2. Aneela Amin, Haris Rashid, Talab Hussain
Centre for High Energy Physics, University of the Punjab, Lahore, Pakistan
Charmonium Group Meeting, April 17, 2019

3. Outline
Overview
Motivation
Data Analysis
Results
Conclusions

4. Motivation
In this study we searched isospin and strangeness violating decay, which is highly suppressed but kinematically it is possible.
To find any hint beyond the Standard Model of Particle Physics.
This work is based upon the analysis of and try to measure its branching fraction using the large statistics at BESIII.

5. Initial Events Selection
Charged tracks
4 good tracks and |cos|<0.93.
Qi=0
PID
dE/dx and TOF information are combined to identify particles.
Pt > 0.5

6. Selection of after Vertex Fitting

7. Selection of after Kinematic Fitting

8. Optimized 2 MC
Data

9. Optimized 2

10. Final Event Selection

11. Final selection criteria

12. Invariant mass of MC & Data after selection criteria

13. Inclusive Backgrounds

14. Inclusive Background
Cont…

15. Inclusive Background
To suppress the channel
use
Data

16. Inclusive Background
To suppress the channel
use

17. Inclusive Background
To suppress the channel
use

18. Inclusive Background
To suppress the channel
use

19. Inclusive Background
To suppress the channel
use

20. Inclusive Background
To suppress the channel
use

21. Inclusive Background
To suppress the channel
use

22. Inclusive Background
To suppress the channel
use

23. Inclusive Background
To suppress the channel
use

24. Inclusive Background
To suppress the channel
use

25. Inclusive Background
To suppress the channel
use

27. Exclusive Background
To suppress the channel
use

28. Exclusive Background
To suppress the channel
use

29. Exclusive Background
To suppress the channel
use

30. Exclusive Background
To suppress the channel
use

31. Exclusive Background
To suppress the channel
use

32. Cont…

37. Initial Events Selection
4 good tracks and |cos|<0.93.
Qi=0
PID
dE/dx and TOF information are combined to identify particles.
Pt > 0.5

38. Selection of after Vertex Fitting

39. Selection of after Vertex Fitting

40. Selection of after Kinematic Fitting

41. Optimized 2

42. Optimized 2

45. Invariant mass of MC & Data after selection criteria

48. Cont…

52. Thanks

53. Distribution of Signal

54. Distribution of Signal for