Ramblings About TDCPV in B 0   o  (and a mention of B 0  K 0 S  0  ) BaBar Physics Workshop July Bruce Schumm UCSC/SCIPP

Contention: Physics can never produce |S|>1 or |C|>1. If either of these happen to be maximal, and you don’t have enough sensitivity to distinguish them from 0, you are not doing physics. How well might we do? TDCPV dictated by

BELLE’s sample of 48  14 events led to C =  0.49(stat)  0.14(syst) S =  0.65(stat)  0.18(syst) Can distinguish S=1 from S=0 at ~90% CL; somewhat better for C Benchmark: BELLE arXiv: v2 [hep-ex] 27 Feb 2008 SIGNAL

BaBar Not-Yet Public  0  Result (from an analysis optimized for  ) BaBar  0  fit yield: 35  9 (3.9  ) Compare to BELLE’s 48  14 (3.4  ); BaBar has greater significance. So we should do a little better…? 0000

Back of The Envelope Assume: N = 30 background-free events (as opposed to N = 35  9) Charge-determination dilution factor of D = 0.35 I get for time-integrated asymmetry A (is this right?)  A  1.0 – Not particularly good…

Idealized Toy Study (Joel Martinez) Assume N = 35 and no background All events tagged with lepton charge (D = ?)  C = 0.58  S = 1.10 Not too encouraging… why?

Idealized Toy Study – Gaussian Fit A little more encouraging… perhaps luck plays a role.  C = 0.46  S = 0.78

Higher statistics… assume N = 70 and no background All events tagged with lepton charge May not yet have reached the 1/  N limit; next step would be to optimize S/B for this measurement.  C = 0.31  S = 0.56

Higher Statistics Gaussian Fits Distributions have become more Gaussian  C = 0.31  S = 0.56

B 0  K 0 S  0  See BELLE arXiv: v1 [hep-ex] 12 Jun 2008 C eff = 0.05  0.18(stat)  0.06(syst) S = 0.11  0.33(stat)  0.08(syst) after removing K *  from K 0 S  0  (requires measuring rates and estimating relative phase from data  additional subtelty Also, b  s  suppression ~20 times less than b  d   less exciting place to look