Isoscalar interaction coupling limit for Lagrangian 7

Isoscalar interaction coupling limit for Lagrangian 10

Isovector interaction coupling limit for Lagrangian 14

Isoscalar interaction coupling limit for Lagrangian 6

Isovector interaction coupling limit for Lagrangian 7

Isovector interaction coupling limit for Lagrangian 9

Isoscalar interaction coupling limit for Lagrangian 18

Isoscalar interaction coupling limit for Lagrangian 4

Isoscalar interaction coupling limit for Lagrangian 2

Isovector interaction coupling limit for Lagrangian 18

Isoscalar interaction coupling limit for Lagrangian 9

Isovector interaction coupling limit for Lagrangian 1

Isovector interaction coupling limit for Lagrangian 8

Isovector interaction coupling limit for Lagrangian 5

Isovector interaction coupling limit for Lagrangian 17

Isoscalar interaction coupling limit for Lagrangian 5

Isoscalar interaction coupling limit for Lagrangian 8

Isovector interaction coupling limit for Lagrangian 12

Isoscalar interaction coupling limit for Lagrangian 11

Isovector interaction coupling limit for Lagrangian 15

Isoscalar interaction coupling limit for Lagrangian 3

Isoscalar interaction coupling limit for Lagrangian 13

Isoscalar interaction coupling limit for Lagrangian 16

Isovector interaction coupling limit for Lagrangian 3

Isovector interaction coupling limit for Lagrangian 20

Isovector interaction coupling limit for Lagrangian 4

Isoscalar interaction coupling limit for Lagrangian 14

Isoscalar interaction coupling limit for Lagrangian 12

Isovector interaction coupling limit for Lagrangian 13

Isovector interaction coupling limit for Lagrangian 11

Isoscalar interaction coupling limit for Lagrangian 20

Isoscalar interaction coupling limit for Lagrangian 17

Isoscalar interaction coupling limit for Lagrangian 15

Isovector interaction coupling limit for Lagrangian 6

Isovector interaction coupling limit for Lagrangian 2

Isovector interaction coupling limit for Lagrangian 10

Isovector interaction coupling limit for Lagrangian 16

Upper limit on the WIMP-nucleus scattering cross section from the single-scatter analysis.

Total acceptance evaluated on a simulated dataset of MIMP events. The mean and upper and lower bounds of the 1 sigma uncertainty band are provided.

Dependence of the parameter $A$ on $(t_1, t_2)$.

Dependence of the parameter $R$ on $(t_1, t_2)$.

Dependence of the parameter $c$ on $(t_1, t_2)$.

Dependence of the parameter $R$ on the two scattered proton transverse momenta.

Correlation coefficients among values of best parameters for the two-channel model, in the case of the exponential parametrisation of the proton-pomeron form factor.

Correlation coefficients among values of best parameters for the two-channel model, in the case of the Orear-type parametrisation of the proton-pomeron form factor.

Correlation coefficients among values of best parameters for the two-channel model, in the case of the power-law parametrisation of the proton-pomeron form factor.

