P Massarotti Charged kaon lifetime Paolo Massarotti Charged

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P. Massarotti Charged kaon lifetime Paolo Massarotti Charged Kaon Meeting 18 october 2005

P. Massarotti Charged kaon lifetime Paolo Massarotti Charged Kaon Meeting 18 october 2005

Sammary: ØEvents selection ØReconstruction efficiency Øt measure ØConclusions Paolo Massarotti Charged Kaon Meeting 18

Sammary: ØEvents selection ØReconstruction efficiency Øt measure ØConclusions Paolo Massarotti Charged Kaon Meeting 18 october 2005

Strategy Signal selection K • Self triggering muon tag • K track on the

Strategy Signal selection K • Self triggering muon tag • K track on the signal side • Decay vertex Signal K extrapolated to the IP. correction applied along the path. Kmn tag K Li m d. E/dx Li = step length Vertex efficiency and resolution functions needed wrt the proper time of the Kaon Paolo Massarotti Charged Kaon Meeting 18 october 2005 vtx

Why self-triggering tag? Tag self trg Tag eff Tag. Trg selfeff trg Paolo Massarotti

Why self-triggering tag? Tag self trg Tag eff Tag. Trg selfeff trg Paolo Massarotti Charged Kaon Meeting 18 october 2005

Definition of signal sample: • Cut at 100 Me. V on boost with 96%

Definition of signal sample: • Cut at 100 Me. V on boost with 96% efficiency 70% signal 30% “bg” (not kaon bg less than 0. 2 %) Daughter P* with kaon mass hypothesis Paolo Massarotti Charged Kaon Meeting 18 october 2005

Reconstruction Efficiency: Neutral vertex technique Considering only kaon decays with a p 0 K

Reconstruction Efficiency: Neutral vertex technique Considering only kaon decays with a p 0 K X p 0 Ep, xp, tp X gg We look for the vertex asking p. K tm Ø clusters on time: (t - r/c)g 1 = (t – r/c)g 2 Kmn tag x. K l. K t 0 p K Ø p 0 invariant mass p 0 Eg, tg, xg Ø agreement between kaon flight time and clusters time Paolo Massarotti p± Charged Kaon Meeting 18 october 2005

Efficiency measures e. G = e. Tr K e. Tr sec e. V 1

Efficiency measures e. G = e. Tr K e. Tr sec e. V 1 kaon • charged daughter 2 Paolo Massarotti Charged Kaon Meeting 18 october 2005

Efficency comparison Monte. Carlo kine vs Monte. Carlo reco fit window definition Fit window

Efficency comparison Monte. Carlo kine vs Monte. Carlo reco fit window definition Fit window 15 : 30 ns MC reco MC kine a. G = (101. 7 0. 7) x 10 -2 b. G = (-. 59 3. 6) x 10 -3 T (ns) Paolo Massarotti Charged Kaon Meeting T (ns) 18 october 2005

Method 2: tracking & vertexing a. Tr K = (96. 25 0. 32) x

Method 2: tracking & vertexing a. Tr K = (96. 25 0. 32) x 10 -2 b. Tr K = (. 98 . 14) x 10 -3 a. VTX = (101. 50 0. 41) x 10 -2 b. VTX = (. 83 . 20) x 10 -3 true MC reco MC true MC MC reco MC MC T (ns) Paolo Massarotti Charged Kaon Meeting T (ns) 18 october 2005

New efficency comparison new cuts to select neutral and charged vertex fiducial volume (40

New efficency comparison new cuts to select neutral and charged vertex fiducial volume (40 < r <150) cm , | z | < 150 cm MC reco MC kine Paolo Massarotti Charged Kloe Kaon general Meeting meeting 18 october 2005 28 october 2004

New efficency comparison Monte. Carlo kine vs Monte. Carlo reco larger fit window a.

New efficency comparison Monte. Carlo kine vs Monte. Carlo reco larger fit window a. G = (96. 0 0. 4) x 10 -2 b. G = (-. 65 1. 9) x 10 -3 Paolo Massarotti a. G = (94. 2 0. 8) x 10 -2 b. G = (-. 06 2. 3) x 10 -3 Charged Kaon Meeting 18 october 2005

Method 2: tracking efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window

Method 2: tracking efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window MC reco MC kine Paolo Massarotti Charged Kaon Meeting 18 october 2005

Method 2: tracking efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window

Method 2: tracking efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window a. TRK = (100. 4 0. 2) x 10 -2 b. TRK = (-. 19 0. 7) x 10 -3 Paolo Massarotti Charged Kaon Meeting a. TRK = (100. 0 0. 2) x 10 -2 b. TRK = (-. 8 0. 9) x 10 -4 18 october 2005

Method 2: vertexing efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window

Method 2: vertexing efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window MC reco MC kine Paolo Massarotti Charged Kaon Meeting 18 october 2005

Method 2: vertexing efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window

Method 2: vertexing efficency Monte. Carlo kine vs Monte. Carlo reco larger fit window a. VTX = (96. 3 0. 3) x 10 -2 b. VTX = (-. 48 . 17) x 10 -3 Paolo Massarotti Charged Kaon Meeting a. VTX = (94. 3 0. 6) x 10 -2 b. VTX = (-. 28 . 27) x 10 -3 18 october 2005

Two methods compared: MC a. Conf = (99. 3 0. 9) x 10 -2

Two methods compared: MC a. Conf = (99. 3 0. 9) x 10 -2 b. Conf = (. 17 . 39) x 10 -3 global product Paolo Massarotti Charged Kaon Meeting 18 october 2005

Two methods compared: Data aconf = (98. 9 0. 9) x 10 -2 bconf

Two methods compared: Data aconf = (98. 9 0. 9) x 10 -2 bconf = (. 21 . 39) x 10 -3 global product Paolo Massarotti Charged Kaon Meeting 18 october 2005

Data and Monte. Carlo compared reco MC Data Paolo Massarotti Charged Kaon Meeting 18

Data and Monte. Carlo compared reco MC Data Paolo Massarotti Charged Kaon Meeting 18 october 2005

Data and Monte. Carlo compared reco MC Data Paolo Massarotti Charged Kaon Meeting 18

Data and Monte. Carlo compared reco MC Data Paolo Massarotti Charged Kaon Meeting 18 october 2005

MC t measure and residual evaluation T+MC = (12. 36 ± 0. 03) ns

MC t measure and residual evaluation T+MC = (12. 36 ± 0. 03) ns Paolo Massarotti T+MC = (12. 36 ± 0. 07) ns Charged Kaon Meeting 18 october 2005

MC t measure and residual evaluation T-MC = (12. 36 ± 0. 03) ns

MC t measure and residual evaluation T-MC = (12. 36 ± 0. 03) ns Paolo Massarotti T-MC = (12. 37 ± 0. 07) ns Charged Kaon Meeting 18 october 2005

Conclusions We have efficiency studied decay reconstruction We have to complete the measure on

Conclusions We have efficiency studied decay reconstruction We have to complete the measure on data (smearing factors) Work is in measurement Paolo Massarotti progress Charged Kaon Meeting for the “time” 18 october 2005