SFitter

1. SFitter Adrien Renaud on behalf of the SFitter team : R. Lafaye, M. Rauch, T. Plehn, D. Zerwas, with M. Dührssen, C. Adam-Bourdarios and J.L. Kneur. Introduction Supersymmetry Higgs sector Conclusion SFitter papers : “ Measuring supersymmetry ” Eur. Phys. J. C 54, 617–644 (2008) “ Measuring the Higgs Sector “ arXiv:0904.3866v2 (2009)

2. From collider data to model parameters • If new physics is found at Collider, and that we have a model for it, we will need • to extract the model parameters from data. •  crucial but difficult… • … because : • High dimensional parameter space (with unconstrained parameters) • on both theory and experimental side, errors are correlated. • Sfitter task is to map a set of measurement into a high-dimensional parameter • space with correct treatment of errors. • Using SFitter for most common EWSB and new Physics : • Higgs : reconstruct Yukawa couplings from LHC data. • Supersymmetry : reconstruct MSSM parameters from LHC (ILC) data.

3. SFitter framework Error treatment : Statistical Gaussian or Poisson, uncorrelated. Experimental systematics (luminosity, efficency)  Gaussian, correlated. Theoritical  CKMfitter prescription No information within theory errors : flat chi2 Likelihood map and analysis : using MCMC to identify primary and secondary minima and refine identified minima with Minuit. Produce lower dimensional plots with both frequentist AND bayesian approaches. Error estimate : Sets of smeared (according to error and correlation) toys-measurements.

4. Supersymmetry mSUGRA : Reconstruction of SPS1a with LHC data Is it possible to identify the correct parameters from a set of observables and their errors ? • Need detailed experimental simulations of measurements and errors

5. Supersymmetry mSUGRA : Reconstruction of SPS1a with LHC data derived from « G. Weiglein et al. [LHC/LC Study Group] arXiv:hep-ph/0410364 »

6. Supersymmetry mSUGRA : Reconstruction of SPS1a with LHC data ATLAS-CSC 2008 Pythia6 + ATLAS full simulation + flavor substraction  SU3 (bulk region)

7. Input data file lha: Mh = /BLOCK MASS/25 lha: ~e_L = /BLOCK MASS/1000011 … lha: ~b_1 = /BLOCK MASS/1000005 lha: ~b_2 = /BLOCK MASS/2000005 // Function definition: // - up to 4 arguments named x, y, z and t // - any parameter (number or lha: line defined above) func: sqx = x*x func: edge3 = sqrt((sqx-sqy)*(sqy-sqz)/sqy) // Data input definition (may be any lha: or func: with arguments) // Uncertainty on the top mass is LHC expectation; today it is 2.1 GeV data: Mt = 171.4 +/- 0.01 stat 0.0 syst 1.0 syst 0.0 hat [GMW] data: Mh = 109.0 +/- 0.01 stat 0.25 syst 0.0 syst 0.0 hat [GMW] data: edge3(~chi_20,~e_R,~chi_10) = 80.9441 +/- 0.042 stat 0.08 syst 0 syst 3.54 hat [GMW] data: edge3(~chi_20,~mu_R,~chi_10) = 80.9441 +/- 0.042 stat 0.08 syst 0 syst 3.54 hat [GMW] … data: thres(~b_1,~chi_20,~e_R,~chi_10) = 198.606 +/- 5.1 stat 0 syst 1.8 syst 11.2 hat [GMW] data: thres(~b_1,~chi_20,~mu_R,~chi_10) = 198.606 +/- 5.1 stat 0 syst 1.8 syst 11.2 hat [GMW] // Correlation example corr: edge2(~g,~b_1,1):edge2(~g,~b_2,1) = 0.8 corr: Mh:Mt = 0.2 // TLatex root alias alias: edge3(~chi_20,~e_R,~chi_10) = edge(#tilde{#chi}_2^0,#tilde{#e}_R,#tilde{#chi}_1^0)

8. Supersymmetry mSUGRA : Reconstruction of SPS1a with LHC data. MCMC + MINUIT :

9. Supersymmetry mSUGRA : Reconstruction of SPS1a with LHC data. MCMC + MINUIT : Profile Likelihood Bayesian pdf

10. Supersymmetry mSUGRA : Reconstruction of SPS1a with LHC data. mu<0 Profile Likelihood Bayesian pdf

11. + Claire Adam, Jean-Loic Kneur MSSM : probing unification at GUT scale  at the LHC the MSSM determination leads to an at least 8 fold degeneracy  M1 < M2 < |mu|, M2<M1 < |mu|,... (plus sign of mu inversion)  some info from the relic density (ok for DS1,DS3,DS7,DS9, not ok for the others) DS2 DS3 DS10

