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Search for FCNC Decays B s(d) → μ + μ -

Search for FCNC Decays B s(d) → μ + μ -. Matthew Herndon, University of Wisconsin Madison University of Illinois HETEP Seminar, March 2010. Why Beyond Standard Model. Standard Model fails to answer many fundamental questions. Many of those questions come from Astrophysics and Cosmology .

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Search for FCNC Decays B s(d) → μ + μ -

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  1. Search for FCNC Decays Bs(d)→ μ+μ- Matthew Herndon, University of Wisconsin Madison University of Illinois HETEP Seminar, March 2010

  2. Why Beyond Standard Model Standard Model fails to answer many fundamental questions Many of those questions come from Astrophysics and Cosmology Colliders will allow us to establish the nature of this new physics in the laboratory and study it in detail • Standard Model predictions validated to high precision, however • Gravity not a part of the SM • What is the very high energy behaviour? • At the beginning of the universe? • Dark Matter? • Astronomical observations of indicate that there is more matter than we see • Where is the Antimatter? • Why is the observed universe mostly matter?

  3. Searches For New Physics Rare Decays present unique opportunity to find and study new physics • How do you search for new physics at a collider? • Direct searches for production of new particles • Particle-antipartical annihilation: top quark • Indirect searches for evidence of new particles • Within a complex process new particles can occur virtually • LHC is now the energy frontier • Tevatron is at an intensity frontier billions B and Charm events on tape • So much data that we can look for some very unusual processes • Where to look • Many weak processes involving B hadrons are very low probability • Look for contributions from other low probability processes – Non Standard Model

  4. Bs(d)→ μ+μ-Beyond the SM Same particles/vertices occur in both B decay diagrams and in dark matter scattering or annihilation diagrams • Bs(d)→μ+μ- • SM: • No tree level decay • GIM, CKM and helicity suppressed • BF(Bs→μ+μ-) = 3.8x10-9 • Look at processes that are suppressed in the SM • Excellent place to spot small contributions from non SM contributions • New Physics: • Loop: MSSM: mSugra, Higgs Doublet • Rate tan6β/(MA)4 • 3 orders of magnitude enhancement

  5. Tevatron and CDF EXCELLENT TRACKING TRIGGERED TO 1.5 GeV/c • Tevatron: 2TeV pp collider • CDF properties • Silicon Tracker • |η|<2, 90cm long, rL00 =1.3 - 1.6cm • Drift Chamber(COT) • 96 layers between 44 and 132cm • Muon coverage • |η|<1.5 • Triggered to |η|<1.0 • Outer chambers: high purity muons Results in this talk uses 3.7fb-1 Bs(d)→ μ+μ- benefits from more data and the excellent CDF detector

  6. Bs→ μμ: Experimental Challenge • Primary problem is large background at hadron colliders • Analysis selection must effectively reduce the large background around mBs = 5.37GeV/c2 to find a possible handful of events • Key elements of the analysis: Design an effective discriminant, determine the efficiency for signal and estimating the background level

  7. Data Sample Several Billion B and Charm Events on Tape 460M Events TRIGGERS ARE CRITICAL 55K Events • Di-muon CMU-CMU(X)trigger with 5.0 GeV scaler sum pT • CMU: pT(μ) > ~2.0 GeV, |η| < ~0.6, CMX: pT(μ) > ~2.2 GeV, 0.6<|η|<1.0 • pT cuts: restrict to a well understood trigger region • Apply basic quality cuts • Drift chamber tracks with hits in 3 silicon layers • Likelihood based muon Id and dE/dx to reject hadrons • Vertex quality • Loose preselection on analysis cuts • PT(μ+μ-) > 4.0 GeV/c, 3D Decay length significance> 2 • Loose isolation and pointing (defined later) • Sample still background dominated • Expect < 20Bs(d)→μ+μ-events: based on previous limits

  8. Bs(d)→ μ+μ-Method 3 X 108Bs events • Relative normalization search • Measure the rate of Bs(d)→ μ+μ- decay relative to B+J/K+, J/→μ+μ- • Apply same sample selection criteria • Systematic uncertainties will cancel out in the ratios of the normalization • Example: muon trigger eff same for J/ or Bss for a given pT

  9. Bs(d)→ μ+μ-Method • Estimate all basic selection acceptances and efficiencies. • Identify variables that discriminate signal and background • Validate modelling using B+ • Design multivariate discriminant, NN, for background rejection • Unbiased optimization based on Pythia signal MC and part of mass sidebands • Validate performance on B+ data • Estimate combinatoric background level from sidebands • Separately estimate B→hh • Validate background prediction method in control regions designed to be enhanced in expected backgrounds • Check low significance signal regions before highest significance region

