1. Jin Huang, also for Xin Qian For Transversity Analysis Meeting Feb 20, 2010 @ JLab

2.  There are difference between red and blue team results ◦ ~70% points consist ◦ For problem points, discrepancy could be as large as 1 sigma ◦ Exist for both SSA and DSA, Asymmetry and Modulation  Xin and I have been hunting these discrepancy for the last week ◦ Cuts/Run Lists ◦ Method Transversity Analysis Meeting Jin Huang 2

3. Transversity Analysis Meeting Jin Huang 3 ~1σ Discrepancy:

4. Transversity Analysis Meeting Jin Huang 4 ~1σ Discrepancy:

5. 1. Run List 2. Cuts/Variable choice 3. Method Difference A.Combining Spin State  Blue: Super Local Pair  Red: One step MLE B.Form angular modulation  Blue: Angular Bin & Fit  Red: One step MLE Transversity Analysis Meeting Jin Huang 5

6.  Difference: ◦ Blue team excluded 20 more runs: Yield out 3σ of local average ◦ Red team excluded 3 more runs: w/ Low Life time due to PS mistakes or RICH tests  For following study: ◦ Use blue team run list for red team analysis Transversity Analysis Meeting Jin Huang 6

7.  Found 5 Difference in cuts / variable usage ◦ Red team cut on pion rejecter E/p>0 (e’pi) events  3~4% of total coincidence events  most of event difference ◦ pT cut, BB_ts_ps_e_c[i]>400 or BB_ts_ps_e[i]>400 ◦ Variable choice: Beam curent & edtp choice  For following study: ◦ Use blue team cuts/variable choices Transversity Analysis Meeting Jin Huang 7

8.  After the synchronization: ◦ Event sample difference no more than 10 -4  ◦ In the data set generating above plot  Red team excluded events during spin flip while blue team cut them out in later stage ◦ All but one event in Red Team sample is in Blue team’s ◦ Red team excluded more events around spin flips (2e-4 difference) Transversity Analysis Meeting Jin Huang 8

9.  Double spin asymmetry agree well now Transversity Analysis Meeting Jin Huang 9

10.  Better after run/cuts sync  Some difference remains for Single Spin Asymmetries  Method Difference ◦ MLE method is known more biased by yield drift than super local pair method in SSA ◦ Not problem the case for DSA Transversity Analysis Meeting Jin Huang 10

11. Transversity Analysis Meeting Jin Huang 11  After run list/cuts/variable adjustment ◦ As shown asymmetry is consistent for DSA. ◦ Angular modulation also became more consistent ◦ Some difference remains: under invesitagtions

12. Transversity Analysis Meeting Jin Huang 12  After run list/cuts/variable adjustment ◦ As shown asymmetry is NOT all consistent for SSA  Could be as large as 50% of σ for low x for pi- ◦ Angular modulation became more consistent in general ◦ Some difference remains  2 term fitting more consistent than 1 term fitting  See next two slides for plots

13. Transversity Analysis Meeting Jin Huang 13 Asymmetry also improved equal much for pi+ high x and low x bin: ~0.5σ Discrepancy on Asymmetry. Also equal Discrepancy on modulation:

14. Transversity Analysis Meeting Jin Huang 14 Points improved: >0.5σ Discrepancy:

15.  Run List/Cuts/Variable difference ◦ Responsible for most difference ◦ not a problem anymore  Method Difference ◦ Combining Spin State  not a problem for DSA  Local pair method has been expected to be better for SSA ◦ Form angular modulation  Under investigation (red team running angular fitting)  (expected) responsible for difference in DSA. Could also involve SSA discrepency Transversity Analysis Meeting Jin Huang 15