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Neutralino dark matter detection Neutralino dark matter detection around the corner?around the corner?
Status and prospects Status and prospects in the Constrained MSSMin the Constrained MSSM
Roberto TrottaOxford Astrophysics & Royal Astronomical Society
With Roberto Ruiz de Austri (Madrid) & Leszek Roszkowsky (Sheffield)
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What is the Universe made of?What is the Universe made of?
Dark energy70%
Dark matter25%
Stars,planets,human beings,...
Gas
Neutral, stable, cold ΩCDMh2 = 0.103 ± 0.009 (WMAP3)
A well motivated candidate:Lightest Supersymmetric Particle
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SUSY frameworkSUSY framework
Lightest SUSY particle: the neutralinoχ0 = lightest mass eigenstate of
quarks squarks
R = +1 R = -1
leptons sleptons
gauge bosons gauginosHiggs higgsinos
χ0 Forbiddenby R-parity
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WIMP relic densityWIMP relic density
Ωχ h2 ∼ 1/<σv>
(1) Thermal equilibrium(2) Pair annhililation(3) Γ << H : freee out
Relic abundance
Mass mχ ≈ 0.4 m1/2∼ 0.1 – 1 TeV
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The Constrained MSSMThe Constrained MSSM
General MSSM scenario: soft SUSY breaking> 120 free parameters in the Lagrangian
Assuming Universal boundary conditions at MGUT
Gaugino masses: M1 = M2 = M3 = m1/2
Scalar masses: mHd
2 = mHu2 = ML
2 = MR2= MQ
2 = MD2= MU
2 =m02
Trilinear couplings Au = Ad = Al = A0
Higgs vev ratio tanβ = vu/vd
A 4 parameters benchmark scenario(m1/2, m0, A0, tanβ)
2D slices of CMSSM parameter space2D slices of CMSSM parameter space
(Nihei, Roszkowski, Ruiz de Austri 2002)
But this is only for fixed A0, tanβ, mt, mb,....
mmbb = 4.0 GeV m= 4.0 GeV mbb = 4.5 GeV= 4.5 GeV
Uncertainty in SM parameters cannot be neglected (Roszkowski, Ruiz de Austri, Nihei 2001)
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Bayesian parameter estimationBayesian parameter estimation
Bayes’ Theorem
prior
posterior
likelihood
θPr
obab
ility
den
sity
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Bayes + Monte Carlo Markov ChainBayes + Monte Carlo Markov Chain
MCMC: a procedure to draw samples from the posterior pdf
MCMC Bayesian Frequentist
Efficiency ∝ N ∝ kN
Nuisance params YES undefined
Marginalization trivial close to impossible
Derived params YES need estimator
Prior information YES undefined
Model comparison YES significance tests only
Theoretical uncert’ies YES only simplistic
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A full 8D Bayesian analysisA full 8D Bayesian analysis
CMSSM parameters
Nuisance (SM) parameters
Collider observablesSUSY mass limits (LEPII), Higgs limits, BR’s, g-2, EW observables
Cosmological CDM abundance(WMAP1 + others)
Roberto Ruiz de Austri (Madrid), RTLeszek Roszkowski (Sheffield) JHEP 05 (2006) 002, hep-ph/0602028
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Direct DM detection in the CMSSMDirect DM detection in the CMSSM
1 event/kg/yre.g. EDELWEISS IICRESST II
1 event/ton/yrEURECA
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DD
Complementarity with LHCComplementarity with LHC
Ruiz, Trotta, Roszkowski (2006)
LHC
LHC
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SUSY @ LHC?SUSY @ LHC?Pr
obab
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den
sity
4 TeV prior2 TeV prior 4 TeV prior, no g-2
Inte
gra
ted p
robab
ility Eg,
gluino mass< 2.7 TeVwith78% prob.
ROBUST
Sleptons, squarks: prior and g-2 dependent
Probab
ility
den
sity
Inte
gra
ted p
robab
ility
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Final remarksFinal remarksBAYESIAN FRAMEWORK + MCMC
Powerful, flexible tool for statistical inferenceHandles effortlessly marginalization, nuisance & derived params, theoretical errors,...
CONSTRAINED MSSM LSP well motivated DM candidateHighly predictive frameworkCareful treatment of uncertainties necessary
OBSERVATIONAL PROSPECTS CMSSM neutralino dark matter: direct detection possible by the end of the decadeDM search complementary to collider SUSY searches Null result: easy to accomodate in the general MSSM, but...