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Test of lepton flavor violation with K e2 decay at KLOE

Test of lepton flavor violation with K e2 decay at KLOE. Matteo Palutan INFN-LNF (for the KLOE Collaboration) CERN, May 25 th 2009. Measurement of R K = G (K e2 )/ G (K m 2 ). Introduction K e2 events counting Study of direct emission in K e2 g Results on R K.

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Test of lepton flavor violation with K e2 decay at KLOE

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  1. Test of lepton flavor violation with Ke2 decay at KLOE Matteo Palutan INFN-LNF (for the KLOE Collaboration) CERN, May 25th 2009

  2. Measurement of RK = G(Ke2)/G(Km2) • Introduction • Ke2 events counting • Study of direct emission in Ke2g • Results on RK Matteo Palutan, Ke2 at KLOE

  3. Standard Model prediction for RK=G(Ke2)/G(Km2) Reduced hadronic uncertainties in the ratio Ke2/Km2 (no fK ) u e, m W ne , nm s IB only Finkemeier 97 Cirigliano-Rosell 07 0.04% uncertainty Strong helicity suppression of electron channel enhances sensitivity to physics beyond the SM Matteo Palutan, Ke2 at KLOE

  4. New Physics potential of RK Masiero, Paradisi Petronzio 06 In MSSM, LFV can give % deviations from SM LFV from loop generates an effective eH+nt coupling uL eR H+ sR nt 1 % effect if DR31 ≈ 5×10-4, tanb ≈ 40, mH ≈ 500 GeV) Matteo Palutan, Ke2 at KLOE

  5. Entering the precision realm for RK PDG 2008 RK = (2.45 ±0.11) × 10-5 4.5% accuracy three measurements from 70’s Main players in the challenge to push down precision on RK KLOE preliminary result with 2001-2004 data: RK = 2.55(5)stat(5)syst × 10-5 from ≈ 8000 Ke2 candidates (3% accuracy) preliminary result with 2003 data: RK = 2.416(43)stat(24)syst × 10-5 from ≈ 4000 Ke2 candidates (2% accuracy) NA48/2 preliminary result with 2004 data: RK = 2.455(45)stat(41)syst × 10-5 from ≈ 4000 Ke2 candidates (3% accuracy) NA62 ≈ 150,000 Ke2 events collected in a dedicated 2007 run aims at <0.5% Matteo Palutan, Ke2 at KLOE

  6. DAFNE e+e- collider at LNF • s ~1019.46 MeV = mf • sf~ 3.1 mb at peak • crossing angle ~ 12.5 mrad • today, Lpeak= 4.51032 cm-2s-1 Matteo Palutan, Ke2 at KLOE

  7. Summary of KLOE data taking L= 2.2fb-1 atfpeak yielding 3×109 K+K-pairs ≈ 50,000 Ke2 decays in fiducial volume Matteo Palutan, Ke2 at KLOE

  8. The KLOE experiment Magnet SC coil, B = 0.6 T EM Calorimeter Pb-scint fiber 4880 PMs, 2440 cells Drift chamber 12582 sense wires 52140 tot wires Carbon fiber walls Al-Be beam pipe r = 10 cm, 0.5 cm thick Matteo Palutan, Ke2 at KLOE

  9. Detector performances Drift Chamber EM Calorimeter Matteo Palutan, Ke2 at KLOE

  10. Charged kaon beams f decay at rest provides almostpure kaon beams of known momentum pK ≈ 100 MeV l ≈ 90 cm (56% of K+ decay in DC) Kaon momentum is measured with 1 MeV resolution in DC • Constraints from f 2-body decay • Particle ID with kinematics and TOF • Tagging provides unbiased control samples for efficiency measurement 4 m Matteo Palutan, Ke2 at KLOE

  11. Measurement of RK = G(Ke2)/G(Km2) • Introduction • Ke2 events counting • Study of direct emission in Ke2g • Results on RK Matteo Palutan, Ke2 at KLOE

  12. Ke2(g): signal definition SM prediction made in terms of IB process only: unobservable! IB SD IB+SD From theory (ChPT) expect SD ≈ IBfor Ke2,but experimental knowledge is poor IB dSD/SD≈15% 1) Consider as “signal” events with Eg<10 MeV (SD negligible) 2) Correct for IB tail, eIB=0.9375(5) Matteo Palutan, Ke2 at KLOE

  13. Analysis basic principles 1) Select kinks in DC (≈ fiducial volume ) - K track from IP - secondary with plep>180 MeV reconstructed kink in DC for decays occurring in the FV, the reconstruction efficiency is ≈ 51% no tag required 2) No tag required on the opposite hemisphere (as we usually do!) gain ×4 of statistics Matteo Palutan, Ke2 at KLOE

