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| CMS-PAS-HIG-24-009 | ||
| Search for a Higgs boson produced in association with a charm quark, decaying to two W bosons in the e$ \nu\mu\nu $ final state | ||
| CMS Collaboration | ||
| 12 May 2025 | ||
| Abstract: This note presents a search for a Higgs boson produced in association with a charm quark (cH) which allows to probe the Higgs-charm Yukawa coupling $ \kappa_{\text{c}} $. Higgs boson decays into a pair of W bosons are considered, where one W boson decays to an electron and a neutrino, while the other W boson decays to a muon and a neutrino. The data, corresponding to an integrated luminosity of 138 fb$ ^{-1} $, were collected between 2016 and 2018 by the CMS detector at the LHC at a center-of-mass energy of $ \sqrt{s}= $ 13 TeV. Upper limits at the 95% confidence level are set on the ratio of the measured yield to the standard model (SM) expectation for cH production. The observed (expected) upper limit is 1065 (506). These limits are interpreted as constraints on the Yukawa coupling of the Higgs boson to the charm quark, yielding $ |\kappa_{\text{c}}| < $ 211 (95) times the SM expectation. | ||
| Links: CDS record (PDF) ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
Feynman diagrams of H boson production in association with a charm quark at leading order in proton-proton collisions. The red dots indicate vertices where the Higgs-charm coupling modifier $ \kappa_\mathrm{c} $ is involved. |
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Figure 1-a:
Feynman diagrams of H boson production in association with a charm quark at leading order in proton-proton collisions. The red dots indicate vertices where the Higgs-charm coupling modifier $ \kappa_\mathrm{c} $ is involved. |
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Figure 1-b:
Feynman diagrams of H boson production in association with a charm quark at leading order in proton-proton collisions. The red dots indicate vertices where the Higgs-charm coupling modifier $ \kappa_\mathrm{c} $ is involved. |
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Figure 2:
Feynman diagram illustrating H boson production in association with a charm quark in the absence of the $ \kappa_\mathrm{c} $ coupling. The crossed vertex represents the effective top quark loop coupling in the $ \mathrm{g}\mathrm{g}\mathrm{H} $ production mode. |
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Figure 3:
The area-normalized distributions of the two BDT classifiers: $ \mathit{D}_\mathrm{Bkg} $ (left) and $ \mathit{D}_\mathrm{H-bkg} $ (right). The $ \mathit{D}_\mathrm{Bkg} $ classifier effectively separates the non Higgs boson background ( $ \mathrm{t} \overline{\mathrm{t}} $, single top, diboson, and V+jets, denoted as other background) contributions from the $ \mathrm{c}\mathrm{H} $ production, but it is not sufficient for suppressing the H-bkg contributions. The dedicated BDT classifier, $ \mathit{D}_\mathrm{H-bkg} $, is capable of distinguishing between other Higgs boson processes ($ \mathrm{g}\mathrm{g}\mathrm{H} $, VBF, VH, $ {\mathrm{t}\overline{\mathrm{t}}} \mathrm{H} $, and $ \mathrm{b}\mathrm{H} $) and $ \mathrm{c}\mathrm{H} $ production. |
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Figure 3-a:
The area-normalized distributions of the two BDT classifiers: $ \mathit{D}_\mathrm{Bkg} $ (left) and $ \mathit{D}_\mathrm{H-bkg} $ (right). The $ \mathit{D}_\mathrm{Bkg} $ classifier effectively separates the non Higgs boson background ( $ \mathrm{t} \overline{\mathrm{t}} $, single top, diboson, and V+jets, denoted as other background) contributions from the $ \mathrm{c}\mathrm{H} $ production, but it is not sufficient for suppressing the H-bkg contributions. The dedicated BDT classifier, $ \mathit{D}_\mathrm{H-bkg} $, is capable of distinguishing between other Higgs boson processes ($ \mathrm{g}\mathrm{g}\mathrm{H} $, VBF, VH, $ {\mathrm{t}\overline{\mathrm{t}}} \mathrm{H} $, and $ \mathrm{b}\mathrm{H} $) and $ \mathrm{c}\mathrm{H} $ production. |
