CMS Collaboration | Measurement of the inclusive $ \mathrm{W} $ and $ \mathrm{Z} $ production cross sections in pp collisions at $ \sqrt{s}= $ 7 TeV | JHEP 10 (2011) 132 | CMS-EWK-10-005 1107.4789 |
| 42 | 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 |
| 43 | K. Hamilton, P. Nason, E. Re, and G. Zanderighi | NNLOPS simulation of Higgs boson production | JHEP 10 (2013) 222 | 1309.0017 |
| 44 | T. Sjostrand et al. | An introduction to PYTHIA 8.2 | CPC 191 (2015) 159 | 1410.3012 |
| 45 | CMS Collaboration | Event generator tunes obtained from underlying event and multiparton scattering measurements | EPJC 76 (2016) 155 | CMS-GEN-14-001 1512.00815 |
| 46 | CMS Collaboration | Extraction and validation of a new set of CMS PYTHIA8 tunes from underlying-event measurements | EPJC 80 (2020) 4 | CMS-GEN-17-001 1903.12179 |
| 47 | NNPDF Collaboration | Parton distributions for the LHC Run II | JHEP 04 (2015) 040 | 1410.8849 |
| 48 | NNPDF Collaboration | Parton distributions from high-precision collider data | EPJC 77 (2017) 663 | 1706.00428 |
| 49 | P. Nason | A new method for combining NLO QCD with shower Monte Carlo algorithms | JHEP 11 (2004) 040 | hep-ph/0409146 |
| 50 | S. Frixione, P. Nason, and C. Oleari | Matching NLO QCD computations with parton shower simulations: the POWHEG method | JHEP 11 (2007) 070 | 0709.2092 |
| 51 | S. Alioli, P. Nason, C. Oleari, and E. Re | NLO Higgs boson production via gluon fusion matched with shower in POWHEG | JHEP 04 (2009) 002 | 0812.0578 |
| 52 | P. Nason and C. Oleari | NLO Higgs boson production via vector-boson fusion matched with shower in POWHEG | JHEP 02 (2010) 037 | 0911.5299 |
| 53 | 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 |
| 54 | H. B. Hartanto, B. Jager, L. Reina, and D. Wackeroth | Higgs boson production in association with top quarks in the POWHEG BOX | PRD 91 (2015) 094003 | 1501.04498 |
| 55 | T. Gleisberg et al. | Event generation with SHERPA 1.1 | JHEP 02 (2009) 007 | 0811.4622 |
| 56 | GEANT4 Collaboration | GEANT4--a simulation toolkit | NIMA 506 (2003) 250 | |
| 57 | CMS Collaboration | Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC | Submitted to JINST | CMS-EGM-17-001 2012.06888 |
| 58 | CMS Collaboration | A measurement of the Higgs boson mass in the diphoton decay channel | PLB 805 (2020) 135425 | CMS-HIG-19-004 2002.06398 |
| 59 | E. Spyromitros-Xioufis, G. Tsoumakas, W. Groves, and I. Vlahavas | Multi-target regression via input space expansion: treating targets as inputs | Machine Learning 104 (2016) 55 | 1211.6581 |
| 60 | CMS Collaboration | Pileup mitigation at CMS in 13 TeV data | JINST 15 (2020) P09018 | CMS-JME-18-001 2003.00503 |
| 61 | 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 |
| 62 | 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 |
| 63 | 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 |
| 64 | ATLAS Collaboration | $ CP $ properties of Higgs boson interactions with top quarks in the $ \mathrm{t\bar{t}}\mathrm{H} $ and $ \mathrm{t}\mathrm{H} $ processes using $ \mathrm{H} \rightarrow \gamma\gamma $ with the ATLAS detector | PRL 125 (2020) 061802 | 2004.04545 |
| 65 | CMS Collaboration | Search for direct production of supersymmetric partners of the top quark in the all-jets final state in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | JHEP 10 (2017) 005 | CMS-SUS-16-049 1707.03316 |
| 66 | 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 |
| 67 | G. Cowan, K. Cranmer, E. Gross, and O. Vitells | Asymptotic formulae for likelihood-based tests of new physics | EPJC 71 (2011) 1554 | 1007.1727 |
| 68 | R. A. Fisher | On the interpretation of $ \chi^2 $ from contingency tables, and the calculation of p | J. Royal Stat. Soc. 85 (1922) 87 | |
| 69 | P. D. Dauncey, M. Kenzie, N. Wardle, and G. J. Davies | Handling uncertainties in background shapes: the discrete profiling method | JINST 10 (2015) P04015 | 1408.6865 |
| 70 | CMS Collaboration | Measurements of $ \mathrm{t\overline{t}} $ differential cross sections in proton-proton collisions at $ \sqrt{s}= $ 13 TeV using events containing two leptons | JHEP 02 (2019) 149 | CMS-TOP-17-014 1811.06625 |
| 71 | CMS Collaboration | Measurements of $ \mathrm{t\bar{t}} $ cross sections in association with $ \mathrm{b} $ jets and inclusive jets and their ratio using dilepton final states in pp collisions at $ \sqrt{s} = $ 13 TeV | PLB 776 (2018) 355 | CMS-TOP-16-010 1705.10141 |
| 72 | J. Butterworth et al. | PDF4LHC recommendations for LHC Run II | JPG 43 (2016) 023001 | 1510.03865 |
| 73 | S. Dulat et al. | New parton distribution functions from a global analysis of quantum chromodynamics | PRD 93 (2016) 033006 | 1506.07443 |
| 74 | L. A. Harland-Lang, A. D. Martin, P. Motylinski, and R. S. Thorne | Parton distributions in the LHC era: MMHT 2014 PDFs | EPJC 75 (2015) 204 | 1412.3989 |
| 75 | S. Carrazza et al. | An unbiased Hessian representation for Monte Carlo PDFs | EPJC 75 (2015) 369 | 1505.06736 |
| 76 | J. Gao and P. Nadolsky | A meta-analysis of parton distribution functions | JHEP 07 (2014) 035 | 1401.0013 |
| 77 | CMS Collaboration | Jet algorithms performance in 13 TeV data | CMS-PAS-JME-16-003 | CMS-PAS-JME-16-003 |
| 78 | CMS Collaboration | Performance of the CMS Level-1 trigger in proton-proton collisions at $ \sqrt{s} = $ 13 TeV | JINST 15 (2020) P10017 | CMS-TRG-17-001 2006.10165 |
| 79 | The ATLAS Collaboration, The CMS Collaboration, The LHC Higgs Combination Group | Procedure for the LHC Higgs boson search combination in Summer 2011 | CMS-NOTE-2011-005 | |
|
|
Compact Muon Solenoid LHC, CERN |
|
|
|
|
|
|