  14. Analysis basic principles 3) Exploit tracking of K and secondary: assuming mn = 0 get M2lep Km2 Kp2 Ke2 (Eg<10MeV) around M2lep=0 we get S/B = 10-3 Ke2 (Eg>10MeV) M2lep (MeV2) Matteo Palutan, Ke2 at KLOE

  15. Background rejection (track quality) Bkg composition: Km2 events with bad pK, plep reconstruction • quality cuts for K: exploit • fKK 2-body kinematics • require good quality vertex and secondary track (χ2 cut) • reduce Km2 tails cutting on the expected error on M2lep (from track parameters) Matteo Palutan, Ke2 at KLOE

  16. Background rejection (track quality) after cuts, we accept ≈35% of decays in the FV MC Km2 most of Ke2 events lost have bad resolution before cuts after cuts MC Ke2 S/B = 1/20 not enough! M2lep (MeV2) Matteo Palutan, Ke2 at KLOE

  17. Background rejection (PID) MeV 1) Particle ID exploits EMC granularity: energy deposits into 5 layers in depth 200 MeV electron • cluster depth • RMS of plane energies • asymmetry of first (last) two energy releases • skewness of cell-depth distribution • E1, Emax, Nmax • DE/Dx MeV 200 MeV muon 2) Add E/P and TOF 4.4 cm Matteo Palutan, Ke2 at KLOE

  18. Background rejection (PID) Combine PID variables using a NN data KLe3 MC KLe3 Use a pure sample of KLe3 to correct cell response in MC and for NN training NNout Matteo Palutan, Ke2 at KLOE

  19. Background rejection (PID) Select a region with good S/B ratio in the M2lep – NNout plane NNout NNout 1 0.8 0.6 0.4 0.2 0 -0.2 Ke2 Km2 -10000 0 10000 M2lep (MeV2) M2lep (MeV2) after selection: e = 30% (≈15k Ke2) S/B ≈ 5 Matteo Palutan, Ke2 at KLOE

  20. Ke2 event counting Two-dimensional binned likelihood fit in the M2lep – NNout plane NNout ev/700 MeV2 NNout χ2= 50/48 Ke2+ M2lep (MeV2) M2lep (MeV2) 0.85% from Ke2 count 7060 (102) Ke2+ 6750 (101) Ke2- sstat= 1% Matteo Palutan, Ke2 at KLOE

  21. Ke2 event counting Two-dimensional binned likelihood fit in the M2lep – NNout plane ev/700 MeV2 NNout χ2= 168/192 Ke2+ M2lep (MeV2) M2lep (MeV2) Vary significantly (×20 ) bkg contamination + lever arm to assess fit systematics Matteo Palutan, Ke2 at KLOE

  22. Ke2 event count: fit stability RK pulls min(NNout) We change by a factor of 20 the amount of bkg falling in the fit region by moving - min(NNout) - max(M2lep) Signal counts change by 15% min bkg From the pulls of the RK measurement we evaluate a 0.3% systematic error max bkg max(M2lep) (MeV2) Matteo Palutan, Ke2 at KLOE

  23. Ke2 fit: radiative corrections The analysis above is inclusive of photons in the final state • in our fit region we expect Km2 PID>0.98 Ke2 (Eg>10MeV) ≈ 10% Ke2(Eg<10MeV) Ke2 • repeat fit by varying Ke2 (Eg>10MeV) Ke2 (Eg>10MeV) by 15% (SD uncertainty): get 0.5% error…too large M2lep (MeV2) • Need a dedicated study of the Ke2 (Eg>10MeV) component Matteo Palutan, Ke2 at KLOE

  24. Measurement of RK = G(Ke2)/G(Km2) • Introduction • Ke2 events counting • Study of direct emission in Ke2g • Results on RK Matteo Palutan, Ke2 at KLOE

  25. Ke2g process Dalitz density helicity suppressed negligible Structure Dependent fV , fA : effective vector and axial couplings SD+ = V+A : g polarization + SD− = V−A : g polarization − Matteo Palutan, Ke2 at KLOE

  26. Dalitz plots for SD+ and SD− pe (MeV) pe (MeV) SD+ SD− Eg (MeV) Eg (MeV) n e+ n e+ g g electron peaks at 100 MeV: very bad, since Ke3 endpoint is 230 MeV electron peaks at 250 MeV, e-g antiparallel Matteo Palutan, Ke2 at KLOE

  27. Ke2g: theory predictions 1) ChPT at O(p4): fV ≈ 0.0945 fA ≈ 0.0425 no dependence on photon energy Bijnens, Ecker, Gasser Nucl. Phys. B396 (1993) from Phys. Rev. D77 014004 2) ChPT at O(p6): fV ≈ 0.082(1+λ(1-x)) fA ≈ 0.034 V linear x dependence (λ≈0.4) Chen, Geng, Lih, Phys. Rev. D77 (2008) 014004 3) LFQM: non trivial x dependence fV = fA = 0 at x=0 Chen, Geng, Lih, Phys. Rev. D77 (2008) 014004 Matteo Palutan, Ke2 at KLOE

