1 / 52

BaBar Particle Identification and Measuring Direct CP Asymmetry in b→sγ

BaBar Particle Identification and Measuring Direct CP Asymmetry in b→sγ. Piti Ongmongkolkul. 1. Outline. BaBar Particle Identification(PID) Is this track Kaon, Pion, Electron or Proton? BaBar Detector Decision Tree Error Correcting Output Code(ECOC) Results

chase
Download Presentation

BaBar Particle Identification and Measuring Direct CP Asymmetry in b→sγ

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. BaBar Particle Identificationand Measuring Direct CP Asymmetry in b→sγ • Piti Ongmongkolkul 1

  2. Outline • BaBar Particle Identification(PID) • Is this track Kaon, Pion, Electron or Proton? • BaBar Detector • Decision Tree • Error Correcting Output Code(ECOC) • Results • b→sγ Direct CP Asymmetry Measurement • Motivation • Current Progress • Outlook 2

  3. BaBar Experiment • Located at SLAC • PEPII Asymmetric e+e- machine • 3 GeV and 9 GeV • Main Goal is to measure CP violation in B meson • Generic enough to do many more interesting physics 3

  4. BaBar Experiment • 2000-2008 • ~470 million B Bbar pairs • +Others • Off resonance (udsc pairs) • Υ(3S) • Υ(2S) • ~1$ per B Bbar pairs 4

  5. SVT • Silicon Vertex Tracker • 5 Layer Silicon Strip • Close to interaction region • tracking • dE/dx SVT 5

  6. DCH • Drift CHamber • 40 layer wire chamber • filled with He-based gas • provides tracking • dE/dx DCH 6

  7. DIRC • Detection of Internally Reflected Cherenkov • Quartz bars and Photo Multiplier Tube array the end • Measure Cherenkov radiation angle θc (function of β) • Mainly for π-K separation DIRC PMT 7

  8. EMC • ElectroMagnetic Calorimeter • 6.5k CsI(Tl) • Photo diode at the end measure energy deposited in the crystals • Electron -- bremsstrahlung + ionizing • photon -- pair production • pKπμ -- ionizing through • E/p is a very good variable for identifying electron. Electrons leave ~all of its energy in EMC. EMC 8

  9. IFR • Instrumented Flux Return • Many Resistive Plates • Identifying K-Long and muon • Just count how many plate it pass through IFR magnet 9

  10. BaBar PID • Identify track whether it’s kaon pion electron or proton • Get B meson’s flavor needed for CP violation study • sin(2β) golden mode • Cleaning up combinatoric background • Used in almost all analysis 10

  11. BaBar PID - How? • Each subsystem provides some information about which type of particle pass through. • SVT DCH provides dE/dx, p, charge • DIRC provides Cherenkov angle θc • EMC provides energy deposited in CsI and various quantity associated with energy cluster (eg. how wide spread it is ) • + combinations of above • Combine all the information • Decision Tree • ECOC (Error Correcting Output Code) 11

  12. Decision Tree • Binary question with many input -- given all these information, is this track an e or a π? • Cuts scan for each variable. • Pick a split that maximize the separation (ex gini-index) • Repeat the process until the node considering has event less than some number 12

  13. Combining Decision Trees • Many trees are trained with slight difference. • Use different set of input variables, different set of weight or different subset of sample. • Average the result X 100 = Better Classifier 13

  14. Added Bonus • Intuitive to see importance of input variables • Sum of change in “score” for each variable splitting • deltaFOM • Reduce number of input variables 14

  15. ECOC* • Decision Tree can answer binary question. • “Is this track a p, π, K or e?” is a multiple choice question. • Error Correcting Output Code -- combining binary classifiers to make a multiclass classifier. • This is a more pedagogical example actual implementation is slightly different but the idea is the same *Dietterich, T., Bakiri, G. (1995). "Solving multiclass problem via error-correcting output code" 15

  16. ECOC -- indicator matrix • 1 vs All is an obvious choice • Is it • (e) or (p π K)--I • (p) or (e π K)--II • (K) or (e p π)--III • (π) or (e p K)--IV • Indicator Matrix • Template for answers • Ask all the question to an unknown track • Pick the closest one 16

  17. ECOC -- Exhaustive Matrix • All the binary questions one could ask • In general there are • 2n-1-1 • Those 4 and • (e π) or (p K)--V • (e p) or (π K)--VI • (e K) or (p π)--VII • Recovery power 17

  18. ECOC -- Recovery Power Hamming Distance • 4 outputs. 1 for each hypothesis win 18

  19. ECOC -- Recovery Power still win 19

  20. ECOC -- Recovery Power • Our implementation uses real numbers instead of 1 and 0 • and use sum of square • ~2 mistake to change the answer if we are unlucky A draw 20

  21. ECOC--recovery power • In 1 VS All • allow ~1 mistake • Used in the the previous PID 21

  22. What I did • Adding 3 columns 22

  23. e vs pion • Color Legend • 1 vs All Matrix • Exhaustive • Old likelihood based 23

  24. Color Legend • 1 vs All Matrix • Exhaustive • Old likelihood based 24

  25. Conclusion I • New method for PID system • ECOC with exhaustive matrix • Adding 3 columns makes a huge difference • Currently the recommended one at BaBar 25

  26. MeasuringDirect CP Violation inUsing Sum of Exclusive Modes 26

  27. Introduction • and • has slightly different branching ratio • SM* predicts *Tobias Hurth, et al. arXiv:hep-ph/0312260v2 25 Nov 2005 27

  28. Feature • Highly suppressed • Flavor changing neutral current • CKM suppressed* • GIM suppressed* • Require interference of Wilson coefficients • New physics could lift CKM or GIM suppression • or change in C’s • up to 15% *Cabibbo Kobayashi Maskawa *Glashow, Iliopoulos, and Maiani Kagan Neubert PHYSICAL REVIEW D, VOLUME 58, 094012 28

