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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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.
New BSMPT implementation of baryon asymmetry computation using WKB transport equations with moment truncations and VEV profile solving, validated in the C2HDM with uncertainty and GW interplay analysis.
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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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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A Deep Dive into Baryon Asymmetry -- the C2HDM
New BSMPT implementation of baryon asymmetry computation using WKB transport equations with moment truncations and VEV profile solving, validated in the C2HDM with uncertainty and GW interplay analysis.
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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.