The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 2, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 3, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 130 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 130 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 140 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 140 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 150 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 150 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 160 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 160 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 170 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 170 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 180 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 180 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 190 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 190 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 210 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 210 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 220 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 220 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 230 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 230 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 240 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 240 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 250 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 250 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 260 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 260 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 270 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 270 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 280 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 280 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 290 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 290 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 310 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 310 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 320 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 320 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 330 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 330 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 340 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 340 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 350 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 350 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 360 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 360 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 370 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 370 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 380 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 380 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 390 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 390 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 400 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 400 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 410 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 410 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 420 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 420 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 430 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 430 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 440 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 440 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 450 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 450 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 460 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 460 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 470 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 470 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 480 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 480 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 490 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 490 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 510 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 510 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 520 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 520 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 530 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 530 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 540 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 540 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 550 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 550 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 560 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 560 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 570 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 570 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 580 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 580 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 590 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 590 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 600 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 600 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 610 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 610 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 620 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 620 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 630 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 630 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 640 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 640 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 650 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 650 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 660 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 660 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 670 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 670 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 680 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 680 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 690 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 690 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 700 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 700 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 200 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 200 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 300 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 300 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 500 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 500 GeV for the nb >= 3 (3 tag) category.

Dijet mass spectra after the background only fit with the background prediction in the high-mass region with two b-tags.

Dijet mass spectra after the background only fit with the background prediction in the low-mass region with two b-tags.

The online b-tagging efficiency with respect to the offline b-tagging efficiency as a function of pT. The b-tagging online and offline working points correspond to an efficiency of 60% and 70%, respectively.

Observed and expected 95% credibility-level upper limits on the cross-section for the b* model in the high-mass region with inclusive b-jet selection.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for the SSM and leptophobic Z' models in the low- and high-mass region with two b-tags selection.

Observed and expected 95% credibility-level upper limits on the cross-section for DM Z' models in the low-mass region with two b-tags selection. The Z' is expected to decay to all five quark flavors other than the top quark and the mediator to SM quark coupling (gSM) equal to 0.1 is assumed.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for DM Z'->bb models in the high-mass region with two b-tags selection. The Z' is expected to decay to bb only and the mediator to SM quark coupling (gSM) equal to 0.25 is assumed.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the high-mass inclusive one b-tag selection.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the combined low- and high-mass two b-tags selection.

The mass distributions for the inclusive one b-tagged selection and two b-tagged selection using an integrated luminosity of 36.1 $fb^{-1}$. The inclusive one b-tagged Pythia8 MC distribution is normalized to the inclusive one b-tagged data. The two b-tagged Pythia8 MC distribution is normalized to the two b-tagged data. The systematic uncertainty band is dominated by the b-tagging scale factor and the b-jet energy scale.

Signal acceptance times efficiency for inclusive 1 b-tag and 2 b-tag categories as a function of the simulated b* and the Z' masses.

Signal acceptance times efficiency for 2 b-tag categories as a function of the simulated Z' masses.

The flavor composition of the simulated dijet background as a function of dijet mass before tagging. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with inclusive one b-tag. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with two b-tags. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ MediumMass SR eff.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

Lower mass requirement for signal regions.

Lower mass requirement for signal regions.

Lower mass requirement for signal regions.

Expected and observed events in the 16 discovery regions along with the according control regions.

Expected and observed events in the 16 discovery regions along with the according control regions.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic R-hadron search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic R-hadron search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector R-hadron search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector R-hadron search.

p0-values and model-independent upper limits on cross-section x acceptance x efficiency for the 16 discovery regions.

p0-values and model-independent upper limits on cross-section x acceptance x efficiency for the 16 discovery regions.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic search for metastable gluino R-hadrons.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic search for metastable gluino R-hadrons.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector direct-stau search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector direct-stau search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector chargino search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector chargino search.

Upper cross-section limit in gluino R-hadron search.

Upper cross-section limit in gluino R-hadron search.

Upper cross-section limit in sbottom R-hadron search.

Upper cross-section limit in sbottom R-hadron search.

Upper cross-section limit in stop R-hadron search.

Upper cross-section limit in stop R-hadron search.

Upper cross-section limit in stau search.

Upper cross-section limit in stau search.

Upper cross-section limit in chargino search.

Upper cross-section limit in chargino search.

Lower mass limit as function of gluino lifetime.

Lower mass limit as function of gluino lifetime.

Acceptance x efficiency, acceptance and efficiency for the full range of simulated masses in the MS-agnostic R-hadron search.

Acceptance x efficiency, acceptance and efficiency for the full range of simulated masses in the MS-agnostic R-hadron search.

Upper cross-section limit in meta-stable gluino R-hadron search.

Upper cross-section limit in meta-stable gluino R-hadron search.

Flavor composition of 800 GeV stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

ETmiss trigger efficiency as function of true ETmiss (EtmissTurnOn).

ETmiss trigger efficiency as function of true ETmiss (EtmissTurnOn).

Single-muon trigger efficiency as function of $|\eta|$ and $\beta$ (SingleMuTurnOn).

Single-muon trigger efficiency as function of $|\eta|$ and $\beta$ (SingleMuTurnOn).

