The Experts below are selected from a list of 90 Experts worldwide ranked by ideXlab platform
Doyoun Kim - One of the best experts on this subject based on the ideXlab platform.
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
'Springer Fachmedien Wiesbaden GmbH', 2018Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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)
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
Journal of High Energy Physics, 2017Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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.
Peter Athron - One of the best experts on this subject based on the ideXlab platform.
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
'Springer Fachmedien Wiesbaden GmbH', 2018Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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)
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
Journal of High Energy Physics, 2017Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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.
Dylan Harries - One of the best experts on this subject based on the ideXlab platform.
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
'Springer Fachmedien Wiesbaden GmbH', 2018Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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)
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
Journal of High Energy Physics, 2017Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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.
Andrew Fowlie - One of the best experts on this subject based on the ideXlab platform.
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
'Springer Fachmedien Wiesbaden GmbH', 2018Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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)
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
Journal of High Energy Physics, 2017Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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.
Benjamin Farmer - One of the best experts on this subject based on the ideXlab platform.
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
'Springer Fachmedien Wiesbaden GmbH', 2018Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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)
-
Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
Journal of High Energy Physics, 2017Co-Authors: Peter Athron, Csaba Balazs, Benjamin Farmer, Andrew Fowlie, Dylan Harries, Doyoun KimAbstract: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.