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Reconstruction of Fundamental SUSY Parameters at LHC and LC

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Reconstruction of Fundamental SUSY Parameters at LHC and LC. R mi Lafaye - CERN/ATLAS on leave from LAPP-IN2P3 ... hep-ph/0212020 [Degrassi et al.] for higher ... – PowerPoint PPT presentation

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Title: Reconstruction of Fundamental SUSY Parameters at LHC and LC


1
Reconstruction of Fundamental SUSY Parameters at
LHC and LC
  • Rémi Lafaye - CERN/ATLAS on leave from LAPP-IN2P3
  • On behalf of the SFitter and Fittino authors
    P. Bechtle, K.
    Desch, R. L, T. Plehn, P. Wienemann and D. Zerwas
  • and the members of the SPA project

2
Outline
  • Reconstruction of Fundamental SUSY Parameters at
    LHC and LC
  • The SPA project
  • SPS1a uncertainties at LHC and LC
  • Top-down approach SPS1a mSUGRA scenario
  • Bottom-up approach SPS1a pMSSM fit
  • Back to GUT scale

3
1. The SPA Project
  • SPA Supersymmetry Parameter Analysis
  • The SPA project is a joint study of theorists and
    experimentalists working on LHC and LC
    phenomenology
  • SPA Tasks
  • High-precision determination of the SUSY Lagrange
    parameters at the electroweak scale
  • Extrapolation to high scale to reconstruct the
    fundamental parameters and the mechanism for SUSY
    breaking
  • Need to match expected experimental accuracy with
    theoretical predictions
  • Extend the set of observables
  • Coherent LHC/LC analysis
  • Starting point LHC/LC study group report G.
    Weiglein et al.

4
1. SPA Conventions
  • SUSY particle masses pole masses
  • Use DR scheme and scale MSUSY 1 TeV
  • Except for Higgs mixing matrix
  • On-shell and scale light Higgs mass
  • Standard Model input

5
1. SPA Framework
  • Common standard SUSY Les Houches Accord (SLHA)
  • Gathering of Tools
  • Spectrum calculators FeynHiggs, IsaSusy,
    SoftSusy, SPheno, SuSpect
  • Observables calculation SDecay, NMHDecay,
    Prospino2
  • Event generators Isajet, Pythia, Whizard
  • Cold dark matter Micromegas, DarkSusy
  • RGE programs
  • Extraction of SUSY parameters
  • SFitter R. L, T. Plehn, D. Zerwas
    Grid scan start MINUIT
  • Fittino P. Bechtle, K. Desch, P. Wienemann
    Tree-level start MINUIT
  • Both include higher order corrections
  • ? Similar results

6
2. Higgs Masses
hep-ph/0212020 Degrassi et al. for higher
order corrections hep-ph/0406166 Allanach
et al. for SoftSusy, SPheno and SuSpect
comparison Higgs mass theoretical uncertainties
dominate, even at LHC
7
2. Gaugino and Sfermions Masses
  • Gjelsten et al, Martyn et al.
  • Theoretical uncertainties from hep-ph/0302102
    Allanach et al.

8
2. LC Cross Sections and BR
Only statistical uncertainties included Martyn
et al.
9
3. mSUGRA Fit Results
Mass measurements only, using experimental and
theoretical uncertainties
SFitter
  • With statistical uncertainties only
  • LHC ? 10 better, LC and LHCLC ? 1 order of
    magnitude better
  • LHC first to provide measurements of mSUGRA
    parameters
  • LC increases precision by an order of magnitude

10
3. mSUGRA Contour Plots
SFitter
1? contour
1? contour
Slight correlations, no secondary minima ? Easy
fit
11
3. Suspect and SoftSusy Comparison
  • Fitting particle mass spectrum (SuSpect) with
  • SuSpect Djouadi, Kneur
  • and
  • SoftSusy Allanach
  • Errors compatible
  • Central values within 1?
  • except for A0 - Systematic ?

SFitter
12
3. mSUGRA Fit Summary
  • SPS1a gluino and most of the squarks not seen at
    LC, only at LHC
  • ? does not worsen the parameter determination at
    LC
  • mSUGRA fit to LC ?m1/2 0.72 GeV
  • mSUGRA fit to LHCLC ?m1/2 0.67 GeV
  • Because
  • gaugino mass unification is an mSUGRA feature
  • m0 dominated by slepton mass measurements over
    squarks
  • (squarks contribution about 10 times lower
    because ?m0 ? ?ms?ms)
  • Bottom up approach needed to cross check mSUGRA
    assumptions
  • and test a larger class of models

13
4. Phenomenological MSSM Fit
  • Summary of accelerators SUSY capabilities
  • LHC gluino, squarks, neutralinos and sleptons
    masses and couplings
  • LC charginos, heavy Higgs and slepton mass high
    precision measurements
  • ? enough information to check mSUGRA
    assumptions without assuming a given SUSY
    breaking scenario
  • Generic MSSM has 105 (too many) free parameters.
  • Make some assumptions
  • All phases 0
  • No mixing between generations
  • No mixing within first 2 generations
  • pMSSM ? 24 parameters

14
4. pMSSM Fit Results
  • Mass measurements only
  • Include theoretical uncertainties
  • 500 GeV-LC gives high precision in the slepton
    sector
  • Only LHC can scan the squark sector apart for
    stop right

SFitter
15
4. pMSSM Fit Results
SFitter
  • 500 GeV-LC gives high precision on crucial
    parameters
  • LHC necessary for any determination of M3 and
    squark sector

16
4. pMSSM Scan Plots
We use a 24 parameter fit, some are easy to fit
SFitter
LC no heavy squarks ? no ?2 dependency
LHC low ?2 dependency
17
4. pMSSM Scan Plots
Others need additional observables
SFitter
Mirror solution and low ?2 dependency
Smooth but very low ?2 dependency
18
4. pMSSM Pull Distributions
  • 120 independent fits - smeared observables
  • Experimental errors only except for mh
  • Start values from tree-level formulae
  • Use mass and cross section measurements
  • mt included in the fit

Pull (Pfit-Ptrue)/?P P a fit parameter
Fittino
tan?
A0
MEAN VALUE 0.0 and RMS 1.0 ? Uncertainties
correctly estimated
19
4. pMSSM Parameters Sensitivity
Vary parameter by ?1? and determine individual
??2 contribution of the various observables using
Fittino
Only a combined LHC and LC study allows a
complete fit without fixing any parameter
20
5. Evolution to GUT scale
Two possibilities 1. Top down fit of a
high-scale scenario to the pMSSM parameters
obtained Ex mSUGRA
tan?
m0
A0
m1/2
Porod et al. using Fittino results
21
5. Extrapolation to GUT scale
2. Bottom-up approach extrapolate pMSSM
parameters to ?GUT using RGE
Porod et al. using Fittino results
22
Next steps
  • Study SPS1a New mSUGRA point defined by SPA
  • ? SPS1a like compatibility with CDM measurements

?
  • To be included in the fitting tools
  • Dark-matter observables
  • New fitting techniques (genetic algorithms)
  • Propagate m?0 measured at LC into LHC analysis
  • Polesello et al.
  • ? improve squark right mass uncertainties
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