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CMS-PAS-HIG-20-010
Search for nonresonant Higgs boson pair production in final states with two bottom quarks and two tau leptons in proton-proton collisions at $\sqrt{s} = $ 13 TeV
Abstract: A search for the nonresonant production of Higgs boson pairs (HH) via gluon-gluon and vector boson fusion processes in final states with two bottom quarks and two tau leptons is presented. The search uses data from proton-proton collisions at a center-of-mass energy of $\sqrt{s}= $ 13 TeV recorded with the CMS detector at the LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. Events in which at least one tau lepton decays hadronically are considered and multiple machine learning techniques are used to identify and extract the signal. The data are found to be consistent, within uncertainties, with the standard model background predictions. Upper limits on the HH production cross section are set to constrain the parameter space for anomalous Higgs boson couplings. The observed (expected) upper limit at 95% confidence level corresponds to 3.3 (5.2) times the standard model prediction for the inclusive HH cross section and to 124 (154) times the standard model prediction for the vector boson fusion HH cross section. At a 95% confidence level, the Higgs field self-coupling is constrained to be within $-$1.8 and 8.8 times the standard model expectation, and the coupling of two Higgs bosons to two vector bosons is constrained to be within $-$0.4 and 2.6.
Figures & Tables Summary Additional Figures References CMS Publications
Figures

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Figure 1:
Feynman diagrams contributing to Higgs boson pair production via gluon-gluon fusion in the SM at leading order.

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Figure 2:
Feynman diagrams contributing to Higgs boson pair production via vector boson fusion in the SM at leading order.

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Figure 3:
DNN prediction distributions in the ${\tau _{{\text h}}\tau _{{\text h}}}$ channel in 2018 for the most sensitive category in the ggF (left) and VBF (right) searches. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Figure 3-a:
DNN prediction distributions in the ${\tau _{{\text h}}\tau _{{\text h}}}$ channel in 2018 for the most sensitive category in the ggF search. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Figure 3-b:
DNN prediction distributions in the ${\tau _{{\text h}}\tau _{{\text h}}}$ channel in 2018 for the most sensitive category in the VBF search. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Figure 4:
Combination of bins of all postfit distributions, ordered and merged according to their prefit signal-to-background ratio, separately for the ${\tau _{\mathrm{e}} \tau _{{\text h}}}$ channel (top left), the ${\tau _{\mu} \tau _{{\text h}}}$ channel (top right), and ${\tau _{{\text h}}\tau _{{\text h}}}$ channel (bottom). The ratio also shows the signal scaled to the observed exclusion limit (see Table 2).

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Figure 4-a:
Combination of bins of all postfit distributions, ordered and merged according to their prefit signal-to-background ratio, separately for the ${\tau _{\mathrm{e}} \tau _{{\text h}}}$ channel. The ratio also shows the signal scaled to the observed exclusion limit (see Table 2).

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Figure 4-b:
Combination of bins of all postfit distributions, ordered and merged according to their prefit signal-to-background ratio, separately for the ${\tau _{\mu} \tau _{{\text h}}}$ channel. The ratio also shows the signal scaled to the observed exclusion limit (see Table 2).

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Figure 4-c:
Combination of bins of all postfit distributions, ordered and merged according to their prefit signal-to-background ratio, separately for the ${\tau _{{\text h}}\tau _{{\text h}}}$ channel. The ratio also shows the signal scaled to the observed exclusion limit (see Table 2).

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Figure 5:
Combination of bins of all postfit distributions, ordered and merged according to their prefit signal-to-background ratio, separately for the background contribution split into physics processes (left), and split into the three considered final state channels (right). The ratio also shows the signal scaled to the observed exclusion limit (see Table 2).

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Figure 5-a:
Combination of bins of all postfit distributions, ordered and merged according to their prefit signal-to-background ratio, separately for the background contribution split into physics processes. The ratio also shows the signal scaled to the observed exclusion limit (see Table 2).

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Figure 5-b:
Combination of bins of all postfit distributions, ordered and merged according to their prefit signal-to-background ratio, separately for the background contribution split into the three considered final state channels. The ratio also shows the signal scaled to the observed exclusion limit (see Table 2).

