Symbolic regression produces an approximate classifier for LHC exclusion limits that enables their direct inclusion during pMSSM global fits.
SModelS: a tool for interpreting simplified-model results from the LHC and its application to supersymmetry
5 Pith papers cite this work, alongside 198 external citations. Polarity classification is still indexing.
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abstract
We present a general procedure to decompose Beyond the Standard Model (BSM) collider signatures presenting a Z2 symmetry into Simplified Model Spectrum (SMS) topologies. Our method provides a way to cast BSM predictions for the LHC in a model independent framework, which can be directly confronted with the relevant experimental constraints. Our concrete implementation currently focusses on supersymmetry searches with missing energy, for which a large variety of SMS results from ATLAS and CMS are available. As show-case examples we apply our procedure to two scans of the minimal supersymmetric standard model. We discuss how the SMS limits constrain various particle masses and which regions of parameter space remain unchallenged by the current SMS interpretations of the LHC results.
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MadAnalysis 5 v1.11 adds validated recasting of two ATLAS compressed-electroweakino searches and shows that a proposed NMSSM scenario fits the soft-lepton and monojet excesses less well than simpler models.
A reweighting method creates model-agnostic likelihoods from histogram analyses, applied to Belle II B+ to K+ nu nubar data for WET constraints and light new physics searches.
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.
SModelS v3.0 largely reproduces ATLAS pMSSM electroweak-ino constraints, with CMS inclusion and combinations tightening limits but leaving some light ino parameter space viable.
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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Deciphering compressed electroweakino excesses with MadAnalysis 5
MadAnalysis 5 v1.11 adds validated recasting of two ATLAS compressed-electroweakino searches and shows that a proposed NMSSM scenario fits the soft-lepton and monojet excesses less well than simpler models.
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Accelerating Discovery: Model-Agnostic Likelihoods for the Reinterpretation of Particle Physics Results and their Application to the Belle II $B^{+}\to K^{+}\nu\bar{\nu}$ Measurement
A reweighting method creates model-agnostic likelihoods from histogram analyses, applied to Belle II B+ to K+ nu nubar data for WET constraints and light new physics searches.
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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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On the coverage of electroweak-inos within the pMSSM with SModelS -- a comparison with the ATLAS pMSSM study
SModelS v3.0 largely reproduces ATLAS pMSSM electroweak-ino constraints, with CMS inclusion and combinations tightening limits but leaving some light ino parameter space viable.