The (p-p)-K$^-$ correlation function obtained using the data-driven approach.

The p-(p-K$^-$) correlation function obtained using the data-driven approach.

Lower-order contributions to the p-p-K$^-$ correlation function obtained using the data-driven approach.

Measured p-p-K$^+$ correlation function.

Measured p-p-K$^-$ correlation function.

p-p-K$^+$ cumulant.

p-p-K$^-$ cumulant.

Self-normalised yield of electrons from heavy-flavour hadron decays as a function of normalised charged-particle pseudorapidity density at midrapidity computed in pp collisions at $\sqrt{s}$ = 13 TeV in different $p_{\rm T}$ intervals

Self-normalised yield of electrons from heavy-flavour hadron decays as a function of normalised charged-particle pseudorapidity density at midrapidity computed in p--pPb collisions at $\sqrt{s_{\rm NN}}$ = 8.16 TeV in different $p_{\rm T}$ intervals

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.

The $\Delta p_{\mathrm{T}}$ of photon-tagged jets as a function of jet $p_{\mathrm{T}}$.

The double $R_{\mathrm{AA}}$ ratio of $R_{\mathrm{AA}}^{\gamma\text{-jet}}/R_{\mathrm{AA}}^{\text{inclusive jet}}$ as a function of jet $p_{\mathrm{T}}$.

The differential cross-section of photon-tagged jets as a function of jet $p_{\mathrm{T}}$ in pp collisions.

The yields of photon-tagged jets as a function of jet $p_{\mathrm{T}}$ in Pb+Pb collisions for different centrality intervals.

The nuclear modification factor of photon-tagged jets as a function of jet $p_{\mathrm{T}}$ for different centrality intervals.

The $\Delta p_{\mathrm{T}}$ of photon-tagged jets as a function of jet $p_{\mathrm{T}}$.

The $R_{\mathrm{CP}}$ of photon-tagged jets as a function of jet $p_{\mathrm{T}}$.

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 observed and expected 95% CL upper limits on the minimal coupling vector LQ pair production cross-sections assuming B = 1 as a function of m$_\text{LQ}$.

The observed and expected 95% CL upper limits on the Yang-Mills coupling vector LQ pair production cross-sections assuming B = 1 as a function of m$_\text{LQ}$.

The observed and expected 95% CL upper limits on the branching ratio into charged leptons as a function of m$_\text{LQ}$ for the scalar LQ.

The observed and expected 95% CL upper limits on the branching ratio into charged leptons as a function of m$_\text{LQ}$ for the vector LQ minimal coupling scenario.

The observed and expected 95% CL upper limits on the branching ratio into charged leptons as a function of m$_\text{LQ}$ for the vector LQ Yang-Mills coupling scenario.

Pseudorapidity distribution of inclusive photons measured within $2.3<\eta_{\rm lab}<3.9$ in pp collisions at $\sqrt{s} = 5020~\mathrm{GeV}$.

Pseudorapidity distribution of inclusive photons measured within $2.3<\eta_{\rm lab}<3.9$ in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Pseudorapidity distribution of inclusive photons measured within $2.3<\eta_{\rm lab}<3.9$ in Pb-p collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Pseudorapidity distribution of inclusive photons measured within $2.3<\eta_{\rm lab}<3.9$ in pp collisions at various LHC energies.

$\langle N_{\rm \gamma} \rangle$ measured within $2.3<\eta_{\rm lab}<3.9$ as a function of collision energy in pp collisions.

Centrality-dependent pseudorapidity distribution of inclusive photons measured within $2.3<\eta_{\rm lab}<3.9$ in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$ (Centrality estimator - CL1).

Centrality-dependent pseudorapidity distribution of inclusive photons measured within $2.3<\eta_{\rm lab}<3.9$ in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$ (Centrality estimator - ZNA).

$\langle N_{\rm \gamma} \rangle$ measured within $2.3<\eta_{\rm lab}<3.9$ as a function of $\langle N_{\rm part} \rangle$ for CL1 centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

$\langle N_{\rm \gamma} \rangle$ measured within $2.3<\eta_{\rm lab}<3.9$ as a function of $\langle N_{\rm part} \rangle$ for ZNA (high-$p_{\rm T}$) centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

$\langle N_{\rm \gamma} \rangle$ measured within $2.3<\eta_{\rm lab}<3.9$ as a function of $\langle N_{\rm part} \rangle$ for ZNA (Pb-side) centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Values of $\langle N_{\rm \gamma} \rangle$/$\langle N_{\rm part} \rangle$ as a function of $\langle N_{\rm part} \rangle$ for CL1 centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Values of $\langle N_{\rm \gamma} \rangle$/$\langle N_{\rm part} \rangle$ as a function of $\langle N_{\rm part} \rangle$ for ZNA (high-$p_{\rm T}$) centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Values of $\langle N_{\rm \gamma} \rangle$/$\langle N_{\rm part} \rangle$ as a function of $\langle N_{\rm part} \rangle$ for ZNA (Pb-side) centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Values of $\langle N_{\rm \gamma} \rangle$/$\langle N_{\rm part} \rangle$ as a function of $\langle N_{\rm \gamma} \rangle$ for CL1 centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Values of $\langle N_{\rm \gamma} \rangle$/$\langle N_{\rm part} \rangle$ as a function of $\langle N_{\rm \gamma} \rangle$ for ZNA (high-$p_{\rm T}$) centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.

Values of $\langle N_{\rm \gamma} \rangle$/$\langle N_{\rm part} \rangle$ as a function of $\langle N_{\rm \gamma} \rangle$ for ZNA (Pb-side) centrality estimator in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5020~\mathrm{GeV}$.