Notre Dame Afb Seminar 2009

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Notre Dame Afb Seminar 2009

  1. 1. Page 1Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Measurement of the Forward-Backward Asymmetry in Top Quark Pair Production in pp Collisions at 1.96 TeV Glenn Strycker University of Michigan On behalf of the CDF Collaboration
  2. 2. Page 2Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Measurement of the Forward-Backward Asymmetry in Top Quark Pair Production in pp Collisions at 1.96 TeV Glenn Strycker University of Michigan On behalf of the CDF Collaboration 1999-2003 2003-2010
  3. 3. Page 3Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Outline  People Involved  What is Afb – why study it?  Theoretical Predictions  Previous Measurements  FNAL and CDF Overview  Measurement Techniques  Correction Procedure  Conclusion
  4. 4. Page 4Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 People Involved University of Michigan: University of California, Davis: Also much work done by the Karlsruhe group: J. Wagner, T. Chwalek, W. Wagner Glenn Strycker Dan Amidei Monica Tecchio Tom Schwarz Robin Erbacher
  5. 5. Page 5Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 The Top Forward-Backward Production Asymmetry has already generated a lot of interest… Asymmetries in tt Production
  6. 6. Page 6Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetries in tt Production
  7. 7. Page 7Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetries in tt Production
  8. 8. Page 8Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetries in tt Production
  9. 9. Page 9Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Simple Asymmetries in the tt System t p p t (cos 0) (cos 0) (cos 0) (cos 0) t t t t N N fb N NA           Forward-Backward Asymmetry: (cos 0) (cos 0) (cos 0) (cos 0) t t t t N N C N NA           Charge Asymmetry: (cos 0) (cos 0)tt N N    C fbA A Assuming CP parity holds,  
  10. 10. Page 10Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 t θ  Use θ, Cos(θ), rapidity (y), Delta y, etc. to measure Afb  Which variable do we use?  Which reference frame should we use?  Possible to do the more complicated measurement cos fbdA d θ p t Asymmetries in tt Production
  11. 11. Page 11Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 t  Use θ, Cos(θ), rapidity (y), Delta y, etc. to measure Afb  Which variable do we use?  Which reference frame should we use?  Possible to do the more complicated measurement cos fbdA d θ p t Asymmetries in tt Production 1 ln 2 L L E p E p       y
  12. 12. Page 12Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24  In lowest order QCD, top quark production is symmetric  NLO QCD predicts a small asymmetry  Asymmetries are important tools for understanding weak interactions, as well as for searching for additional (chiral) couplings t p p t Asymmetries in tt Production
  13. 13. Page 13Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions + + tt ttj Ctt = -1 Ctt = +1 Ctt = -1 Ctt = +1 Halzen, Hoyer, Kim; Kuhn, Rodrigo Dittmaier, Uwer, Weinzier; Almeida, Sterman, Vogelsang Afb ~ +10-12% Afb (NLO) Afb (NNLO) Consensus working value Afb ~ 5 ± 1.5% ~ -7% ~ -1%
  14. 14. Page 14Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions + + tt ttj Ctt = -1 Ctt = +1 Ctt = -1 Ctt = +1 Halzen, Hoyer, Kim; Kuhn, Rodrigo Dittmaier, Uwer, Weinzier; Almeida, Sterman, Vogelsang Afb ~ +10-12% Afb (NLO) Afb (NNLO) ~ -7% ~ -1% Note that ggtt results in no asymmetry, so our measurement will be diluted by 15% before any other effects Consensus working value Afb ~ 5 ± 1.5%
  15. 15. Page 15Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009)
  16. 16. Page 16Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) c = βcos(θ)
  17. 17. Page 17Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) Vector coupling mG = mass of axigluon ΓG = width of axigluon Axial coupling
  18. 18. Page 18Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) gluon exchange gluon propagator
  19. 19. Page 19Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) Interference Term
  20. 20. Page 20Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) Note that there is a symmetric part and an asymmetric part
  21. 21. Page 21Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) Pole term for axigluon
  22. 22. Page 22Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) Again, note that there is a symmetric part and an asymmetric part
  23. 23. Page 23Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) Since we observe no pole in Mtt, this constrains the possible values for gA and gV that give a positive asymmetry
  24. 24. Page 24Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Lagrangian for Axigluon+Gluon Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009) Allows us to restrict regions for coupling parameters that won’t change tt cross section
  25. 25. Page 25Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Recent Measurement History Previously Blessed Results (1.9 fb-1): Afb cos(θ) method: Afb = 0.17 ± 0.08 (Davis/Michigan) Afb ∆y method: Afb = 0.24 ± 0.14 (Karlsruhe) Phys. Rev. Lett. 101, 202001 (2008) D-zero Results (0.9 fb-1): Afb = 0.12 ± 0.08 ± 0.01
  26. 26. Page 26Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Fermilab and CDF Fermilab and CDF...
