1. S. E. Tzamarias The project is co-funded by the European Social Fund & National Resources EPEAEK-II (PYTHAGORAS) KM3Net Kick-off Meeting, Erlangen-Nuremberg, 11-13 April 2006 HOU Contribution to WP4 (Information & Technology)

2. Events Generator Neutrino (all flavors) Induced Events Atmospheric Muon Generation Atmospheric Neutrinos Cosmic Neutrinos (Several Models) Neutrino Interactions (use of Pythia) Example: Earth Absorption Nadir Angle Probability of a ν μ to cross Earth Extensive Air Showers Production of Secondaries, transportation, energy loss Example: ν e interacting inside a grid-like detector

3. Monte Carlo Development : Simulation TechniqueCherenkov photon emission A new, very efficient, general purpose, Cherenkov simulation algorithm find the center of mass m1 of group1 find the center of mass m2 of group2 Define 2 points inside the detector, p1 & p2 For all PMTs Which point is closer ? p1p2 Add PMT to group1 Add PMT to group2 is m1=p1 and m2=p2 yes no converge Stage 1:Define PMT clusters according to the detector geometry Stage 2: Use the Clusters for the Cherenkov photon production The simulation strategy is applicable and efficient for any detector architecture without any extra optimization

4. Monte Carlo Development : Simulation of the Detector Response (GEANT4) Angular Distribution of Cherenkov Photons EM Shower Parameterization Parameterization of EM Shower Longitudal profile of shower Number of Cherenkov Photons Emitted (~shower energy) Angular profile of emitted photons General purpose: Simulation of (any) PMT Response Simulation of electronic functions mV

5. Simulation Example 1 TeV Vertically incident muon K 40 Noise Hits Signal Hits (Hit amplitudes > 2p.e.s)

6. Computer Power Computer Farm with 15 computers (15 double xeons ) We are currently installing 64 more computers (64 double opterons) 350 Gflops Current Studies PMT orientation and photon directionality nested vs uniform architecture for ~1TeV muons fast triggers and filtering algorithms detector calibration using EAS

7. Fast Triggering Algorithms Estimation of Information Rate 1km 3 Grid (18522 15inch PMTs) Information Rate = PMT Number * K 40 Noise Rate * (Bytes/Hit) = 18522 * 50kHz * 32 ≈ 30GB/sec Cannot be saved directly to any media

8. Charge & Multiplicity Characteristics Charge/hit distribution Number of pes noise signal Multiplicity (signal) Multiplicity (noise) Number of active PMTs in 6 μs window No Cut 1TeV Vertical Muons

9. Charge & Multiplicity Characteristics Selection based on hits with at least 2 photoelectrons Multiplicity (signal) Multiplicity (noise) Information Rate = PMT Number * K 40 Noise Rate * (Bytes/Hit) = 18522 * 3kHz * 32 ≈ 1.8GB/sec By Using clustering like DUMAND the background rate is reduced by 75% (450 MByte/sec) and the signal hit has a higher than 60% probability to survive

10. Fast Triggering Algorithms Estimation of Information Rate 1km 3 Grid (18522 triplets of PMTs) 3 PMTs per hemisphere in coincidence 10nsec time window, 2 out of 3 coincidence Each triplet’s total photocathode = 15inch PMT photocathode Information Rate = PMT Number * K 40 Noise Rate * (Bytes/Hit) = 3* 18522 * 17 Hz * 32 ≈ 30MB/sec Triplet coincidence rate=17Hz (17kHz background per PMT)

11. Number of active triples Background Signal 1TeV Vertical Muons Fast Triggering Algorithms Use of the number of activate triplets as fast selection trigger Distributions normalized to 1

12. Fast Triggering Algorithms Estimation of Event Rate and Efficiency Event Rate (kHz) Cut to the number of active triplets Efficiency Cut to the number of active triplets 180 kByte/event 10TeV 1TeV

13. Fast Triggering Algorithms 1TeV Vertical Muons Use also the Dumand clustering: Background Signal Number of active triples

14. Fast Triggering Algorithms Estimation of Event Rate and Efficiency Event Rate (kHz) 180 kByte/event Cut to the number of active triplets Efficiency Cut to the number of active triplets 1TeV

15. Fast Triggering Algorithms Raw Hits Absolute time Time Stretching Trigger Level trigger Accepted Interval Triggering Method

16. 36 PMs in 3 subcylinder 35 3” photomultipliers in a cylinder Determination of photon direction, e.g. via multi-anodic PMs plus a matrix of Winston cones. Large photocathode area with arrays of small PMTs packed into pressure housings Alternative Options for photodetection

17. t1t1 t2t2 t3t3 Ethernet A. Leisos H.O.U., Univ. Athens, Univ. Patras, INP DEMOKRITOS, NTUA

18. A Station GPS Scintillator PC ~20 m TCP/IP Scintillator A. Leisos

19. Eurocosmics

20. The General Idea… Angular offset Efficiency Resolution Position Detector calibration using EAS