1. Update on diffuse extraterrestrial neutrino flux search with 2000 AMANDA-II data Jessica Hodges, Gary Hill, Jodi Cooley This version of the presentation has been expanded to include work done after the meeting – where part of the nch problem was found to be related to no cross-talk cleaning in the cascade fit

2. Review of previous work Jodi Cooley’s thesis work – presented Mons October 2003  Basic quality cuts  2-D cut against coincident muons  2-D cut against nch>50 and positive smoothness – likelihood ratio track/shower vs ldirc  2-D on cogz versus l.r. track/shower  model rejection potential optimised on nch

3. Review of previous work  Cuts developed on 50% of data  After nch>80 cut – 6 events on atmospheric background of 3.3  Second 50% of data yielded 4 events  Combined 100% data  nch>87 – 9 events on atmospheric background of 4.5  One event believed to be a coincident muon  What does this excess mean?

4. New developments  Reinvestigation of coincident muons using new dcorsika simulations  Discovery that the nch>50, positive smoothness cut isn’t justified (which was suggested by others earlier!)  Very recently started checking things with second 50% data, but only for nch less than 80 (less than where the cut would be)

5. The 50<nch<80, positive smoothness problem  Jodi noticed a bump in the nch distribtion above 50 channels

6. The 50<nch<80, positive smoothness problem  nch>50, big excess at positive smoothness

7. The 50<nch<80, positive smoothness problem  nch>50, big excess at positive smoothness

8. First half of data set ldirc versus l.r. track/shower

9. First half of data set ldirc versus l.r. track/shower

10. Second half of data set ldirc versus l.r. track/shower

11. Second half of data set ldirc versus l.r. track/shower

12. Summary of the 50<nch<80, positive smoothness problem  Expect 14.1 atmospheric neutrinos  First half data – 35 events  Second half data – 15 events  After cut – expect 8.2 atmos  First half data – 9 events  Second half data – 7 events

13. Summary of the 50<nch<80, positive smoothness problem DataAtmospheric neutrinos TotalPassFailTotalPassFail 1.3592614.18.25.9 2.157814.18.25.9 F.50163428.216.411.8

14. Summary of the 50<nch<80, positive smoothness problem DataAtmospheric neutrinos TotalPassFailTotalPassFail 1.3592614.18.25.9 2.157814.18.25.9 F.50163428.216.411.8

15. Summary of the 50<nch<80, positive smoothness problem  26 events on 5.9 is quite a fluctuation  34 events on 10.8 is as well….  ….even accounting for all the plots I’ve looked at in my life

16. Second half nch plot

17. First half nch plot

18. Full year nch plot Still a bump in the full year

19. Full year smoothness plot Still an excess at positive smoothness

20. Examine the 34 events  Look at distributions, both 1 and 2 dimensional  See if any of the events lie in “bad” corners of the cut space – indicative of background

21. line fit velocity Excess at slow velocities

22. smoothness, ndirc Excess at largest smoothness Excess at largest ndirc!

23. likelihood ratios, up/down, track/shower Maybe trend to lower ratios Tendency to lower ratios as seen already

24. ldirc, ldirb Nothing obviously bad

25. Cosine zenith, nch Maybe less vertical than expected Higher nch as observed already

26. Distributions of the 34 events Looks ok

27. Distributions of the 34 events Maybe a pileup toward low speed and high smoothness

28. Distributions of the 34 events No obvious disagreement

29. My conclusions about nch>50, positive smoothness  Some of the 34 events are some kind of unsimulated background, some are good track events  The difference between the two data halves is certainly a fluctuation on these underlying distributions  Hard to imagine a periodic signal that just happens to coincide with our data separation by file numbers

30. My conclusions about nch>50, positive smoothness  Some of these events are very nice tracks with long direct lengths  Eliminate the original cut – maybe look at cutting on line fit velocity vs smoothness  Tighten other cuts  Good events will survive to higher levels  Bad events will get eliminated elsewhere  See what happens in subsequent years

31. Passing rates with tightened cuts  Start with cuts just described  Tighten gradually until events disappear  Examine passing rates of data and simulation

32. Passing rates with tightened cuts  l.r. up to zenith-weighted downgoing fit - jkchi(12)-jkchi(11) = 35 - 53  ldirb(11) = 10 - 28  ndirc(11) = 155 - 200  | smootallphit(11) | = 0.275 - 0.05  10 cut sets defined (40 - 49)

33. First half data vs cut level

34. Second half data vs cut level

35. Total data vs cut level

36. Limit setting potential versus cut level E 2  (E) < 2.35  10 -7 GeV -1 cm -2 s -1 sr -1

37. The cut against coincident muons  Original cut: slope 18  New cut: slope 4

38. The cut against coincident muons  Original cut: slope 18  MRF : 0.2348

39. The cut against coincident muons  New cut: slope 4  MRF : 0.2379

40. Outlook for the 2000 diffuse analysis  Some sort of weird effect was seen in the 1 st 50%, but not in the 2 nd  Eliminate the problematic cut  Tighten cut against coincident muons

41. Explanation of one part of the nch>50, positive smoothness problem  Clue (Doug Cowen) – cascade fit is very sensitive to noise hits  If the Monte Carlo and data have slightly different noise, then a cascade fit comparison might not make sense

42. The cascade fit was performed before the cross talk filter was applied!  Cascade fits on data have been done with all the cross talk present  Monte Carlo contains no cross talk  Likelihood ratios based on different hit selections make no sense

43. track/shower l.r. before nch>50 cut Dramatic improvement in the agreement of this variable!

44. Bump in nch, correlates with excess at positive smoothness

45. track/shower l.r., ldirc vs t/s l.r. for nch>50, positive smoothness

46. Same plots, with consistent cross talk cleaning

47. Data and simulation now agree! (in shape)

48. Where they did not before

49. Place a new cut – data and atmos neutrinos are now both split about 50:50 about this cut

51. Place a different cut – excess now shows up in corner, but that’s where the E -2 is more prevalent…

53. Examine the 22 events in the corner

60. Scanning of the events inside the green circle reveals some indication of residual cross talk – a classic “string 9/10 event”

62. New conclusions  Once the cascade fit is correctly performed using the cross talk filtering selection, the excess of events at nch>50 and positive smoothness moves to the low l.r. / low ldirc corner of the 2D plot - which could be indicative of background  However, this is the region where the E -2 signal prediction is expected to cluster  We cannot cut this region away!