d L /dz and  L : Results and Plans J. Thompson, A. Roodman SLAC MDI Meeting - July 22, 2005

2 Introduction Today: Present results as shown at PAC05 Elaborate on the details Lay out a “To Do” list for the future

3 Reminder Using dimuon events, we can measure: the z distribution of luminosity dL/dz the (actual) sizes of the beam spot in x and y as a function of z:  L x,  L y (account for resolution by measuring it in data; using estimated vertex error) A function of z,  * y Extract  * y,  z /2, z 0 from fit Extract  * y,  y,eff from fit

4 Assumptions The formulas just shown make a few assumptions:  * y =  * y,HER =  * y,LER magnetic waists are aligned with bunch crossing point z 0 = z 0,HER = z 0,LER

5 Typical dL/dz fit Data from June 9-25, 2004 Error bars are shown (tiny) Solid curve is best fit dL/dz; dashed curve is a Gaussian with width  z /2  2 /dof = 1.3  * y = 1.62 ± 0.04 cm  z = ± cm

6 Typical  L y (z) fit  L y extracted using 2  m bias correction (taken from MC), as are all results Data sample: January 6-19, 2004

7 Run 4 September 2003 July 2004 A couple  L y (z) data points missing (too high) Questions: A true upward trend? Source of discrepancy between methods?

8 Caution: Very correlated with  * y results, very sensitive to bias correction from MC Run 4

9 LxLx This measurement is done well in MC Are these numbers about what people expect? Run 4 From B. Viaud, C. O’Grady, W. Kozanecki PAC05 paper:

10 Another sample: more detail Adjacent bins early in Run 4 LxLx z

11 Final examples From late in Run 4 (note  L x (z) behavior) LxLx z

12 To Do Category 1: Stuff I should have already done 1.Find and fix the overall bias of 2  m on  L y 2.Figure out why the  L y (z) fits to hourglass MC do not work well 3.Better toy studies – both more sophisticated and more thorough Category 2: Explore these results 1.Fit correlations ~25% between sLx and sLy Make sure dL/dz fits are not being affected by bunch length changes (Witold suggested cross-checks months ago….) 2.Evaluate quantitative systematics due to bias correction (in progress) 3.Crosschecks: different binning in z (done—no changes), use only slices of , redo with  L x fixed, play with resolution function, SVT misalignment 4.Try to correlate some of the results we have with changes PEP-II made over the course of Run 4

13 To Do con’t 1.Rewrite fitting code (not sexy, but would probably help a lot of things) 2.Write documentation (a BAD) 3.Change assumptions? 4.Look at Run 5 data 5.Split fits by bunch number? 6.Suggestions? Category 3