1. Update on km3 Clancy James & MC Working Group KM3NeT General Meeting Catania, 21/02/2012

2. ANTARES/KM3NeT MC software tools Corsika Mupage Genhen km3mc TriggerEfficiency Neutrinos CC( e   ) NC(all ) CC  RECO GEASIM Background (K40) Physics simulation Detector response (simulation of hits) Simulation of background hits Trigger (DAQ) simulation Event reconstruction Detector model (gendet)  -proparation ( mum, music ) atm  fluxes (fluxnew) Input/output (iof77, iogcc )

3. km3mc chain km3mc read physics event and produce hits in detector OMs. Hits are produced based on event geometry and hit probability tables. gen generate the photon tables, for a single segment of 2 m length with GEANT 3. photon tables (hbook rz file) hit Calculate a hit probability from the photon tables for a OM parameters 5 tables are necessary for km3mc: 1) muons with E=100 GeV 2-5) electrons with E = 0.1, 1., 10, 100 GeV hit tables (hbook rz file) table description ( ASCII file) table description ( ASCII file ) Detector events (signal hits, background) Simulated events (geometry, kinematics) water modelOM parameters

4. New in v4r3 Current km3 version in ANTARES: v4r2 ‘fixed’ a ‘bug’ in km3 v3/v4 Can now use seawater Towards v4r3…

5. Reminder: gedanken experiments Standard geometry for case ‘B4’: Muon E = 1 TeV 1 PMT facing towards track 50 m track offset Repeat for 10 6 identical muon tracks Plot time-distribution of photon hits d = 50 m l = 100 m Direct Cherenkov photon path (430 nm) 74 m θCθCθCθC 45 m PMT

6. CHANGE OF BINNING Modification #1:

7. Problems with v4r2 from C. Kopper, Bamberg Strange ‘kink’ ‘faster than direct’ photons! (Look at the red lines!)

8. v3r[km3NET version] (Rosa, Rezo, Maarten) Case A3

9. Present in v3r9 also – but no kink! Also from C. Kopper, Bamberg

10. What goes wrong??? Histogramming! Step 1 (‘gen’) – generate photons incident on spheres of increasing radius. Step 2 (‘hit’) – bin the scattered photons in the theta-direction. Muon track (1 m length) Shell at radius r r (stolen from Goulven, Amsterdam, 2010)

11. Example of gen output These are scattered photons! (most scatters are small)

12. + binning of scattered photons by ‘hit’ Interpolate between bins to get hit times, probability etc ‘low’ bins ‘high’ bins θCθC Interpolation regime low Interpolation regime high

13. Binning near the Cherenkov peak ‘low’ bins‘high’ bins θCθC Broadly scattered photons Similar to direct photons Broadly scattered photons

14. What does this produce? v4r2 Artificial discontinuity in photon times Unphysically early photons (0.2% chance per PMT at 1 TeV)

15. Solution: Different bins spacing Easy! (change input file) Sacrifices accuracy away from theta_C More bins Requires recompile (allow larger arrays) Possible memory leaks in PAW New histogram method Ultimately, must do this Previous solutions depend on precise scattering function used Will break down at large distances (more later) Requires programming!

16. Minimal solution – more bins near theta_C Change distribution of bins to favour angles near the Cherenkov peak Two closest bins lie within the peak: interpolation OK! USE ‘hit’ keys: BEHI 0.2 0.2 BELO 0.2 0.2 (formally) BEHI 0.5 0.7 BELO 0.5 0.7

17. New vs old binning: NEW: BEHI 0.2 0.2 BELO 0.2 0.2 OLD: BEHI 0.5 0.7 BELO 0.5 0.7 Worse at large angles…

18. Does it work? (results with v4r2: new and old) Yes! 20 bins are good enough

19. Conclusion on “problems with km3 v3 & v4” Caused by binning in the ‘theta’ direction Problem exists with v3rX. O ~ 0.few% of photons ‘mildly unphysical’ More tuning needed for optimal BELO/BEHI (0.2 is TOO SMALL at small distances for other reasons) If you use km3, find out how the hit-tables were generated! v4r3 will allow more bins in the theta-direction (from 20 to 600 ???)

20. USING SEAWATER IN KM3MC (GEN) Modification #2:

21. ANTARES is in the sea! Shock! Horror! Gasp! Different atomic composition (salt!) Different density (salt + pressure) km3 mc MUSIC package used seawater km3 gen GEANT3.21 used pure water Initially: use model by Millero, Chen, Bradshaw, Schleicher (1978) 3.844% salinity (treated as all NaCl) depth 2475m temp 13.2 degrees Density: ~1.04 g/cm 3

22. Does it matter? Using 10 6 events in case B4: how many photons? Yes – but not as much as the binning! (note: seawater results with lower statistics than RBR MC data) pure water seawater 50 bins at 0.2 20 bins at 0.2 20 bins at 0.7 161.6 +- 0.4 +- 2 k 174.2 +- 0.4 +- 2 k 155.9 +- 0.4 +- 2 k 168.3 +- 0.4 +- 2 k Common Poisson error from gen tables Common error Poisson from gen tables Independent random errors from km3 runs. 174.6 +- 0.4 +- 2 k 168.8 +- 0.4 +- 2 k BELO/ BEHI

23. Conclusion Sea water in GEANT produces less photons than pure water (secondary electron tracks shorter) New, more accurate binning produces more Problems with v3/v4 almost fixed Cause of errors found Using BELO/BEHI = 0.2 introduces new problems Still verifying that a compromise works

24. Next Steps Finish testing of binning for BELO/BEHI Write this up as an ANTARES internal note, and release v4r3 (in seawater + new binning parameters). Begin work on v4r4: suitable for km3NET (unify versions) completely new theta-histogram method Add muon energy loss to o/p various other mods (see Strasbourg talk) NO major re-write needed/anticipated …

25. EXTRA MATERIAL

26. Inverse cumulative distributions… ‘Region of Death’

27. ASIDE: photon distribution at low R Why BELO/BEHI=0.2 does NOT work

28. Phenomenology at small R Direct photons from primary muons: large ‘angular’ range Direct photons from secondary electrons: forward-peaked (β < 1) Cherenkov peak spread over a large angular range Fine binning near the ‘peak’ runs out of statistics! muon BELO/HI=0.2 DOES NOT WORK! What is the optimum?