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Figure 6:
Upper limit on the HH ggF + VBF signal strength at 95% CL for $\kappa _{\lambda} = $ 1, separated into different years and combined for the full Run 2 data set.

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Figure 7:
Observed and expected upper limits at 95% CL as a function of $\kappa _{\lambda}$ on the HH ggF + VBF signal strength (left) and on the HH ggF + VBF cross section times the bb$ \tau \tau $ branching ratio (right). In both cases all other couplings are set to their SM expectation.

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Figure 7-a:
Observed and expected upper limits at 95% CL as a function of $\kappa _{\lambda}$ on the HH ggF + VBF signal strength. All other couplings are set to their SM expectation.

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Figure 7-b:
Observed and expected upper limits at 95% CL as a function of $\kappa _{\lambda}$ on the HH ggF + VBF cross section times the bb$ \tau \tau $ branching ratio. All other couplings are set to their SM expectation.

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Figure 8:
Upper limit on the HH VBF signal strength at 95% CL for $\kappa _{2{\mathrm{V}}} = $ 1, separated into different years and combined for the full Run 2 data set.

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Figure 9:
Observed and expected upper limits at 95% CL as a function of $\kappa _{2{\mathrm{V}}}$ on the HH VBF signal strength (left) and on the HH VBF cross section times the bb$ \tau \tau $ branching ratio (right). In both cases all other couplings are set to their SM expectation.

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Figure 9-a:
Observed and expected upper limits at 95% CL as a function of $\kappa _{2{\mathrm{V}}}$ on the HH VBF signal strength. All other couplings are set to their SM expectation.

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Figure 9-b:
Observed and expected upper limits at 95% CL as a function of $\kappa _{2{\mathrm{V}}}$ on the HH VBF cross section times the bb$ \tau \tau $ branching ratio. All other couplings are set to their SM expectation.

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Figure 10:
Two-dimensional exclusion regions as a function of the $\kappa _{\lambda}$ and $\kappa _{\mathrm{t}}$ couplings for the full Run2 combination (left), both $\kappa _{2{\mathrm{V}}}$ and $\kappa _{{\mathrm{V}}}$ are fixed to unity. Two-dimensional exclusion regions as a function of the $\kappa _{2{\mathrm{V}}}$ and $\kappa _{{\mathrm{V}}}$ couplings (right), both $\kappa _{\lambda}$ and $\kappa _{\mathrm{t}}$ are set to unity. Expected uncertainties on exclusion boundaries are inferred from uncertainty bands of the limit calculation, and are denoted by dark and light grey areas. The blue area marks parameter combinations that are observed to be excluded. For visual guidance, theoretical cross section values are illustrated by thin, labeled contour lines with the SM configuration denoted by a red diamond.

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Figure 10-a:
Two-dimensional exclusion regions as a function of the $\kappa _{\lambda}$ and $\kappa _{\mathrm{t}}$ couplings for the full Run2 combination, both $\kappa _{2{\mathrm{V}}}$ and $\kappa _{{\mathrm{V}}}$ are fixed to unity. Expected uncertainties on exclusion boundaries are inferred from uncertainty bands of the limit calculation, and are denoted by dark and light grey areas. The blue area marks parameter combinations that are observed to be excluded. For visual guidance, theoretical cross section values are illustrated by thin, labeled contour lines with the SM configuration denoted by a red diamond.

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Figure 10-b:
Two-dimensional exclusion regions as a function of the $\kappa _{2{\mathrm{V}}}$ and $\kappa _{{\mathrm{V}}}$ couplings, both $\kappa _{\lambda}$ and $\kappa _{\mathrm{t}}$ are set to unity. Expected uncertainties on exclusion boundaries are inferred from uncertainty bands of the limit calculation, and are denoted by dark and light grey areas. The blue area marks parameter combinations that are observed to be excluded. For visual guidance, theoretical cross section values are illustrated by thin, labeled contour lines with the SM configuration denoted by a red diamond.

