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.
FlexibleSUSY 2.0: Extensions to investigate the phenomenology of SUSY and non-SUSY models
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abstract
We document major new features and improvements of FlexibleSUSY, a Mathematica and C++ package with a dependency on the external package SARAH, that generates fast and precise spectrum generators. The extensions presented here significantly increase the generality and capabilities of the FlexibleSUSY package, which already works with a wide class of models, while maintaining an elegant structure and easy to use interfaces. The FlexibleBSM extension makes it possible to also create spectrum generators for non-supersymmetric extensions of the Standard Model. The FlexibleCPV extension adds the option of complex parameters to the spectrum generators, allowing the study of many interesting models with new sources of $CP$ violation. FlexibleMW computes the decay of the muon for the generated model and thereby allows FlexibleSUSY to predict the mass of the $W$ boson from the input parameters by using the more precise electroweak input of $\{ G_F, M_Z, \alpha_{\text{em}} \}$ instead of $\{ M_W, M_Z, \alpha_{\text{em}} \}$. The FlexibleAMU extension provides a calculator of the anomalous magnetic moment of the muon in any model FlexibleSUSY can generate a spectrum for. FlexibleSAS introduces a new solver for the boundary value problem which makes use of semi-analytic expressions for dimensionful parameters to find solutions in models where the classic two-scale solver will not work such as the constrained E$_6$SSM. FlexibleEFTHiggs is a hybrid calculation of the Higgs mass which combines the virtues of both effective field theory calculations and fixed-order calculations. All of these extensions are included in FlexibleSUSY 2.0, which is released simultaneously with this manual.
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2026 2verdicts
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Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.
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Jarvis-HEP: A lightweight Python framework for workflow composition and parameter scans in high-energy physics
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.