1 / 68

B s Mixing at CDF: The need for MC

Sinéad M. Farrington University of Liverpool MCNet School Durham April 2007. B s Mixing at CDF: The need for MC. 0. Observation of B s Mixing. -. Last year the phenomenon of mixing was observed for the first time in the B s meson system I shall:

belle-bradshaw
Download Presentation

B s Mixing at CDF: The need for MC

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Sinéad M. Farrington University of Liverpool MCNet School Durham April 2007 Bs Mixing at CDF:The need for MC 0

  2. Observation of Bs Mixing - • Last year the phenomenon of mixing was observed for the first time • in the Bs meson system • I shall: • Explain why Bs mixing is interesting • Explain briefly the experimental method to measure it • Show how we relied on MC and, crucially, how we assessed the associated • systematic errors 2

  3. MATTER ANTIMATTER b b u, c, t, ? s b s s s b Bs Bs Bs 0 0 0 Bs 0 u,c,t,? 0 Bs Physics Bound states: Matterantimatter: NEW PHYSICS? Vts* occurs via W+ W- Vts 0 0 • The mass eigenstates (H and L) are superpositions of Bs and Bs • System characterised by 4 parameters: • masses: mH, mL lifetimes: GH, GL(G=1/t) • Predicted Dms around 20ps-1 • No measurements of Dms have been made until now: • B factories do not produce Bs Mesons • Limits set by LEP, SLD, Tevatron "I have no satisfaction in formulas unless I feel their numerical magnitude." (Kelvin)

  4. from Dmd Lower limit on Dms from Dmd/Dms Why ismsinteresting? • Probe of New Physics - may enter in box diagrams 2) Measure CKM matrix element: Dmdknown accurately from B factories • Vtd known to 15% • Ratio Vtd/VtsDmd/Dms related by constants: •  (from lattice QCD) known to ~4% • So: measure Dms gives Vts CKM Fit result: Dms: 18.3+6.5 (1s) ps-1 Standard Model Predicts rate of mixing, Dm=mH-mL, so Measure rate of mixing Vts (or hints of NEW physics) 4

  5. Measuring ms In principle: Measure asymmetry of number of matter and antimatter decays: In practice:Dm is measured by more complex techniques: amplitude scan and likelihood profile Test Case: B0d mixing 5 H. G. Moser, A. Roussarie, NIM A384 (1997)

  6. Whichever technique is used, the information we need to extract from the events is: Mixing Ingredients 1) Signal samples - semileptonic and hadronic modes Time of Decay - and knowledge of Proper decay time resolution Flavour tagging - had the B mixed when it decayed? - opposite side - same side (this is where the main MC application enters!) 6

  7. jet charge p soft lepton fragmentation K b hadron f Bs Ds p- • To know whether a B meson “mixed” or not, need to know • flavour (B or B) when it was produced • flavour (B or B) when it decayed Flavour Tagging To determine B flavour at production, use tagging techniques: b quarks produced in pairs  only need to determine flavour of one of them Opposite side Same Side SAME SIDE Same Side K Tag eD2 = 4.8±0.04 %(semileptonic) 3.5±0.06 % (hadronic) OPPOSITE SIDE Soft Muon Tag semileptonic BR ~10% Soft Electron Tag Jet charge tagsum of charges in jet eD2 =1.82±0.04 % (semileptonic) 1.81±0.10 % (hadronic) Figure of merit is eD2e = efficiency (% events tagger can be applied) D = dilution (% events tagger is correct) 7

  8. Calibrating Flavour Taggers e-/m- p+ b ne/m b K+ c Bd K- D- p- Opposite side Same Side • Opposite side: can be calibrated with a sample of any B meson: • Take sample of B+/Bd (mixing behaviour known) – “same side” • Calculate how many B’s in that sample mixed • Look on opposite side for leptons • How often is there a lepton? (efficiency, e) • How often is it the correct sign? (dilution, D) This is a completely data driven method to obtain the tagger power BUT! We can’t apply this to the same side tagger! 8