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Figure 11:
Observed likelihood scan as a function of $\kappa _{\lambda}$ (left) and $\kappa _{2{\mathrm{V}}}$ (right) for the full Run 2 combination. The dashed lines show the intersection with threshold values one and four, corresponding to 68% and 95% confidence intervals, respectively.

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Figure 11-a:
Observed likelihood scan as a function of $\kappa _{\lambda}$ for the full Run 2 combination. The dashed lines show the intersection with threshold values one and four, corresponding to 68% and 95% confidence intervals, respectively.

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Figure 11-b:
Observed likelihood scan as a function of $\kappa _{2{\mathrm{V}}}$ for the full Run 2 combination. The dashed lines show the intersection with threshold values one and four, corresponding to 68% and 95% confidence intervals, respectively.
Tables

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Table 1:
Summary of selections applied to the $\tau \tau $ pair. Trigger thresholds in parentheses refer to the 2017-2018 data-taking period.

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Table 2:
Expected and observed upper limits at 95% CL for the SM point ($\kappa _{\lambda} = $ 1), where $\sigma _{ggF + \text {VBF}}^{SM}=$ 2.39 fb represents the product of the ggF plus VBF HH cross section (32.776 fb) and the branching fraction $\mathcal {B}({\mathrm{H} \mathrm{H}} \to \mathrm{b} \mathrm{b} \tau \tau)=$ 0.073.

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Table 3:
Expected and observed upper limits at 95% CL for the SM point ($\kappa _{2{\mathrm{V}}} = $ 1), where $\sigma _{\text {VBF}}^{SM}=$ 0.126 fb represents the product of the VBF HH cross section (1.726 fb) and the branching fraction $\mathcal {B}({\mathrm{H} \mathrm{H}} \to \mathrm{b} \mathrm{b} \tau \tau)=$ 0.073.
Summary
A search for nonresonant Higgs boson pair (HH) production via gluon-gluon fusion and vector boson fusion (VBF) processes in final states with two bottom quarks and two $\tau$ leptons was presented. The search uses the full Run 2 data set of proton-proton collisions at a center-of-mass energy of $\sqrt{s} = $ 13 TeV recorded with the CMS detector at the LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. The three decay modes of the $\tau\tau$ pair with the largest branching fraction have been selected, requiring one $\tau$ to be always decaying hadronically and the other one either leptonically or hadronically. Upper limits at the 95% confidence level (CL) on the inclusive HH production cross sections are set, as well as on the VBF HH production cross sections.

This analysis benefits from an improved trigger strategy as well as from a series of techniques developed especially for this search: among others, several neural networks to identify the b jets from the H decay, categorize the events, and perform signal extraction. At the same time, this analysis builds up on the improvements made by the CMS Collaboration in the jet and $\tau$ lepton identification and reconstruction algorithms. All these techniques enable the achievement of particularly stringent results on the HH production cross sections.

The observed 95% CL upper limit on HH total production cross section corresponds to 3.3 times the theoretical SM prediction, and the expected limit is 5.2 times the SM prediction. The observed 95% CL upper limit for the VBF HH SM cross section corresponds to 124 times the theoretical SM prediction and the expected limits is about 154 times the SM prediction.

The observed (expected) 95% CL constraints on $\kappa_{\lambda}$ and $\kappa_{2\mathrm{V}}$, derived from limits on the HH production cross section times the bb$\tau\tau$ branching ratio, are found to be $-$1.8 $< \kappa_{\lambda} < $ 8.8 ($-$3 $ < \kappa_{\lambda} < $ 9.9) and $-$0.4 $ < \kappa_{2\mathrm{V}} < $ 2.6 ($-$0.6 $ < \kappa_{2\mathrm{V}} < $ 2.8), respectively.
Additional Figures

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Additional Figure 1:
Distributions of the reconstructed mass of the bb pair in the most sensitive category of the analysis (res2b). Events are shown in the $\mathrm{e} {{\tau} _\mathrm {h}} $ (left), $\mu {{\tau} _\mathrm {h}} $ (center), and ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ (right) channels for the full Run 2 combination, after the selection on the reconstructed masses of the $ {\tau} {\tau} $ and bb pairs, as described in the paper, has been applied.

