The second-order Fourier sine coefficients of $\Lambda$ polarization along the beam direction as functions of $N_\mathrm{trk}^\mathrm{offline}$ in pPb collisions at 8.16 TeV extracted with HF based event planes. The HF-based event plane is reconstructed only with the HF detectors toward the Pb going direction.

The second-order Fourier sine coefficients of $\bar{\Lambda}$ polarization along the beam direction as functions of $N_\mathrm{trk}^\mathrm{offline}$ in pPb collisions at 8.16 TeV extracted with HF based event planes. The HF-based event plane is reconstructed only with the HF detectors toward the Pb going direction.

The second-order Fourier sine coefficients of $\Lambda+\bar{\Lambda}$ polarization along the beam direction as functions of $N_\mathrm{trk}^\mathrm{offline}$ in pPb collisions at 8.16 TeV extracted with HF based event planes. The HF-based event plane is reconstructed only with the HF detectors toward the Pb going direction.

Suppl. Fig. 7. The reconstructed shower angle for all single photon events. The individual signal and background event type categories added together form the unconstrained prediction.

Suppl. Fig. 7. The constrained covariance matrix for the reconstructed shower angle for all single-photon events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Suppl. Fig. 7. The unconstrained covariance matrix for reconstructed shower angle for all single-photon events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 3. The reconstructed number of protons, with a proton KE energy threshold of 35 MeV, for all single-photon events. The individual signal and background event type categories added together form the unconstrained prediction.

Fig. 4, Suppl. Fig. 8. The reconstructed shower energy for zero proton events binned from 0 to 600 MeV. The individual signal and background event type categories added together form the unconstrained prediction.

Fig. 4. The constrained covariance matrix for the reconstructed shower energy for zero proton events binned from 0 to 600 MeV. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 4. The unconstrained covariance matrix for reconstructed shower energy for zero proton events binned from 0 to 600 MeV. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 6. The reconstructed shower energy for zero proton events binned from 150 to 1250 MeV, with LEE prediction. The individual signal and background event type categories added together form the unconstrained prediction. The "LEE" category is the unfolded MiniBooNE LEE model prediction scaled under the neutrino-target nucleon interaction assumption.

Fig. 6. The constrained covariance matrix for the reconstructed shower energy for zero proton events binned from 150 to 1250 MeV. Both with and without the LEE model added. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 6. The unconstrained covariance matrix for reconstructed shower energy for zero proton events binned from 150 to 1250 MeV. Both with and without the LEE model added. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Suppl. Fig. 10. The reconstructed shower backwards projected distance for zero proton events. The individual signal and background event type categories added together form the unconstrained prediction.

Suppl. Fig. 9. The reconstructed shower angle for zero proton events. Includes LEE model prediction. The individual signal and background event type categories added together form the unconstrained prediction. The "LEE" category is the unfolded MiniBooNE LEE model prediction scaled under the neutrino-target nucleon interaction assumption.

Suppl. Fig. 9. The constrained covariance matrix for the reconstructed shower angle for zero proton events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Suppl. Fig. 9. The unconstrained covariance matrix for reconstructed shower angle for zero proton events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

1$\gamma$Xp shower energy and angle selection efficiencies for true 1$\gamma$Xp events. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. Energy and Angle values represent bin lower edges.

1$\gamma$0p shower energy and angle selection efficiencies for true single-photon events with no other true particles of any energy. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. Energy and Angle values represent bin lower edges.

Covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Pearson data statistical uncertainties have been included, and include small correlations due to events which can be selected by both WC and Pandora. The first four bins are the WC $1\gamma Np$, WC $1\gamma 0p$, Pandora $1\gamma 1p$, and Pandora $1\gamma 0p$ channels, and the next four sets of 16 bins are the NC $\pi^0 Np$, NC $\pi^0 0p$, $\nu_\mu$CC $Np$, and $\nu_\mu$CC $0p$ channels. This corresponds to Fig. 1 of the paper and Fig. 6 of the Supplemental Material.

