Jin Huang, Xin Qian For Transversity Analysis Meeting May 3, 2010

Transversity Analysis Meeting Jin Huang 2  After run list/cuts/variable adjustment ◦ DSA Asymmetry is very consistent ◦ Angular modulation became more consistent (not totally) ◦ The remaining difference is investigated during last week

 simpler to check DSA, which we start with  Using same method for both team ◦ Divide phi_h – phi_S to 100 angular bins ◦ For each bin, calculate raw asymmetry  A raw = (N + - N - )/ (N + + N - ) ◦ Then fit the DSA modulation  We found ◦ The difference remains ◦ Each team’s result is consistent with its own previous one  Therefore ◦ Good News: each team is self consistent, not likely a coding error ◦ Difference from low level of the analysis Transversity Analysis Meeting Jin Huang 3

 The phi_S, theta_S data had problem Transversity Analysis Meeting Jin Huang 4

 Both team are using their own copy of root files developed from original skim ones.  We found there is a problem on phi_S -> phi_S + pi affecting all transverse root files last October  A fix is applied blue team files in December ◦ It was correct  Another patch was generated for my copy of root files in January ◦ However, ~10% of run was not corrected in the patch Transversity Analysis Meeting Jin Huang 5

 Xin generated an updated patch for my copy of data  Multiple Check event by event  Confident no further problem on spin angles Transversity Analysis Meeting Jin Huang 6

 A_LT modulation with polarization correction Transversity Analysis Meeting Jin Huang 7

Transversity Analysis Meeting Jin Huang 8 Red: MLE Final Blue: Blue team Final Difference could be 40% of σ for 1 term fit 2 term fit is more consistent:

 The event list is very close  Method 1.Combine Spin States: Local Pair VS MLE  Results have difference  We know MLE is more sensitive to yield drifts  Believe Local Pair method is better for Pion analysis 2.Extract Angular Modulation: Angular Fit VS MLE  Believe to be large stat. (ex. (e’pi))  Indirectly tested on DSA  Tested for both 1 term 1D fit and 2 term 2D fit  Xin showed that at low stat. (ex. (e’K)), MLE have better statistic precision Transversity Analysis Meeting Jin Huang 9

 Raw SSA Based on very similar data set  Difference believed to be from different way combining local spin states Transversity Analysis Meeting Jin Huang 10

 Indirectly checked by fitting sin(phi_h±phi_S) on DSA: Transversity Analysis Meeting Jin Huang 11

 Difference on Method ◦ Blue team Fit method is better for Pion SSA analysis ◦ MLE method is better for Kaon SSA/DSA analysis ◦ Both MLE/Fit methods OK for DSA pion analysis  Difference on Cut/Run List ◦ Remove Extra 17 Problematic Runs (L1A/DMA/… problem) identified by blue team ◦ 8 Runs with low LT remain off from MLE run list. OK for blue team method (local pair with in these runs) ◦ Remove “LHRS pion rejecter response>0” cut  3~4% more event in statistic ◦ Other difference on Cut/Variable use are negligible Transversity Analysis Meeting Jin Huang 12