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Additional Figure 2:
Distributions of the mass of the $ {\tau} {\tau} $ pair, reconstructed using the SVfit algorithm [47], in the most sensitive category of the analysis (res2b). Events are shown in the $\mathrm{e} {{\tau} _\mathrm {h}} $ (left), $\mu {{\tau} _\mathrm {h}} $ (center), and ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ (right) channels for the full Run 2 combination, after the selection on the reconstructed masses of the $ {\tau} {\tau} $ and bb pairs, as described in the paper, has been applied.

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Additional Figure 3:
Distributions of the reconstructed mass of the HH pair in the most sensitive category of the analysis (res2b). Events are shown in the $\mathrm{e} {{\tau} _\mathrm {h}} $ (left), $\mu {{\tau} _\mathrm {h}} $ (center), and ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ (right) channels for the full Run 2 combination, after the selection on the reconstructed masses of the $ {\tau} {\tau} $ and bb pairs, as described in the paper, has been applied.

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Additional Figure 4:
Normalized distribution of reconstructed $m_{{{\mathrm {H}} {\mathrm {H}}}}$ for the gluon fusion simulated signal events (ggHH) in a common baseline selection for the combination in the three channels, with and without trigger selection applied. Two b jet and two ${\tau}$ lepton candidates are required in the event. The efficiency of the trigger selection is shown in the bottom frame.

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Additional Figure 5:
Normalized distribution of reconstructed $m_{{{\mathrm {H}} {\mathrm {H}}}}$ for the vector boson fusion simulated signal events (qqHH) in a common baseline selection for the combination in the three channels, with and without trigger selection applied. Two b jet and two ${\tau}$ lepton candidates are required in the event. The efficiency of the trigger selection is shown in the bottom frame.

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Additional Figure 6:
DNN prediction distributions in the $\mathrm{e} {{\tau} _\mathrm {h}} $ channel in 2016 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 7:
DNN prediction distributions in the $\mathrm{e} {{\tau} _\mathrm {h}} $ channel in 2017 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 8:
DNN prediction distributions in the $\mathrm{e} {{\tau} _\mathrm {h}} $ channel in 2017 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 9:
DNN prediction distributions in the $\mu {{\tau} _\mathrm {h}} $ channel in 2016 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 10:
DNN prediction distributions in the $\mu {{\tau} _\mathrm {h}} $ channel in 2017 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 11:
DNN prediction distributions in the $\mu {{\tau} _\mathrm {h}} $ channel in 2018 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 12:
DNN prediction distributions in the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2016 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 13:
DNN prediction distributions in the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2017 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 14:
DNN prediction distributions in the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2018 for the eight analysis categories. The shaded band in the plots represents the statistical plus systematic uncertainty.

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Additional Figure 15:
Upper limit on the HH ggF + VBF signal strength at 95% CL, separated into different years and channels, and combined in different channels. All Higgs couplings are set to their SM expectation.

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Additional Figure 16:
Upper limit on the HH VBF signal strength at 95% CL, separated into different years and channels, and combined in different channels. All Higgs couplings are set to their SM expectation.

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Additional Figure 17:
Observed and expected upper limits, separated into categories, on the HH ggF + VBF signal strength at 95% CL as a function of $\kappa _{\lambda}$, with all other couplings set to their SM expectation.

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Additional Figure 18:
Observed and expected upper limits, separated into categories, on the HH VBF signal strength at 95% CL as a function of $\kappa _{2}$, with all other couplings set to their SM expectation.

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Additional Figure 19:
Two-dimensional exclusion regions as a function of the $\kappa _{\lambda}$ and $\kappa _{2}$ coupling modifiers for the full Run2 combination, both $\kappa _{}$ and $\kappa _{\mathrm{t}}$ are fixed to unity. Expected uncertainties on exclusion boundaries are inferred from uncertainty bands of the limit calculation, and are denoted by dark and light grey areas. The blue area marks parameter combinations that are observed to be excluded. For visual guidance, theoretical cross section values are illustrated by thin, labeled contour lines with the SM configuration denoted by a red diamond.