Constrained WC $1\gamma Np$ energy distribution. There are 6 bins from 0 to 600 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained WC $1\gamma 0p$ energy distribution. There are 14 bins from 0 to 700 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained Pandora $1\gamma 1p$ energy distribution. There are 6 bins from 0 to 600 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained Pandora $1\gamma 0p$ energy distribution. There are 14 bins from 0 to 700 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained covariance matrix showing constrained uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Pearson data statistical uncertainties have been included, and include small correlations due to events which can be selected by both WC and Pandora. The first seven bins are the WC $1\gamma Np$ reconstructed shower energy from 0-600 MeV with an overflow bin, the next 15 bins are the WC $1\gamma 0p$ reconstructed shower energy from 0-700 MeV with an overflow bin, the next seven bins are the Pandora $1\gamma 1p$ reconstructed shower energy from 0-600 MeV with an overflow bin, and the last 15 bins are the Pandora $1\gamma 0p$ reconstructed shower energy from 0-700 MeV with an overflow bin. This corresponds to Fig. 2 of the paper.

2D efficiency matrix showing the efficiency of the WC $1\gamma Np$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 15 bins from 0 to 1500 MeV in true photon energy. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the WC $1\gamma 0p$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the Pandora $1\gamma 1p$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 15 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the Pandora $1\gamma 0p$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the WC $1\gamma 0p$ selection with respect to all true zero-primary-final-state-proton NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied.

2D efficiency matrix showing the efficiency of the Pandora $1\gamma 0p$ selection with respect to all true zero-primary-final-state-proton NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied.

$a_2(1320)$ differential cross section in the m=-2 projection split into different reflectivity components, $\frac{d\sigma^+_{-2}}{dt}$ and $\frac{d\sigma^-_{-2}}{dt}$, in bins of four-momentum transfer. The first uncertainty is statistical, the second systematic.

$a_2(1320)$ differential cross section in the m=0 projection split into different reflectivity components, $\frac{d\sigma^+_{0}}{dt}$ and $\frac{d\sigma^-_{0}}{dt}$, in bins of four-momentum transfer. The first uncertainty is statistical, the second systematic.

$a_2(1320)$ differential cross section in the m=+1 projection split into different reflectivity components, $\frac{d\sigma^+_{+1}}{dt}$ and $\frac{d\sigma^-_{+1}}{dt}$, in bins of four-momentum transfer. The first uncertainty is statistical, the second systematic.

$a_2(1320)$ differential cross section in the m=+2 projection split into different reflectivity components, $\frac{d\sigma^+_{+2}}{dt}$ and $\frac{d\sigma^-_{+2}}{dt}$, in bins of four-momentum transfer. The first uncertainty is statistical, the second systematic.

Matrix of the correlations of the systematic uncertainties between pairs of physics parameters, as obtained from the analysis to data at 13 TeV.

Matrix of the correlations between the physics parameters as obtained from the combination between the CMS 8 TeV and 13 TeV results. Correlations include both statistical and systematic uncertainties.

Cutflow for VBF Z' to WW in ditau 2016 channel for different signal scenarios

Cutflow for VBF Z' to WW in ditau 2017 channel for different signal scenarios

Cutflow for VBF Z' to WW in ditau 2018 channel for different signal scenarios

Cutflow for VBF Z' to tautau in mutau 2016 channel for different signal scenarios

Cutflow for VBF Z' to tautau in mutau 2017 channel for different signal scenarios

Cutflow for VBF Z' to tautau in mutau 2018 channel for different signal scenarios

Cutflow for VBF Z' to WW in mutau 2016 channel for different signal scenarios

Cutflow for VBF Z' to WW in mutau 2017 channel for different signal scenarios

Cutflow for VBF Z' to WW in mutau 2018 channel for different signal scenarios

Cutflow for VBF Z' to tautau in etau 2016 channel for different signal scenarios

Cutflow for VBF Z' to tautau in etau 2017 channel for different signal scenarios

Cutflow for VBF Z' to tautau in etau 2018 channel for different signal scenarios

Cutflow for VBF Z' to WW in etau 2016 channel for different signal scenarios

Cutflow for VBF Z' to WW in etau 2017 channel for different signal scenarios

Cutflow for VBF Z' to WW in etau 2018 channel for different signal scenarios

Cutflow for VBF Z' to tautau in emu 2016 channel for different signal scenarios

Cutflow for VBF Z' to tautau in emu 2017 channel for different signal scenarios

Cutflow for VBF Z' to tautau in emu 2018 channel for different signal scenarios

Cutflow for VBF Z' to WW in emu 2016 channel for different signal scenarios

Cutflow for VBF Z' to WW in emu 2017 channel for different signal scenarios

Cutflow for VBF Z' to WW in emu 2018 channel for different signal scenarios

Observed and expected background yields for different mass ranges in the mutau channel. The quoted uncertainty includes both the statistical and the systematic components. The last bin contains the overflow bin.