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Figure 3-b:
The area-normalized distributions of the two BDT classifiers: $ \mathit{D}_\mathrm{Bkg} $ (left) and $ \mathit{D}_\mathrm{H-bkg} $ (right). The $ \mathit{D}_\mathrm{Bkg} $ classifier effectively separates the non Higgs boson background ( $ \mathrm{t} \overline{\mathrm{t}} $, single top, diboson, and V+jets, denoted as other background) contributions from the $ \mathrm{c}\mathrm{H} $ production, but it is not sufficient for suppressing the H-bkg contributions. The dedicated BDT classifier, $ \mathit{D}_\mathrm{H-bkg} $, is capable of distinguishing between other Higgs boson processes ($ \mathrm{g}\mathrm{g}\mathrm{H} $, VBF, VH, $ {\mathrm{t}\overline{\mathrm{t}}} \mathrm{H} $, and $ \mathrm{b}\mathrm{H} $) and $ \mathrm{c}\mathrm{H} $ production. |
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Figure 4:
Distributions of $ \mathit{D}_\mathrm{Bkg} $ (left) and $ \mathit{D}_\mathrm{H-bkg} $ (right) for different H boson production processes. The splitting of H-bkg into three components is based on the flavor of the additional jet associated with the H boson. The yield of the $ \mathrm{b}\mathrm{H} $ process is scaled by a factor of 10, and $ \mathrm{c}\mathrm{H} $ is scaled by a factor of 100. |
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Figure 4-a:
Distributions of $ \mathit{D}_\mathrm{Bkg} $ (left) and $ \mathit{D}_\mathrm{H-bkg} $ (right) for different H boson production processes. The splitting of H-bkg into three components is based on the flavor of the additional jet associated with the H boson. The yield of the $ \mathrm{b}\mathrm{H} $ process is scaled by a factor of 10, and $ \mathrm{c}\mathrm{H} $ is scaled by a factor of 100. |
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Figure 4-b:
Distributions of $ \mathit{D}_\mathrm{Bkg} $ (left) and $ \mathit{D}_\mathrm{H-bkg} $ (right) for different H boson production processes. The splitting of H-bkg into three components is based on the flavor of the additional jet associated with the H boson. The yield of the $ \mathrm{b}\mathrm{H} $ process is scaled by a factor of 10, and $ \mathrm{c}\mathrm{H} $ is scaled by a factor of 100. |
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Figure 5:
Observed and expected distributions of one-parameter-of-interest scenario after performing the fit in signal and control regions. The upper left diagram shows the distribution of events as a function of $ S/B $ in the $ N_{\mathrm{c}-j}= $ 1 signal region, while the upper right shows the $ N_{\mathrm{c}-j} > $ 1 signal region, where $ S $ and $ B $ are the signal and background yields, respectively. The lower left plot shows the distribution of $ \mathit{D}_\mathrm{Bkg} $ used in the high $ m_{\ell\ell} $ control region, while the normalization factor of the top CR is shown in the lower right. Within each plot, the upper panel provides the number of events from simulation and data in logarithmic scale, the middle panel shows the fraction of each background process in each bin, and the lower panel provides the ratio of data to simulated background events. The red lines represent background plus signal with $ \mu_{\mathrm{c}\mathrm{H}}= $ 1 divided by background. The hashed area shows the statistical uncertainty only, and gray lines show the coverage of statistical and systematic uncertainties. |
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Figure 5-a:
Observed and expected distributions of one-parameter-of-interest scenario after performing the fit in signal and control regions. The upper left diagram shows the distribution of events as a function of $ S/B $ in the $ N_{\mathrm{c}-j}= $ 1 signal region, while the upper right shows the $ N_{\mathrm{c}-j} > $ 1 signal region, where $ S $ and $ B $ are the signal and background yields, respectively. The lower left plot shows the distribution of $ \mathit{D}_\mathrm{Bkg} $ used in the high $ m_{\ell\ell} $ control region, while the normalization factor of the top CR is shown in the lower right. Within each plot, the upper panel provides the number of events from simulation and data in logarithmic scale, the middle panel shows the fraction of each background process in each bin, and the lower panel provides the ratio of data to simulated background events. The red lines represent background plus signal with $ \mu_{\mathrm{c}\mathrm{H}}= $ 1 divided by background. The hashed area shows the statistical uncertainty only, and gray lines show the coverage of statistical and systematic uncertainties. |