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Additional Figure 20:
Observed likelihood scan as a function of $\kappa _{\mathrm{t}}$ for the full Run 2 combination. The dashed lines show the intersection with threshold values one and four, corresponding to 68% and 95% confidence intervals, respectively.

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Additional Figure 21:
Observed likelihood scan as a function of $\kappa _{}$ for the full Run 2 combination. The dashed lines show the intersection with threshold values one and four, corresponding to 68% and 95% confidence intervals, respectively.

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Additional Figure 22:
2D likelihood scan as function of $\kappa _{2}$ and $\kappa _{}$, assuming $r=\kappa _{\mathrm{t}}=\kappa _{\lambda}=1$. The best fit value and its uncertainty are denoted by the black marker and lines, whereas the full uncertainty contours referring to one and two standard deviations are visualized by the green and yellow lines, respectively. The enclosing box refers to the uncertainty construction as described in [62], Figure 40.5. The red diamond represents the SM prediction.

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Additional Figure 23:
2D likelihood scan as function of $\kappa _{\lambda}$ and $\kappa _{2}$, assuming $r=\kappa _{\mathrm{t}}=\kappa _{}=1$. The best fit value and its uncertainty are denoted by the black marker and lines, whereas the full uncertainty contours referring to one and two standard deviations are visualized by the green and yellow lines, respectively. The enclosing box refers to the uncertainty construction as described in [62], Figure 40.5. The red diamond represents the SM prediction.

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Additional Figure 24:
2D likelihood scan as function of $\kappa _{\lambda}$ and $\kappa _{\mathrm{t}}$, assuming $r=\kappa _{2}=\kappa _{}=1$. The best fit value and its uncertainty are denoted by the black marker and lines, whereas the full uncertainty contours referring to one and two standard deviations are visualized by the green and yellow lines, respectively. The enclosing box refers to the uncertainty construction as described in [62], Figure 40.5. The red diamond represents the SM prediction.

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Additional Figure 25:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the res2b category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2016.

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Additional Figure 25-a:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the res2b category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2016.

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Additional Figure 25-b:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the res2b category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2016.

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Additional Figure 25-c:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the res2b category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2016.

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Additional Figure 26:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the \textit {classVBF} category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2018.

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Additional Figure 26-a:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the \textit {classVBF} category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2018.

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Additional Figure 26-b:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the \textit {classVBF} category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2018.

