Oracle9i Performance Tuning Chapter 11 Advanced Tuning Topics.
Fine Tuning Standard Model and Beyond Peter Athron Dr David Miller In collaboration with.
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Transcript of Fine Tuning Standard Model and Beyond Peter Athron Dr David Miller In collaboration with.
![Page 1: Fine Tuning Standard Model and Beyond Peter Athron Dr David Miller In collaboration with.](https://reader038.fdocuments.in/reader038/viewer/2022103111/5518a089550346991f8b485e/html5/thumbnails/1.jpg)
Fine Tuning Standard Model and Beyond
Peter Athron
Dr David MillerIn collaboration with
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physical mass = “bare mass” + “loops”
= +
divergent Cut off integral at Planck Scale
Fine tuning
Hierarchy Problem
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Supersymmetry The only possible extension to space-time
Unifies gauge couplings
Provides Dark Matter candidates
Baryogenesis in the early universe
Elegant solution to the Hierarchy Problem!
Essential ingredient for M-Theory
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Bosonic degrees of freedom = Fermionic degrees of freedom.
) Two scalar superpartners for each fermion
In Susy
No Fine Tuning?
Quadratic divergences cancelled!
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MSSM At Tree Level:
Sparticle mass limits ) Parameters
But
Exact Susy Softly Broken Susy
LEP search fruitless!! Lower bounds on sparticles
Fine Tuning reintroduced?
Little Hierarchy Problem
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R. Barbieri & G.F. Giudice, (1988)
Define Tuning
is fine tuned
% change in from 1% change in
Observable
Parameter
Traditional Measure
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Criticisms of Traditional Measure
Considers each parameter separately
The fine tuning is about cancellations between parameters . A good fine tuning measure considers all parameters together.
Implicitly assumes a uniform distribution of parameters
Parameters in LGUT may be different to those in LSUSY Corresponds to choosing parameters from a different probability distribution
Takes infinitesimal perturbations about the point
MSSM observables are complicated functions of many parameters. Many small isolated regions of parameter space may give the same value of the observable.
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New Measure
the volume of parameter space,
the subspace of s.t. the observable
Tuning occurs when variations in dimensionless parameters ) larger variations in dimensionless observables.
Parameter space point,
Tuning is defined as:
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Fine tuning as a function of Higgs Mass Fine tuning as a function of the New Physics scale
SM Revisited
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Fine Tuning in the MSSM
Choose a point P in the parameter space at GUT scale Take random fluctuations about this point. Using a modified version of Softsusy (B.C. Allanach)
Run to Electro-Weak Symmetry Breaking scale. Predict Mz and sparticle masses
Count how often Mz is ok Apply fine tuning measure
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If the tuning in the MSSM is fine for flat probability distributions:
Nature is fine tuned.
EWSB by some other mechanism than the Higgs
e.g. Technicolor
The Hierarchy problem is solved other new physics
e.g. Little Higgs, Large Extra Dimensions
Extended Higgs sector SSM’s are favoured e.g. NMSSM, nMSSM, ESSM
The MSSM parameters are not all equally likely. What probability distribution minimises tuning? Is there a GUT with this distribution?
Also contains tunings
S.F. King, S. Moretti, R. Nevzarov,
hep-ph/0510419, hep-ph/0511256
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Conclusions
Fine Tuning in the SM SUSY
Broken SUSY appears fine tuned Little Hierarchy Problem
Current measures of tuning neglect: Probability distribution of parameters.
Many parameter nature of fine tuning
Cancellations a finite distance from point New measure addresses these issues
Results for MSSM coming soon
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Ruled out by experiment
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Fine tuning as a function of Higgs Mass
Fine tuning as a function of the New Physics scale
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Numerical Approximation
Where is the number of points in space
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Is the Tuning Fine?
Aesthetic question. How much tuning are we prepared to tolerate?
Intuitive physical notion. How do we measure tuning?