png pdf |
Figure 5-b:
Observed and expected distributions of one-parameter-of-interest scenario after performing the fit in signal and control regions. The upper left diagram shows the distribution of events as a function of $ S/B $ in the $ N_{\mathrm{c}-j}= $ 1 signal region, while the upper right shows the $ N_{\mathrm{c}-j} > $ 1 signal region, where $ S $ and $ B $ are the signal and background yields, respectively. The lower left plot shows the distribution of $ \mathit{D}_\mathrm{Bkg} $ used in the high $ m_{\ell\ell} $ control region, while the normalization factor of the top CR is shown in the lower right. Within each plot, the upper panel provides the number of events from simulation and data in logarithmic scale, the middle panel shows the fraction of each background process in each bin, and the lower panel provides the ratio of data to simulated background events. The red lines represent background plus signal with $ \mu_{\mathrm{c}\mathrm{H}}= $ 1 divided by background. The hashed area shows the statistical uncertainty only, and gray lines show the coverage of statistical and systematic uncertainties. |
png pdf |
Figure 5-c:
Observed and expected distributions of one-parameter-of-interest scenario after performing the fit in signal and control regions. The upper left diagram shows the distribution of events as a function of $ S/B $ in the $ N_{\mathrm{c}-j}= $ 1 signal region, while the upper right shows the $ N_{\mathrm{c}-j} > $ 1 signal region, where $ S $ and $ B $ are the signal and background yields, respectively. The lower left plot shows the distribution of $ \mathit{D}_\mathrm{Bkg} $ used in the high $ m_{\ell\ell} $ control region, while the normalization factor of the top CR is shown in the lower right. Within each plot, the upper panel provides the number of events from simulation and data in logarithmic scale, the middle panel shows the fraction of each background process in each bin, and the lower panel provides the ratio of data to simulated background events. The red lines represent background plus signal with $ \mu_{\mathrm{c}\mathrm{H}}= $ 1 divided by background. The hashed area shows the statistical uncertainty only, and gray lines show the coverage of statistical and systematic uncertainties. |
png pdf |
Figure 5-d:
Observed and expected distributions of one-parameter-of-interest scenario after performing the fit in signal and control regions. The upper left diagram shows the distribution of events as a function of $ S/B $ in the $ N_{\mathrm{c}-j}= $ 1 signal region, while the upper right shows the $ N_{\mathrm{c}-j} > $ 1 signal region, where $ S $ and $ B $ are the signal and background yields, respectively. The lower left plot shows the distribution of $ \mathit{D}_\mathrm{Bkg} $ used in the high $ m_{\ell\ell} $ control region, while the normalization factor of the top CR is shown in the lower right. Within each plot, the upper panel provides the number of events from simulation and data in logarithmic scale, the middle panel shows the fraction of each background process in each bin, and the lower panel provides the ratio of data to simulated background events. The red lines represent background plus signal with $ \mu_{\mathrm{c}\mathrm{H}}= $ 1 divided by background. The hashed area shows the statistical uncertainty only, and gray lines show the coverage of statistical and systematic uncertainties. |
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Figure 6:
