Indirect constraints on the (C)MSSM parameter space

Transcription

1 Indirect constraints on the (C)MSSM parameter space Frédéric Ronga ETH Zurich Switzerland CKM Workshop, Rome September 11, 2008 Contents 1 Introduction 2 Combining today s constraints 3 Prospects for LHC discoveries 4 Sensitivity to individual observables 5 Conclusion

2 Introduction The LHC has turned on! Busy beam event lighting up the CMS detector, Sep. 10, 2008 last moment to circumscribe the SUSY playground for LHC... global fit to today s experimental data F.J. Ronga (ETHZ) CMSSM CKM / 14

3 Introduction Using external constraints: the CMSSM case Today s external constraints Low Energy (precision) data: Flavour Physics (in particular B Physics) Other low-energy observables (e.g., g 2) High energy (precision) data: Precision electroweak observables (e.g., m top, m W ) Cosmology/Astroparticle data: e.g., relic density How to exploit this information? state-of-the-art theoretical predictions ( tools ) a framework to consistently combine the tools Collaboration between experiment and theory Buchmüller, Oliver (CERN) Exp. De Roeck, Albert (CERN & Uni. Antwerpen) Exp. Flächer, Henning (CERN) Exp. Isidori, Gino (INFN Frascati) Theo. Paradisi, Paride (Tech. Uni. München) Theo. Weiglein, Georg (Durham) Theo. Cavanaugh, Richard (Uni. of Florida) Exp. Ellis, John (CERN) Theo. Heinemeyer, Sven (Santander) Theo. Olive, Keith (Uni. of Minnesota) Theo. Ronga, Frédéric (CERN) Exp. F.J. Ronga (ETHZ) CMSSM CKM / 14

4 Combining today s constraints

5 Combining today s constraints Common framework for indirect constraints Steering Code Input parameters e.g. M 0, m 1/2, a0, tan(ß), sign(µ) Spectrum calculators SoftSusy Higgs sector FeynHiggs SLHA Predictors SuSpect Cosmology MicrOMEGAs DarkSUSY Consistency Relies on the SUSY Les Houches Accord (SLHA) Modularity Compare calculations Add/remove predictions State-of-the art calculations Direct use of code from experts Flavour Physics Isidori et al. MicrOMEGAS EWK Physics SUSYPope FeynHiggs Predictions Legend Data Components Modules F.J. Ronga (ETHZ) CMSSM CKM / 14

6 Combining today s constraints Use-case: fit today s data (χ 2 minimisation) Steering Code Input parameters e.g. M 0, m 1/2, a0, tan(ß), sign(µ) Spectrum calculators SoftSusy Higgs sector FeynHiggs SLHA Predictors SuSpect Cosmology MicrOMEGAs DarkSUSY Constrain SUSY parameter space Even more interesting when combined with discoveries!... Various modes: Overall best minimum (Minuit) χ 2 scan Markov chain Monte Carlo Flavour Physics Isidori et al. MicrOMEGAS EWK Physics SUSYPope FeynHiggs χ 2 Predictions References Legend Data Components Modules F.J. Ronga (ETHZ) CMSSM CKM / 14

7 Combining today s constraints χ 2 fit of the CMSSM parameters Multi-parameter χ 2 fit: χ 2 = N i (C i P i ) 2 M σ(c i ) 2 + σ(p i ) 2 + j (f obs SM j f fit SM j ) 2 σ(f SMj ) 2 C i : experimental constraint P i : predicted value for a given CMSSM parameter set fitting for all CMSSM parameters: m 0 common scalar mass (at GUT scale) m 1/2 common gaugino mass (at GUT scale) a 0 tri-linear mass parameter (at GUT scale) tan β ratio of Higgs vacuum expectation values sign(µ) sign of Higgs mixing parameter (fixed) including relevant SM uncertainties (m top, m Z, α (5) had ) Details in O. Buchmüller et al., PLB 657/1-3 pp F.J. Ronga (ETHZ) CMSSM CKM / 14

8 Combining today s constraints List of available predictions [relevant today already] Low energy observables R(b sγ) Isidori & Paradisi micromegas R(B τν) Isidori & Paradisi BR(K τν) Isidori & Paradisi R(B X s ll) Isidori & Paradisi R(K πν ν) Isidori & Paradisi BR(B s ll) Isidori & Paradisi micromegas BR(B d ll) Isidori & Paradisi R( m s ) Isidori & Paradisi R( m s )/R( m d ) Isidori & Paradisi R( m K ) Isidori & Paradisi R( 0 (K γ)) SuperIso (g 2) FeynHiggs Higgs sector observables FeynHiggs m light h Cosmology observables Ωh 2 micromegas DarkSUSY DarkSUSY σ SI p Electroweak observables α (5) had (m2 Z ) SUSY-Pope m Z SUSY-Pope σhad 0 SUSY-Pope R l SUSY-Pope A fb (l) SUSY-Pope A l (P τ ) SUSY-Pope R b SUSY-Pope R c SUSY-Pope A fb (b) SUSY-Pope A fb (c) SUSY-Pope A b SUSY-Pope A c SUSY-Pope A l (SLD) SUSY-Pope sin 2 θw(q l fb ) SUSY-Pope m W SUSY-Pope SUSY-Pope m t not used in this study F.J. Ronga (ETHZ) CMSSM CKM / 14