  9. b b s } s u u K+ Bs 0 • This is the first time this type of tagger has been implemented • Completely different principle from opposite side tags • charge of B and K correlated • Use Time Of Flight detector, dE/dx information from tracking detector to select Kaon track • The kaon is also selected based on its kinematics • The dilution and efficiency of this tagger cannot be calibrated independently of the B meson type (in Bd case, we would have a pion instead: pion ID different, fragmentation of Bd could be different) Same Side Kaon Tagger 9 Entirely new calibration strategy is needed

  10. CDF Public Note 8206 • If MC reproduces distributions well for B0,B+, then rely on it to predict tagger dilution and efficiency in Bs (with appropriate systematic errors) • High statistics Bd and B+ samples in which to make data/MC comparisons: • Compare e.g. transverse momentum distributions • split into particle content (pions, kaons, protons) Same Side Kaon Tagger tagging track tagging track 10

  11. Then enhance kaon fraction by making selection on particle ID • Check still get good comparison within available statistics • (assign systematic error for this comparison) Same Side Kaon Tagger • Two key points: • this was not achieved by using “out of the box” Pythia • after finding a good comparison, most important to assign systematic errors 11

  12. Each of these modifications is driven by previous measurements, and then associated systematic errors are assigned • Data and MC are used in tandem (and consultation with theorists on what are “reasonable” variations to assess systematics) • Multiple proton-antiproton interactions • Fragmentation Model • As well as usual GEANT detector simulation, specific response of particle ID systems treated especially for this analysis • Trigger prescales Modifications to MC will discuss further After these modifications we make a comparison of all of the relevant variables between MC and data for all B meson types 12

  13. More than one pp pair can interact in a bunch crossing • Gives rise to additional particles (usually low momentum) • These could be additional SSKT tagging tracks • Pythia does have a switch to simulate this • but in this analysis data is used to simulate additional tracks 1)Calculate how many additional tracks should be added • do this by looking at the (N+1)th event in our data files • count how many tagging tracks are present in the signal region 2)Harvest tagging tracks from data (which fail one or more of the real cuts) 3)Embed these tracks in MC according to fraction determined in 1) Multiple p-p interactions 13

  14. E. Ben-Haim et al. Phys. Lett. B580, 108 (2004) • The Lund string fragmentation model is used throughout • This has a “z” parameter to define the fraction of energy the B meson takes from the string • Default z parameterisation is symmetric Lund function • use tuning to LEP data specifically for B mesons Fragmentation Function 14

  15. After all the modifications we compare all relevant distributions including efficiency and dilution in data and MC for Bd, B+ Efficiency and Dilution in Data/MC So we conclude that for Bd, B+ there is a good match between data and MC. Thus we can move to using MC only for the Bs case. 15

  16. already showed some comparisons for Bd and B+ • here are comparisons for Bs Comparisons for Bs Limited statistics  statistical error of comparison is included as systematic error 16

  17. Bs Dilution and Efficiency Results • Statistical errors only: What about the systematic errors? 17

  18. A reminder of what we’ve done: • modified MC • checked that it compares well with data for Bd, B+ • compared efficiency and dilution for Bd, B+ from data and MC • on the basis that they compare well, we extracted efficiency and dilution for Bs from MC • To apply these numbers in our analysis we need a good understanding of the systematic errors • Several sources: • bb production mechanism • fragmentation fraction • particle content around the B • variation within data statistics • B** fraction • particle ID detectors simulation • pile-up Systematic Errors will discuss further 18

  19. Q Q • Three main methods for producing bb in proton-antiproton collisions • Flavour Creation, Flavour Excitation, Gluon Splitting (default mix 5:11:4) • In gluon splitting case, the two b’s are close together – could pick up tagging tracks from the opposite b • Systematic error obtained by fitting Df distribution in data and varying MC distribution within the errors • This results in varying Gluon Splitting [-68%,+46%], Flavour Excitation and Creation [-50%,+50%] bb Production Mechanism 19

  20. Track multiplicity, transverse momentum of B meson and fragmentation tracks are sensitive to fragmentation function • Tuning made at LEP should apply equally at Tevatron • Variables compare well with data for Bd, B+ • No reason to be suspicious of fragmentation used as a default, but systematic errors assigned to cover the possibility of problems • Simultaneous fit to these distributions to determine allowed parameters of the symmetric Lund function • data not sufficient to give a tight constraint • reasonable variation can be obtained, beyond which comparison between MC and data is degraded • The variations are used to assign systematic errors: Fragmentation 20