  27. 27. Page 27Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Fermilab  Tevatron ~4 miles around  1.96 TeV Collisions  Over 6 fb-1 data integrated luminosity  We're still the most energetic and highest luminosity hadron collider on Earth!
  28. 28. Page 28Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Fermilab  Tevatron ~4 miles around  1.96 TeV Collisions  Over 6 fb-1 data integrated luminosity  We're still the most energetic and highest luminosity hadron collider on Earth!
  29. 29. Page 29Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Fermilab
  30. 30. Page 30Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Event Reconstruction
  31. 31. Page 31Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Event Reconstruction
  32. 32. Page 32Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Event Reconstruction
  33. 33. Page 33Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Event Reconstruction
  34. 34. Page 34Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Event Reconstruction Reconstruction  Match jets to b, b, up, down  Constrain fit W mass to 80.4 GeV/c2  Constrain fit for a 175.0 GeV/c2 Top  Float momenta of jets within known resolution  Use combination with lowest χ2 ? ? 2 2 2 2 2 2 2 2 2 2,, 2 2,, )()()()( , )( , )(2 top topbl top topbjj w wl w wjj j fitUE j measUE j i fiti t measi t MMMMMMMM yxj pp jetslep pp                
  35. 35. Page 35Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Top Pair Production and Decay Top signals isolated using secondary vertex = “b-tag” Lepton + Jets mode: qq → g → tt → (W+b)(W-b) → (l+νb)(qqb) → l+ + Et + 4j + ≥ 1 “tagged” jet Vertex for b-quarks is roughly ½ mm Charm jets are only tagged ~1/10 the time
  36. 36. Page 36Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Selection  Measurement is performed using semi-leptonic top pair decays  3.2 fb-1 of CDF data  ≥ 4 jets (Et > 20 GeV and |η| < 2)  ≥ 1 b-tagged jet  1 electron (Et > 20 GeV and |η| < 1) –or– 1 muon (Pt > 20 GeV/c and |η| <1)  Missing Transverse Energy > 20 GeV 776 Candidate Events Data Sample
  37. 37. Page 37Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Selection  Measurement is performed using semi-leptonic top pair decays  3.2 fb-1 of CDF data  ≥ 4 jets (Et > 20 GeV and |η| < 2)  ≥ 1 b-tagged jet  1 electron (Et > 20 GeV and |η| < 1) –or– 1 muon (Pt > 20 GeV/c and |η| <1)  Missing Transverse Energy > 20 GeV Data Sample 776 Candidate Events
  38. 38. Page 38Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24  Hadronic top decay is more accurately reconstructed, so we will measure yhad  Get hadronic top charge from lepton  Invoke CP invariance and multiply hadronic-only distribution by -1 * lepton charge to find equivalent top rapidity in each event  Measure Afb using -Qlep• yhad in the lab frame, count forward and backward events  Correct Afb back to parton level backward forward → W– b → l ν b → W+ b → j j b t t Measurement Techniques
  39. 39. Page 39Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Selection  Measurement is performed using semi-leptonic top pair decays  3.2 fb-1 of CDF data  ≥ 4 jets (Et > 20 GeV and |η| < 2)  ≥ 1 b-tagged jet  1 electron (Et > 20 GeV and |η| < 1) –or– 1 muon (Pt > 20 GeV/c and |η| <1)  Missing Transverse Energy > 20 GeV Backgrounds  Use W+Jets tagged backgrounds to model the ttbar tagged backgrounds present in the semi-leptonic sample Data Sample 167 ± 34 Background Events
  40. 40. Page 40Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Data Sample Say number of events and number of events in backgrounds. Process W+HF Jets 86.56 ± 27.40 Mistags (W+LF) 27.43 ± 7.70 Non-W (QCD) 33.44 ± 28.06 Single Top 7.82 ± 0.50 WW/WZ/ZZ 7.57 ± 0.74 Z+Jets 4.78 ± 0.59 Top 569.08 ± 78.81 Total Prediction 736.64 ± 89.22 776 Candidate Events 167 ± 34 Predicted Background Selection  Measurement is performed using semi-leptonic top pair decays  3.2 fb-1 of CDF data  ≥ 4 jets (Et > 20 GeV and |η| < 2)  ≥ 1 b-tagged jet  1 electron (Et > 20 GeV and |η| < 1) –or– 1 muon (Pt > 20 GeV/c and |η| <1)  Missing Transverse Energy > 20 GeV Backgrounds  Use W+Jets tagged backgrounds to model the ttbar tagged backgrounds present in the semi-leptonic sample
