Bayesian method of SUSY parameter reconstruction - a case study Leszek Roszkowski U. of Sheffield, England and SINS, Warsaw, Poland with Roberto Ruiz de Austri and Roberto Trotta, arXiv:0907.0594 public tool: SuperBayes package, available from www.superbayes.org GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.1
Outline GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.2
Outline SUSY, Constrained MSSM (CMSSM) case study: ATLAS SU3 benchmark point GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.2
Outline SUSY, Constrained MSSM (CMSSM) case study: ATLAS SU3 benchmark point Bayesian parameter reconstruction for SU3 GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.2
Outline SUSY, Constrained MSSM (CMSSM) case study: ATLAS SU3 benchmark point Bayesian parameter reconstruction for SU3 impact of additional info on Ω χ h 2 prior dependence, profile likelihood summary GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.2
A conjecture GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.3
A conjecture SUSY cannot be experimentally ruled out GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.3
A conjecture SUSY cannot be experimentally ruled out it can only be discovered... GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.3
A conjecture SUSY cannot be experimentally ruled out it can only be discovered... ...or abandoned GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.3
Parameter reconstruction GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.4
Parameter reconstruction ...once positive measurements are made... GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.4
Parameter reconstruction ...once positive measurements are made... task: reconstruct underlying SUSY parameters model dependent program GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.4
Constrained MSSM (CMSSM) Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.5
Constrained MSSM (CMSSM) Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At M GUT ≃ 2 × 10 16 GeV : M 1 = M 2 = m e g = m 1 / 2 gauginos scalars m 2 q i = m 2 l i = m 2 H b = m 2 H t = m 2 0 e e 3–linear soft terms A b = A t = A 0 GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.5
Constrained MSSM (CMSSM) Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At M GUT ≃ 2 × 10 16 GeV : M 1 = M 2 = m e g = m 1 / 2 gauginos scalars m 2 q i = m 2 l i = m 2 H b = m 2 H t = m 2 0 e e 3–linear soft terms A b = A t = A 0 radiative EWSB Ht tan 2 β m 2 Hb − m 2 − m 2 µ 2 = Z tan 2 β − 1 2 GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.5
Constrained MSSM (CMSSM) Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At M GUT ≃ 2 × 10 16 GeV : M 1 = M 2 = m e g = m 1 / 2 gauginos scalars m 2 q i = m 2 l i = m 2 H b = m 2 H t = m 2 0 e e 3–linear soft terms A b = A t = A 0 radiative EWSB Ht tan 2 β m 2 Hb − m 2 − m 2 µ 2 = Z tan 2 β − 1 2 five independent parameters: m 1 / 2 , m 0 , A 0 , tan β, sgn( µ ) GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.5
Constrained MSSM (CMSSM) Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At M GUT ≃ 2 × 10 16 GeV : M 1 = M 2 = m e g = m 1 / 2 gauginos scalars m 2 q i = m 2 l i = m 2 H b = m 2 H t = m 2 0 e e 3–linear soft terms A b = A t = A 0 radiative EWSB Ht tan 2 β m 2 Hb − m 2 − m 2 µ 2 = Z tan 2 β − 1 2 five independent parameters: m 1 / 2 , m 0 , A 0 , tan β, sgn( µ ) well developed machinery to compute masses and couplings GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.5
Constrained MSSM (CMSSM) Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At M GUT ≃ 2 × 10 16 GeV : M 1 = M 2 = m e g = m 1 / 2 gauginos scalars m 2 q i = m 2 l i = m 2 H b = m 2 H t = m 2 0 e e 3–linear soft terms A b = A t = A 0 radiative EWSB Ht tan 2 β m 2 Hb − m 2 − m 2 µ 2 = Z tan 2 β − 1 2 five independent parameters: m 1 / 2 , m 0 , A 0 , tan β, sgn( µ ) well developed machinery to compute masses and couplings neutralino χ mostly bino GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.5
