Apostolos Apostolos TsirigotisTsirigotis

Simulation Studies of km3 ArchitecturesSimulation 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)

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

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 modelsIt is going to be updated

Earth

Event Generation

Shadowing of neutrinos by Earth Survival probability

Nadir Angle P

rob

abil

ity

of

a ν μ

to

cro

ss E

arth

Neutrino Interaction Probability in the active volume of the detector

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

Filtering, Prefit and Reconstruction Algorithms

Local (storey) CoincidenceApplicable only when there are more than one PMT looking towards the same hemisphere

Global clustering (causality) filter50% Background rejection while all signal hits survive (1km3 Grid & 1 TeV muon)

Local clustering (causality) filter75% Background rejection while 90% of signal hits survive (1km3 Grid & 1 TeV muon)

Prefit and Filtering based on clustering of candidate track segments

•Χ2 fit without taking into account the charge (number of photons)•Kalman Filter (novel application in this area)

MultiPMT Optical Module (NIKHEF Design)

Outside view Inside 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)

Optical Module ReadoutOptical Module Readout

•Use a time-over-threshold (TOT) system (multiple thresholds)•Estimation of charge from the time-over-thresholds

+

multiplicity

Time (ns)

Trigger

Input

125 meters

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

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 floor2 MultiPMT OMs per Storey, one looking down the other up10878 Optical Modules

x(m)

y(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 floor2 MultiPMT OMs per Storey, one looking down the other up10374 Optical Modules

200m 300m

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

Prefit Resolution

Space angle difference (degrees) Zenith angle difference (degrees)

σ = 0.47 degrees

(1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs)

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)

Fit Resolution (1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs)

Space angle difference (degrees)

median 0.1 degrees

σ = 1.05

theta pool (θsim – θrec)/σrecv

Goodness of fit (1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs)

phi pool (φsim – φrec)/σrec

σ = 1.01

Goodness of fit (1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs)

Χ2 probabilitycut

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

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

Resolution Estimation (1 TeV Muons, isotropic flux, IceCube Geometry, 9600 OMs)

σ=0.094 degrees σ=0.07 degrees

Zenith angle difference of subdetectors (degrees) Zenith angle difference of whole detector (degrees)

Atmospheric (CC) neutrino events (1-10TeV)Comparison of three different Geometries

Space angle difference between neutrino and muon track

degrees

degrees

median 0.7 degrees

median 0.3 degrees

1 TeV muon neutrino

5 TeV muon neutrino

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)

Rec

on

stru

ctio

n E

ffic

ien

cy

All three geometries have the same resolution (~0.07 degrees in zenith angle)

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)

Mu

on

eff

ect

ive

are

a (m

2)