Candidate reconstruction efficiency for ID+Calo selection (IDCaloEff).

Candidate reconstruction efficiency for ID+Calo selection (IDCaloEff).

Candidate reconstruction efficiency for loose selection (LooseEff).

Candidate reconstruction efficiency for loose selection (LooseEff).

Efficiency for a loose candidate to be promoted to a tight candidate (TightPromotionEff).

Efficiency for a loose candidate to be promoted to a tight candidate (TightPromotionEff).

Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels in the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

The product of acceptance, efficiency, and branching fraction of the qbX signal with $\mathrm{X} \rightarrow \tau\tau$ and $m_{\mathrm{B}}=170~\mathrm{GeV}$ in $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels of the 1b1f and 1b1c event categories, as a function of the X boson mass. The selections are as described in the paper. The uncertainty refers to the statistical uncertainty only.

Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1f category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.

Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1c category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.

Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1b1f category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.

Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1b1c category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 300 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 450 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1f category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1c category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1b1f category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1b1c category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.

Observed 95% confidence-level upper limits on the cross section for Drell-Yan spin-1/2 HECO production as a function of mass for various values of electric charge in the range $20\le|z|\le100$.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 4000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 4000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 200 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 1000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 1500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 2000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 2500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 3000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 4000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 200 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 1000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 1500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 2000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 2500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 3000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 4000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 200 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 1000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 1500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 2000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 2500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 3000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 4000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 200 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 1000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 1500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 2000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 2500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 3000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 4000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 200 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 1000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 1500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 2000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 2500 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 3000 GeV.

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 4000 GeV.

Upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the visible cross section in the electron+neutrino channel as a function of the transverse mass threshold.

Observed upper limits at the 95% CL on the visible cross section in the muon+neutrino channel as a function of the transverse mass threshold.

Product of acceptance and efficiency for the electron and muon selections as a function of the $W^\prime$ pole mass.

Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.

Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> ee. The error bars indicate the total uncertainties.

Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.

Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.

Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.

Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.

Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.

Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.

95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.

95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.

95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.

95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.

Fraction of detector volume covered by the material veto as a function of z and Rxy of the displaced dilepton vertex.

Fraction of detector volume covered by the disabled pixel modules veto veto as a function of z and Rxy of the displaced dilepton vertex.

Observed Rxy distribution of vertices composed of two non-leptonic tracks in a control sample in the data and the predicted distribution obtained from the event mixing. The error bars indicate the statistical uncertainties.

Rxy distributions of Kshort vertices from the large radius tracking in the data and background MC samples. Data has been normalised such that the total number of Kshort from the standard tracking in the data agrees with the total number of Kshort from the standard tracking in the MC. The error bars indicate the statistical uncertainties.

Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the statistical uncertainties.

Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the statistical uncertainties.

Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the statistical uncertainties.

Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.

Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.

Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.

Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.

Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.

Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.

Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.

Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.

Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.

Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.

Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.

Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.

Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.

Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.

Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.

Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.

Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.

Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.

Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.

Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.

Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.

Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.

Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.

Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> ee.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> emu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> mumu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> ee.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> emu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> mumu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> ee.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> emu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> mumu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> ee.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> emu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> mumu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> ee.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> emu.

Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> mumu.

Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 100 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.

Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 250 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.

Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 500 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.

Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 750 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.

Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 1000 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.

Observed yields and pre-fit background predictions for Njets 8-9.

Observed yields and pre-fit background predictions for Njets >=10.

Observed yields and pre-fit background predictions for aggregated bins.

Pre-fit background covariance matrix $\sigma_{xy}$ for the 174 analysis bins.

Pre-fit background correlation matrix $\rho_{xy}$ for the 174 analysis bins.

Observed yields and post-fit background predictions for Njets 2-3.

Observed yields and post-fit background predictions for Njets 4-5.

Observed yields and post-fit background predictions for Njets 6-7.

Observed yields and post-fit background predictions for Njets 8-9.

Observed yields and post-fit background predictions for Njets >=10.

Simulated signal yields for representative gluino signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative gluino signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

The 95% CL observed and expected upper limits on the production cross sections of the T1tttt signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1bbbb signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1qqqq signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T5qqqqVV signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2tt signal model as a function of the top squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2bb signal model as a function of the bottom squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2qq signal model as a function of the LSP and light squark masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

The observed significance of the SMS models for T1tttt as function of the gluino and LSP masses.

The observed significance of the SMS models for T1bbbb as function of the gluino and LSP masses.

The observed significance of the SMS models for T1qqqq as function of the gluino and LSP masses.

The observed significance of the SMS models for T5qqqqVV as function of the gluino and LSP masses.

The observed significance of the SMS models for T2tt as function of the top squark and LSP masses.

The observed significance of the SMS models for T2bb as function of the bottom squark and LSP masses.

The observed significance of the SMS models for T2qq as function of the LSP and light squark masses.

The efficiency times acceptance of the SMS models for T1tttt as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1bbbb as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1qqqq as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T5qqqqVV as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2tt as function of the top squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2bb as function of the bottom squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2qq as function of the LSP and light squark masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) ~ m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) ~ m(LSP). Only statistical uncertainties are shown.