  21. Particle species around the B meson gives insight on fragmentation • Agrees well between data and MC for Bd, B+ • Slight discrepancy for Bs: (20.2±1.4)% kaons in data, (23.6±0.2)% in MC • Vary the kaon fraction in the data downwards in two ways: • reweight all events with a kaon tagging track • reweight only those events with prompt kaons from b-string Particle Content around B Meson 21

  22. We claim the comparisons of data and MC are good • but that is only valid within the errors on our data! Variation within Data Statistics MC samples varied within ranges allowed by statistical uncertainties 22

  23. Including all of the systematic errors we can remake the comparisons of data and MC • Note that the MC distributions envelope the data distributions Compare again with data 23

  24. Dilution and its systematic errors: Final SSKT Results Final Tagger Power: eS2<D2>= (4.0+0.9-1.2) % (Notes: <D> is the average dilution over all quantities, in reality we bin dilution in momentum, particle ID variable to get extra power. S is a scale factor to account for any differences between data and MC in dependency of dilution on variables.) MC simulations combined with measurements in data make this measurement possible 24

  25. The Results 25

  26. Amplitude scan performed on Bs candidates • Inputs for each candidate: • Mass • Decay time • Decay time resolution • Tag decisions • Predicted dilution Put the 3 Ingredients Together • All elements are then folded into the amplitude scan “With three parameters, I can fit an elephant.” (Kelvin) 26

  27. probability of fake from random tags = 8x10-8 Equivalent to 5.4s significance Combined Amplitude Scan Amplitude consistent with 1 ms = 17.77±0.10(stat)±0.07(syst) ps-1

  28. Vts / Vtd= 0.2060 ± 0.0007 (exp) +0.0081 (theo) -0.0060 Conclusions • CDF has found a signature consistent with Bs - Bs oscillations • probability of this being a fluctuation is 8x10-8 • MC enabled the calibration of the most powerful flavour tagger • would not have been possible to such accuracy without experimental data to inform the use of MC • In my view the best (safest) possible way to use MC in analysis • use the data to make all possible checks • use previous measurements, talk to theorists and use data itself to assign systematic errors for all of the unknowns • Gives confidence in the results ms = 17.77±0.10(stat)±0.07(syst) ps-1

  29. Interpretation of Results This measurement decreases uncertainty on CKM triangle apex: October 2006 Easter 2006

  30. Likelihood Significance • probability of fake from random tags = 8x10-8measure ms • Equivalent to 5.4s significance ms = 17.77±0.10(stat)±0.07(syst) ps-1

  31. Asymmetry Oscillations folded modulo 2p/Dms

  32. |Vts| / |Vtd| • Can extract Vts value • compare to Belle bs(hep-ex/050679): |Vtd| / |Vts| = 0.199 +0.026 (exp) +0.018 (theo) • our result: |Vtd| / |Vts| = 0.2060 ± 0.0007(exp) +0.0081 (theo) -0.025 -0.016 -0.0060 • inputs: • m(B0)/m(Bs) = 0.9832 (PDG 2006) •  = 1.21 +0.05 (Lattice 2005) •  md = 0.507±0.005 (PDG 2006) -0.04

  33. Interpretation of Results Measurements compared with global fit (CKM fitter group) updated this month In excellent agreement with expectations

  34. Systematic Uncertainties on ms • Systematic uncertainties from fit model evaluated on toy Monte Carlo • Have negligible impact • Relevant systematic uncertainties are from lifetime scale All systematic uncertainties are common between hadronic and semileptonic samples

  35.  L Hadronic: fully reconstructed 1) Signal Samples for BsMixing Semileptonic: partially reconstructed These modes are flavour specific: the charges tag the B at decay Crucial: Triggering using displaced track trigger (Silicon Vertex Trigger) 35

  36. Triggering On Displaced Tracks • trigger Bs→ Ds-, Bs→ Ds- l+ Secondary Vertex Primary Vertex d0 Online accuracy • trigger processes 20 TB /sec • trigger requirement: • two displaced tracks: • (pT > 2 GeV/c, 120 m<|d0|<1mm) • requires precision tracking in silicon • vertex detector

