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SCIENCE CHINA Physics, Mechanics & Astronomy, Volume 63 , Issue 10 : 101011(2020) https://doi.org/10.1007/s11433-019-1517-5

Higgs assisted razor search for Higgsinos at a 100 TeV $pp$ collider

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  • ReceivedDec 18, 2019
  • AcceptedJan 21, 2020
  • PublishedApr 17, 2020
PACS numbers

Abstract

A 100 TeV proton-proton collider will be an extremely effective way to probe the electroweak sector of the minimal supersymmetric standard model (MSSM). In this paper, we describe a search strategy for discovering pair-produced Higgsino-like next-to-lightest supersymmetric particles (NLSPs) at a 100 TeV hadron collider that decay to Bino-like lightest supersymmetric particles (LSPs) via intermediate $Z$ and SM Higgs bosons that in turn decay to a pair of leptons and a pair of $b$-quarks respectively: $\widetilde{\chi}^0_{2}\widetilde{\chi}^0_{3}$ $\rightarrow$ $(Z\widetilde{\chi}^0_1)(h\widetilde{\chi}^0_1)\rightarrow~bb$ $\ell\ell+\widetilde{\chi}^0_1\widetilde{\chi}^0_1$. In addition, we examine the potential for machine learning techniques to boost the power of our searches. Using this analysis, Higgsinos up to 1.4 TeV can be discovered at the 5$\sigma$ level for Binos with mass of about 0.9 TeV using 3000 fb$^{-1}$ of data.Additionally, Higgsinos up to 1.8 TeV can be excluded at 95% C.L. for Binos with mass of about 1.4 TeV. This search channel extends the multi-lepton search limits, especially in the region where the mass difference between the Higgsino NLSPs and the Bino LSP is small.


Acknowledgment

This research was supported in part by the National Science Foundation, USA (Grant No. NSF PHY-1748958). The research activities of AP and SS were supported in part by the Department of Energy (Grant No. DE-FG02-13ER41976/de-sc0009913). We would like to thank Matt Leone and Ken Johns for helpful discussions. An allocation of computer time from the UA Research Computing High Performance Computing (HPC) and High Throughput Computing (HTC) at the University of Arizona is gratefully acknowledged. We also thank KITP for its hospitality when this draft was completed.


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  • Figure 1

    (Color online) Higgsino pair production $\widetilde{\chi}^0_2\widetilde{\chi}^0_3$ cross section (a), calculated using Prospino2 [52], and decay branching fractions (b), calculated in SUSY-HIT [53], as a function of $\mu$ for $M_1=25$ GeV.

  • Figure 2

    (Color online) Normalized distributions of the razor kinematic variables $M_R$ (a) and $M_T^R$ (b) for a signal benchmark point with $\mu=1$ TeV and $M_1=25$ GeV, as well as the dominant $tt$ and $tbW$ backgrounds after the trigger and identification cuts.

  • Figure 3

    (Color online) Distribution of the decision function of the gradient boosted decision tree classifier for the representative signal benchmark point ($\mu~=~1$ TeV, $M_1~=~25$ GeV) and backgrounds.

  • Figure 4

    (Color online) Discovery (red) and exclusion (blue) contours for the traditional cut-and-count analysis (solid) and boosted decision tree analysis (dashed), for 100 TeV $pp$ collider with an integrated luminosity of 3000 fb$^{-1}$.

  • Table 1   Comparison of Higgsino pair production cross-sections for $(\widetilde{\chi}^0_{2,3}\widetilde{\chi}^\pm_1)$ and $(\widetilde{\chi}^0_{2}\widetilde{\chi}^0_{3})$, for $\mu\approx~1$ TeV, at a 100 TeV collider. The pair-production cross section for $\widetilde{\chi}^0_{2,3}\widetilde{\chi}^\pm_1$ is taken from ref. , while the pair-production cross-section for $\widetilde{\chi}^0_2\widetilde{\chi}^0_3$ is calculated at Next-to-Leading Order (NLO) using Prospino2. The branching ratios to the diboson intermediate states are calculated using SUSY-HIT, and the branching fractions to the SM final states are taken from ref.
    Stage $\widetilde{\chi}^0_{2,3}\widetilde{\chi}^\pm_1$ (fb) $\widetilde{\chi}^0_2\widetilde{\chi}^0_3$ (fb)
    Pair production cross section 60 17.2
    Intermediate diboson contribution ($WZ$) 29.7 ($Zh$) 9.15
    Applying BR$(W\rightarrow~\ell\nu)$, BR$(Z\rightarrow~\ell\ell)$ & BR$(h\rightarrow~bb)$ 0.42 0.37
  • Table 2   Representative cut flow table for a signal benchmark point with $\mu=1$ TeV, $M_1~=~25$ GeV at 100 TeV $pp$ collider, for a traditional cut-and-count analysis. All cross sections are given in unit of fb, and the units for the missing energy, invariant mass, and razor variable cuts are GeV. The significance, $S$/$\sqrt{B}$, is calculated for an integrated luminosity of 3 ab$^{-1}$
    Cuts $\sigma_{\rm~signal}$ $\sigma_{t\bar{t}}$ $\sigma_{tbW}$ $\sigma_{bbWW}$ $\sigma_{BG~{\rm(total)}}$ $S$/$B$ $S$/$\sqrt{B}$
    Original 0.37 35998 4176 7.8 40182 $9.1\times10^{-6}$ 0.10
    Trigger 0.31 5321 1058 2.5 6382 $4.9\times10^{-5}$ 0.21
    SFOS leptons 0.25 1774 360 0.88 2135 $1.2\times10^{-4}$ 0.30
    2 $b$ jets 0.04 290 62 0.09 352 $1.3\times10^{-4}$ 0.13
    ${E\!\!\!/_T}~>~400$ 0.03 5.3 6.8 0.007 12 0.003 0.49
    $m_{\ell\ell}\in~[85,~95]$ 0.03 2.1 3.3 0.004 5.3 0.005 0.62
    $m_{bb}\in~[75,150]$ 0.02 0.59 0.30 $8.2\times10^{-4}$ 0.90 0.02 1.3
    $M_R~>~800$ 0.02 0.03 0.20 $3.3\times10^{-4}$ 0.23 0.09 2.2
    $M^R_T~>~400$ 0.02 0.008 0.18 $1.9\times10^{-4}$ 0.19 0.10 2.4
  • Table 3   Representative cut flow table for the same benchmark point and integrated luminosity as in Table , but using a BDT analysis instead. The preselection is equivalent to the trigger and identification cuts listed in Table . As before, all the cross sections are in fb
    Cuts $\sigma_{\rm~signal}$ $\sigma_{t\bar{t}}$ $\sigma_{tbW}$ $\sigma_{bbWW}$ $\sigma_{{\rm~background}~{\rm(total)}}$ $S$/$B$ $S$/$\sqrt{B}$
    Original 0.37 35998 4176 7.8 40182 $9.1\times10^{-6}$ 0.10
    Preselection 0.04 290 62 0.09 352 $~1.3\times10^{-4}$ 0.13
    $BDT~response~>~5.1$ 0.04 0.02 0.04 $4.8\times10^{-4}$ 0.06 0.63 8.4

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