  29. More • Small long distance contribution (~1%)* • Depend very weakly on photon energy cutoff* • low energy photon will bring large background • Good probe for new physics. Happy middle ground for both theorist and experimentalist. Kagan Neubert PHYSICAL REVIEW D, VOLUME 58, 094012 29

  30. Current State • Our analysis will be done using full babar data set ~ 22% increased in data BaBar arXiv:0805.4796v3 [hep-ex] 7 Dec 2008 ~380e6 events (full data set 471e6) Belle arXiv:hep-ex/0308038v4 22 Jul 2004 ~140e6 events (full data set 700e6) 30

  31. Measurement • Goal is to get the Acp • Select Event as clean as possible • Reconstruct B from 16 final states • For charged B total charge tells us the flavor • Kaon identification tell us neutral B flavor • Get the yield for each flavor and done • Blind Analysis 31

  32. But.... • Best Candidate Selection • Peaking BBbar • Fake high energy photon from pi0 • continuum background • For 1 event, there are many ways to reconstruct B • All we have is a list of tracks with some PID associate with it. Remember 1 event has 2 B’s although we only use one. Need to match which tracks belong B of our interest. • Even with mass, energy, vertexing among other things. There are still ~10-100 B candidates/event. • Select the best candidate • B doesn’t always decay to Xs gamma • but could be mis-reconstructed as B->Xsγ • branching fraction ~ 3x10^-4 • Photons from pi0 • e+e- collision doesn’t always go to B pairs • light quark pairs 32

  33. Best Candidate • Best Candidate Selection • Fake high energy photon from pi0 • continuum background • Peaking BBbar • One event has many B candidates • ee→Υ(4S)→BB • We expect each B to have half of the beam energy in CM frame. If we pick the right set of tracks. • Minimize • Used in all previous analysis but.... 33

  34. Better • Best Candidate Selection • Peaking BBbar • Fake high energy photon from pi0 • continuum background • Binary question if looking candidate individually • Is this B candidate correctly reconstructed? • Classifier(Decision Tree) • Separate correctly reconstruct B and mis-reconstructed one • Exploit more information* • XsMass • Minimum pi0 momentum • Thrust of B • ΔE (normalized by resolution) • Fox Wolfram Moment 0 and 5 • Multiple candidates each with classifier score. • Select the one with the best classifier score *selected from deltaFOM 34

  35. More Information 35

  36. Improvement • Best Candidate Selection • Peaking BBbar • Fake high energy photon from pi0 • continuum background Better 36

  37. Peaking BBbar • Best Candidate Selection • Peaking BBbar • Fake high energy photon from pi0 • continuum background • Bonus from SSC • We trained the classifier to separate correctly reconstructed B and mis-reconstructed one • BBbar background is mis-reconstructed by definition • Cutting on the output gives us handle on peaking BBbar Background 37

  38. Pi0 Veto • Best Candidate Selection • Peaking BBbar • Fake high energy photon from pi0 • continuum background • Fake high energy photon from pi0 • pi0 decays primarily to 2 photon • Is this photon from pi0? 38

  39. Pi0 Veto • Best Candidate Selection • Peaking BBbar • Fake high energy photon from pi0 • continuum background • Pair up given high energy photon with all other photons in the event • many pi0 candidates per photon • Train a classifier separate true pi0 candidate and fake pi0 candidate* • Invariant Mass • Energy of the other photon • Take the maximum output • The higher the score the more likely it comes from pi0 • Since it’s linked with continuum background we used this as a variable for another classifier 39 *selected from deltaFOM

  40. Continuum* • Best Candidate Selection • Peaking BBbar • Fake high energy photon from pi0 • continuum background • light quark pairs udsc. Very jetty event. • mass of Υ(4S) ~ 2*mass of B. Isotropic. • Build classifier to separate continuum and BBbar • Legendre Moments along photon axis and ratio • cosine angle of B and beam axis in CM frame • cosine angle thrust of B candidate and thrust of rest of event in CM frame • cosine angle of photon and thrust of rest of event • various momentum flow(momentum around B axis in various cone size) • pi0 Classifier 40 *Done by Dr. David Doll

  41. Combining them Optimizing 41

  42. ΔE SSC 42

  43. Getting Acp • Work in progress • Simultaneous Fitting of • should peak around mass of B 43

  44. Resolution • Generate 2000 set of sample based on pdf and refit to get Acp • Compared to previous analysis of 0.030 ~ 1.5-2 times better* with only 20% more data • The improvement comes from better candidate selection and handle on BBbar background. *There is some precision problem with the fitting program though but the residual should be correct 44

  45. More to be done • Finalize Fitting procedure • Subtract off Inherent Detector CP Asymmetry (~1%) • Our detector is made of matter • Sideband/Offpeak • Acp in peaking BBbar component if any • Dilution from mis-PID (expected to be negligibly small) • Fitting Systematic 45

  46. Conclusion • BaBar PID • ECOC with exhaustive matrix • Current recommended one • Acp • Event selection is finalized • Need to Extract Acp • Do systematic and etc. 46

  47. Backup 47

  48. Different level of tightness • Each analysis has different requirement. Some need sample to be really clean and can take a hit from efficiency. Some need efficiency and just need pid to clean up a bit. • 4 output 1 for each hypothesis • Picking the best one means • e<p and e<K and e<π • Generalize • e/p>a and e/K>b and e/π>c 48

  49. Bethe-Bloc • Mostly ionization for pi p K • Ionization and bremsstrahlung (~β) for electron which lose almost all of its energy in CsI 49

  50. Acp formula helper 50

More Related