  37. Now we use the entire range, capitalising on satellites also Previous mixing fit range Example Hadronic Mass Spectrum signal Bs→ Ds, Ds→  → K+K- partially reconstructed B mesons (satellites) combinatorial background B0→ D- decays

  38. Hadronic Signal Yields • Neural Network selection used in these modes • Particle ID (dE/dx, Time of Flight) used to suppress backgrounds

  39. Semileptonic Samples: Ds- l+ x Bs mesons not fully reconstructed: Fully reconstructed Ds mesons: Mixing fit range Particle ID used; new trigger paths added  The candidate’s m(lDs-) is included in the fit: discriminates against “physics backgrounds” of the type B0/+→ D+Ds 61500 semileptonic candidates

  40. Summary of Yield changes since April 2006 • 1fb-1 of data used in both analyses • What changed? • Hadronic modes: • Added partially reconstructed “satellite” Bs decays • Add Neural Net for candidate selection • Used particle identification to eliminate background • Semileptonic Modes: • Used particle identification to eliminate background • Added new trigger path Effective increase in statistics x2.5 from these changes

  41. 850 Per Bs meson What do the candidates cost?: FECb Tevatron Accelerator Value: $7M/year ($741M RPV at 70% spread over 25 years and 3 experiments) CDF Detector Value: $0.8M/year ($95M total facilities RPV at 70% value) Tevatron Operation to CDF: $48M/year ($120M/year at 40% of overall facilities) CDF Operation: $5M/year Total CDF data $61M/year B Physics Program: $12M/year (1/5 per physics group) 0 The Bsottom Line: $ 41

  42. osc. period at ms = 18 ps-1 2) Time of Decay • Reconstruct decay length by vertexing • Measure pT of decay products Proper time resolution: Semileptonic: Hadronic: Crucial: Vertex resolution (Silicon Vertex Detector, in particular Layer00 very close to beampipe) 42

  43. Layer 00 • So-called because we already had layer 0 when this device was designed! • UK designed, built and (mostly) paid for this detector! • layer of silicon placed directly on beryllium beam pipe • Radius of 1.5 cm • additional impact parameter resolution I.P resolution without L00

  44. B decays pp collision Classic B Lifetime Measurement • reconstruct B meson mass, pT, Lxy • calculate proper decay time (ct) • extract c from combined mass+lifetime fit • signal probability: psignal(t) = e-t’/ R(t’,t) • background pbkg(t) modeled from sidebands

  45. Hadronic Lifetime Measurement • Displaced track trigger biases the lifetime distribution • Correct with an efficiency function derived from MC: p = e-t’/ R(t’,t)  (t) 0.2 0.4 0.0 proper time (cm)

  46. Hadronic Lifetime Measurements Errors are statistical only World Averages: B0: 1.534 ± 0.013 ps B-: 1.653 ± 0.014 ps Bs: 1.469 ± 0.059 ps Good agreement in all modes

  47. Semileptonic Lifetime Measurement • neutrino momentum missing • Correct with “K factor” from MC: • Also correct for displaced track trigger bias as in hadronic case High m(lD) candidates have narrow K factor distribution: almost fully reconstructed events! Capitalise on this by binning K factor in m(lD)

  48. Errors are statistical only Lifetimes measured on first 355 pb-1 Compare to World Average: Bs: (1.469±0.059) ps All Lifetime results are consistent with world average Gives confidence in fitters, backgrounds, ct resolution Semileptonic Lifetime Results

  49. p p The CDF Detector and Triggers • (bb) << (pp)  B events are selected with specialised triggers • Displaced vertex trigger exploits long lifetime of B’s • Yields per pb-1 are ~3x those of Run I 49

  50. Ecom=2TeV - p CDF p Ep=0.96TeV Ep=0.96TeV 1km D0 ECoM=2TeV The Tevatron - Fermilab, Chicago Currently the world’s highest energy collider Hadron collisions can produce a wide spectrum of b hadrons (in a challenging environment) Bs cannot be produced at the B factories since their Centre of Mass energy is below threshold (except for a special run by Belle) 50

More Related