12. + Claire Adam, Jean-Loic Kneur MSSM : probing unification at GUT scale DS7 DS1  can categorize the degeneracies via gauginos: 6 clearly not compatible with unification  1 difficult to exclude unification (parameters identical to true solution with the exception of the sign of mu)  true solution unifies  scalars precision not good enough for additional information (coupled RGEs lead to an increase of the RMS as function of the scale)

13. For that SFitter needs tools : • Spectrum generators : SoftSUSY, SuSPECT or ISASUSY • NLO cross sections for LHC : Prospino2 • Branching Ratio : SUSY-HIT • Dark Matter : micrOMEGAs (yesterday talk by G. Belanger) • Flavor Physics : SuperIso (yesterday talk by N. Mahmoudi) • The communication of parameters and results between the different programs is performed by the SUSY-Les-Houches-Accord data format using the implementation of SLHAio (Sven Kreiss). • In the two following slides I show, as an example, the implementation of SuperIso in SFitter (and the result of the fit). • SuperIso : N. Mahmoudi publicly available • flavor physics in SM, MSSM, 2HDM, NMSSM. • susy contribution to isospin asymmetry at NLO .

14. Add in the input File for Sfitter : lha: delta0m = /BLOCK INDIRECT CONSTRAINTS/6 data: delta0m = 0.0375 +/- 0.0289 stat 0 syst 0 syst 0 hat [ICRM] Create a ToolSuperIso class : extern "C" float delta0_calculator(char name[]); ToolSuperiso::ToolSuperiso() { name = "SUPERISO"; title = "Superiso 2.4"; authors = “N.Mahmoudi"; SLHAio::Path slhaio_path_io; slhaio_path_io.set("/SLHA/BLOCK INDIRECT CONSTRAINTS/6",-999.,"Isospin Asymmetry"); delta0m = &(slhaio_path_io.getDouble("/SLHA/BLOCK INDIRECT CONSTRAINTS/6")); } int ToolSuperiso::Compute() { slhaio_writefile("/SLHA/",“slha_file_for_SuperIso.out"); *delta0m = double(delta0_calculator(" slha_file_for_SuperIso.out ")); return 0; } And SFitter do the rest in a WorkFlow fashion.

15. B Physics : • BaBar Bell 2009 • Tool : SuperIso • Heavy Flavor Averaging Group 2006 • Tool : Suspect • PDG 2008 • Tool : SuperIso • W boson mass : • Tevatron Electroweak WG 2008 • Tool : Suspect • Muon Magnetic Moment : • Tevatron Electroweak WG 2008 • Tool : Suspect • DM Relic density • WMAP • Tool : Micromegas mSUGRA MINUIT fit

16. The Higgs sector +Michael Duehrssen JHEP 0908:009,2009 A difficult scenario: only the lightest Higgs boson (120GeV) seen: several measurements possible LHC: Gluon fusion and VBF in well defined final states (many authors and papers) Duehrssen et al.: Phys.Rev.D70:113009,2004. hep-ph/0406323 ttHbb: 50% signal reduction Hbb: J. M. Butterworth, A. R. Davison , M. Rubin, G. P. Salam Phys.Rev.Lett.100:242001,2008. Theory Errors Experimental Errors Correlated measurements and parameters: apply SUSY search techniques for parameter extraction Difficulty to be mastered: convolution of Gaussian+Poisson+Flat errors

17. The Higgs sector: likelihood maps Using Hdecay anf HIGLU. No new particles in the loops : frequentist bayesian Definition: ΔHjj deviation of Hjj coupling from SM value : Loop induced coupling : • frequentist approach better adapted (no real secondary minima) • general positive correlation among non-Hbb couplings due to total width ≈ Hbb Add ΔHgg and ΔHγγ:sign preference power of Hγγdisappears : Measurements at LHC: σ · BR·L· ~ g2·g2/Γ blind to simultaneous coupling/√width changes:

18. The Higgs sector: precision Coupling ratios Hbb: J. M. Butterworth, A. R. Davison , M. Rubin, G. P. Salam Phys.Rev.Lett.100:242001,2008. 30fb-1 theory errors (10000 toy MC) • subjet analysis essential for Hbb! • 30fb-1 precision 30% to 50% (absolute) • slightly higher precision for ratios (cancellation of errors, but dominated by stat errors)

19. Conclusions • SFitter is a tool to extract the fundamental parameters from experimental measurements • particularly powerful for cases where the parameters and observables depend on each other in a non-trivial way • full propagation of errors • uses SLHA standard • extendable to new tools • has been applied to: • extract parameters of mSUGRA and the MSSM • extrapolate the MSSM parameters to the high scale (pub foreseen this summer) • extract the Higgs coupling parameters • futur work: interface to NMSSM ( Cyril/Ulrich)

20. BACKUP DS7