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Additional Figure 26-c:
Displays in the transverse (top left) and longitudinal (top right) planes and tridimensional (bottom) view of a candidate $ {{\mathrm {H}} {\mathrm {H}}} \to {\tau} {\tau} {\mathrm {b}} {\mathrm {b}} $ event in the \textit {classVBF} category of the ${{\tau} _{{\text h}} {\tau} _{{\text h}}}$ channel in 2018.
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 proton-proton collisions at $ \sqrt{s}= $ 7 and 8 TeV JHEP 06 (2013) 081 CMS-HIG-12-036
1303.4571
4 ATLAS, CMS Collaboration Combined measurement of the Higgs boson mass in proton-proton collisions at $ \sqrt{s}= $ 7 and 8 TeV with the ATLAS and CMS Experiments PRL 114 (2015) 191803 1503.07589
5 ATLAS, CMS Collaboration Measurements of the Higgs boson production and decay rates and constraints on its couplings from a combined ATLAS and CMS analysis of the LHC proton-proton collision data at $ \sqrt{s}= $ 7 and 8 TeV JHEP 08 (2016) 045 1606.02266
6 M. Grazzini et al. Higgs boson pair production at NNLO with top quark mass effects JHEP 05 (2018) 1803.0246
7 F. A. Dreyer and A. Karlberg Vector-boson fusion Higgs pair production at $ {\mathrm{N}}^{3}\mathrm{LO} $ PRD 98 (2018) 114016 1811.07906
8 B. Di Micco et al. Higgs boson pair production at colliders: status and perspectives Rev. Phys. 5 (2020) 100045 1910.00012
9 CMS Collaboration Search for Higgs boson pair production in events with two bottom quarks and two tau leptons in proton-proton collisions at $ \sqrt{s} = $ 13 TeV PLB 778 (2017) 101 CMS-HIG-17-002
1707.02909
10 ATLAS Collaboration Search for resonant and nonresonant Higgs boson pair production in the $ \mathrm{b}\mathrm{\bar{b}}\tau^{+}\tau^{-} $ decay channel in proton-proton collisions at $ \sqrt{s} = $ 13 TeV with the ATLAS detector PRL 121 (2018) 191801 1808.00336
11 CMS Collaboration Identification of hadronic tau lepton decays using a deep neural network 2022. Submitted to JINST CMS-TAU-20-001
2201.08458
12 E. Bols et al. Jet flavour classification using DeepJet JINST 15 (2020) P12012 2008.10519
13 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
14 CMS Collaboration The CMS trigger system JINST 12 (2017) P01020 CMS-TRG-12-001
1609.02366
15 CMS Collaboration The CMS experiment at the CERN LHC JINST 3 (2008) S08004 CMS-00-001
16 CMS Collaboration CMS luminosity measurements for the 2016 data-taking period CMS-PAS-LUM-17-001 CMS-PAS-LUM-17-001
17 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
18 CMS Collaboration Precision luminosity measurement in proton-proton collisions at $ \sqrt{s} = $ 13 TeV in 2015 and 2016 at CMS EPJC 81 (2021) 800 CMS-LUM-17-003
2104.01927
19 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
20 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) 1405.0301
21 E. Re Single-top Wt-channel production matched with parton showers using the POWHEG method EPJC 71 (2011) 1009.2450
22 J. M. Campbell, R. K. Ellis, P. Nason, and E. Re Top-pair production and decay at NLO matched with parton showers JHEP 04 (2015) 1412.1828
23 G. Heinrich et al. Probing the trilinear Higgs boson coupling in di-Higgs production at NLO QCD including parton shower effects JHEP 06 (2019) 1903.08137
24 J. Alwall et al. Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions EPJC 53 (2007) 0706.2569
25 R. Frederix and S. Frixione Merging meets matching in MC@NLO JHEP 12 (2012) 1209.6215
26 T. Sjostrand et al. An introduction to PYTHIA 8.2 Computer Physics Communications 191 (2015) 1410.3012
27 CMS Collaboration Event generator tunes obtained from underlying event and multiparton scattering measurements EPJC 76 (2016) CMS-GEN-14-001
1512.00815
28 CMS Collaboration Investigations of the impact of the parton shower tuning in PYTHIA 8 in the modelling of $ \mathrm{t}\mathrm{\bar{t}} $ at $ \sqrt{s}= $ 8 and 13 TeV CMS-PAS-TOP-16-021 CMS-PAS-TOP-16-021
29 CMS Collaboration Extraction and validation of a new set of CMS PYTHIA 8 tunes from underlying-event measurements EPJC 80 (2020) CMS-GEN-17-001
1903.12179
30 CMS Collaboration Particle-flow reconstruction and global event description with the CMS detector JINST 12 (2017) P10003 CMS-PRF-14-001
1706.04965
31 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
32 CMS Collaboration Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC JINST 16 (2021) P05014 CMS-EGM-17-001
