SFitterAdrien 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.

1. Introduction2. Supersymmetry 3. Higgs sector4. Conclusion

SFitter papers :“ Measuring supersymmetry ” Eur. Phys. J. C 54, 617–644 (2008)“ Measuring the Higgs Sector “ arXiv:0904.3866v2 (2009)

From collider data to model parameters

If new physics is found at Collider, and that we have a model for it, we will needto 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 parameterspace 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.

SFitter frameworkError 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.

SupersymmetrymSUGRA : 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

SupersymmetrymSUGRA : Reconstruction of SPS1a with LHC data

derived from « G. Weiglein et al. [LHC/LC Study Group] arXiv:hep-ph/0410364 »

SupersymmetrymSUGRA : Reconstruction of SPS1a with LHC data

Pythia6 + ATLAS full simulation

+ flavor substraction

ATLAS-CSC 2008

SU3 (bulk region)

Input data filelha: Mh = /BLOCK MASS/25lha: ~e_L = /BLOCK MASS/1000011

…lha: ~b_1 = /BLOCK MASS/1000005lha: ~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*xfunc: 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 GeVdata: 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 examplecorr: edge2(~g,~b_1,1):edge2(~g,~b_2,1) = 0.8corr: Mh:Mt = 0.2

// TLatex root aliasalias: edge3(~chi_20,~e_R,~chi_10) = edge(#tilde{#chi}_2^0,#tilde{#e}_R,#tilde{#chi}_1^0)

SupersymmetrymSUGRA : Reconstruction of SPS1a with LHC data.

MCMC + MINUIT :

SupersymmetrymSUGRA : Reconstruction of SPS1a with LHC data.

MCMC + MINUIT :

Profile Likelihood Bayesian pdf

SupersymmetrymSUGRA : Reconstruction of SPS1a with LHC data.

Profile Likelihood Bayesian pdf

mu<0

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

+ Claire Adam, Jean-Loic Kneur

MSSM : probing unification at GUT scale

DS1

DS7

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)

+ Claire Adam, Jean-Loic Kneur

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 availableflavor physics in SM, MSSM, 2HDM, NMSSM.susy contribution to isospin asymmetry at NLO .

Add in the input File for Sfitter :

lha: delta0m = /BLOCK INDIRECT CONSTRAINTS/6data: 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.

mSUGRA MINUIT fit Muon Magnetic Moment :• Tevatron Electroweak WG 2008 Tool : Suspect

W boson mass :• Tevatron Electroweak WG 2008 Tool : Suspect

DM Relic density• WMAP Tool : Micromegas

B Physics :

• BaBar Bell 2009 Tool : SuperIso

• Heavy Flavor Averaging Group 2006 Tool : Suspect

• PDG 2008 Tool : SuperIso

Value Error

M0 110 35

M1/2 341.5 0.9

TANB 15.4 0.6

A0 760 130

The Higgs sector

Theory Errors

Experimental Errors

+Michael DuehrssenJHEP 0908:009,2009

Hbb: J. M. Butterworth, A. R. Davison , M. Rubin, G. P. Salam Phys.Rev.Lett.100:242001,2008.

ttHbb: 50% signal reduction

Duehrssen et al.: Phys.Rev.D70:113009,2004. hep-ph/0406323

Correlated measurements and parameters: applySUSY search techniques for parameter extraction

Difficulty to be mastered: convolution of Gaussian+Poisson+Flat errors

A difficult scenario: only the lightest Higgs boson (120GeV) seen: several measurements possibleLHC: Gluon fusion and VBF in well defined final states (many authors and papers)

The Higgs sector: likelihood maps

• frequentist approach better adapted (no real secondary minima) • general positive correlation among non-Hbb couplings due to total width ≈ Hbb

frequentist bayesianDefinition: ΔHjj deviation of Hjj coupling from SM value :

Add ΔHgg and ΔHγγ: sign preference power of Hγγ disappears :

Loop induced coupling :

Measurements at LHC:σ · BR · L · ~ g2 · g2/Γ blind to simultaneous coupling/√width changes:

Using Hdecay anf HIGLU. No new particles in the loops :

The Higgs sector: precision

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)

Coupling ratios

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)

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