9 Combining today s constraints What s new? Extensive sampling of the CMSSM parameter space: 25 million Markov chain Monte Carlo points all constraints included (in particular from flavour physics) overall best fit point determined using Minuit All constraints updated to most recent values W and top masses (latest Tevatron results) B physics (B τν, b sγ) g 2 Prospects for LHC discoveries Influence of various constraints Re-weighting of χ 2 on 25 million points removal/inclusion of constraints, scaling of constraints error Details in: O. Buchmüller et al., arxiv: F.J. Ronga (ETHZ) CMSSM CKM / 14

10 Prospects for LHC discoveries

11 Prospects for LHC discoveries Sparticle searches M 1/2 [GeV] τ LSP 1 5σ discovery reach 1/fb tanβ = 10, A 0 = 0, µ> 0 jets + MET (CMS) lepton + 4 jets (ATLAS) lepton + 4 jets (ATLAS) 600 SS 2µ (CMS) 500 Higgs (2/fb ) (CMS) 400 full CMSSM 300 parameter space 68% C.L % C.L. 100 NO EWSB M 0 [GeV] F.J. Ronga (ETHZ) CMSSM CKM / 14

12 Prospects for LHC discoveries Sparticle searches M 1/2 [GeV] "# LSP 1 5σ discovery reach jets + MET (CMS) tan! = 10, A 0 = 0, µ > 0 14 TeV TeV TeV If CMSSM is realised in nature, a signal will be seen fairly early! full CMSSM parameter space 68% C.L. 95% C.L. Otherwise, exclusion will be possible... NO EWSB M 0 [GeV] Including direct searches at LEP and Tevatron (dashed areas). F.J. Ronga (ETHZ) CMSSM CKM / 14

13 Prospects for LHC discoveries Prediction for B s µµ Best fit point: BR(B s µµ) = "!!. / 0120 %4 "&' &' 4 3 -, Preliminary! + * ) ( & ' %&' ' &' (' )' *' +',' -'!"#$!! F.J. Ronga (ETHZ) CMSSM CKM / 14

14 Prospects for LHC discoveries Prediction for B s µµ Best fit point: BR(B s µµ) = / "!! &' 4 3 -, + * ) ( %4 "&' Preliminary! If CMSSM (and minimal flavour violation) is realised in nature this will not be a free lunch... & ' %&' ' &' (' )' *' +',' -'!"#$!! LHCb reach, from P. Koppenburg s talk on Tuesday F.J. Ronga (ETHZ) CMSSM CKM / 14

15 / Prospects for LHC discoveries Prediction for B s µµ Best fit point: BR(B s µµ) = "!! &' 4 3 -, + * ) ( %4 "&' Preliminary! If CMSSM (and minimal flavour violation) is realised in nature this will not be a free lunch... & ' %&' ' &' (' )' *' +',' -'!"#$!! LHCb reach, from P. Koppenburg s talk on Tuesday But: still an order of magnitude to go. Plenty of room for NP discovery! F.J. Ronga (ETHZ) CMSSM CKM / 14

16 Sensitivity to individual observables

17 Sensitivity to individual observables How big is the influence of cosmological data? Compare 95% CL with/without WMAP constraint M 1/2 [GeV] with WMAP without WMAP [GeV] M with WMAP without WMAP M 0 [GeV] tanβ Enforces correlation between m 0 and tan β (coannihilation strips ) Moderate influence F.J. Ronga (ETHZ) CMSSM CKM / 14

18 Sensitivity to individual observables How big is the influence of b sγ? Compare 95% CL in various error scaling scenarios m 1/2 [GeV] m0 [GeV] error 0.9 error 1.0 error 1.1 error 1.2 error 1.3 error error 0.9 error 1.0 error 1.1 error 1.2 error 1.3 error m 0 [GeV] Reducing the error has a big effect on tan β Very sensitive observable tan β F.J. Ronga (ETHZ) CMSSM CKM / 14