Isoscalar WIMP-nucleon elastic coupling limit for Operator 9

Isoscalar WIMP-nucleon elastic coupling limit for Operator 12

Isoscalar WIMP-nucleon elastic coupling limit for Operator 7

Isoscalar WIMP-nucleon elastic coupling limit for Operator 13

Isoscalar WIMP-nucleon elastic coupling limit for Operator 3

Isoscalar WIMP-nucleon elastic coupling limit for Operator 5

Isoscalar WIMP-nucleon elastic coupling limit for Operator 11

Isoscalar WIMP-nucleon elastic coupling limit for Operator 14

Isoscalar WIMP-nucleon elastic coupling limit for Operator 4

Isoscalar WIMP-nucleon elastic coupling limit for Operator 10

Isoscalar WIMP-nucleon elastic coupling limit for Operator 1

Isoscalar WIMP-nucleon elastic coupling limit for Operator 6

Isoscalar WIMP-nucleon elastic coupling limit for Operator 15

Isovector WIMP-nucleon elastic coupling limit for Operator 3

Isovector WIMP-nucleon elastic coupling limit for Operator 10

Isovector WIMP-nucleon elastic coupling limit for Operator 13

Isovector WIMP-nucleon elastic coupling limit for Operator 12

Isovector WIMP-nucleon elastic coupling limit for Operator 8

Isovector WIMP-nucleon elastic coupling limit for Operator 1

Isovector WIMP-nucleon elastic coupling limit for Operator 4

Isovector WIMP-nucleon elastic coupling limit for Operator 5

Isovector WIMP-nucleon elastic coupling limit for Operator 7

Isovector WIMP-nucleon elastic coupling limit for Operator 11

Isovector WIMP-nucleon elastic coupling limit for Operator 15

Isovector WIMP-nucleon elastic coupling limit for Operator 9

Isovector WIMP-nucleon elastic coupling limit for Operator 14

Isovector WIMP-nucleon elastic coupling limit for Operator 6

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 12

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 3

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 9

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 7

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 10

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 15

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 8

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 4

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 5

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 6

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 13

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 11

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 14

Isoscalar WIMP-nucleon inelastic coupling limit for Operator 1

Isovector WIMP-nucleon inelastic coupling limit for Operator 13

Isovector WIMP-nucleon inelastic coupling limit for Operator 1

Isovector WIMP-nucleon inelastic coupling limit for Operator 4

Isovector WIMP-nucleon inelastic coupling limit for Operator 7

Isovector WIMP-nucleon inelastic coupling limit for Operator 9

Isovector WIMP-nucleon inelastic coupling limit for Operator 3

Isovector WIMP-nucleon inelastic coupling limit for Operator 11

Isovector WIMP-nucleon inelastic coupling limit for Operator 5

Isovector WIMP-nucleon inelastic coupling limit for Operator 10

Isovector WIMP-nucleon inelastic coupling limit for Operator 8

Isovector WIMP-nucleon inelastic coupling limit for Operator 14

Isovector WIMP-nucleon inelastic coupling limit for Operator 15

Isovector WIMP-nucleon inelastic coupling limit for Operator 6

Isovector WIMP-nucleon inelastic coupling limit for Operator 12

The observed 90% C.L upper limit on neutrino effective millicharge (\delta_{Q}[e_{0}]) in SR1. The data contains observed upper limit, median sensitivity and 1\sigma and 2\sigma sensitivity range.

The observerd 90% C.L upper limit on solar axion g_{ae} coupling constant in valid across the mass range for SR1. The data contains observed upper limit, median sensitivity and 1\sigma and 2\sigma sensitivity range as a function of Solar Axion Mass .

The observed 90% C.L. upper limit on axion like particle (ALP) coupling constant (g_{ae}) in SR1. ALP mass spanning from 1 keV to 17 keV is considered. The data contains observed upper limit, median sensitivity and 1\sigma and 2\sigma sensitivity range as a function of ALP Mass.

The observed 90% C.L. upper limit on hidden photon (HP) coupling constant squared (\kappa^2) in SR1. HP mass spanning from 1 keV to 17 keV is considered. The data contains observed upper limit, median sensitivity and 1\sigma and 2\sigma sensitivity range as a function of HP Mass.

The observed 90% C.L. upper limit for the spin-independent (cm^2) WIMP cross-section vs. WIMP mass (GeV/c^2), using the Migdal signal pathway. The result is obtained for WIMPs undergoing the Migdal effect from 0.5 to 9 GeV/c2. The data contains observed upper limit, median sensitivity and 1\sigma and 2\sigma sensitivity range as a function of WIMP Mass.

The observed 90% C.L. upper limit for the spin-dependent WIMP cross-section (cm^2) vs. WIMP mass (GeV/c^2) for coupling on neutrons. The result is obtained for WIMPs undergoing the Migdal effect from 0.5 to 9 GeV/c2. The data contains observed upper limit, median sensitivity and 1\sigma and 2\sigma sensitivity range as a function of WIMP Mass.

The observed 90% C.L. upper limit for the spin-dependent WIMP cross-section (cm^2) vs. WIMP mass (GeV/c^2) for coupling on protons. The result is obtained for WIMPs undergoing the Migdal effect from 0.5 to 9 GeV/c2. The data contains observed upper limit, median sensitivity and 1\sigma and 2\sigma sensitivity range as a function of WIMP Mass.

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.

Expected and observed upper limits on the AQGC operators $a^Z_C/\Lambda^2$, with no unitarization. The $y$ axis shows the limit on the ratio of the observed cross section to the cross section predicted for each anomalous coupling value ($\sigma_\mathrm{AQGC}$).

Limits on LEP-like dimension-6 anomalous quartic gauge coupling parameters, with and without unitarization via a clipping procedure.

Conversion of limits on $a^W_0$ to dimension-8 $f_{M,i}$ operators, using the assumption of vanishing $WWZ\gamma$ couplings to eliminate some parameters. When quoting limits on one of the operators, the other is fixed to zero. The results for $|f_{M,0}/\Lambda^{4}|$ and $|f_{M,4}/\Lambda^{4}|$ are shown with and without clipping of the signal model at 1.4 TeV, when the other parameter is fixed to the SM value of zero.

Conversion of limits on $a^W_0$ and $a^W_C$ to dimension-8 $f_{M,i}$ operators, using the assumption that all $f_{M,i}$ except one are equal to zero. The results are shown with and without clipping of the signal model at 1.4 TeV.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$ with unitarization imposed by clipping the signal model at 1.4 TeV. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^Z_0/\Lambda^2$ vs. $a^Z_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^Z$ and $a_C^Z$ couplings, respectively.