Upper limits of $ \mu_{\mathrm{c}\mathrm{H}} $ at 95%CL for each data-taking period, and the combination of the periods. The blue (red) line shows the 1 (2) standard deviation result of the 1POI fit with fixing the H-bkg+c contribution to the SM prediction. The green (yellow) line shows the 1 (2) standard deviation result of the 2POI fit with floating H-bkg+c contribution. The blue circles represent the median of the expected limit, while the black circles represent the observed limit. |
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Figure 7:
Two-dimensional likelihood contour of $ \mu_{\mathrm{c}\mathrm{H}} $ and $ \mu_{\text{H-bkg}+{\mathrm{c}}} $. The color scale represents twice the negative log likelihood difference with respect to the best fit point. The observed 95% (dashed) and 68% (solid) contours are shown in black lines, and the best fit point as a black cross. The SM expectation is marked by a red diamond. The kink of the curve represents the change of the nuisance in the likelihood fit. |
| Tables | |
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Table 1:
Definitions of the signal and control regions. Two SRs are defined according to their c jet multiplicity. Events with dilepton invariant mass above 72 GeV are considered as CRs. Events with an inverted transverse masses requirement that have at least two c jets are considered in top CR and the rest of events are tagged as high $ m_{\ell\ell} $ CR. |
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Table 2:
Summary of input variables used in the BDT trainings. |
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Table 3:
Relative impact of individual uncertainty sources on the measurement of $ \mu_{\mathrm{c}\mathrm{H}} $ expressed as the change in the one standard deviation when each source is fixed. Statistical uncertainties are derived by fixing all constrained nuisance parameters. |
| Summary |
| The first search for the associated production of a charm quark and a Higgs boson ($ \mathrm{c}\mathrm{H} $) in which the Higgs boson decays to a pair of W bosons has been presented. Decays of W bosons to e$ \nu\mu\nu $ are considered. The search is based on the data collected from 2016 to 2018 with the CMS detector at the LHC, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. The observed (expected) upper limit at 95% confidence level (CL) on the ratio of the measured production cross section with respect the value expected from the Standard Model for $ \mathrm{c}\mathrm{H} $ production $ \mu_{\mathrm{c}\mathrm{H}} $ is set at 1065 (506) times the standard model (SM) prediction at next-to-leading order. This search provides an alternative probe to the Yukawa coupling between the Higgs boson and charm quark. The observed (expected) allowed interval on the Higgs-charm coupling strength modifier $ \kappa_\mathrm{c} $ is constrained to $ |\kappa_\mathrm{c}| < $ 211 (95) at 95% CL. |
| References | ||||
| 0 | 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 |
| 2 | 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 |
| 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 | A portrait of the Higgs boson by the CMS experiment ten years after the discovery | Nature 607 (2022) 60 | CMS-HIG-22-001 2207.00043 |
| 5 | ATLAS and CMS Collaborations | Measurements of the Higgs boson production and decay rates and constraints on its couplings from a combined ATLAS and CMS analysis of the LHC pp collision data at $ \sqrt{s}= $ 7 and 8 TeV | JHEP 08 (2016) 045 | 1606.02266 |
| 6 | CMS Collaboration | Combined measurements and interpretations of Higgs boson production and decay at $ \sqrt{s}= $ 13 TeV | CDS | |
| 7 | CMS Collaboration | Measurement of simplified template cross sections of the Higgs boson produced in association with W or Z bosons in the H$ \to \mathrm{b}\bar{\mathrm{b}} $ decay channel in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | PRD 109 (2024) 092011 | CMS-HIG-20-001 2312.07562 |
| 8 | ATLAS Collaboration | Measurements of WH and ZH production in the $ \mathrm{H}\rightarrow \mathrm{b}\overline{\mathrm{b}} $ decay channel in $ pp $ collisions at 13 TeV with the ATLAS detector | EPJC 81 (2021) 178 | 2007.02873 |
