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Fully Inclusive b->sStatus Report
UCSC: Eisner, Schmitz, SchummEdinburgh: TinslayPisa: Bucci, Walsh
Royal Holloway: Brown, McMahonSLAC: Jessop, Ozcan
John WalshINFN-Pisa
OutlineI. IntroductionII. New FeaturesIII. BB Background
DeterminationIV. Plans/Conclusions
BaBar Italia – Aprile 2003Capri
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Physics of b->s
• Sensitive to New Physics due to internal loop.
• SM theoretical prediction on fairly solid ground:– Gambino and Misiak: 3.57 +-
0.30 x 10-4
• Very low expected CP violation
• Distribution of mXs (and hence E*) depends mb and p, Fermi motion of b quark inside B meson
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Key Points of Inclusive Analysis• Select high energy photons: the minimum photon energy
is an important aspect of the analysis– Lower energy threshold
• less model dependence • higher BB background higher systematic uncertainty.
• Backgrounds – few handles to suppress them compared to exclusive analyses– Continuum events
• Photon from initial state radiation, ISR 0 () decay photon
– BB events• () decay photon (90-95%)• hadronic fakes (5-10%)
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Analysis Strategy
• Photon selection – similar to K* analysis• Background suppression
– shape cuts, lepton tags, 0/ vetoes
• Off-resonance data to subtract remaining continuum background safe, although sacrifice statistical precision
• Use control samples to study BB background:– dedicated 0/ skim – hadronic control sample– use to correct BB MC estimates
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• Branching ratio measurement (56 ifb on-peak):• B(bXs) = 3.88 +- 0.36 (stat) +- 0.37 (syst) + 0.43 – 0.23
(model)
• Systemics from ICHEP result– Photon Selection 3.7 % – Event Shape Cuts negligible– Lepton Tags 2.0 %– Normalization 1.1 %– BB background 7.8 %
• Rely on MC simulation to estimate the BB background• Use a control sample to establish how well MC simulation models data,
derive correction factors
ICHEP 2002 Result
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New Features for 2003
• Use full (up to 2002) data set: – 80 ifb On-resonant data– 9.6 ifb Off-resonant data
• Improve event-shape selection by combining several variables optimally into Fisher Discriminant
• Improved treatment of BB background: dedicated measurement of 0 and yields in BB events (Pisa group)
• Reduce minimum photon energy cut – 2 GeV is the goal
• Determination of photon spectrum as well as branching ratio
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Fisher Discriminant – Event Shape
• Have found it useful to combine several event shape variables into a Fisher Discriminant– R2’/R2 (R2’ is 2nd FW
moment with photon removed from calculation for ISR removal)
– 18 energy flow cones around photon direction
• Gives significant improvement in S2/(S+B’) compared to ICHEP analysis
• Introduces small energy-dependence in efficiency negligible increase in model dependence
Fisher > 0.575
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Determining Background from BB
• ICHEP treatment – – use control sample of events that fail the 0/ vetoes– compare rates in data and MC as function of photon energy
– Drawbacks:• limited statistics
need to extrapolate from low energy bins
• mismatch in bsg and control sample p0/h energy due to inverting vetoes
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Improved BB Background Determination
• New / skim:– increase statistics with dedicated 0/ skim with lower
photon energy threshold (1 GeV instead of 1.5 Gev)
• Method:1. Select candidates using all the standard bs selection cuts,
except for 0/ vetoes2. Perform fits of the 0/ mass distributions in bins of 0/
energy, thus determining the background subtracted 0/ energy spectra.
3. Compare continuum subtracted data spectrum with MC BB spectrum and take ratio as “correction factors”, in bins of 0/ energy.
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Results – 0
• mass fits
• energy spectrum
• data/MC ratio
0 Energy (GeV)
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Results –
• mass fits
• energy spectrum
• data/MC ratio
Energy (GeV)
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Validation: Mass fits
• Compare fit yield with number of truth-matched candidates
• On MC we find that fit yields are systematically less than the number of “true” candidates. Typical yield about 85-90%.
• Find that using Novosibirsk does not help significantly, culprit is long tails in mass distribution
• Similar problem with fits• Is problem with fit or with
truth-matching?
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2 vs Ghit Truth-Matching
• Our original skim produced with 2 truth matching
• We compared with a small sample run with GHIT matching
• Qualitatively, it appears that the Ghit performance is significantly better
• Decided to reproduce 0/ skim with GHIT matching
All candidates
Truth-matched 0s
2 matching Ghit matching
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0 mass fits – Log scale
• The better truth-matching required a better fit function
• Fit function:– signal: double
gaussian with power-law low energy tail
– background: polynomial (of degree 1, 2 or 3)
• Use MC and high-statistics untagged sample to help determine some parameters
• Fit yields now within 3% of true value
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mass fits – Log scale
• Fit function:– signal: gaussian
with low and high energy power law tails
– background: polynomial (of degree 1, 2 or 3)
• Fewer energy bins due to low statistics
• Again fit yields within 2-3% of true value
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Yields from Low Statistics
• Sometimes it’s necessary to obtain a 0 yield from very low statistics. In this case, we estimate yield by simple counting in the signal region, with sideband subtraction.
• We are currently validating this technique. There seems to be a slight bias, which we are investigating.
Estimate - Truth
(Estimate – Truth)/error
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Next Steps
• Produce new BB background correction factors for 0 and as soon as the last skim jobs are complete
• Correct BB MC and perform checks on unblinded control regions:– 1.5 < E* < 1.9 GeV of standard sample (lower side-
band)– 1.0 < E* < 2.5 GeV of 0/ sample
• Extract photon energy spectrum• Unblind and move towards publication
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Conclusions
• The inclusive bs analysis is moving forward, although at a slower pace than was hoped
• An inclusive measurement of 0 and yields in BB events to a precision of a few percent has proved more difficult than originally envisioned, but we feel things are under control
• We have improved continuum background suppresion with a Fisher Discriminant and studyied the associated systematic effects
• We are converging towards a new result and hopefully it will be available soon.