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Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at $\sqrt{s}$ = 13 TeV

The CMS collaboration
CMS-PAS-EXO-20-004, 2021.

Abstract
A search is presented for new particles produced in proton-proton collisions at $\sqrt{s}=13~\mathrm{TeV}$ at the LHC, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of $101~\mathrm{fb}^{-1}$, collected in 2017$-$2018 with the CMS detector. Separate categories are defined for events with narrow jets from initial-state radiation and with large-radius jets consistent with a hadronic decay of a W or a Z boson. Novel machine learning techniques are used to identify hadronic W and Z boson decays. The analysis is combined with an earlier search based on a data sample corresponding to an integrated luminosity of $36~\mathrm{fb}^{-1}$, collected in 2016. No significant excess of events is observed with respect to the standard model background expectation, as determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on gravitons in models with large extra dimensions. Several of the new limits are the most restrictive to date.

  • Signal templates, DMsimp, spin-1, Monojet

    Supplementary material

    10.17182/hepdata.106002.v1/t1

    Differential signal yields for various signal hypotheses.

  • Signal templates, DMsimp, spin-0, Monojet

    Supplementary material

    10.17182/hepdata.106002.v1/t2

    Differential signal yields for various signal hypotheses.

  • Signal templates, ADD, Monojet

    Supplementary material

    10.17182/hepdata.106002.v1/t3

    Differential signal yields for various signal hypotheses.

  • Signal templates, LQ, Monojet

    Supplementary material

    10.17182/hepdata.106002.v1/t4

    Differential signal yields for various signal hypotheses.

  • Signal templates, DMsimp, spin-1, Mono-V ($\tau_{21}$)

    Supplementary material

    10.17182/hepdata.106002.v1/t5

    Differential signal yields for various signal hypotheses.

  • Signal templates, DMsimp, spin-0, Mono-V ($\tau_{21}$)

    Supplementary material

    10.17182/hepdata.106002.v1/t6

    Differential signal yields for various signal hypotheses.

  • Signal templates, ADD, Mono-V ($\tau_{21}$)

    Supplementary material

    10.17182/hepdata.106002.v1/t7

    Differential signal yields for various signal hypotheses.

  • Signal templates, LQ, Mono-V ($\tau_{21}$)

    Supplementary material

    10.17182/hepdata.106002.v1/t8

    Differential signal yields for various signal hypotheses.

  • Yields (Mono-V (high purity))

    Data from Figs. 3, 4, as well as supplementary material.

    10.17182/hepdata.106002.v1/t9

    Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only...

  • Yields (Mono-V (low purity))

    Data from Figs. 3, 4, as well as supplementary material.

    10.17182/hepdata.106002.v1/t10

    Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only...

  • Yields (Monojet)

    Data from Figs. 3, 4, as well as supplementary material.

    10.17182/hepdata.106002.v1/t11

    Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only...

  • Simplified likelihood: covariance matrix (Monojet + mono-V)

    Supplementary material

    10.17182/hepdata.106002.v1/t12

    Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions,...

  • Simplified likelihood: Yields (Monojet + mono-V)

    Supplementary material

    10.17182/hepdata.106002.v1/t13

    Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit...

  • Simplified likelihood: covariance matrix (Monojet)

    Supplementary material

    10.17182/hepdata.106002.v1/t14

    Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions,...

  • Simplified likelihood: Yields (Monojet)

    Supplementary material

    10.17182/hepdata.106002.v1/t15

    Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit...

  • Simplified likelihood: covariance matrix (Mono-V)

    Supplementary material

    10.17182/hepdata.106002.v1/t16

    Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions,...

  • Simplified likelihood: Yields (Mono-V)

    Supplementary material

    10.17182/hepdata.106002.v1/t17

    Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit...