Constrained MSSM (CMSSM) Kane, Kolda, LR, Wells (1993) ...“benchmark framework” for the LHC (...e.g., mSUGRA) At M GUT ≃ 2 × 10 16 GeV : M 1 = M 2 = m e g = m 1 / 2 gauginos scalars m 2 q i = m 2 l i = m 2 H b = m 2 H t = m 2 0 e e 3–linear soft terms A b = A t = A 0 radiative EWSB Ht tan 2 β m 2 Hb − m 2 − m 2 µ 2 = Z tan 2 β − 1 2 five independent parameters: m 1 / 2 , m 0 , A 0 , tan β, sgn( µ ) well developed machinery to compute some useful mass relations: masses and couplings bino: m χ ≃ 0 . 4 m 1 / 2 neutralino χ mostly bino gluino e g : m e g ≃ 2 . 7 m 1 / 2 q 0 . 15 m 2 1 / 2 + m 2 τ 1 ≃ supersymmetric tau (stau) e τ 1 : m e 0 GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.5
Case study: ATLAS SU3 Point ATLAS SU3 benchmark point, arXiv:0901.0512 GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.6
Case study: ATLAS SU3 Point ATLAS SU3 benchmark point, arXiv:0901.0512 Parameter SU3 benchmark value m 0 100 GeV m 1 / 2 300 GeV tan β 6.0 A 0 − 300 GeV Ω χ h 2 0 . 23319 ⇐ SUSY mass spectrum χ = χ 0 117.9 GeV 1 χ 0 223.4 GeV 2 f m e 152.2 GeV l m e 652.4 GeV q f m e l - lightest slepton mass m e - average light squark q mass GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.6
Case study: ATLAS SU3 Point ATLAS SU3 benchmark point, arXiv:0901.0512 Parameter SU3 benchmark value m 0 100 GeV m 1 / 2 300 GeV study endpoint measurements tan β 6.0 dileptons + lepton+jets analysis of A 0 − 300 GeV the decay chain Ω χ h 2 2 ( → e 0 . 23319 ⇐ l ± l ∓ ) q → χ 0 1 l + l − q q L → χ 0 e and SUSY mass spectrum the high- p T and large missing χ = χ 0 117.9 GeV 1 energy analysis of the decay chain χ 0 223.4 GeV 2 q R → χ 0 e 1 q f m e 152.2 GeV l χ 2 minimization m e 652.4 GeV q int. lum. 1 fb − 1 f m e l - lightest slepton mass m e - average light squark q mass GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.6
ATLAS SU3 measurements Aad, et al. , arXiv:0901.0512 1st errors: parabolic 2nd errors: jet energy scale The covariance matrix (ATLAS): 2 − m χ 0 l − m χ 0 q − m χ 0 m χ 0 m χ 0 m e f m e 1 1 1 1 3 . 72 × 10 3 1 . 92 × 10 3 10 . 75 × 10 2 m χ 0 53 . 40 1 m χ 0 2 − m χ 0 3 . 6 29 . 0 − 1 . 3 1 1 . 12 × 10 3 l − m χ 0 m e f 4 . 65 1 m e q − m χ 0 14 . 1 1 GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.7
SU3 parameter reconstruction by ATLAS Aad, et al. , arXiv:0901.0512 2D likelihood maps (int. lum. 1 fb − 1 ) theory errors neglected neglect effect of SM parameters ranges around the true value found GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.8
Bayesian Analysis of the CMSSM Apply to the CMSSM: recent development, led by 2 groups GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.9
Bayesian Analysis of the CMSSM Apply to the CMSSM: recent development, led by 2 groups m = ( θ, ψ ) – model’s all relevant parameters GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.9
Bayesian Analysis of the CMSSM Apply to the CMSSM: recent development, led by 2 groups m = ( θ, ψ ) – model’s all relevant parameters CMSSM parameters θ = m 1 / 2 , m 0 , A 0 , tan β relevant SM param’s ψ = M t , m b ( m b ) MS , α MS , α em ( M Z ) MS s GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.9
Bayesian Analysis of the CMSSM Apply to the CMSSM: recent development, led by 2 groups m = ( θ, ψ ) – model’s all relevant parameters CMSSM parameters θ = m 1 / 2 , m 0 , A 0 , tan β relevant SM param’s ψ = M t , m b ( m b ) MS , α MS , α em ( M Z ) MS s ξ = ( ξ 1 , ξ 2 , . . . , ξ m ) : set of derived variables (observables): ξ ( m ) GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.9
Bayesian Analysis of the CMSSM Apply to the CMSSM: recent development, led by 2 groups m = ( θ, ψ ) – model’s all relevant parameters CMSSM parameters θ = m 1 / 2 , m 0 , A 0 , tan β relevant SM param’s ψ = M t , m b ( m b ) MS , α MS , α em ( M Z ) MS s ξ = ( ξ 1 , ξ 2 , . . . , ξ m ) : set of derived variables (observables): ξ ( m ) d : data ( Ω CDM h 2 , b → sγ , m h , etc) GGI mini-workshop on LHC and dark matter, 10 June 2010 – p.9
Recommend
More recommend
