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Ke2 and Kmu2 Mengkai Shieh Northwestern University.

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Presentation on theme: "Ke2 and Kmu2 Mengkai Shieh Northwestern University."— Presentation transcript:

1 Ke2 and Kmu2 Mengkai Shieh Northwestern University

2 Pisa 17-9-03 M. Shieh, Northwestern University Physics Motivation Measure Br Ratio of Ke2 more precisely Measure Br Ratio of Ke2 more precisely Test Lepton Universality Test Lepton Universality

3 Pisa 17-9-03 M. Shieh, Northwestern University Data Sample Eventually, full run based on Ke2 and Kmu2 triggers Eventually, full run based on Ke2 and Kmu2 triggers Today, only Monte Carlo and data based on minimum bias run (only Q1 trigger) so no trigger issues. Today, only Monte Carlo and data based on minimum bias run (only Q1 trigger) so no trigger issues.

4 Pisa 17-9-03 M. Shieh, Northwestern University Initial Cuts 1 track 1 track 1 cluster 1 cluster e/p > 0.9 e/p > 0.9 HAC Energy < 10 GeV HAC Energy < 10 GeV LKR Energy > 2 GeV LKR Energy > 2 GeV 2 GeV< track p < 80 GeV 2 GeV< track p < 80 GeV Track and cluster correspond Track and cluster correspond Fiducial cuts 12cm < r < 110cm Fiducial cuts 12cm < r < 110cm 5 sigma timing cut 5 sigma timing cut

5 Pisa 17-9-03 M. Shieh, Northwestern University Tuning of Cuts Look at Monte Carlo results Look at Monte Carlo results Maximize signal events Maximize signal events Minimize background Minimize background K->pi0ev(Br 5%)K->pi0ev(Br 5%) K->pipi0(Br 21%)K->pipi0(Br 21%)

6 Pisa 17-9-03 M. Shieh, Northwestern University Monte Carlo Results Ke2 (signal), Br: 1.55 X 10-5 Ke2 (signal), Br: 1.55 X 10-5 Ke3 (background), Br: 0.05 Ke3 (background), Br: 0.05 Kpipi0 (background), Br: 0.21 Kpipi0 (background), Br: 0.21 Kmu2 (normalization) Kmu2 (normalization)

7 Pisa 17-9-03 M. Shieh, Northwestern University Ke2, Ke3 MC Vertex Ke2 acceptance relatively flat, Ke3 drops sharply. Ke2 acceptance relatively flat, Ke3 drops sharply. Can use vertex to make a good cut. Can use vertex to make a good cut.

8 Pisa 17-9-03 M. Shieh, Northwestern University Ke2, Ke3 MC p T Can cut for pt > 0.2 Can cut for pt > 0.2

9 Pisa 17-9-03 M. Shieh, Northwestern University Ke2, Ke3 MC M fake Mfake calculated with electron mass Mfake calculated with electron mass Can cut for Mfake > 0.45, Mfake 0.45, Mfake < 0.525

10 Pisa 17-9-03 M. Shieh, Northwestern University Ke2, Ke3 MC p e Can cut on electron p Can cut on electron p Ke3 gone for p > 52 GeV Ke3 gone for p > 52 GeV

11 Pisa 17-9-03 M. Shieh, Northwestern University 2-Dimensional Cuts Look at 2-Dim acceptance plots to determine cuts for maximizing signal events while effectively cutting out the background. Look at 2-Dim acceptance plots to determine cuts for maximizing signal events while effectively cutting out the background.

12 Pisa 17-9-03 M. Shieh, Northwestern University Acc vert vs Acc pt

13 Pisa 17-9-03 M. Shieh, Northwestern University Acc vert vs Acc Mfake

14 Pisa 17-9-03 M. Shieh, Northwestern University Kpipi0 MC p T

15 Pisa 17-9-03 M. Shieh, Northwestern University Kpipi0 MC M fake

16 Pisa 17-9-03 M. Shieh, Northwestern University Kpipi0 MC p pi

17 Pisa 17-9-03 M. Shieh, Northwestern University Data Tuning Tuning Minimum bias runsMinimum bias runs 25 Aug 2003. Vus run 25 Aug 2003. Vus run ------------------------- ------------------------- Runs 15746, 15747. Runs 15746, 15747. Intensity 1/8, trigger Q1/4. Intensity 1/8, trigger Q1/4. Total of 1860 bursts. Total of 1860 bursts. Future Ke2, Kmu2 triggers Future Ke2, Kmu2 triggers

18 Pisa 17-9-03 M. Shieh, Northwestern University Extra Cuts (vertex>2000||pt>.2)&&mfake>0.45 &&mfake 2000||pt>.2)&&mfake>0.45 &&mfake<0.525&&pt<.25 Acc for Ke2 =.511 Acc for Ke2 =.511 Acc for Ke3 = 0 Acc for Ke3 = 0

19 Pisa 17-9-03 M. Shieh, Northwestern University Data

20 Pisa 17-9-03 M. Shieh, Northwestern University Data

21 Pisa 17-9-03 M. Shieh, Northwestern University Data/Conclusion flux and trigger efficiency cancel flux and trigger efficiency cancel We get N e and   from the data and acceptances from the Monte Carlo. We get N e and   from the data and acceptances from the Monte Carlo. Left and right sides are not equal, therefore, we still have background that we need to eliminate. Left and right sides are not equal, therefore, we still have background that we need to eliminate. If we use the more rigid cuts instead of the looser box cut for vertex and pt (vertex>2000 && pt>.2), we get the following values: N_e=10, acc_e=.296, and above equation becomes: If we use the more rigid cuts instead of the looser box cut for vertex and pt (vertex>2000 && pt>.2), we get the following values: N_e=10, acc_e=.296, and above equation becomes: right side=.96x10^-5, left side=1.7x10^-5 May need to investigate pipi0 more to make a better selection. May need to investigate pipi0 more to make a better selection.


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