| 9 | ATLAS Collaboration | Measurements of WH and ZH production with Higgs boson decays into bottom quarks and direct constraints on the charm Yukawa coupling in 13 TeV pp collisions with the ATLAS detector | JHEP 2025 (2025) | 2410.19611 |
| 10 | ATLAS Collaboration | Measurements of Higgs boson production cross-sections in the $ H\to\tau^{+}\tau^{-} $ decay channel in pp collisions at $ \sqrt{s} = $ 13 TeV with the ATLAS detector | JHEP 08 (2022) 175 | 2201.08269 |
| 11 | CMS Collaboration | Measurements of Higgs boson production in the decay channel with a pair of $ \tau $ leptons in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | EPJC 83 (2023) 562 | CMS-HIG-19-010 2204.12957 |
| 12 | CMS Collaboration | Evidence for Higgs boson decay to a pair of muons | JHEP 01 (2021) 148 | CMS-HIG-19-006 2009.04363 |
| 13 | ATLAS Collaboration | A search for the dimuon decay of the standard model Higgs boson with the ATLAS detector | PLB 812 (2021) 135980 | 2007.07830 |
| 14 | ATLAS Collaboration | Direct constraint on the Higgs-charm coupling from a search for Higgs boson decays into charm quarks with the ATLAS detector | EPJC 82 (2022) 717 | 2201.11428 |
| 15 | CMS Collaboration | Search for Higgs boson decay to a charm quark-antiquark pair in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | PRL 131 (2023) 061801 | CMS-HIG-21-008 2205.05550 |
| 16 | CMS Collaboration | Search for Higgs boson decay to a charm quark-antiquark pair via ttH production | CDS | |
| 17 | CMS Collaboration | Search for Higgs boson and observation of Z boson through their decay into a charm quark-antiquark pair in boosted topologies in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | PRL 131 (2023) 041801 | CMS-HIG-21-012 2211.14181 |
| 18 | E. Bols et al. | Jet flavour classification using DeepJet | JINST 15 (2020) P12012 | 2008.10519 |
| 19 | CMS Collaboration | A new calibration method for charm jet identification validated with proton-proton collision events at $ \sqrt{s}= $ 13 TeV | JINST 17 (2022) P03014 | CMS-BTV-20-001 2111.03027 |
| 20 | CMS Collaboration | Combination and interpretation of differential Higgs boson production cross sections in proton-proton collisions at $ \sqrt{s} $ = 13 TeV | Submitted to JHEP | CMS-HIG-23-013 2504.13081 |
| 21 | N. M. Coyle, C. E. M. Wagner, and V. Wei | Bounding the charm Yukawa coupling | PRD 100 (2019) 073013 | 1905.09360 |
| 22 | I. Brivio, F. Goertz, and G. Isidori | Probing the charm quark Yukawa coupling in $ \text{Higgs}+\text{Charm} $ production | PRL 115 (2015) 211801 | 1507.02916 |
| 23 | CMS Collaboration | Search for the associated production of a Higgs boson with a charm quark in the diphoton decay channel in pp collisions at $ \sqrt{s} = $ 13 TeV | Submitted to JHEP | CMS-HIG-23-010 2503.08797 |
| 24 | ATLAS Collaboration | Search for the associated production of charm quarks and a Higgs boson decaying into a photon pair with the ATLAS detector | JHEP 02 (2025) 045 | 2407.15550 |
| 25 | CMS Collaboration | The CMS experiment at the CERN LHC | JINST 3 (2008) S08004 | |
| 26 | CMS Collaboration | Development of the CMS detector for the CERN LHC Run 3 | JINST 19 (2024) P05064 | CMS-PRF-21-001 2309.05466 |
| 27 | 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 |
| 28 | CMS Collaboration | The CMS trigger system | JINST 12 (2017) P01020 | CMS-TRG-12-001 1609.02366 |
| 29 | 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 |
| 30 | CMS Collaboration | CMS luminosity measurement for the 2017 data-taking period at $ \sqrt{s} $ = 13 TeV | CMS Physics Analysis Summary, 2018 link |
CMS-PAS-LUM-17-004 |
| 31 | CMS Collaboration | CMS luminosity measurement for the 2018 data-taking period at $ \sqrt{s} $ = 13 TeV | CMS Physics Analysis Summary, 2019 link |
CMS-PAS-LUM-18-002 |
| 32 | CMS Collaboration | Simulation of the Silicon strip tracker pre-amplifier in early 2016 data | CMS Detector Performance Summary CMS-DP-2020-045, 2020 CDS |
