The total coherent $\mathrm{J}/\psi$ photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$, measured in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$ values used correspond to the center of each rapidity range. The theoretical uncertainties is due to the uncertainties in the photon flux.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The photon flux values from STARLight as a function of rapidity, in different neutron multiplicity classes: 0n0n, 0nXn, and XnXn.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0n0n neutron multiplicity class.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0nXn neutron multiplicity class.

The covariance matrix for the flux in the XnXn neutron multiplicity class.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

Values of $N^{EXP}_{coll}$ versus $p_{T}$ as defined in Eq. 2 for three d+Au event classes, (a) $0\%–100\%$, (b) $0\%–5\%$ and (c) $60\%–88\%$. Also shown are fits to the data (solid lines) and the corresponding value $N^{GL}_{coll}$ (dashed lines).

Panels (d) to (f) show the nuclear modification factors $R^{\pi^{0}}_{dAu,EXP}$, calculated with Eq. 3, for the same event selections as in (a) to (c) together with fits to the data, (d) $0\%–100\%$, (e) $0\%–5\%$ and (f) $60\%–88\%$.

The Ratio $N^{EXP}_{coll}/N^{GL}_{coll}$ as a function of $N^{EXP}_{coll}$. Horizontal and vertical bars are the statistical uncertainties. The values for $0\%–100\%$ d+Au collisions are represented by a solid blue line, with the statistical uncertainty given as band. The scale uncertainties that are common to all data points are shown for the $0\%–100\%$ value.

Average $R^{\pi^{0}}_{dAu,EXP}$ as a function of $N^{EXP}_{coll}$. Horizontal and vertical bars are the statistical uncertainties. The values for $0\%–100\%$ d+Au collisions are represented by a solid blue line, with the statistical uncertainty given as band. The scale uncertainties(16.5%) that are common to all data points are shown for the $0\%–100\%$ value.

Average $R^{\pi^{0}}_{dAu,EXP}$ as a function of $N^{EXP}_{coll}$. Horizontal and vertical bars are the statistical uncertainties. The values for $0\%–100\%$ d+Au collisions are represented by a solid blue line, with the statistical uncertainty given as band. The scale uncertainties($16.5\%$) that are common to all data points are shown for the $0\%–100\%$ value. The systematic uncertainties on $N^{EXP}_{coll}$, $\approx16\%$, are dominated by uncertainties on the p+p data set and thus are a common scale uncertainty for all d+Au event classes.

$P_z$ sine coefficients of $\Lambda+\bar{\Lambda}$ as a function of transverse momentum in isobar collisions at 200 GeV.

$P_z$ sine coefficients of $\Lambda+\bar{\Lambda}$ as a function of the number of participants in isobar collisions at 200 GeV. The number of participants for isobar collisions were taken from Table III of Phys.Rev.C105, 014901 (2022) and averaged. Same data as the centrality dependence in Fig. 3.

Cutflow for two representative signal samples used in this analysis. The excited tau mass $m_{\tau^\ast} = 2.75$ TeV and the contact interaction scale $\Lambda=10$ TeV. The LQ mass $m_\mathrm{LQ} = 1.3$ TeV. The event yields include all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Acceptance x efficiency of the $\tau^\ast$ signal SR selection

Acceptance x efficiency of the LQ signal SR selection

HFE (electrons from semileptonic decays of heavy-flavor hadrons) invariant yields in different centrality intervals of Au+Au collisions at $\sqrt{s_{\rm NN}}=200$ GeV. The vertical bars and the boxes represent statistical and systematic uncertainties, respectively. The horizontal bars indicate the bin width.

HFE (electrons from semileptonic decays of heavy-flavor hadrons) $R_{\rm AA}$ (red circles) as a function of $p_{\rm T}$ in different centrality intervals of Au+Au collisions at $\sqrt{s_{\rm NN}}=200$ GeV, compared with STAR (yellow stars) and PHENIX (green squares) published results, and Duke ((modified Langevin transport model, blue line) and PHSD (parton-hadron-string dynamics model, orange line) model calculations. Vertical bars and boxes around data points represent combined statistical and systematic uncertainties from both Au+Au and $p$+$p$ measurements, respectively. Boxes at unity show the global uncertainties, which for this analysis include the 8% global uncertainty on $p$+$p$ reference and the $N_{\rm coll}$ uncertainties. The left box is for PHENIX and the right one for STAR.