Observed and expected background yields for different mass ranges in the ditau channel. The quoted uncertainty includes both the statistical and the systematic components. The last bin contains the overflow bin.

Observed and expected background yields for different mass ranges in the etau channel. The quoted uncertainty includes both the statistical and the systematic components. The last bin contains the overflow bin.

Observed and expected background yields for different mass ranges in the emu channel. The quoted uncertainty includes both the statistical and the systematic components. The last bin contains the overflow bin.

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.1.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.25.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.50.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.75.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 1.0.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.1.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.25.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.50.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.75.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to tautau, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 1.0.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.1.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.25.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.50.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 0.75.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 0 and $k_V = 1.0.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.1.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.25.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.50.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 0.75.$

Combined $95\%$ confidence level expected and observed upper limits on the product of the $\mathrm{Z'}$ cross section and the branching fraction for a $\mathrm{Z'}$ boson decaying to WW, as a function of $\mathrm{Z'}$ mass and assuming g_(1,2) = 1 and $k_V = 1.0.$

Cross sections for different signal models for VBF Z'. To calculate cross section for branching fraction (br) 0.20 and kV = 0.1, subsitute the values in (br {x} $\kappa_{V}^{2}$ {x} xsec)

Combined 95% CL lower limits on m(Z') as a function of the Z' branching fraction to tautau for g_(1,2)=0 scenario. The observed limits corresponding to $\kappa_V$ equal to 0.1, 0.5, and 1.0 are shown here.

Combined 95% CL lower limits on m(Z') as a function of the Z' branching fraction to tautau for g_(1,2)=1 scenario. The observed limits corresponding to $\kappa_V$ equal to 0.1, 0.5, and 1.0 are shown here.

Combined 95% CL lower limits on m(Z') as a function of the Z' branching fraction to WW for g_(1,2)=0 scenario. The observed limits corresponding to $\kappa_V$ equal to 0.1, 0.5, and 1.0 are shown here.

Combined 95% CL lower limits on m(Z') as a function of the Z' branching fraction to WW for g_(1,2)=1 scenario. The observed limits corresponding to $\kappa_V$ equal to 0.1, 0.5, and 1.0 are shown here.

Differential cross sections for exclusive dielectron production, in the fiducial phase space of Table 1, as functions of the pair invariant mass. Data are compared with SUPERCHIC + FSR(PHOTOS++), STARLIGHT + FSR(PY8), and gamma-UPC + FSR(PY8) predictions.

Differential cross sections for exclusive dielectron production, in the fiducial phase space of Table 1, as functions of the pair |cos $\theta$*|. Data are compared with SUPERCHIC + FSR(PHOTOS++), STARLIGHT + FSR(PY8), and gamma-UPC + FSR(PY8) predictions.

Differential exclusive diphoton cross sections in the fiducial phase space of Table 1 as a function of the diphoton rapidity measured in data compared with SUPERCHIC and gamma-UPC@NLO predictions.

Differential exclusive diphoton cross sections in the fiducial phase space of Table 1 as a function of the diphoton invariant mass measured in data compared with SUPERCHIC and gamma-UPC@NLO predictions.

Observed and expected 95% CL limits on the production cross section $\sigma(\gamma\gamma \rightarrow a \rightarrow \gamma\gamma)$ as a function of the ALP mass $m_{a}$. The uncertainties indicate regions containing 68 and 95% of the distribution of limits expected under the background-only hypothesis. The additional datasets indicate the expected ALP cross sections as a function of $m_{a}$ for decreasing photon couplings ($g_{a\gamma} = 0.3, 0.1, 0.05 TeV^{-1}$).