19 Sensitivity to individual observables Quantifying the sensitivity Relative Change in Area [%] Percentage change in contour content as a function of relative uncertainty (g 2) b sγ 2 Ωh B τν m W (m 0, m 1/2 ) plane Importance of g 2, b sγ B τν fairly sensitive Ωh 2 not so sensitive in these projections Relative Change in Uncertainty F.J. Ronga (ETHZ) CMSSM CKM / 14

20 Conclusion Summary New global fits to the CMSSM CPU (and disk) intensive 25 million MCMCs latest experimental and theoretical input Prospects for the CMSSM at LHC the end of a long story? Sensitivity to individual observables (g 2) µ and BR(b sγ) are the winners BR(B u τν τ ) also makes a difference moderate influence of Ωh 2 Now we ll be busy understanding new data (back to reality... ) F.J. Ronga (ETHZ) CMSSM CKM / 14

21 Conclusion Summary New global fits to the CMSSM CPU (and disk) intensive 25 million MCMCs latest experimental and theoretical input Prospects for the CMSSM at LHC the end of a long story? Sensitivity to individual observables (g 2) µ and BR(b sγ) are the winners BR(B u τν τ ) also makes a difference moderate influence of Ωh 2 Now we ll be busy understanding new data (back to reality... ) F.J. Ronga (ETHZ) CMSSM CKM / 14

22 Conclusion Summary New global fits to the CMSSM CPU (and disk) intensive 25 million MCMCs latest experimental and theoretical input Prospects for the CMSSM at LHC the end of a long story? Sensitivity to individual observables (g 2) µ and BR(b sγ) are the winners BR(B u τν τ ) also makes a difference moderate influence of Ωh 2 Now we ll be busy understanding new data (back to reality... ) F.J. Ronga (ETHZ) CMSSM CKM / 14

23 Conclusion Summary New global fits to the CMSSM CPU (and disk) intensive 25 million MCMCs latest experimental and theoretical input Prospects for the CMSSM at LHC the end of a long story? Sensitivity to individual observables (g 2) µ and BR(b sγ) are the winners BR(B u τν τ ) also makes a difference moderate influence of Ωh 2 Now we ll be busy understanding new data (back to reality... ) F.J. Ronga (ETHZ) CMSSM CKM / 14

24 Backup slides

25 Backup Experimental constraints Observable Constraint Add. Th. Unc. m W [GeV] ± aµ exp aµ SM (30.2 ± 8.8) m h [GeV] > (see text) 3.0 BR exp b sγ /BRSM b sγ ± exp ± th(sm) m t [GeV] ± 1.2 Ω CDM h ± BR(B s µ + µ ) < BR exp B τν /BRSM B τν 1.15 ± 0.40 [exp+th] BR(B d µ + µ ) < BR exp B X s ll /BRSM B X s ll 0.99 ± 0.32 BR exp K µν /BRSM K µν ± [exp+th] BR exp K πν ν /BRSM M exp B s hline ( Mexp Bs ( M exp B d K πν ν < 4.5 / MB SM s 1.11 ± 0.01 exp ± 0.32 th(sm) / M SM ) Bs / M SM ɛ exp K / ɛsm B d ) 1.09 ± 0.01 exp ± 0.16 th(sm) K 0.92 ± 0.14 [exp+th] F.J. Ronga (ETHZ) CMSSM CKM / 14

26 Backup CMSSM and SM EWK fits [previous study] CMSSM Variable Measurement Fit #" ) ± (5) (m had Z mz [GeV] ± $ [GeV] ± Z 0! [nb] ± had Rl ± ,l A ± fb Al (P ) % ± Rb ± Rc ± ,b A ± fb 0,c A ± fb Ab 0.923± A ± c Al (SLD) ± sin & lept eff (Q ) fb ± m [GeV] W ± m [GeV] t ± R(b(s' ) 1.13 ± meas fit meas O -O /! Bs(µµ [ 10 ] < N/A (upper limit) -9 # a µ [ 10 ] 2.95 ± ) h 0.113± O. Buchmüller et al., PLB 657/1-3 pp χ 2 /ndof = 17.0/13 (20% prob.) SM Variable Measurement Fit #" ) ± (5) (m had Z mz [GeV] ± $ [GeV] ± Z 0! [nb] ± had Rl ± ,l A ± fb Al (P ) % ± Rb ± Rc ± ,b A ± fb 0,c A ± fb Ab 0.923± A ± c Al (SLD) ± sin & lept eff (Q ) fb ± m [GeV] W ± m [GeV] t ± $ [GeV] W ± meas fit meas O -O /! arxiv:hep-ex/ χ 2 /ndof = 18.2/13 (15% prob.) F.J. Ronga (ETHZ) CMSSM CKM / 14