Symbolic regression produces an approximate classifier for LHC exclusion limits that enables their direct inclusion during pMSSM global fits.
Bayesian active search on parameter space: A 95 GeV spin-0 resonance in the (B−L)SSM
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A 2HDM extended by two real scalar singlets is scanned with evolutionary strategies to locate regions satisfying vacuum, unitarity, oblique-parameter, collider and dark-matter constraints.
Mono-Z' events from Z' plus singlet Higgs production in the BLSSM-IS, with h' decaying to LSP dark matter pairs, yield a detectable leptonic signal independent of the specific DM candidate.
citing papers explorer
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Symbolic Classification-Enabled LHC Limits Online BSM Global Fits
Symbolic regression produces an approximate classifier for LHC exclusion limits that enables their direct inclusion during pMSSM global fits.
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Machine Learning in the 2HDM2S model for Dark Matter
A 2HDM extended by two real scalar singlets is scanned with evolutionary strategies to locate regions satisfying vacuum, unitarity, oblique-parameter, collider and dark-matter constraints.
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Mono-Z' Signatures in the B-L Supersymmetric Standard Model at the LHC
Mono-Z' events from Z' plus singlet Higgs production in the BLSSM-IS, with h' decaying to LSP dark matter pairs, yield a detectable leptonic signal independent of the specific DM candidate.