  41. 41. Page 41Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Raw Asymmetry Signal MC is MC@NLO, normalized so signal+background = number of data events
  42. 42. Page 42Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Raw Asymmetry Signal MC is MC@NLO, normalized so signal+background = number of data events We wish to correct for this shape
  43. 43. Page 43Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Background Subtraction  Background has a known asymmetry that modifies the top Afb measurement  Check anti-tagged data and MC for consistency and cross-section  Subtract backgrounds from our data Backgrounds in W+Jets
  44. 44. Page 44Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Background Subtraction  Background has a known asymmetry that modifies the top Afb measurement  Check anti-tagged data and MC for consistency and cross-section  Subtract backgrounds from our data
  45. 45. Page 45Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Background Subtraction  Background has a known asymmetry that modifies the top Afb measurement  Check anti-tagged data and MC for consistency and cross-section  Subtract backgrounds from our data
  46. 46. Page 46Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Background Subtraction • We subtract off this total background from the data shape, 167 events out of 776 data events, which has Afb = -0.059 ± 0.0079 • Negative values mostly due to electroweak processes (W+HF)  Background has a known asymmetry that modifies the top Afb measurement  Check anti-tagged data and MC for consistency and cross-section  Subtract backgrounds from our data
  47. 47. Page 47Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Background Afbs
  48. 48. Page 48Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetry Correction Technique  We optimize for number of bins and bin spacing  Reconstruction of the event causes smearing between bins. We use a matrix unfolding technique to correct for this effect.  Acceptance efficiencies also bias our sample, so an analogous correction is made using an acceptance matrix Sij = Nij recon/Ni truth Aii = Ni sel/Ni gen Ncorrected = A-1•S-1•Nbkg-sub Bin smearing
  49. 49. Page 49Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Sij = Nij recon/Ni truth Aii = Ni sel/Ni gen Ncorrected = A-1•S-1•Nbkg-sub Corrected Asymmetry Measurement
  50. 50. Page 50Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Test of Method  We make control samples with known asymmetry by reweighting Pythia Cos(θ) signal in the ttbar frame by 1+A•Cos(θtt)  Propagate these changes to obtain appropriate factors for reweighting Ypp  Check corrected measurement vs known Afb for Cos(θtt) signal
  51. 51. Page 51Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Corrected Asymmetry Measurement Raw Afb = 9.8 ± 3.6% Bkg-sub Afb = 14.1 ± 4.6% Final Corrected Afb = 19.3 ± 6.5%
  52. 52. Page 52Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Corrected Asymmetry Measurement Raw Afb = 9.8 ± 3.6% Bkg-sub Afb = 14.1 ± 4.6% Final Corrected Afb = 19.3 ± 6.5% ~3σ significance from LO QCD (A=0%)
  53. 53. Page 53Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Corrected Asymmetry Measurement Raw Afb = 9.8 ± 3.6% Bkg-sub Afb = 14.1 ± 4.6% Final Corrected Afb = 19.3 ± 6.5% >2σ significance from NLO (A~5%)
  54. 54. Page 54Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 nominal bkg QCD difference Wbb difference new uncertainty 0.187 0.200 0.013 0.178 -0.009 0.013 Sigma is the max abs value of these two differences Background subtraction is our largest component of the systematic error. We have two main sources: background shape and size. For the shape uncertainty:  Take the QCD (or WHF) contribution of the background and rescale it to have the method II number of events.  Make a distribution using “Reweighted Signal + Modified Bkg”  Subtract off the original Method II background, unfold, and measure an Afb.  Compare with nominal value Background Shape Systematic Uncertainty
