1. 1 Raghunath Ganugapati(Newt) && Paolo Desiati Event Topology Studies for detection of prompt muons in the down going muon flux IceCube Collaboration Meeting,March 23 rd,2005,Berkeley

2. 2 Detection With AMANDA-II Extra Terrestrial Neutrinos High energy spectrum hypothesis d  /dE œ E -2 Backgrounds Conventional Atmospheric µ d  /dE œ E -3.7 Conventional Atmospheric from decay of (π ±, K ± ) d  /dE œ E -3.7 Possible  components from decay of atmospheric charmed particles. d  /dE œ E -2.7

3. 3 Uncertainty in Prompt Lepton Cross Sections The uncertainty~3 orders Need for accelerator data extrapolation Crossover between 40TeV and 3 PeV ZhVd AMANDA II (neutrinos)

4. 4 Neutrino Vs Muon Fluxes Ref:GGV,hep-ph/0209111 v1 10 Sep 2002 Essentially same to ~100TeV at sea level Constraint on a prompt µ is equivalent to a constraint on prompt    Use down going muon data

5. 5 Analysis Description

6. 6 Signal Simulation Single µ with an assumed energy spectrum of prompt µ (RPQM) and isotropic in zenith and azimuth angle at the surface of the earth Standard AMANDA codes used for propagation and detector response. Charm-D model will also be used. Signal,Background Simulation and Data The conventional muons produced from the π ± and K ± decay is the B.G. CORSIKA 6.02 with the QGSJET01 model of hadron interactions and decay used. Background Data 70 days life time worth data taken by the AMANDA II during 2001 will be studied.

7. 7 Levels (L2 is the standard minimum bias data) Zenith Angle(L3) Event Quality Related(L4) Topology(single muon and a bundle of muons)(L5) Early Hit(Topology1) dE/dX method(Topology2) Energy(L6) Strategies for separation of Signal from Background

8. 8 Zenith distribution(L3) True track Reco Track Cos(zenith) B/S vs Cos(zenith) True track(S) Reco Track(S) Reco Track(BG) TrueTrack(BG) S/B ratio improves near the horizon Lots of misreconstructed muon near horizon Angular resolution very important to see enhancement of S/B near the horizon. Cut these out

9. 9 Quality Cuts(L4) Track Length(>120m) Distance between direct hits projected on to the length of the track Number of Direct Hit(>6) The more the number of direct hits the better the guess track and less likely to converge to a false minimum Reduced Chi square(<7.3) Chisquare computed using time residuals and divided by total number of hits Pre and Post hits (prehit<1.5 and posthit<1.5) Well reconstructed muon have very few hits that arrive later or before in time (Peter Stefan's dE/dX method) Singles Singles(after QC) Multiples Multiples(after QC) Angular Resolution Improve from 8 to 3.5 degrees

10. 10 Muon Bundles log10(energy at cpd) GeV Singles Multiples Signal The multiple muon background goes with same slope as the signal Need to improve the sensitivity Of our instrument to prompt muon

11. 11 Topology 1 (Early Hit)(L5) snapshot Cherenkov cone BCD from reconstructed track propagating in time relative to the tracks. Limitations Random Noise hits (3.0 photo electron cut) Misreconstructed single muon ( Good angular resolution vital ) Muon1 Muon2 Early Hit Reconstructed track A B Δθ The hit at B is earlier by time length(AB)/c ice C D

12. 12 Topology 1(Eview Earlyhits) Earlyhit Amplitude>3pe (proximity cut) (Noise Hits suppressed) Distance<50m (proximity cut) timedelay<-15ns Reconstructed Track Well reconstructed single muon should not have this Muon BundleSingle Muon (misreco)

13. 13 Time Residuals and Convoluted Pandel Time delay(16 PPandel)Time delay(64 CPandel) Excess Earlyhits in MC Data BG MC

14. 14 EarlyHits 0 degree 2 degree 5 degree Cut these out Does retain A decent bit of single muon Earlyhits 1 muon 2 3 4-10 10-25 25-50 Cut these Muon Multiplicity True Track(Ideal) Result (Reco Track) Filtering Efficiency(Topology 1)

