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Charged kaon lifetime

P. Massarotti. Charged kaon lifetime. Outlook. Length measurement: Resolution effects evaluation Fit error Angular checks Efficiency checks Time measurement: efficiency evaluation MC fit. 0.024. KLOE. Analysis status : length. t = (12.367 ±0.044 stat ± 0.065 syst ) ns.

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Charged kaon lifetime

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  1. P. Massarotti Charged kaon lifetime

  2. Outlook Length measurement: Resolution effects evaluation Fit error Angular checks Efficiency checks Time measurement: efficiency evaluation MC fit

  3. 0.024 KLOE Analysis status: length t = (12.367±0.044stat ±0.065syst) ns Weighted mean between t+andt- preliminary

  4. Point of Closest Approach The resolution functions given by the P.C.A. method are an underestimate of the correct resolution functions but these ones reproduct the corrept asimmetry. So we use as resolution functions The Gaussian given by the MonteCarlo true with the centres given by the P.C.A. method. With these resolution functions we can reproduce the different MonteCarlo lifetimes and we also obtain a smaller systematic given by the fit stability as a function of the range used: ± 32 ps

  5. Resolution checks: MC t+ measurements We weight MC proper time distribution to obtain differentlifetimes t+11=(10.998±0.058)nsc2 =1.17 Pc2 =28.9% t +12 = (12.019 ± 0.075) ns c2 =1.35 Pc2 =18.1% t + = (12.390 ± 0.059) ns c2 =1.06 Pc2 =39% t+13=(12.994±0.076)nsc2 =1.50 Pc2 =10.7% t +14 = (14.004 ± 0.084) ns c2 =1.64 Pc2 =6.7%

  6. nbins Nexpj = S Csmearij× ei × eicorr × Nitheo i = 1 To do: fit error We make the fit in the region between 15 and 35 ns. To fit the proper time distribution we construct an histogram,expected histo, between 12 and 45 ns. This is a region larger than the actual fit region in order to take into account border effects. The number of entries in each bin is given by theintegral of the exponential decay function, which depends on one parameter only,the lifetime, convoluted with theefficiency curve. A smearing matrix accounts for the effects of the resolution. We also take into account a tinycorrection to be applied to the efficiencygiven by the ratio of the MonteCarlo datalike and MonteCarlo kine efficiencies.

  7. What about the bin error ? We have calculated the error is given by: Is this over- or under-estimated? MC Toy to evaluate the correct error on the bin entries is needed

  8. Angular checks: • We have to evaluate the lifetime for two different angular windows: • Vertex between 75o and 105o • Vertex smaller than 75o or greater than 105o Efficiency checks: We have to evaluate the systematics given by the efficiency cuts

  9. Ep,xp,tp Eg,tg,xg p± xK pK lK Kmn tag tm t0 pK p0 Eg,tg,xg Time Strategy • Self triggering muon tag • Considering only kaon decays with a p0 K X p0 X gg we lookfor the neutral vertex asking • clusters on time: (t - r/c)g1 = (t – r/c)g2 • p0 invariant mass • agreement between kaon flight time and clusters time

  10. Time: Efficency comparison MonteCarlo kine vs MonteCarlo reco  fit window definition Fit window 10 : 40 ns MC reco MC kine

  11. Time: Data and MonteCarlo reco MC Data reco MC Data

  12. Time: MCmeasure between 18 and 37 ns t +MC = (12.319 ± 0.072) ns c2 =1.08 Pc2 = 36% T(ns) We have to evaluate data

  13. KLOE soccer tournament 2006 Neutral kaons Bossi Gatti Moulson Passeri Spadaro Charged kaons Branchini Massarotti Meola Patera Versaci Radiatives: Bini, De Santis, Nguyen, Venanzoni, Mr X

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