  55. 55. Page 55Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Calc. Uncert. Background Shape 0.011 Background Size 0.018 ISR/FSR 0.008 JES 0.002 PDF 0.001 MC Generator 0.003 Shape / Unfolding 0.006 Total Uncertainty 0.024 Vary simulated data by ±σ and calculate Afb difference with known sample Systematic Uncertainties and Final Result
  56. 56. Page 56Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Systematic Errors and Result Calc. Uncert. Background Shape 0.011 Background Size 0.018 ISR/FSR 0.008 JES 0.002 PDF 0.001 MC Generator 0.003 Shape / Unfolding 0.006 Total Uncertainty 0.024 Final Corrected Afb = 19.3 ± 6.5 ± 2.4% Vary simulated data by ±σ and calculate Afb difference with known sample
  57. 57. Page 57Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Calc. Uncert. Background Shape 0.011 Background Size 0.018 ISR/FSR 0.008 JES 0.002 PDF 0.001 MC Generator 0.003 Shape / Unfolding 0.006 Total Uncertainty 0.024 Final Corrected Afb = 19.3 ± 6.5 ± 2.4% Vary simulated data by ±σ and calculate Afb difference with known sample Statistical error dominates total error Systematic Uncertainties and Final Result
  58. 58. Page 58Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Corrected Asymmetry Measurement Raw Afb = 9.8 ± 3.6% Bkg-sub Afb = 14.1 ± 4.6% Final Corrected Afb = 19.3 ± 6.5% ± 2.4%
  59. 59. Page 59Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 q q t t F F C 2 G 2 2 2 2 G G G 2 2 2 2 2 G G G T C πβ2 2 2dσ S Ndcos θ 2s 2s (s-m ) q t 2 2 V V(s-m ) +m Γ q t s A A (s-m ) +m Γ q 2 q 2 t 2 2 2 V A V t 2 2 2 q q t t A V A V A = α 1+c + 4m + [g g (1+c + 4m ) +2g g c]+ ×[((g ) +(g ) )((g ) (1+c + 4m ) +(g ) (1+c + 4m ))+8g g g g c] { } Back to theory… Theoretical Predictions Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009)
  60. 60. Page 60Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions 2 2 2 2 2 2 2 2 2 2 2 2 2 cos 2 2 ( ) 2 2 ( ) ( ) 2 2 2 2 2 2 2 2 1 4 [ (1 4 ) 2 ] [(( ) ( ) )(( ) (1 4 ) ( ) (1 4 )) 8 ] { } q q t t F F C G G G G G G G T Cd S Nd s s s m q t V Vs m m q t s A A s m m q q t V A V t q q t t A V A V A c m g g c m g g c g g g c m g c m g g g g c                            Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009)
  61. 61. Page 61Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions 2 2 2 2 2 2 2 2 2 2 2 2 2 cos 2 2 ( ) 2 2 ( ) ( ) 2 2 2 2 2 2 2 2 1 4 [ (1 4 ) 2 ] [(( ) ( ) )(( ) (1 4 ) ( ) (1 4 )) 8 ] { } q q t t F F C G G G G G G G T Cd S Nd s s s m q t V Vs m m q t s A A s m m q q t V A V t q q t t A V A V A c m g g c m g g c g g g c m g c m g g g g c                            Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009)
  62. 62. Page 62Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions 2 2 2 2 2 2 2 2 2 2 2 2 2 cos 2 2 ( ) 2 2 ( ) ( ) 2 2 2 2 2 2 2 2 1 4 [ (1 4 ) 2 ] [(( ) ( ) )(( ) (1 4 ) ( ) (1 4 )) 8 ] { } q q t t F F C G G G G G G G T Cd S Nd s s s m q t V Vs m m q t s A A s m m q q t V A V t q q t t A V A V A c m g g c m g g c g g g c m g c m g g g g c                            Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009)
  63. 63. Page 63Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions 2 2 2 2 2 2 2 2 2 2 2 2 2 cos 2 2 ( ) 2 2 ( ) ( ) 2 2 2 2 2 2 2 2 1 4 [ (1 4 ) 2 ] [(( ) ( ) )(( ) (1 4 ) ( ) (1 4 )) 8 ] { } q q t t F F C G G G G G G G T Cd S Nd s s s m q t V Vs m m q t s A A s m m q q t V A V t q q t t A V A V A c m g g c m g g c g g g c m g c m g g g g c                            Ferrario and Rodrigo – Physical Review D 80, 051701(R) (2009)
  64. 64. Page 64Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions 2 2 2 2 2 2 2 2 2 2 2 2 2 cos 2 2 ( ) 2 2 ( ) ( ) 2 2 2 2 2 2 2 2 1 4 [ (1 4 ) 2 ] [(( ) ( ) )(( ) (1 4 ) ( ) (1 4 )) 8 ] { } q q t t F F C G G G G G G G T Cd S Nd s s s m q t V Vs m m q t s A A s m m q q t V A V t q q t t A V A V A c m g g c m g g c g g g c m g c m g g g g c                            Frampton, Shu, and Wang – [hep-ph] arxiv:0911.2955 IPMU-09-0135
  65. 65. Page 65Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Future Plans • dA/dM (Afb vs Mtt) • dA/dy (Afb as a function of y) • increase data set • understand the systematic uncertainties better • submit thesis!