HFE (electrons from semileptonic decays of heavy-flavor hadrons) $R_{\rm AA}$ (red circles) as a function of $N_{\rm part}$ in Au+Au collisions at $\sqrt{s_{\rm NN}}=200$ GeV, compared with PHENIX measurements (green squares), and Duke (blue line) and PHSD (orange line) model calculations. Vertical bars and boxes around data points represent statistical and systematic uncertainties from Au+Au measurements, respectively. The gray band represents the $N_{\rm coll}$ uncertainties. The boxes at unity show the global uncertainties including the total uncertainties of the $p$+$p$ reference.

Comparison of the $m_{miss}$ shapes for the simulated signal events within the fiducial region and those outside it, after including the effect of PU protons as describe in the text, for a generated $m_{X}$ mass of 1000 GeV. The distributions are shown for single(+z)-single(−z) proton reconstruction categories.

Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.

Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for different proton reconstruction categories in the $Z \rightarrow \mu\mu $ analysis, and for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the positive CT-PPS arm is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the negative CT-PPS arm is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The di-proton invariant mass is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The $m_{miss}$ is shown.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow ee$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow \mu\mu$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $\gamma$ analysis.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The sample VR category shown is defined by $N_\textrm{RT} \geq 2$, $H_T > 1100$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT}=1$, $N_\textrm{BT} \geq 1$, $H_T > 1400$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty after the fit.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT} = 2$, $H_T > 1100$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty after the fit.

Expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from each final state and the combination with previous CMS results (EPJC 80 (2020) 75 and JHEP 11 (2019) 082). The same-sign dilepton and multilepton (SSDL\&ML) final state results are from EPJC 80 (2020) 75.

Measured signal strength ($\mu = \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}}/ \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}} ^{\textrm{SM}}$), corresponding cross section (in fb), and the expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from all analysis channels. This table shows production from each analysis channel in this Letter, the combination of those channels, the results from previously published results, and the full combination of all CMS 2016-2018 results.

Observed and expected 95% CL upper limits on ${{(\sigma_{\text{H}}/\sigma_{\text{H}}^{\mathrm{SM}}) \times {{\mathcal{B}(\text{H} \to \text{inv})}}}}$ for the combined VBF, ttH, VH and ggH channels using all available CMS data for 2016--2018, Run1, 2015, and their combination, assuming a SM Higgs boson with a mass of 125 GeV.

Observed and expected 95% CL upper limits on ${{(\sigma_{\text{H}}/\sigma_{\text{H}}^{\mathrm{SM}}) \times {{\mathcal{B}(\text{H} \to \text{inv})}}}}$ for the VBF, ttH(lep), ttH(had), V(qq)H, Z(ll)H, Z(bb)H and ggH channels using all available CMS data, and their combination, assuming a SM Higgs boson with a mass of 125 GeV.

The 90% CL upper limits on the spin-independent DM-nucleon scattering cross section in Higgs-portal models, assuming a scalar, fermionic or vectorial DM candidate (with a UV-complete vector model), compared to direct detection experimets CRESST-III, DarkSide-50, LUX_ZEPLIN and PandaX-4T (2022 results).

Postfit event yields in each category and hadronic recoil bin of the ttH category SR for the different background and signal processes summed across 2016, 2017 and 2018 samples. The background and signal yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only. The Postfit signal contributions for a Higgs boson, produced in ttH, VH (split into WH and ZH), ggH and VBF, decaying to invisible particles with a branching fraction of $\mathcal{B}(\text{H} \to \text{inv}) = 1$, and the observed event yields are reported.

Postfit event yields in each category and hadronic recoil bin of the VH category SR for the different background and signal processes summed across 2016, 2017 and 2018 samples. The background and signal yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only. The Postfit signal contributions for a Higgs boson, produced in ttH, VH (split into WH and ZH), ggH and VBF, decaying to invisible particles with a branching fraction of $\mathcal{B}(\text{H} \to \text{inv}) = 1$, and the observed event yields are reported.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the ttH category e$+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the VH category e$+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the ttH category $\mu+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the VH category $\mu+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the ttH category ee$+$jets, $\mu\mu+$jets, and $\ell\ell+$jets CRs for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the VH category ee$+$jets, $\mu\mu+$jets, and $\gamma+$jets CRs for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.