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Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models

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Title
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
Author(s)
Peter Athron; Csaba Balazs; Benjamin Farmer; Andrew Fowlie; Dylan Harries; Doyoun Kim
Publication Date
2017-10
Journal
JOURNAL OF HIGH ENERGY PHYSICS, v.2017, no.10, pp.160
Publisher
SPRINGER
Abstract
The Higgs boson discovery stirred interest in next-to-minimal supersymmetric models, due to the apparent fine-tuning required to accommodate it in minimal theories. To assess their naturalness, we compare fine-tuning in a ℤ3 conserving semi-constrained Next-to-Minimal Supersymmetric Standard Model (NMSSM) to the constrained MSSM (CMSSM). We contrast popular fine-tuning measures with naturalness priors, which automatically appear in statistical measures of the plausibility that a given model reproduces the weak scale. Our comparison shows that naturalness priors provide valuable insight into the hierarchy problem and rigorously ground naturalness in Bayesian statistics. For the CMSSM and semi-constrained NMSSM we demonstrate qualitative agreement between naturalness priors and popular fine tuning measures. Thus, we give a clear plausibility argument that favours relatively light superpartners. © 2017, The Author(s)
URI
https://pr.ibs.re.kr/handle/8788114/4199
DOI
10.1007/JHEP10(2017)160
ISSN
1029-8479
Appears in Collections:
HiddenCommunity > 1. Journal Papers (저널논문)
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