HOU Reconstruction & Simulation (HOURS): A complete simulation and reconstruction package for Very...
-
Upload
francine-murphy -
Category
Documents
-
view
226 -
download
1
Transcript of HOU Reconstruction & Simulation (HOURS): A complete simulation and reconstruction package for Very...
HOU Reconstruction & Simulation (HOURS): A complete simulation and
reconstruction package for Very Large Volume underwater neutrino Telescopes.
A.Leisos, A. G. Tsirigotis, S.E.Tzamarias
In the framework of the KM3NeT Design Study
VLVnT 2009 - Athens, 15 October 2009
The HOURS software chain
Underwater Neutrino Detector
•Generation of atmospheric muons and neutrino events (F77–CORSIKA,Pythia)
•Detailed detector simulation (GEANT4-GDML) (C++)
•Optical noise and PMT response simulation (F77)
•Filtering Algorithms (F77 –C++)
•Muon reconstruction (C++)
•Effective areas, angular resolution and sensitivities calculation (scripts)
Extensive Air Shower Calibration Detector (Sea Top)
•Atmospheric Shower Simulation (CORSIKA) – Unthinning Algorithm (F77)
•Detailed EAS detector response Simulation (GEANT4) (C++)
•Reconstruction of the shower direction (F77)
•Muon Transportation to the Underwater Detector (C++)
•Estimation of: resolution, offset (F77)
CORSIKA(Extensive Air
Shower Simulation)
All Flavor NeutrinoInteraction Events
(Secondary Particles Generation)
Atmospheric MuonGeneration from
CORSIKA
GEANT4(KM3NeT Detector Description
and Simulation)
GEANT4(Muon Propagation
to KM3NeT)
Optical Noise, PMT response and Electronics Simulation
Prefit & Filtering Algorithms
Muon Reconstruction
EAS detector Simulation
Shower direction reconstruction
The HOURS software chain Flow Chart
SeaTop CalibrationNeutrino Telescope
Performance
Event Generation – Flux Parameterization
•Neutrino Interaction Events(PYTHIA)
•Atmospheric Muon Generation(CORSIKA)
μ
•Atmospheric Neutrinos(Bartol Flux)
ν
ν
•Cosmic Neutrinos(AGN – GRB – GZK and more)
Earth
Event Generation – Shadowing of neutrinos by Earth
Earth Density Profile
Column Depth
Survival probability
Nadir Angle P
rob
abil
ity
of
a ν μ
to
cro
ss E
arth
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 photonsVisualization
Particle Tracks and Hits
Detector components
Angular Distribution of Cherenkov Photons
Simulation of the PMT response to optical photons
Single Photoelectron Spectrum
mV
Quantum Efficiency
Πρότυπος παλμός
Standard electrical pulse for a response to a single p.e.
Arrival Pulse Time resolution
Prefit, filtering and muon reconstruction algorithms
•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 Χ2 fit 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
dm
L-dm
(Vx,Vy,Vz) pseudo-vertex
dγ
d
Track Parameters
θ : zenith angle φ: azimuth angle (Vx,Vy,Vz): pseudo-vertex coordinates
θc
(x,y,z)
Kalman Filter – Muon Track Reconstruction - Algorithm
Extrapolate the state vector
Extrapolate the covariance matrix
Calculate the residual of predictionsDecide to include or not the measurement (rough criterion)
Update the state vector
Update the covariance matrix
2Calculate the contribution of the filtered pointDecide to include or not the measurement (precise criterion)
Prediction Filtering
Initial estimates for the state vector and
covariance matrix
State vector
1
exp
k
k
x x
tH
x
0 0,x CInitial estimation
Update Equations
Kalman Gain Matrix
Updated residual and chi-square contribution (rejection criterion for hit)
timing uncertainty
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.
0 0( , ).x C
Kalman Filter – Muon Track Reconstruction - Algorithm
_ _ _( - ) /muon reco muon real reco
_ _ _( - ) /muon reco muon real reco
Muon Track Reconstruction
Chi-square probability
Energy (log(E/GeV))
Neutrino
Muon
Angular resolution
Charge Likelihood – Used in muon energy estimation
hit nohit
hit nohit
N N
i data ii 1 i 1
;E,D, ;E,D,
(N N )
ln P (V ) P (0 )
L
i data PMTresolutiondatan 1
P (V ;E,D, ) F(n;E,D, )G n(V ;n, )
dataV Hit charge in PEs
Probability depends on muon energy, distance from track and PMT orientation
F(n;E,D, ) Not a poisson distribution, due to discrete radiation processes
Ln(F
(n))
Ln(n)
E=1TeVD=37mθ=0deg
Log(E/GeV)
hit nohitL (N N )
Log(Etrue/GeV)
Lo
g(E
reco
/GeV
)
Log(E/GeV)
Simulation data from E-2 neutrino flux and SeaWiet detector (300 Strings, 130m between strings, 20 MultiOMs/string, 40m MultiOM distance)True muon energy at the closest approach to the detector center (impact point)
Δ(Log(E/GeV))
True and reconstructed muon energy distribution
Muon energy reconstruction Results 1
Muon energy reconstruction Results 2
Log(Etrue/GeV) Log(Etrue/GeV)
RM
S(Δ
(Lo
g(E
/GeV
)))
Mea
n(Δ
(Lo
g(E
/GeV
)))
Neutrino Detector Performance
Atmospheric Muon background + Atmospheric Neutrino Background
( ) a signal
9090
( )bg
s
nK K
n
90 90
0
( ) ( , )!
bg
o
n nbg
bg o bgn o
n en n n
n
Point Source Sensitivity
m2
Neutrino Energy (log(E/GeV))
Angular resolution (median)
deg
rees
Neutrino Energy (log(E/GeV))
Neutrino Effective area
9 2 2 1 110 ( )E cm s GeV
Sea top Detector Simulation Tools
CORSIKA(Extensive Air Shower
Simulation)
GEANT4(Scintillation, WLS & PMT response)
Fast Simulation also available
Unthinning Algorithm
DAQSIM(DAQ Simulation)
HOUANA(Analysis &
Track Reconstruction)
Zentih (degrees)
Sea top Detector Simulation Tools
Charge (in units of mean p.e. charge)
At the Detector Center
Data
- Monte Carlo Prediction
GEANT4Muon Propagation to KM3
HOU-KM3Muon track (s) reconstruction
dm
L-dm
(Vx,Vy,Vz) pseudo-vertex
dγ
d
Track Parameters
θ : zenith angle φ: azimuth angle (Vx,Vy,Vz): pseudo-vertex coordinates
θc
(x,y,z)
Sea top Detector Simulation Tools
Conclusions
•The study of the response of a km3-scale underwater neutrino
telescope is a crucial point both for the design of the detector
and for the experimental analysis.
•The HOU Reconstruction & Simulation (HOURS) software
package is a complete simulation package of the detector
response from the expected neutrino fluxes to the event
reconstruction and sensitivity estimation for different neutrino
sources.
GEANT4 Simulation – Detector Description
• 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
Particle Physical Processes
All Decays (unstable), multiple scattering (charged), continuous energy loss, ionization and δ-ray production (charged), Cherenkov effect (charged)
μ-/μ+ Bremsstrahlung, photonuclear interaction, direct (e+,e-) pair production
e-/e+ Bremsstrahlung, e+e- annihilation
γ γ conversion, photoelectric effect, Compton scattering
Hadrons Hadronic Interactions
Optical Photons
Absorption, medium boundary interactions