Sep/15/ Search for   e/ K.Hayasaka(Nagoya U.) Belle Collaboration

Nara 2 Introduction Lepton Flavour Violating (LFV) process: forbidden in SM probe of new physics SUSY model predicts: most sensitive mode in the LFV decays. We SHOULD search for not only for   but also for  e. B ~ B ~

Nara 3 asymmetric collider cross s~110GeV 2 (bb):()=1.05:0.912  A B-factory is also a -factory! KEKB accelerator/Belle detector _ Peak Lum. 1.4x10 34 cm -2 s -1 Total Logged Lum. 288fb -1 asymmetric detector ID:eff. 87.5% e-ID:eff. 92.4%

Nara 4 Signatures of the Signal and of the BGs Signal Event – (e+)+(e+n) /   e ee  generic decay Expected BG Events – Bhabha process e e e e    ee generic decay e  –  process

Nara 5 Selection Criteria 2 charged tracks + more than 1  – signal side : 1 charged+1 photon – tag side : 1 charged+ n photons e-ID>0.9 & e-ID<0.1 restrict kinematical variables – momentum e,tag,,missing – polar angle e,tag,,missing – opening angle e-tag, e-, tag-missing – missing mass vs missing mom. analysis for 87fb -1 data sample   e ee  generic decay tag missing 1-1 prong

Nara 6 Nagoya Cut P miss vs m 2 miss  events have large missing mass signal MC  MC   ee e  charged particle 98% of the  bkg is removed.

Nara 7 All selections applied for signal MC events M e  and E resolutions 25.7/14.3MeV/c 2 +5 region 6.5% - Asymmetric Gaussian +1 /36.0MeV E=E e +E  -E M e = (P e +P  ) 2 ee MeMe EE # of events.

Nara 8 Blind Analysis Signal dominant region is masked. Masked!  BG :  MC Bhabha BG : data Shape of BG distribution is evaluated. Its height is decided with data distribution of the side-band region. side-band region

Nara 9 BG distribution (MC) Estimate BG distribution from  MC curve (Landau+Gauss) reproduce BG distribution by function

Nara 10 BG distribution (data) Estimate BG from MC and data data(side band) MCee 64 =613 Masked! profile plot curve (Landau+Gauss) MC ~

Nara events found. (# of estimated BG:64) 20 events survived in +5 region signal MC surviving data signal events dominate +5 - Final Candidates (  e) -

Nara 12 Evaluation of signal events fit by unbinned expanded maximum likelihood with signal and BG shape  s 0 =0,b 0 =20 Estimation for U.L. of s 90%CL  by Toy MC: generate events result – s 90 =3.8 events Branching fraction Br=s 0 /2N <3.8x10 -7 :detection efficiency N:total event number Signal yield : s 0 e-ID ineff. 0.01/0.02 ev. BG function 0.13 ev. Efficiency & Luminosity : 2N  Track rec. eff.2.0% Photon rec. eff.2.8% Selection criteria2.5% Luminosity1.4% Trigger eff.5.0% MC statistics0.2% Total6.8%

Nara 13 Search for    Almost same selection criteria as   e – for tag side track, require not to be  MainBG(  from -ID ineff.) Data (x ineff.)

Nara 14 Final Candidates (    ) 54 events survived in +5 region 1.71<M inv <1.82GeV/c 2 +5  signal MC - 11% fitting result(UEML) s=0 Evaluation for U.L. Br<3.1x10 including systemaric uncertaunties -

Nara 15 Conclusion & Summary Obtain BR UL’s with blind analyses. BG distributions are modeled well. Results are 10 times more sensitive than CLEO’s.    (86.3fb -1 ) N=7.87x observed events  =11% Br<3.1x10   e  (86.7fb -1 ) N=7.90x observed events  =6.5% Br<3.8x10 Phys. Rev. Lett. 92(2004) Preliminary result cf. Br<1.1x10 (CLEO)cf. Br<2.7x10 (CLEO)

Nara 16 Unbinned Extended Maximum Likelihood fit s:#signal,b:#BG S i :signal prob. of i-th event B i :BG prob. of i-th event N: #remaining events Search for s and b which maximize L we fit over 5 region

Nara 17 Belle detector Asymmetric detector: forward/backward KLM  detection for /K L ID:eff. 87.5% ECL  detection for e,eID:eff. 92.4%

Nara 18 Upper bound of cos miss-tag e e e e  matter  e missing Bhabha events restrict: cos miss-tag <0.99 more than a half of bhabha events removed