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The new $(g-2)_\mu$ and Right-Handed Sneutrino Dark Matter

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arxiv 2107.02285 v2 pith:PQJIHMPI submitted 2021-07-05 hep-ph

classification hep-ph
keywords darklesssimmatterright-handedtildedetectionsneutrinosupersymmetric
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

In this paper we investigate the $(g-2)_\mu$ discrepancy in the context of the R-parity conserving next-to-minimal supersymmetric Standard Model plus right-handed neutrinos superfields. The model has the ability to reproduce neutrino physics data and includes the interesting possibility to have the right-handed sneutrino as the lightest supersymmetric particle and a viable dark matter candidate. Since right-handed sneutrinos are singlets, no new contributions for $\delta a_{\mu}$ with respect to the MSSM and NMSSM are present. However, the possibility to have the right-handed sneutrino as the lightest supersymmetric particle opens new ways to escape Large Hadron Collider and direct detection constraints. In particular, we find that dark matter masses within $10 \lesssim m_{\tilde{\nu}_{R}} \lesssim 600$ GeV are fully compatible with current experimental constraints. Remarkably, not only spectra with light sleptons are needed, but we obtain solutions with $m_{\tilde{\mu}} \gtrsim 600$ GeV in the entire dark matter mass range that could be probed by new $(g-2)_\mu$ data in the near future. In addition, dark matter direct detection experiments will be able to explore a sizable portion of the allowed parameter space with $m_{\tilde{\nu}_{R}} \lesssim 300$ GeV, while indirect detection experiments will be able to probe a much smaller fraction within $200 \lesssim m_{\tilde{\nu}_{R}} \lesssim 350$ GeV.

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Cited by 1 Pith paper

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  1. Shedding Light on Dark Matter at the LHC with Machine Learning

    hep-ph 2025-09 conditional novelty 5.0 of 10

    A machine-learned LHC analysis projects 5-sigma sensitivity to singlino-dominated NMSSM dark matter via radiative higgsino decays to photons, covering higgsino masses up to 225 GeV.

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