  10. Signal vs. Background + L3D P() - L3D di-muon vertex primary vertex + L3D P() - L3D di-muon vertex 55K Events primary vertex Cut on mass, lifetime, pT , how well p points to the vertex and isolation • Need to discriminate signal from background • Reduce background by a factor of ~ 10000 • Signal characteristics • Final state fully reconstructed • Bs is long lived (cτ = 438 μm) • B fragmentation is hard: few additional tracks • Background contributions and characteristics • Sequential semi-leptonic decay: b → cμ-X → μ+μ-X • Double semileptonic decay: bb → μ+μ-X • Continuum μ+μ- • μ + fake, fake+fake • Partially reconstructed, lower pT, short lived, doesn’t point to the primary vertex, and has additional tracks -

  11. Discriminating Variables • 7 primary discriminating variables • Mass mmm2.5σwindow:σ = 24MeV/c2 • λ=cτ/cτBs, λ/λ, α : |φB – φvtx| in 3D • Isolation: pTB/( trk + pTB) • pTBs, pTmlow • Combine in NN Unbiased optimization based on simulated signal and data sidebands: 2fb-1 optimization Extensively tested for mass bias Set limits using 3NN bins and 5 mass bins

  12. Basic Validation Very stable performance with time Effective 2x upgrade • Validation vs. published dataset and B+→J/ψK+ MC • New data ~1.7fb-1 • Upgrade: new trigger acceptance muons cross dead region of tracker

  13. Detailed Validation • Validation vs. published dataset and B+→J/ψK+ MC • All preselection variables and discriminating variables • pT and iso not expected to agree. Reweighed to match B+ and Bs data

  14. NN Validation • Discriminating variable validation using: B+→J/ψK+ MC • pT and isolation reweighing applied • NN validation • Compare performance on B+→J/ψK+ data and MC • ~4% difference assigned as a systematic uncertainty • ~4% uncertainty from pT and iso reweighing • Can reliably estimate efficiency of NN

  15. Control Regions + - primary vertex Fake di-muon vertex • Use independent data samples to test background estimates • OS-: opposite sign muons, negative lifetime(signal sample is OS+) • SS+ and SS-: same sign muons, positive and negative lifetime. No trigger matching • ** OS-, SS: Opposite side B hadrons • FM: OS- and OS+: fake μ enhanced, one μ fails the muon Id cuts loose vertex cuts • ** FM: False muon backgrounds • Compare predicted vs. observed # of bg. events: For multiple NN cuts

  16. Control Regions • Comparison of control with signal region NN input distributions • Do not expect perfect agreement • Isolation different for events where muons originate from different b hadrons. • Test background prediction method by using sidebands to make predictions in extended signal region • Extended to maximize statistics • Extended signal region: 4σ(mμμ), 5.169 < mμμ < 5.469 GeV • Sideband region: 0.5 GeV on either side of the signal region

  17. Control Regions • Background predictions and observed background in control regions • Errors based on statistics of sideband region. • 24 Independent checks of the background estimation method

  18. Expected Sensitivity Have reached single event sensitivity to the SM • Efficiencies and acceptances • NN efficiencies. 0.8<NN<0.95, 12%, 0.95<NN<0.995, 22%, NN>0.995, 44% • We expect substantial signal! • NN>0.8, 1.2 events • 0.7 events with NN>0.995

  19. Expected Background • Combinatoric backgrounds: from linear fit to sidbands. • Highest NN bin. Compare to p0 and exponitial fit for systematic uncertainty. • B→hh • Use Bs(d) → μ+μ efficiencies with analytic model of B→hh mass shape • Convolute with muon fake rates measured in D* data

  20. Bhh Background Bhh background small but not negligible • Clearly peaks in signal region • Sideband estimates not useful • Convolute known branching ratios and acceptance with K and  fake rates. • All decays observed/measured at CDF Small for Bs Order of magnitude larger for Bd

  21. Expected and Observed Data

  22. DiMuon Mass vs. NN • Mass distributions in three NN bins and vs NN for UU and UX combined • Bs NN>0.995, 6 background expected, 7 events observed, signal 0.7

  23. Bs(d)→ μ+μ-Limits • Set limits using CLs methodology • Systematic uncertainties included • Cross check using Bayesian method, consistent at 5% level • Limit 4.3x10-8 (3.3x10-8 expected) • PVAL 23%, +0.73 sigma • D0 expected sensitivity with 5fb-1: 5.3x10-8 • Previous CDF result with 1.9fb-1: 5.8x10-8 (4.8x10-8 expected) • CDF continues to have the world’s best limits • Analysis now background limited and reaching a sensitivity where SM signal is substantial!