Exclusion limits at 95% CL in the axion-photon coupling $g_{a\gamma}$ versus axion mass $m_a$ plane, for the operator $\frac{1}{4\Lambda}aF\widetilde{F}$ (assuming ALPs coupled only to photons) extracted in this analysis.

Cutflow for signal samples in the muon-tau channel for 2016 signal samples. Each entry other than the total is the relative efficiency with respect to the previous selection.

Cutflow for signal samples in the muon-tau channel for 2017 signal samples. Each entry other than the total is the relative efficiency with respect to the previous selection.

Cutflow for signal samples in the muon-tau channel for 2018 signal samples. Each entry other than the total is the relative efficiency with respect to the previous selection.

Cutflow for signal samples in the electron-tau channel for 2016 signal samples. Each entry other than the total is the relative efficiency with respect to the previous selection.

Cutflow for signal samples in the electron-tau channel for 2017 signal samples. Each entry other than the total is the relative efficiency with respect to the previous selection.

Cutflow for signal samples in the electron-tau channel for 2018 signal samples. Each entry other than the total is the relative efficiency with respect to the previous selection.

Yields for the muon-tau channel in 2016 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the muon-tau channel in 2017 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the muon-tau channel in 2018 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the electron-tau channel in 2016 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the electron-tau channel in 2017 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the electron-tau channel in 2018 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the di-tau channel in 2016 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the di-tau channel in 2017 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Yields for the di-tau channel in 2018 as a function of reconstructed mass. Data and each background are listed with their respective uncertainties. The last bin contains the overflow bin.

Covariance matrix for all bins and all channels used in the background-only fit of this analysis. There are the e-tau, the mu-tau, and the tau-tau analysis channels, each present for 2016, 2017, and 2018. Each has 6 bins in the reconstructed mass (mrec[GeV]) indicated with their borders in the bin naming. The bin labels have channel name, year name, then bin name.

95% confidence level expected limit with 1 and 2 sigma uncertainties, as well as observed limits on Z' model cross section times branching ratio to di-tau in the e-tau channel.

95% confidence level expected limit with 1 and 2 sigma uncertainties, as well as observed limits on Z' model cross section times branching ratio to di-tau in the mu-tau channel.

95% confidence level expected limit with 1 and 2 sigma uncertainties, as well as observed limits on Z' model cross section times branching ratio to ditau in the ditau channel.

95% confidence level expected limit with 1 and 2 sigma uncertainties, as well as observed limits on Z' model cross section times branching ratio to ditau for the combination of all channels.

Invariant mass distribution of final state particles in SR1 HF category ($\text{H}\to\text{J}/\psi\gamma$ signal)

Invariant mass distribution of final state particles in SR1 Z-LP category ($\text{Z}\to\text{J}/\psi\gamma$ signal)

Invariant mass distribution of final state particles in SR1 Z-HP category ($\text{Z}\to\text{J}/\psi\gamma$ signal)

Invariant mass distribution of final state particles in SR2 category ($\text{H}\to\psi(\text{2S})\gamma$ signal)

Invariant mass distribution of final state particles in SR2 category ($\text{H}\to\psi(\text{2S})\gamma$ signal)

Invariant mass distribution of final state particles in control region category ($\text{H}\to\mu\mu\gamma$ background)

Observed and expected (with $\pm 1$, $\pm 2$ standard deviation bands) exclusion limits at 95% C.L. on the branching fraction $\mathcal{B}$ of the $(\text{H,Z}) \to \psi(\text{nS})\gamma$ decays

Observed (expected) upper limits at 95% C.L. on the normalized values with respect to the SM expectation, denoted as the signal strength parameter $\mu$, of the product of the cross section $\sigma$ and the branching fraction $\mathcal{B}$ of the $(\text{H,Z}) \to \psi(\text{nS})\gamma$ decays, and the branching fraction, assuming a SM Z and H boson cross section.

Results for the $P_3$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_4^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_5^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_6^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_8^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the CP averaged observables $F_L$ and $P_1$–$P_8^\prime$. The first uncertainties are statistical and the second systematic.

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 1.1 < $q^2$ < 2 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 2 < $q^2$ < 4.3 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 4.3 < $q^2$ < 6 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 6 < $q^2$ < 8.68 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 10.09 < $q^2$ < 12.86 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 14.18 < $q^2$ < 16 GeV$^2$