|
| 33 | GEANT4 Collaboration | GEANT 4---a simulation toolkit | NIM A 506 (2003) 250 | |
| 34 | T. Sjöstrand et al. | An introduction to PYTHIA 8.2 | Comput. Phys. Commun. 191 (2015) 159 | 1410.3012 |
| 35 | NNPDF Collaboration | Parton distributions from high-precision collider data | EPJC 77 (2017) 663 | 1706.00428 |
| 36 | CMS Collaboration | Event generator tunes obtained from underlying event and multiparton scattering measurements | EPJC 76 (2016) 155 | CMS-GEN-14-001 1512.00815 |
| 37 | M. Wiesemann et al. | Higgs production in association with bottom quarks | JHEP 02 (2015) 132 | 1409.5301 |
| 38 | R. Frederix and S. Frixione | Merging meets matching in MC@NLO | JHEP 12 (2012) 061 | 1209.6215 |
| 39 | P. Nason | A new method for combining NLO QCD with shower Monte Carlo algorithms | JHEP 11 (2004) 040 | hep-ph/0409146 |
| 40 | P. Nason and C. Oleari | NLO Higgs boson production via vector-boson fusion matched with shower in POWHEG | JHEP 02 (2010) 037 | 0911.5299 |
| 41 | S. Frixione, P. Nason, and C. Oleari | Matching NLO QCD computations with parton shower simulations: the POWHEG method | JHEP 11 (2007) 070 | 0709.2092 |
| 42 | 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 |
| 43 | E. Bagnaschi, G. Degrassi, P. Slavich, and A. Vicini | Higgs production via gluon fusion in the POWHEG approach in the SM and in the MSSM | JHEP 02 (2012) 088 | 1111.2854 |
| 44 | G. Luisoni, P. Nason, C. Oleari, and F. Tramontano | $ \mathrm{HW}^{\pm} $/HZ+ 0 and 1 jet at NLO with the POWHEG BOX interfaced to gosam and their merging within MiNLO | JHEP 10 (2013) 083 | 1306.2542 |
| 45 | 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 |
| 46 | S. Manzoni et al. | Taming a leading theoretical uncertainty in HH measurements via accurate simulations for $ \textrm{b}\overline{\textrm{b}}\textrm{H} $ production | JHEP 09 (2023) 179 | 2307.09992 |
| 47 | CMS Collaboration | Particle-flow reconstruction and global event description with the CMS detector | JINST 12 (2017) P10003 | CMS-PRF-14-001 1706.04965 |
| 48 | 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 |
| 49 | CMS Collaboration | ECAL 2016 refined calibration and Run2 summary plots | CMS Detector Performance Summary CMS-DP-2020-021, 2020 CDS |
|
| 50 | 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 |
| 51 | M. Cacciari, G. P. Salam, and G. Soyez | The anti-$ k_{\mathrm{T}} $ jet clustering algorithm | JHEP 04 (2008) 063 | 0802.1189 |
| 52 | M. Cacciari, G. P. Salam, and G. Soyez | FastJet user manual | EPJC 72 (2012) 1896 | 1111.6097 |
| 53 | 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 |
| 54 | CMS Collaboration | Performance of the DeepJet b tagging algorithm using 41.9/fb of data from proton-proton collisions at 13 TeV with phase 1 CMS detector | CMS Detector Performance Summary CMS-DP-2018-058, 2018 CDS |
|
| 55 | CMS Collaboration | Performance summary of AK4 jet charm tagging with the CMS Run2 legacy dataset | CMS Detector Performance Summary CMS-DP-2023-006, 2023 CDS |
|
| 56 | 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 |
| 57 | 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, KDD '16, ACM, New York, NY, 2016 link |
|
| 58 | D. Sculley | Web-scale k-means clustering | in Proceedings of the 19th International Conference on World Wide Web, WWW '10, Association for Computing Machinery, New York, NY, 2010 link |
|
| 59 | CMS Collaboration | The CMS statistical analysis and combination tool: Combine | Comput. Softw. Big Sci. 8 (2024) 19 | CMS-CAT-23-001 2404.06614 |
| 60 | W. Verkerke and D. Kirkby | The RooFit toolkit for data modeling | in Proc. 13th International Conference on Computing in High Energy and Nuclear Physics (CHEP ), La Jolla CA, 2003 link |
physics/0306116 |
| 61 | L. Moneta et al. | The RooStats project | PoS ACAT 057, 2010 link |
1009.1003 |
| 62 | W. S. Cleveland | Robust locally weighted regression and smoothing scatterplots | Journal of the American Statistical Association 74 (1979) 829 | |