  28. Ke2g selection: photon detection • A photon is required with energy Egcalo > 20 MeV to reject bkg (we loose Ke2IB, too) • Time of arrival compatible with that of the event (electron): (r = distance from K decay vtx) Km2 Kp2 Ke2g Dteg/s Dteg/s Dteg/s • from p0 • b(p+) ≈ 0.8 instead of 1 Fake g from accidental bkg Matteo Palutan, Ke2 at KLOE

  29. Ke2g selection After photon detection bkg is dominated by data Ke3 Ev/(4000 MeV2) • Km2 in the low M2lep region Km2 Ke2 (Eg>10MeV) • Ke3 for M2lep > 20000 pe >200MeV pe <200MeV No sensitivity for Ke2g with pe<200 MeV (SD− amplitude) M2lep (MeV2) Matteo Palutan, Ke2 at KLOE

  30. Ke2g selection: photon matching 1) Eg evaluated from the kinematics of Ke2g decay, using: pK, pe and photon direction ng 12 MeV resolution Ke2g (scalo ≈ 30 MeV) Ke3 2) is very useful as a discriminating variable against background DEg/s Matteo Palutan, Ke2 at KLOE

  31. Ke2g event counting Fit projections on M2lep axis • Two-dimensional binned likelihood fit in the 100< Eg<150 MeV data Ke2g (Eg>10 MeV) M2lep – DEg/s plane Km2 Ke3 5 bins of Eg: (10, 50) (50,100) (100,150) (150,200) (200,250) 30000 150< Eg<200 MeV • Most populated bins data Ke2g (Eg>10 MeV) 100< Eg<150 MeV: N = 463 ± 32 χ2 = 87/106 Km2 Ke3 150< Eg<200 MeV: N = 494 ± 38 χ2 = 100/106 30000 M2lep (MeV2) Matteo Palutan, Ke2 at KLOE

  32. Ke2g event counting Fit projections on DEg/s (all Eg bins together) according to M2lep, we show separately regions dominated by signal and bkg data fit Km2 Ke3 data fit Km2 Ke3 DEg/s DEg/s In total, we count Ne2g = 1484 ± 63 Matteo Palutan, Ke2 at KLOE

  33. Ke2g spectrum vs ChPT O(p4) We measure: data ChPT O(p4) χ2=5.4/5 Data are compared with ChPT O(p4) calculation Integrating we obtain: Eg (MeV) in agreement with 1.447×10-5 of ChPT O(p4) This confirm the SD content of our MC, evaluated with ChPT O(p4), within the achieved accuracy, 4.6%, and allows to assess a 0.2% systematic error on Ke2IB Matteo Palutan, Ke2 at KLOE

  34. Ke2g spectrum: fit to ChPT O(p6) data fit χ2=1.9/3 • We fit our data to extract fV+fA (SD+),allowing for a slope of the vector ff • fV = fV0 (1+λ(1-x)) • Since we are not sensitive to the SD− amplitude (acceptance≈2%) we keep fV-fA fixed to the ChPT O(p6) prediction We obtain fV0+fA = (0.125±0.007) Eg (MeV) λ = 0.38 ± 0.21 Compare to ChPT O(p6) , fV0+fA ≈ 0.116 Phys. Rev. D77 (2008) 014004 Matteo Palutan, Ke2 at KLOE

  35. Ke2g spectrum vs LFQM The spectrum predicted by the Light Front Quark Model is excluded by our data, χ2=127/5 Eg (MeV) Matteo Palutan, Ke2 at KLOE

  36. Measurement of RK = G(Ke2)/G(Km2) • Introduction • Ke2 events counting • Study of direct emission in Ke2g • Results on RK Matteo Palutan, Ke2 at KLOE

  37. Reconstruction efficiencies We use MC, with corrections from data control samples 1) kink reconstruction (tracking): K+e3 and K+m2 data control samples selected with tagging and additional criteria based on EMC info’s only (next slide) 2) cluster efficiency (e, m): KL control samples, selected with tagging and kinematic criteria based on DC info’s only 3) trigger: exploit the OR combination of EMC and DC triggers (almost uncorrelated); downscaled samples are used to measure efficiencies for cosmic-ray and machine background vetoes we obtain: e(Ke2)/e(Km2) = 0.946±0.007 Matteo Palutan, Ke2 at KLOE

  38. Control samples for tracking efficiencies Just an example: selection of K+e3 control sample to measure tracking efficiency for electrons 1) Tagging decay (Km2 or Kp2): reconstruction of the opposite charge kaon flight path Tag(Km2) Matteo Palutan, Ke2 at KLOE