  • Cut flow for Monojet, Fermion portal

    Supplementary material

    10.17182/hepdata.106002.v1/t18

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Monojet, ADD

    Supplementary material

    10.17182/hepdata.106002.v1/t19

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Monojet, DM, spin-1 mediator

    Supplementary material

    10.17182/hepdata.106002.v1/t20

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Monojet, DM, spin-0 mediator

    Supplementary material

    10.17182/hepdata.106002.v1/t21

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Monojet, Higgs portal

    Supplementary material

    10.17182/hepdata.106002.v1/t22

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Monojet, Leptoquark

    Supplementary material

    10.17182/hepdata.106002.v1/t23

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (low purity), Fermion portal

    Supplementary material

    10.17182/hepdata.106002.v1/t24

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (low purity), ADD

    Supplementary material

    10.17182/hepdata.106002.v1/t25

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (low purity), DM, spin-1 mediator

    Supplementary material

    10.17182/hepdata.106002.v1/t26

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (low purity), DM, spin-0 mediator

    Supplementary material

    10.17182/hepdata.106002.v1/t27

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (low purity), Higgs portal

    Supplementary material

    10.17182/hepdata.106002.v1/t28

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (low purity), Leptoquark

    Supplementary material

    10.17182/hepdata.106002.v1/t29

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (high purity), Fermion portal

    Supplementary material

    10.17182/hepdata.106002.v1/t30

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (high purity), ADD

    Supplementary material

    10.17182/hepdata.106002.v1/t31

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (high purity), DM, spin-1 mediator

    Supplementary material

    10.17182/hepdata.106002.v1/t32

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (high purity), DM, spin-0 mediator

    Supplementary material

    10.17182/hepdata.106002.v1/t33

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (high purity), Higgs portal

    Supplementary material

    10.17182/hepdata.106002.v1/t34

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • Cut flow for Mono-V (high purity), Leptoquark

    Supplementary material

    10.17182/hepdata.106002.v1/t35

    Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in...

  • 2D exclusion contour, axial, Median Expected

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t36

    Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

  • 2D exclusion contour, axial, Observed

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t37

    Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

  • 2D exclusion contour, axial, Expected plus 1 s.d.

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t38

    Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

  • 2D exclusion contour, axial, Expected minus 1 s.d.

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t39

    Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

  • 2D exclusion contour, vector, Median Expected

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t40

    Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

  • 2D exclusion contour, vector, Observed

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t41

    Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

  • 2D exclusion contour, vector, Expected plus 1 s.d.

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t42

    Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

  • 2D exclusion contour, vector, Expected minus 1 s.d.

    Data from Fig. 6

    10.17182/hepdata.106002.v1/t43

    Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

  • Coupling limits on $g_{\chi}$, axial mediator

    Data from Fig. 7, as well as supplementary material

    10.17182/hepdata.106002.v1/t44

    Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.

  • Coupling limits on $g_{q}$, axial mediator

    Data from Fig. 7, as well as supplementary material

    10.17182/hepdata.106002.v1/t45

    Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.

  • Coupling limits on $g_{\chi}$, vector mediator

    Data from Fig. 7, as well as supplementary material

    10.17182/hepdata.106002.v1/t46

    Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.

  • Coupling limits on $g_{q}$, vector mediator

    Data from Fig. 7, as well as supplementary material

    10.17182/hepdata.106002.v1/t47

    Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.

  • Signal strength limits, scalar mediator

    Data from Fig. 8

    10.17182/hepdata.106002.v1/t48

    Exclusion limits on the signal strength in the simplified model with scalar couplings.

  • Signal strength limits, pseudoscalar mediator

    Data from Fig. 8

    10.17182/hepdata.106002.v1/t49

    Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.

  • ADD $M_{D}$ limits

    Data from Fig. 10

    10.17182/hepdata.106002.v1/t50

    Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.

  • 2D exclusion contour, fermion portal, Median Expected

    Data from Fig. 9

    10.17182/hepdata.106002.v1/t51

    Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

  • 2D exclusion contour, fermion portal, Observed

    Data from Fig. 9

    10.17182/hepdata.106002.v1/t52

    Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

  • 2D exclusion contour, fermion portal, Expected plus 1 s.d.

    Data from Fig. 9

    10.17182/hepdata.106002.v1/t53

    Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

  • 2D exclusion contour, fermion portal, Expected minus 1 s.d.

    Data from Fig. 9

    10.17182/hepdata.106002.v1/t54

    Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

  • DeepAK8 tagging efficiencies

    Supplementary material.

    10.17182/hepdata.106002.v1/t55

    Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the...

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