| 63 | W. S. Cleveland and S. J. Devlin | Locally weighted regression: An approach to regression analysis by local fitting | Journal of the American Statistical Association 83 (1988) 596 | |
| 64 | J. Campbell, T. Neumann, and Z. Sullivan | Single-top-quark production in the $ t $-channel at NNLO | JHEP 02 (2021) 040 | 2012.01574 |
| 65 | PDF4LHC Working Group Collaboration | The PDF4LHC21 combination of global PDF fits for the LHC Run III | JPG 49 (2022) 080501 | 2203.05506 |
| 66 | N. Kidonakis and N. Yamanaka | Higher-order corrections for $ \mathrm{tW} $ production at high-energy hadron colliders | JHEP 05 (2021) 278 | 2102.11300 |
| 67 | K. Melnikov and F. Petriello | Electroweak gauge boson production at hadron colliders through $ o(\alpha_s^2) $ | PRD 74 (2006) 114017 | hep-ph/0609070 |
| 68 | S. Catani et al. | Vector boson production at hadron colliders: a fully exclusive QCD calculation at NNLO | PRL 103 (2009) 082001 | 0903.2120 |
| 69 | J. Baglio, C. Duhr, B. Mistlberger, and R. Szafron | Inclusive production cross sections at N$ ^{3} $LO | JHEP 12 (2022) 066 | 2209.06138 |
| 70 | C. Anastasiou, L. J. Dixon, K. Melnikov, and F. Petriello | High precision QCD at hadron colliders: Electroweak gauge boson rapidity distributions at NNLO | PRD 69 (2004) 094008 | hep-ph/0312266 |
| 71 | S. Dittmaier, A. Huss, and C. Schwinn | Mixed QCD-electroweak $ \mathcal{O}(\alpha_s\alpha) $ corrections to Drell-Yan processes in the resonance region: pole approximation and non-factorizable corrections | NPB 885 (2014) 318 | 1403.3216 |
| 72 | J. M. Campbell and R. K. Ellis | MCFM for the Tevatron and the LHC | Nucl. Phys. B Proc. Suppl. 205-206 (2010) 10 | 1007.3492 |
| 73 | Caola, Fabrizio and Melnikov, Kirill and Röntsch, Raoul and Tancredi, Lorenzo | QCD corrections to $ \mathrm{W}^+\mathrm{W}^- $ production through gluon fusion | PLB 754 (2016) 275 | 1511.08617 |
| 74 | T. Melia, P. Nason, R. Rontsch, and G. Zanderighi | $ \mathrm{W}^+\mathrm{W}^- $, WZ and ZZ production in the POWHEG BOX | JHEP 11 (2011) 078 | 1107.5051 |
| 75 | J. M. Campbell, R. K. Ellis, and C. Williams | Vector boson pair production at the LHC | JHEP 07 (2011) 018 | 1105.0020 |
| 76 | Cascioli, F. and Gehrmann, T. and Grazzini, M. and Kallweit, S. and Maierhöfer, P. and von Manteuffel, A. and Pozzorini, S. and Rathlev, D. and Tancredi, L. and Weihs, E. | ZZ production at hadron colliders in NNLO QCD | PLB 735 (2014) 311 | 1405.2219 |
| 77 | M. Grazzini, S. Kallweit, and D. Rathlev | ZZ production at the LHC: fiducial cross sections and distributions in NNLO QCD | PLB 750 (2015) 407 | 1507.06257 |
| 78 | S. Kallweit and M. Wiesemann | ZZ production at the LHC: NNLO predictions for 2 $ \ell2\nu $ and 4 $ \ell $ signatures | PLB 786 (2018) 382 | 1806.05941 |
| 79 | J. M. Lindert et al. | Precise predictions for $ \textrm{V}+ $jets dark matter backgrounds | EPJC 77 (2017) 829 | 1705.04664 |
| 80 | LHC Higgs Cross Section Working Group Collaboration | Handbook of LHC Higgs cross sections: 4. deciphering the nature of the Higgs sector | 1610.07922 | |
| 81 | N. Kidonakis | NNLL threshold resummation for top-pair and single-top production | Phys. Part. Nucl. 45 (2014) 714 | 1210.7813 |
| 82 | S. Catani et al. | Top-quark pair production at the LHC: Fully differential QCD predictions at NNLO | JHEP 07 (2019) 100 | 1906.06535 |
| 83 | M. Czakon, D. Heymes, and A. Mitov | High-precision differential predictions for top-quark pairs at the LHC | PRL 116 (2016) 082003 | 1511.00549 |
| 84 | M. Czakon et al. | Top-pair production at the LHC through NNLO QCD and NLO EW | JHEP 10 (2017) 186 | 1705.04105 |
| 85 | R. J. Barlow and C. Beeston | Fitting using finite Monte Carlo samples | Comput. Phys. Commun. 77 (1993) 219 | |
| 86 | J. A. Aguilar-Saavedra, J. M. Cano, and J. M. No | More light on Higgs flavor at the LHC: Higgs boson couplings to light quarks through $ h+\gamma $ production | PRD 103 (2021) 095023 | 2008.12538 |
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Compact Muon Solenoid LHC, CERN |
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