  39. Control samples for tracking efficiencies Just an example: selection of K+e3 control sample to measure tracking efficiency for electrons 1) Tagging decay (Km2 or Kp2): reconstruction of the opposite charge kaon flight path Tag(Km2) 2) A p0->gg decay vertex is reconstructed along the K decay path, using TOF g g Matteo Palutan, Ke2 at KLOE

  40. Control samples for tracking efficiencies Just an example: selection of K+e3 control sample to measure tracking efficiency for electrons 1) Tagging decay (Km2 or Kp2): reconstruction of the opposite charge kaon flight path Tag(Km2) 2) A p0->gg decay vertex is reconstructed along the K decay path, using TOF e 3) Electron cluster required; pe estimated from a kinematic fit with constraints on E/p, TOF, re and Emiss− Pmiss g g We evaluate the K + electron kink reconstruction efficiency Matteo Palutan, Ke2 at KLOE

  41. Control samples for tracking efficiencies pe(fit)-pe(reco) (MeV) pm(fit)-pm(reco) (MeV) with a similar method, we get s ≈ 7 MeV for muon tracks s ≈ 19 MeV Matteo Palutan, Ke2 at KLOE

  42. Systematics and checks Cross-checkon efficiencies: use same algorithms to measure Rl3 = G(Ke3)/G(Km3) Rl3 = 1.507 ± 0.005 for K+ Rl3 = 1.510 ± 0.006 for K− SM expectation (FlaviaNet) Rl3 = 1.506± 0.003 Summary of systematics: Tracking Trigger syst on Ke2 counts Ke2g SD component Clustering for e, m 0.6%K+ control samples 0.4%downscaled events 0.3%fit stability 0.2%measurement on data 0.2%KL control samples Total Syst 0.8% 0.6% from statistics of control samples Matteo Palutan, Ke2 at KLOE

  43. RK : KLOE result RK = (2.493 ± 0.025 ± 0.019)×10−5 Total error 1.3% = 1.0%stat + 0.8%syst 0.9% from 14k Ke2 + bkg subtraction dominated by statistics • The result does not depend upon the kaon charge: K+: 2.496(37) vs K+: 2.490(38) uncorrelated errors only • Our measurement agrees with SM prediction, RK = 2.477(1)×10−5 Matteo Palutan, Ke2 at KLOE

  44. RK : world average PDG2008 PDG 2008: Clark, 1972 RK = (2.45 ±0.11) × 10-5 4.5% accuracy Heard, 1975 Heintze, 1976 NA48/2 (2003) New world average: NA48/2 (2004) RK = (2.468 ±0.025) × 10-5 SM 1% accuracy KLOE Matteo Palutan, Ke2 at KLOE

  45. RK : sensitivity to new physics Sensitivity shown as 95% CL excluded regions in the MH - tanb plane, for different values of the LFV effective coupling, D13 = 10−3, 5×10−4, 10−4 KLOE Matteo Palutan, Ke2 at KLOE

  46. Conclusions Using 2.2 fb-1 of data acquired at the f peak, we measured RK = (2.493 ± 0.025stat ± 0.019syst)×10−5 This result confirms the SM prediction within the 1.3% accuracy, and has been used to improve the constraints on the parameter space of the MSSM with lepton flavor violation We also presented today the first measurement of the decay spectrum in a region dominated by SD Results are in good agreement with expectations from ChPT Matteo Palutan, Ke2 at KLOE

  47. Km2: sensitivity to new physics Scalar currents, e.g. due to Higgs exchange, affect K mnwidth [Hou, Isidori-Paradisi] Rl23=1 in SM we find Rl23= 1.008 ± 0.008 limited by lattice uncertainty on f+(0) and fK/fp Matteo Palutan, Ke2 at KLOE

  48. KLOE measurement of kaon parameters KS e3PLB 636 (2006) 173 KS  pp EPJC 48 (2006) 767 KS  gg JHEP 05(2008) 051 KL decay distribution (t)PLB 626 (2005) 15 KL decays and lifetime PLB 632 (2006) 43 KL p+p-PLB 638 (2006) 140 KL ggPLB 566(2003) 61 K0mass JHEP 12(2007)073 KLe3g EPJC 55 (2008) 539 ff KLe3PLB 636 (2006) 166 ffKLm3JHEP 12(2007)105 K+m2PLB 632 (2006) 76 K+ lifetime JHEP 01(2008)073 K+l3JHEP 02(2008)098 K+t’ PLB 597 (2004) 139 K+p2PLB 666 (2008) 305 KS BRs KL BRs lifetime FFs K±BRs lifetime KLOE Vus JHEP 04(2008)059 Matteo Palutan, Ke2 at KLOE

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