  24. History and Future

  25. Bs→ μ+μ-:Physics Reach Excluded! Typical example of SUSY Constraints However, large amount of recent work specifically on dark matter BF(Bs +- ) < 4.3x10-8 at 95% CL • Strongly limits specific SUSY models: SUSY SO(10) models • Allows for massive neutrino • Incorporates dark matter results BF(Bs +- ) = 1.0x10-7 BF(Bs +- ) = 5x10-8 Dark matter constraints A previous result circa 2005 L. Roszkowski et al. JHEP 0509 2005 029 25

  26. Bs→ μ+μ-and Dark Matter Excluded by newBs→μ+μ- tan=50 S. Baek, D.G. Cerdeno Y.G. Kim, P. Ko, C. Munoz, JHEP 0506 017, 2005 • Bs→μ+μ- correlated to dark matter searches • CMSSM supergravity model • Bs→μ+μ- and neutralino scattering cross sections are both a strong function of tanβ • In focus point region , high tanβ(50), positive μ, favoured in CDM allowed fits • Current bounds on Bs→μ+μ-exclude parts of the dark matter parameter space

  27. Conclusions BF(Bs +- ) < 4.3x10-8 at 95% CL BF(Bd +- ) < 7.6x10-9 at 95% CL Worlds Best Limits! B(s,d)→μ+μ-results Best Bs and Bd results: well ahead of D0 and the B factories Limit excludes allowed parameter space of SO(10) models Expanding sensitivity to interesting areas of MSSM parameter space Results correlated with some of the other most interesting topics in physics such as Higgs searches and dark matter!

  28. Backup

  29. B Physics and Dark Matter Results can then be compared to experimental sensitivities • B Physics constraints impact dark matter in two ways • Dark matter annihilation rates • Interesting for indirect detection experiments • Annihilation of neutralinos • Dark matter scattering cross sections • Interesting for direct detection experiments • Nucleon neutralino scattering cross sections • Models are (n,c)MSSM models with constraints to simplify the parameter space: Key parameters are tanβ and MA as in the flavour sector along with m1/2 • Two typical programs of analysis are performed • Calculation of a specific property: Nucleon neutralino scattering cross sections • Constraints from Bs(d)→μ+μ- and b s as well as g-2, lower bounds on the Higgs mass, precision electroweak data, and the measured dark matter density. • General scan of allowed SUSY parameter gives ranges of allowed values

  30. SUSY and Dark Matter Informs you about what types of dark matter Interactions are interesting • What’s consistent with the constraints? • There are various areas of SUSY parameter space that are allowed by flavour, precision electroweak, WMAP • Stau co-annihilation • Funnel • Bulk Region • Low m0 and m1/2, good for LHC • Focus Point • Large m0 neutralino becomes higgsino like • Enhanced Higgs exchange scattering diagrams • Disfavoured by g-2, but g-2 data is controversial H. Baer et. al. TeV

  31. Flavour Constraints on m ~ Definite preferred neutralino masses J. Ellis, S. Heinemeyer, K. Olive, A.M Weber and G. Weiglein hep-ph/0706.0652 • An analysis uses all available flavour constraints • Bs→μ+μ-, b s,Bs Oscillations,B  • CMSSM - constrained so that SUSY scalers and the Higgs and the gauginos have a common mass at the GUT scale: m0 and m1/2 respectively Focus Point Stau co-annihilation This region favoured because of g-2

  32. B Physics and Dark Matter Current experiments starting to probe interesting regions However… Analysis shows a preference for the Focus Point region, g-2 deweighted Higgsino component of Neutralino is enhanced. Enhances dominant Higgs exchange scattering diagrams Interesting relative to light Higgs searches at Tevatron and LHC Probability in some regions has gone down • Putting everything together including most recent theory work on b s R. Austri, R. Trotta, L. Roszkowski, hep-ph/0705.2012 S. Baek, et.al.JHEP 0506 017, 2005

  33. Bs→ μ+μ-and Dark Matter Excluded by newBs→μ+μ- tan=50 S. Baek, D.G. Cerdeno Y.G. Kim, P. Ko, C. Munoz, JHEP 0506 017, 2005 • Bs→μ+μ- correlated to dark matter searches • CMSSM supergravity model • Bs→μ+μ- and neutralino scattering cross sections are both a strong function of tanβ • In focus point region, high tanβ(50), positive μ, CDM allowed • Current bounds on Bs→μ+μ-exclude parts of the dark matter parameter space

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