1. Apostolos Tsirigotis Simulation Studies of km3 Architectures KM3NeT Collaboration Meeting 16-18 April 2007, Pylos, Greece The project is co-funded by the European Social Fund & National Resources EPEAEK-II (PYTHAGORAS)

2. The Underwater Neutrino Telescope software chain Generation of atmospheric muons and neutrino events Detailed detector simulation (GEANT4) Optical noise and PMT response simulation Prefit & Filtering Algorithms Muon reconstruction

3. Event Generation – Flux Parameterization Neutrino Interaction Events Atmospheric Muon Generation (2 Parameterization Models) μ Atmospheric Neutrinos 1 Conventional (no prompt) Model ν ν Cosmic Neutrinos 5 diffuse flux models It is going to be updated Earth

4. Event Generation Shadowing of neutrinos by Earth Survival probability Nadir Angle Probability of a ν μ to cross Earth Neutrino Interaction Probability in the active volume of the detector

5. Detector Simulation Any detector geometry can be described in a very effective way Use of Geomery Description Markup Language (GDML, version 2.5.0) software package All the relevant physics processes are included in the simulation All the interactions and transportations of the secondary particles are simulated (Multiple track simulation) For the simulation of the neutrino interaction events PYTHIA is used Fast simulation techniques and EM shower parameterization Optical Noise and PMT response simulation Visualization of detector components, particle tracks and hits

6. Filtering, Prefit and Reconstruction Algorithms Local (storey) Coincidence Applicable only when there are more than one PMT looking towards the same hemisphere Global clustering (causality) filter 50% Background rejection while all signal hits survive (1km3 Grid & 1 TeV muon) Local clustering (causality) filter 75% Background rejection while 90% of signal hits survive (1km3 Grid & 1 TeV muon) Prefit and Filtering based on clustering of candidate track segments Χ 2 fit without taking into account the charge (number of photons) Kalman Filter (novel application in this area)

7. MultiPMT Optical Module (NIKHEF Design) Outside viewInside View 20 x 3” PMTs (Photonis XP53X2) in each 17” Optical Module Single PMT Rate (dark current + K40) ~ 4kHz 120 Hz Double coincidence rate per OM (20 ns window) 6 Noise Hits per 6μsec window (9600 MultiPMT OMs in a KM3 Grid)

8. Optical Module Readout Use a time-over-threshold (TOT) system (multiple thresholds) Estimation of charge from the time-over-thresholds + multiplicity

9. Time (ns) Trigger Input

10. 125 meters IceCube Geometry: 9600 OMs looking up & down in a hexagonal grid. 80 Strings, 60 storeys each. 17m between storeys

11. Nestor Geometry with 37 Towers in a hexagonal formation. Each tower has 21 floors 120 meters in diameter, with 50 meters between floors. 7 Storeys per floor 2 MultiPMT OMs per Storey, one looking down the other up 10878 Optical Modules x(m) y(m) x(m) Nestor Geometry with 19 Towers in a hexagonal formation. Each tower has 21 floors 120 meters in diameter, with 50 meters between floors. 13 Storeys per floor 2 MultiPMT OMs per Storey, one looking down the other up 10374 Optical Modules 200m 300m

12. Prefit and Filtering Efficiency (1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) Events with number of hits (noise+signal) >4 Number of Active OMs Events passing the prefit criteria Noise Signal Noise Signal Number of Active OMs Signal Noise Number of Active OMs Events passing the prefit criteria after background filtering Percentage of noise hits after filtering percentage

13. Prefit Resolution Space angle difference (degrees) Zenith angle difference (degrees) σ = 0.47 degrees (1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs)

14. Fit Resolution(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) Azimuth angle difference (degrees) σ = 0.07 degrees σ=0.085 degrees Zenith angle difference (degrees)

15. Fit Resolution(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) Space angle difference (degrees) median 0.1 degrees

16. σ = 1.05 theta pool (θ sim – θ rec )/σ recv Goodness of fit(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) phi pool (φ sim – φ rec )/σ rec σ = 1.01

17. Goodness of fit(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) Χ 2 probability cut

18. Resolution Estimation(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) Divide the detector in 2 identical sub detectors Reconstruct the muon separately for each sub detector Compare the 2 reconstructed track directions Number of active OMs in one subdetector Number of active OMs in whole detector

19. Resolution Estimation(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) Zenith angle difference between the 2 reconstructed directions (degrees) Space angle difference between the 2 reconstructed directions (degrees) σ=0.14 degrees

20. Resolution Estimation(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs) σ=0.094 degreesσ=0.07 degrees Zenith angle difference of subdetectors (degrees)Zenith angle difference of whole detector (degrees)

21. Atmospheric (CC) neutrino events (1-10TeV)Comparison of three different Geometries Space angle difference between neutrino and muon track degrees median 0.7 degrees median 0.3 degrees 1 TeV muon neutrino 5 TeV muon neutrino

22. Atmospheric (CC) neutrino events (1-10TeV)Comparison of three different Geometries IceCube Geometry (Only Down looking OMs) IceCube Geometry (Up- Down looking OMs) Nestor Geometry (Up Down looking OMs) Muon Energy (GeV) Reconstruction Efficiency All three geometries have the same resolution (~0.07 degrees in zenith angle)

23. Atmospheric (CC) neutrino events (100GeV-10TeV)Comparison of 4 different Detectors IceCube Geometry (Only Down looking OMs) IceCube Geometry (Up- Down looking OMs) Nestor Sparse Geometry (Up Down looking OMs) Nestor Dense Geometry (Up Down looking OMs) Neutrino Energy (GeV) Muon effective area (m 2 )