2012.06888
33 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
34 CMS Collaboration Performance of $ \tau $-lepton reconstruction and identification in CMS JINST 7 (2012) P01001 CMS-TAU-11-001
1109.6034
35 CMS Collaboration Reconstruction and identification of $ \tau $ lepton decays to hadrons and $ \nu_\tau $ at CMS JINST 11 (2016) P01019 CMS-TAU-14-001
1510.07488
36 CMS Collaboration Performance of reconstruction and identification of $ \tau $ leptons decaying to hadrons and $ \nu_\tau $ in proton-proton collisions at $ \sqrt{s}= $ 13 TeV JINST 13 (2018) P10005 CMS-TAU-16-003
1809.02816
37 M. Cacciari, G. P. Salam, and G. Soyez The anti-$ {k_{\mathrm{T}}} $ jet clustering algorithm JHEP 04 (2008) 063 0802.1189
38 M. Cacciari, G. P. Salam, and G. Soyez FastJet user manual EPJC 72 (2012) 1896 1111.6097
39 Y. L. Dokshitzer, G. D. Leder, S. Moretti, and B. R. Webber Better jet clustering algorithms JHEP 08 (1997) 001 hep-ph/9707323
40 M. Wobisch and T. Wengler Hadronization corrections to jet cross-sections in deep inelastic scattering in Proceedings of the Workshop on Monte Carlo Generators for HERA Physics, Hamburg, Germany, p. 270 1998 hep-ph/9907280
41 M. Dasgupta, A. Fregoso, S. Marzani, and G. P. Salam Towards an understanding of jet substructure JHEP 09 (2013) 029 1307.0007
42 J. M. Butterworth, A. R. Davison, M. Rubin, and G. P. Salam Jet substructure as a new Higgs search channel at the LHC PRL 100 (2008) 242001 0802.2470
43 CMS Collaboration Pileup mitigation at CMS in $ \sqrt{s} = $ 13 TeV data JINST 15 (2020) P09018 CMS-JME-18-001
2003.00503
44 D. Bertolini, P. Harris, M. Low, and N. Tran Pileup per particle identification JHEP 10 (2014) 059 1407.6013
45 CMS Collaboration Jet energy scale and resolution in the CMS experiment in proton-proton collisions at $ \sqrt{s} = $ 8 TeV JINST 12 (2017) P02014 CMS-JME-13-004
1607.03663
46 CMS Collaboration Jet energy scale and resolution measurement with Run-2 legacy data collected by CMS at $ \sqrt{s} = $ 13 TeV CDS
47 L. Bianchini, J. Conway, E. K. Friis, and C. Veelken Reconstruction of the Higgs mass in $ \mathrm{H}{}\to\tau\tau $ events by dynamical likelihood techniques Journal of Physics: Conference Series 513 (2014) 022035
48 G. C. Strong On the impact of selected modern deep-learning techniques to the performance and celerity of classification models in an experimental high-energy physics use case Machine Learning: Science and Technology (2020) 2002.01427
49 S. J. Hanson A stochastic version of the delta rule Physica D: Nonlinear Phenomena 42 (1990) 265
50 N. Srivastava et al. Dropout: a simple way to prevent neural networks from overfitting Journal of Machine Learning Research 15 (2014) 1929
51 F. Rosenblatt The perceptron: a probabilistic model for information storage and organization in the brain Psychological Review 65 (1957) 386
52 S. Linnainmaa The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors Master's thesis, Univ. Helsinki
53 P. J. Werbos Applications of advances in nonlinear sensitivity analysis in Proceedings of the 10th IFIP Conference, 31.8 - 4.9, NYC, p. 762 1981
54 D. E. Rumelhart, G. E. Hinton, and R. J. Williams Learning representations by back-propagating errors Nature 323 (1986) 533
55 CMS Collaboration Prospects for HH measurements at the HL-LHC CMS-PAS-FTR-18-019 CMS-PAS-FTR-18-019
56 E. M. Cepeda et al. Higgs physics at the HL-LHC and HE-LHC CERN Yellow Rep. Monogr. 7 (2018) 221 1902.00134
57 D. de Florian et al. Handbook of LHC Higgs cross sections: 4. Deciphering the Nature of the Higgs sector CERN Yellow Reports: Monographs - Volume 2/2017 (2016) 1610.07922
58 B. Cabouat and Sjostrand, Torbjorn Some dipole shower studies EPJC 78 (2018), no. 3, 226 1710.00391v2
59 A. L. Read Presentation of search results: the CL$ _{\text{s}} $ technique JPG 28 (2002) 2693
60 T. Junk Confidence level computation for combining searches with small statistics NIMA 434 (1999) 435 hep-ex/9902006
61 J. B. Močkus and L. J. Močkus Bayesian approach to global optimization and application to multiobjective and constrained problems Journal of Optimization Theory and Applications 70 (1991) 157 2108.00002
62 Particle Data Group, P.A. Zyla et al. Review of Particle Physics PTEP 8 (2020) 083C01
Compact Muon Solenoid
LHC, CERN