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B s  D s K

B s  D s K. Steve Blusk, Liming Zhang, (& Sheldon, when he learns Gaudi, Python, RooFit…  ). Introduction. State of Affairs. g. SM?. l = sin q C  0.22; (A  0.8). |V ub /V cb | : Systematics limited, SM dominated |V td /V ts | : f B errors dominant, SM +NP

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B s  D s K

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  1. Bs Ds K Steve Blusk, Liming Zhang, (& Sheldon, when he learns Gaudi, Python, RooFit…)

  2. Introduction State of Affairs g SM? l= sinqC0.22; (A0.8) • |Vub/Vcb| : Systematics limited, SM dominated • |Vtd/Vts| : fB errors dominant, SM+NP • sin(2b): Exp. error dominant (SM + NP) • Need : • Accurate measurement of g with TREES only • Precise measurement of g in LOOPS (SM+NP) • Precise measurement of a (SM + NP) • Reduce theory errors.. • If h≠0  CP Violation • Since Vcb real & base=1, arg(Vub) = g

  3. Interference between direct decay and mixing+decay(4 time-dep rates) Bs± DsK± Direct decay Phase relativeto Direct decay fs g+d Vts t Vtb s W W t Vtb* Vts* |l| ~ 1 sin term dominates Both O(l3), with different weak (& strong phases)

  4. Bs± DsK±, continued • It can be shown: • Dms =17.77±0.11 ps-1 (CDF) can be (re)measured in LHCb using BsDsp, • DGs and fs can be measured in BsJ/yf (presumably, a separate measurement). • SM: DGs ~ 0.07 ps-1, fs ~ -0.04 • This leaves us with four unknowns: l, g, d, A, which can be determined. • Expect l~1  sin term dominates • Time-dependence in these four decays can vary dramatically depending on d±g • Additional factor for mistag rate, (1-2wBs), in front of cos, sin terms not shown

  5. Sketch of dependence on d

  6. Previous work Bs  Ds K • Access to g also via B+DK+ • depends on time-integrated ratesonly. • Several modes/analyses could givesg~ 5-13o, depending on D decaystrong phases (2 fb-1) • Would be nice to push the errorhere down below 10o . • Currently, we only consider DsKKp • Other Ds modes could add (Liming) • BsDs* K? (comes for “free” in thetrigger, depending on mass window) • Broad low mass bump • Can we deal with it? From LHCb-2003-103, s(g+fs)~13o

  7. Likelihood Fit devleopments • Now using RooFit  very flexible for complicated PDF’s (still on learning curve) • Implemented 2 multi-dimensional PDFs • BsDsp: mass*time*(mix or unmix) – two 2D PDFs: • BsDsK: mass*time*flavor tag(Bs/Bs)*Ds-flavor(Ds+/Ds-) – Four 2D PDFs • Mass, time each have signal term & background terms • Acceptance, mass resolution and time resolution included • Fit variables in PDF: • Common to BsDsp and BsDsK: DGs, Dms, tBs, wBs, MBs, s(MBs), st_ • Sample-dependent: g, d, acceptance & background pars in mass & time,

  8. Reconstruction Effects (on BsDsK) Similar for Dsp ~ 10 fb-1 of data ~6200 / year total ~54% tag eff w = 0.33

  9. BsDsp, Fit to Mixed Events ~0.4 fb-1

  10. BsDsK Toy Data from RooFit 6300 events/yr * 5 years B/S ~ 0.5 wBs = 0.334±0.010 eBs = 0.54±0.02 st = 42 fs • = 67o d = 20o Dms = 17.7±0.1 ps-1 DGs = 0.07±0.01 ps-1

  11. BsDsK Fit to Toy Data

  12. Work ongoing • Looking into other Ds decay modes (Liming) • Efficiency • Backgrounds • Can we use BsDs*K ? • Needs further investigation • Develop likelihood fit • Simultaneous fit for Dsp and DsK • First RooFit implementation seems to be working, but more robustness tests needed, pull distributions, etc.

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