  66. 66. Page 66Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Conclusions  Previous results (1.9 fb-1): Afb cos(θ) method: Afb = 17 ± 8%  Current results (3.2 fb-1): Afb -Q*yhadtop method: Afb = 19.3 ± 6.5 ± 2.4%  Are measured values are higher than the 5% SM prediction, but consistent within ~2 sigma lab lab
  67. 67. Page 67Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 and while our current asymmetry measurement is quite exciting…
  68. 68. Page 68Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Stay tuned for more exciting asymmetries!
  69. 69. Page 69Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 The End
  70. 70. Page 70Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Backup Slides Backup Slides
  71. 71. Page 71Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Measurement of Forward-Backward Asymmetry in Top Quark Pair Production in ppbar Collisions at 1.96 TeV Glenn Strycker University of Michigan On behalf of the CDF Collaboration 1999-2003 2003-2010
  72. 72. Page 72Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Previous Methods  Earlier Michigan/Davis measurements counted forward and background events from a Cos(θ) distribution in the lab frame.  Karlsruhe group investigated ∆y, the difference in rapidity between the top and antitop. This quantity is Lorentz-invariant, so the corresponding Afb is a measurement in the ttbar frame.
  73. 73. Page 73Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Fermilab
  74. 74. Page 74Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 CDF The CDF Detector
  75. 75. Page 75Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 CDF Here are several important components of CDF
  76. 76. Page 76Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 CDF Construction of CDF
  77. 77. Page 77Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 CDF Geometry y=0 y=2 Rapidity Geometry of CDF y=1 1 ln 2 L L E p y E p       
  78. 78. Page 78Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Various Plots of Observables
  79. 79. Page 79Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Jet Energies
  80. 80. Page 80Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Jet Rapidities
  81. 81. Page 81Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Validation Plots for Fitter Variables Overflow bin
  82. 82. Page 82Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Validation Plots for Fitter Variables
  83. 83. Page 83Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Reconstructed W Quantities
  84. 84. Page 84Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Reconstructed B Quantities
  85. 85. Page 85Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Background Systematics – Size nominal afb less less difference more more difference new uncertainty 0.187 0.176 -0.011 0.200 0.013 0.012 What if our Method II numbers are off? Then we will be subtracting off the wrong amount of background. Use our reweighted dataset for three cases: 1) subtract off background + find Afb 2) subtract off 0.75x background 3) subtract off 1.25x background  Use |more-less|/2 if the more/less values are on either side of the nominal value  Use |max difference/2| if values are on the same side
  86. 86. Page 86Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 “Reweight Function” Systematic nominal Cos+Cos^6 diff Cos+Sin^2 diff Cos^5 diff Cos^3 diff new uncertainty 0.187 0.185 -0.002 0.188 0.001 0.195 0.007 0.193 0.006 0.004 What if our reweighted shape does not match the data? 1+A*Cos() Cos^6 Sin^2 Cos^5 Cos^3 Cos() Rapidity Y Uncertainty (for now) is the max abs value of these differences divided by 2 A = 0.20A = 0.20 If we are reweighting central or outer bins more heavily than we should, our unfolding technique will have error. To find the uncertainty...  Use several functions, each with an “A” parameter  Adjust A to get a given true asymmetry in the lab frame  Compare the unfolded Afb for each function with our nominal 1+A*cos(θtt) reweighted MC.
