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This report details the Hellenic Open University's significant contribution to the KM3NeT project, focusing on GEANT4 simulation, detector geometry, optical photon scattering, muon energy estimation, detector components, and more. The study includes NuOne and SeaWiet detectors in a benchmark analysis, with results on atmospheric muon and neutrino backgrounds, sensitivity, effective area, angular resolution, energy reconstruction, and statistical properties. The HOU software chain covers various aspects like detector simulation, muon reconstruction, effective areas, and calibration detectors. Methods for event generation, atmospheric muon and neutrino simulation, scintillation counter simulation, Earth shadowing effects, reconstruction algorithms, track parameters, and filtering techniques are extensively discussed. State-of-the-art approaches like global and local clustering, prefit algorithms, Kalman filter applications, charge-direction likelihood, and Kalman gain matrix are employed for precise track reconstruction and event analysis.
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Physics Laboratory School of Science and Technology Hellenic Open University Report of the HOU contribution to KM3NeT TDR (WP2) A. G. Tsirigotis WP2 Meeting - Marseilles, 29June-3July 2009 In the framework of the KM3NeT Design Study
GEANT4 Simulation– Detector Description • Any detector geometry can be described in a very effective way Use of Geomery Description Markup Language (GDML-XML) software package • All the relevant physics processes are included in the simulation • (OPTICAL PHOTON SCATTERING ALSO) Fast Simulation EM Shower Parameterization • Number of Cherenkov Photons Emitted (~shower energy) • Angular and Longitudal profile of emitted photons Detector components Particle Tracks and Hits Visualization
Charge Likelihood – Used in muon energy estimation Hit charge in PEs Probability depends on muon energy, distance from track and PMT orientation Not a poisson distribution, due to discrete radiation processes E=1TeV D=37m θ=0deg Ln(F(n)) Ln(n) Log(E/GeV)
67 meters maximum abs. length no optical photon scattering Detectors Benchmark Detector, and: NuOne: 91 Towers in a hexagonal grid, seperated by 130m. 20 floors each Tower. 30m between floors. Bar length 8m SieWiet: 91 Strings in a hexagonal grid, seperated by 130m, 20 MultiPMTs per floor, 30m between floors. Tower Geometry Floor Geometry 30m 45o 45o
Optical Modules Single PMT Optical Module Multi PMTOptical Module • 10 inch PMT housed in a 17inch benthos sphere • 35%Maximum Quantum Efficiency • Genova ANTARES Parametrization for OM angular acceptance • 31- 3inch multi PMT OM housed in a 17inch benthos sphere • 35%Maximum Quantum Efficiency • NIKHEF Parametrization for PMT angular acceptance (0.1+0.9cos(θ)) 75KHz of K40 optical noise 7KHz of K40 optical noise
Results Atmospheric Muon background (CORSIKA files – 1 hour lifetime) + Atmospheric Neutrino Background (bartol flux) Sensitivity signal
Results : E-2 source flux (100GeV – 1000PeV) – 1 year of observation Point Source Sensitivity (x10-9E2(dN/dE)(cm-2s-1GeV) (VERY PRELIMINARY) NuOne Benchmark Effective area (m2) Neutrino Energy (log(E/GeV))
Angular resolution at sensitivity limit Benchmark detector NuOne Detector Neutrino Neutrino Angular resolution (median degrees) Muon Muon Energy (log(E/GeV))
Energy resolution at sensitivity limit (NuOne detector) RMS(Log(E/GeV)) Log(Etrue/GeV)
Comparison between benchmark and SeaWiet Same cuts applied Muon angular resolution • Seawiet with OM-directionality • Seawiet without OM-directionality • Benchmark detector degrees Effective area (m2) Muon Energy (log(E/GeV)) Neutrino angular resolution degrees Neutrino Energy (log(E/GeV)) Neutrino Energy (log(E/GeV))
Muon reconstruction statistical properties Chi-square probability
Coming very soon • Estimation of sensitivity errors • Calculation of point source sensitivity of SeaWiet • Calculation of diffuse flux sensitivities for all detectors and depths
The HOU software chain • Underwater Neutrino Detector • Generation of atmospheric muons and neutrino events (F77) • Detailed detector simulation (GEANT4-GDML) (C++) • Optical noise and PMT response simulation (F77) • Filtering Algorithms (F77 –C++) • Muon reconstruction (C++) • Effective areas, resolution and more (scripts) • Extensive Air Shower Calibration Detector (Sea Top) • Atmospheric Shower Simulation (CORSIKA) – Unthinning Algorithm (F77) • Detailed Scintillation Counter Simulation (GEANT4) (C++) – Fast Scintillation Counter Simulation (F77) • Reconstruction of the shower direction (F77) • Muon Transportation to the Underwater Detector (C++) • Estimation of: resolution, offset (F77)
Event Generation – Flux Parameterization μ ν ν • Atmospheric Muon Generation • (CORSIKA Files, Parametrized fluxes ) • Neutrino Interaction Events • Atmospheric Neutrinos • (Bartol Flux) • Cosmic Neutrinos • (AGN – GRB – GZK and more) Earth Shadowing of neutrinos by Earth Survival probability
Prefit, filtering and muon reconstruction algorithms d L-dm (x,y,z) θc dγ Track Parameters θ : zenith angle φ: azimuth angle (Vx,Vy,Vz): pseudo-vertex coordinates dm (Vx,Vy,Vz) pseudo-vertex • Local (storey) Coincidence (Applicable only when there are more than one PMT looking towards the same hemisphere) • Global clustering (causality) filter • Local clustering (causality) filter • Prefit and Filtering based on clustering of candidate track segments (Direct Walk technique) • Combination of Χ2fit and Kalman Filter (novel application in this area) using the arrival time information of the hits • Charge – Direction Likelihood using the charge (number of photons) of the hits
Kalman Filter application to track reconstruction State vector Initial estimation Update Equations timing uncertainty Kalman Gain Matrix Updated residual and chi-square contribution (rejection criterion for hit) Many (40-200) candidate tracks are estimated starting from different initial conditions The best candidate is chosen using the chi-square value and the number of hits each track has accumulated.
