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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EasyScan_HEP 2 adds AI-agent interfaces to a HEP parameter scan framework for natural-language to .ini config translation and new sampler integration.
BSMArt version 2 adds new scanning algorithms including Affine MC, MLScanner, and CMA-ES variants to simplify and accelerate parameter space exploration in new physics models, demonstrated on soft lepton excess searches at the LHC.
Machine learning optimization of a generalized SU(5) parameter y finds y ≈ 0.8 produces the closest match to the original model while resolving the fermion mass discrepancy.
citing papers explorer
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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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EasyScan_HEP 2: Agent-Ready Parameter Scans for High-Energy Physics
EasyScan_HEP 2 adds AI-agent interfaces to a HEP parameter scan framework for natural-language to .ini config translation and new sampler integration.
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BSMArt 2: simpler and faster parameter space scans
BSMArt version 2 adds new scanning algorithms including Affine MC, MLScanner, and CMA-ES variants to simplify and accelerate parameter space exploration in new physics models, demonstrated on soft lepton excess searches at the LHC.
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Good flavor search in SU(5): a machine learning approach
Machine learning optimization of a generalized SU(5) parameter y finds y ≈ 0.8 produces the closest match to the original model while resolving the fermion mass discrepancy.