  87. 87. Page 87Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Signal Systematics What if our MC parameters are incorrect, introducing error into our unfolding matrices? To measure this uncertainty we use the following method:  generate MC with more/less of various components  reweight by same A parameter as used earlier  use our original unfolding matrices to find a corrected Afb  compare to our original nominal value. nominal afb less more less difference more difference new uncertainty ISR 0.187 0.191 0.186 0.004 -0.001 0.003 FSR 0.187 0.172 0.178 -0.015 -0.009 0.007 JES 0.187 0.181 0.189 -0.006 0.002 0.004 PDF 0.187 0.183 0.189 -0.004 0.002 0.002 TopMC 0.187 0.175 -0.012 0.012
  88. 88. Page 88Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Verify Correction Procedure Now that we've subtracted background we can calculate our smear and acceptance matrices from truth info in MC. How do we know that this unfold method is returning reasonable values? We test our method on MC reweighted to have an asymmetry. We will calculate the corrected measurement and compare with the truth asymmetry of the signal MC
  89. 89. Page 89Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Reweighted Shapes To test unfolding method, we use “fake” data samples with different forms of known asymmetry AFB. Simplest case: add linear (1+AFBcos(θtt)) term to Pythia MC true cos(θ) distribution in ttbar frame.  Define weights:  Ni is the content of bin i-th  ni is the content of ith bin assuming a AFBcos(θi) distribution  Reweight events in reconstructed cos(θ) using wi i ii N nN iw  
  90. 90. Page 90Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Test of method Propagation of Afb from ttbar frame to lab frame rapidity  We make control samples with known asymmetry by reweighting Pythia Cos(θ) signal in the ttbar frame by 1+A•Cos(θtt)  Propagate these changes to obtain appropriate factors for reweighting Ypp  Check corrected measurement vs known Afb for Cos(θtt) signal
  91. 91. Page 91Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Correction Bias Check  First plot (truth info precut) shows the dilution of true Afb caused by changing reference frames (center of momentum → lab frame)  Second plot shows the statistical fluctuations across subsets of the MC sample – MC is consistent with itself
  92. 92. Page 92Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Nominal Comparison – Reweighted MC We use the standard technique of simulating the entire analysis and varying the model assumptions to understand their effect and calculate the systematic uncertainty. In this analysis, in order to find the correct uncertainties we must first generate a sample having a known asymmetry. black = ttbar MC blue = 0.20 reweight Rapidity Y  reweight cos(θtt) distribution → rapidity distribution as explained on previous slides  choose our “A” parameter such that our final corrected rapidity Afb in the reweighted sample is closest to that observed in the corrected data measurement.
