B.Sciascia Kpm Meeting - LNF - February, 3 rd Charged kaon meeting LNF - February, 3 rd 2004 B.Sciascia TagBias  Bug on error calculation  Sensitivity with 8pb-1 MC K   2   -Tracking vs K- Tracking K  l3  Selection  Fit ......

B.Sciascia Kpm Meeting - LNF - February, 3 rd K     Tag Bias K      1.16  0.03  0.1  K     e   0.5  0.2  0.6  K        1.8  0.3  0.7  K  K    1.31  0.09  0.2  K  K    5.0  0.4  1.  K  K    18.4  0.2  0.7  K      1.15  0.03  0.1  K     e   0.8  0.2  0.6  K        1.2  0.3  0.7  K  K    1.1  0.09  0.2  K  K    4.5  0.4  1.  K  K    17.4  0.2  0.7  Tag K  Signal K  Tag K  Signal K  MC: 96 pb -1 (480 pb -1 of Data equiv.) MC: 8 pb -1 Run (40 pb -1 of Data equiv.)   -Tag   -Trg

B.Sciascia Kpm Meeting - LNF - February, 3 rd  -Tracking vs K- Tracking Reconstruction: FilFo   -Tracking  EvCl 1 (5 Algos)  “Kaon joining”  EvCl 2 (5 Algos)  K -Tracking Correlation (MC)   K + TagBias (MC)   K - TagBias (MC)    SELE (K  )  0.01   0.01   SELE (K + )  0.01   0.01  BR(K     )  0.04   0.04  BR(K +   + )  0.04   0.04   -Trk vs K-Trk Abs.Rel.  BR(K - )  0.75   BR(K + )  0.75  Systematics: to be studied

B.Sciascia Kpm Meeting - LNF - February, 3 rd K l 3 selection (1) “Usual”  -Tag Track: - K TRK + V2 + d TRK + Good_Extrap. - p  (m  )  190MeV (2-body rejec.) - Asso. cluster  0 : - 2 not-asso cluster -  (  t) wrt VTX  1 ns - m  inv. mass ToF selection

B.Sciascia Kpm Meeting - LNF - February, 3 rd K l 3 Selection (2)

B.Sciascia Kpm Meeting - LNF - February, 3 rd All selected    -  tag  No AutoTrg

B.Sciascia Kpm Meeting - LNF - February, 3 rd “Pezzetto” effect Correction for e + e - only

B.Sciascia Kpm Meeting - LNF - February, 3 rd All selected:  -trig    tag   -Trg  MC K-K- K+K+ K e3 13.3%13.5% K3K3 12.5%12.7%

B.Sciascia Kpm Meeting - LNF - February, 3 rd Cluster smearing “Cluster+Vertex” smearing: K -  t  130ps = 60ps  115ps   K-Vtx  0.7cm K +  t  120ps = 60ps  104ps   K-Vtx  0.6cm Data MC Data MC smeared

B.Sciascia Kpm Meeting - LNF - February, 3 rd Fit to m 2 distribution (1) Input histograms

B.Sciascia Kpm Meeting - LNF - February, 3 rd Fit to m 2 distribution (2) Data: 20 Pb -1 (Run ) MC: stat. (96 Pb -1 )

B.Sciascia Kpm Meeting - LNF - February, 3 rd N kl3 /N tag stability Only DATA: Run (120 Pb -1 )

B.Sciascia Kpm Meeting - LNF - February, 3 rd Fit to K - m 2 distribution Data 2002 MC 2002 Check: Data = MC 2001; MC = MC 2002 BR( K -  0 e - ) = (4.84  0.06)  BR( K -  0  - ) = (3.30  0.06) 

B.Sciascia Kpm Meeting - LNF - February, 3 rd Fit to K + m 2 distribution Data 2002 MC 2002 Check: Data = MC 2001; MC = MC 2002 BR( K   0 e  ) = (5.06  0.06)  BR( K   0   ) = (3.29  0.06) 

B.Sciascia Kpm Meeting - LNF - February, 3 rd K l sample Data: 2002 MC: 2002

B.Sciascia Kpm Meeting - LNF - February, 3 rd “Efficiency” (1) MC  Tot  Trk+V+Ext r  2-body  Asso 00  ToF K - e3 13.3%22.5%85.8%93.0%82.5%89.6% K-3K-3 12.5%21.2%92.9%85.5%82.4%89.7% K + e3 13.4%22.6%85.7%93.2%82.5%89.7% K+3K+3 12.7%21.4%92.9%85.9%82.5%90.0%  Efficiency TIMES Acceptance  MC   -Tag   -Trg Tracking (see Vincenzo talk) Vertex (see Patrizia talk)  Trk-to-clu asso     ToF

B.Sciascia Kpm Meeting - LNF - February, 3 rd “Efficiency” (2)  Data 2002   -  tag, no autoTrg K - l3 K + l3 “dEdx game”? (see PaoloB talk)

B.Sciascia Kpm Meeting - LNF - February, 3 rd TagBias update Waiting for “New MC”: - Small sample (Run ) - HW+Tracking efficiencies (ready) -  on EMC (by A.A., C.B, M.T, and T.S., ready) -  and K on EMC (by M.A., C.B, M.T, and T.S., almost ready) Conclusions Efficiencies and Systematics... First check on Trk 1/Trk 2; EvCl 1/EvCl 2 difference K  semileptonic decay - Work in progress (Christmas-stop + AFS-stop) Data sample - Fit to m 2 distribution