15. 15 Topology 2 (Energy Deposition dE/dX)(L5)

16. 16 Hit Selection and Estimators(L5) Quality Cuts (already discussed) I choose only direct hits(-15ns to 75 ns)(less effected by ice properties) Use hits with in 50m radius cylinder around the track(less scattered) Take only hits with amplitude greater 3.0 P.E for reconstruction. Estimator1 B= Nphoton Observed Photon Nphoton expected from MIM Estimator1 gives Estimator2 y = σ B/

17. 17 Filtering Efficiency(L5) Result (Reco track) True track(Ideal) y = σ B/ Cut these out Signal BG

18. 18 Energy Cut(L6) Nhits(Energy Observable) 2001 exp data 2001 signal (RPQM)+BG BG Signal Integral Spectra Data Description Avg Upper limit 0% sys) 10% sys (20% sys) (30% sys) (40% sys) Best Cut Nhit=310,Signal=9.4,B.G=6 MRF=0.7(30%SYS) MRF Data observed=16 Signal Expectation (RPQM)=9.4 B.G Expectation=6.0 Event upper limit=22.4 MRF sim =0.70 (30% SYS) MRF data =22.4/9.4= 2.3(preliminary) Nhits(Energy Observable)

19. 19 Constraining Charm Neutrino models by analysis of downgoing Muon Data A Restrictive limit means enhance sensitivity to diffuse neutrinos AMANDA II (neutrinos) AMANDA II (muons) ZHVd

20. 20 BACK UP SLIDES

21. 21 Energy Correlation Number of Hits Vs log10(energy at cpd) GeV

22. 22 Note that the distribution of less than 3.0P.E. hits remains almost flat outside 50m. Could be noise?(Randomness) Why than does it fall down as we come close to the track? There is a pile up in amplitude for noise hits inside 50m from the track as the pulse from early noise hit gets smeared out with the actual hits from muons Greater than 3.0P.E hits Less than 3.0P.E hits Perpendicular distance from reconstructed track for BGMC muons(m) Good hits Random Hits ~10 times greater Amplitude-Perpendicular distance to the Hit space Δt<-15ns only Dump this space out

23. 23 Dust Clear Ice Reconstructed track in data True track Geometrical Effect Reconstructed track in simulation The Monte Carlo tracks are reconstructed away from the true track than in the data because of various assumptions and the way the time delay is calculated. The tracks are reconstructed pivoted about the centre of the detector so any discrepancies in timing tend to scale roughly as the distance from the centre and hence outer strings become more susceptible to the differences than the inner ones. Δθ Leverarm(AB)*Δθ A B

24. 24 Done with all hits (not just direct hits) Singles Multiples Keep These Filtering Efficiency(L5) When all hits are chosen notice what happens? Any possible separation of S-B is destroyed by the fluctuation of ice properties

25. 25 Amplitude-Time Residual space Amplitude(P.E) Data Background Data Background A projection of the amplitude for a region of space in time residual less than –15ns is shown; there appears to be some disagreement between the data and the simulation in the low amplitude regime. This bin(0-2 P.E) has significantly large number of hits compared with the other neighboring bins. What are these hits?Noise? Ignore these R2

26. 26 Ice Properties Ice properties themselves introduce some fluctuations into the observed amplitude Think what the optical properties of a dust layer could do to the Photo Electron recorded? May be need to apply corrections to the PE recorded depending on the layer of ice to retrieve information in original form to undo what ice does (for Horizontal muons this gets tricky!!!)

27. 27 Dust Clear Ice True track Δθ A B Reco Track Large Amplitude Seen when lower is expected from reco track hypothesis Small Amplitude Seen when large is expected from reco track hypothesis Reconstruction Errors

28. 28 Data Agreement(16fold-ppandel) Number of Hits Data B.G Signal The Overall Agreement is not extremely good within the limit of systematics (30-40%) A possibility to improve the scenario is to use a 64-iteration Convoluted Pandel and repeat the whole procedure described