  93. 93. Page 93Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Test of 1+A•Cos(θ) Hypothesis The simplest form of an asymmetry is 1+A•cos(θtt)  Use Pythia MC (initial Afb=0) and reweight by 1+A•cos(θtt) in the rest frame  Propagate reweights to lab frame and rapidity variable to make a template  Set up binned likelihood fit to data rapidity distribution using signal (templates) plus background contribution (Gaussian-constrained to background parameters)  The good fit to the data supports the linear hypothesis
  94. 94. Page 94Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Rapidity Template Fit We can test our 1+Acos(θtt) linear hypothesis by comparing template models with the data  Set up binned likelihood fit to data rapidity distribution using signal (templates) plus background contribution (Gaussian-constrained to M24U parameters)  Find minimum of -log(likelihood) vs Afb tt  From template generation, we found the dilution factor to be Afb pp/Afb tt = 0.5593 ± 0.0023, which we use to convert results to ppbar frame
  95. 95. Page 95Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Rapidity Template Fit -log(likelihood) fit is tested with PE's and is found to have good coverage Here is the best fit – 30% asymmetry in the ttbar frame
  96. 96. Page 96Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetry Analogy  Who has the better football team?  Which metric should we use? (overall record, scores, Heisman winners?)  Are the differences (asymmetries) statistically significant? -VS- Afb = Asymmetry“Forward-Backward” → A“Football”
  97. 97. Page 97Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetry Analogy -VS- 21 Wins 1887 1888(2) 1898 1899 1900 1902 1908 1942 1978 1981 1985 1986 1991 1994 1997 1999 2003 2006 2007 2009 15 Wins 1909 1943 1979 1980 1982 1987 1988 1989 1990 1993 1998 2002 2004 2005 2008 1 Tie 1992 Asymmetry is A = 16.2% ± 15.8% LARGE Asymmetry, but *NOT Statistically Significant! *In fact, A>1910 = 3.6% ± 18% Afootball = WinsMichigan − WinsND Total GamesPlayed Information from Wikipedia and http://grfx.cstv.com/photos/schools/nd/sports/m-footbl/auto_pdf/07fbguidehistory.pdf
  98. 98. Page 98Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetry Analogy Information from Wikipedia and http://grfx.cstv.com/photos/schools/nd/sports/m-footbl/auto_pdf/07fbguidehistory.pdf “Score Asymmetry” is Ascore = 11.6% ± 2.7% only a medium-sized asymmetry, but a 4.4 sigma significance A= Points Michigan − PointsND Total Points Scored – To be unbiased, we should look at MC and choose our “best” variable before using it to measure data. Notre Dame won by... Michigan won by...
  99. 99. Page 99Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Asymmetry Analogy  Choosing the “correct” variable isn't trivial  There are additional convolutions, smearing, acceptance effects, and systematic errors to take into account  Maybe physics is easier than football! (At least we have MC...) Afb = Asymmetry“Forward-Backward” → A“Football”
  100. 100. Page 100Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Vary simulated data by ±σ and calculate Afb difference with known sample Calc. Uncert. Background Shape 0.011 Background Size 0.018 ISR/FSR 0.008 JES 0.002 PDF 0.001 MC Generator 0.003 Shape / Unfolding 0.006 Total Uncertainty 0.024 Systematic Errors and Result Final Corrected Afb = 19.3 ± 6.5 ± 2.4% Hmm... statistical error dominates total error
  101. 101. Page 101Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Simple Asymmetries in the tt System t p p t ( 0) ( 0) ( 0) ( 0) t t t t N y N y fb N y N yA       Forward-Backward Asymmetry: ( 0) ( 0) ( 0) ( 0) t t t t N y N y C N y N yA       Charge Asymmetry: ( 0) ( 0)tt N y N y   C fbA A Assuming CP parity holds,  
  102. 102. Page 102Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Fermilab This slide should have last weeks data, total data, estimates of future integrated luminosity, etc.
  103. 103. Page 103Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Publications Referencing Our Results ArXiv:0906.5541 – Ferrario and Rodrigo
  104. 104. Page 104Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24  Forward-backward Afb – does the top preferentially go one way or the other?  Count events from rapidity distribution in lab frame and calculate: Afb = (forward-backward)/total  QCD at lowest order predicts 0 asymmetry  NLO processes predicted an asymmetry Afb = 5±1.5% lab  Unexpected new top production processes with chiral or axial couplings may cause an additional asymmetry + + t p p t Asymmetries in tt Production
  105. 105. Page 105Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Theoretical Predictions 2 2 2 2 2 2 2 2 2 2 2 2 2 cos 2 2 ( ) 2 2 ( ) ( ) 2 2 2 2 2 2 2 2 1 4 [ (1 4 ) 2 ] [(( ) ( ) )(( ) (1 4 ) ( ) (1 4 )) 8 ] { } q q t t F F C G G G G G G G T Cd S Nd s s s m q t V Vs m m q t s A A s m m q q t V A V t q q t t A V A V A c m g g c m g g c g g g c m g c m g g g g c                           
  106. 106. Page 106Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24 Event Reconstruction
  107. 107. Page 107Glenn Strycker – University of Michigan Notre Dame HEP Seminar – 2009-11-24  Are more top quarks produced in the direction of the proton?  First order measurement – simply count numbers produced forward and backward  To increase sensitivity, account for acceptance and reconstruction effects t p p t Asymmetries in tt Production

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