IMPACT OF WATER OPTICAL PROPERTIES ON TRACKS RECONSTRUCTION

IMPACT OF WATER OPTICAL PROPERTIES ON IMPACT OF WATER OPTICAL PROPERTIES ON TRACKS RECONSTRUCTIONTRACKS RECONSTRUCTION

IMPACT OF WATER OPTICAL PROPERTIES ON IMPACT OF WATER OPTICAL PROPERTIES ON TRACKS RECONSTRUCTIONTRACKS RECONSTRUCTION

H Yepes -Ramirez H Yepes -Ramirez IFIC (CSIC – Universitat de València)IFIC (CSIC – Universitat de València)

ANTARES Collaboration Meeting

Moscow, June 06th-10th, 2011

OUTLINEOUTLINEOUTLINEOUTLINE

ANTARES Collaboration Meeting ANTARES Collaboration Meeting Moscow, Moscow, JuneJune 06 06thth-10-10thth2

Brief reminder of light propagation Brief reminder of light propagation in sea water: in sea water: ANTARES Monte Carlo

model

Simulation: Simulation: absorption and scattering inputs, codes and data selection

Selected resultsSelected results

Conclusions and outlookConclusions and outlook

Brief reminder of light propagation Brief reminder of light propagation in sea water: in sea water: ANTARES Monte Carlo

model

Simulation: Simulation: absorption and scattering inputs, codes and data selection

Selected resultsSelected results

Conclusions and outlookConclusions and outlook

Brief reminder of light Brief reminder of light propagation in sea waterpropagation in sea water

Brief reminder of light Brief reminder of light propagation in sea waterpropagation in sea water


Scattering phase function (Scattering phase function ())

Morel and Loisel approach

Molecular scattering (Rayleigh) Isotropic (<cos>=0)

= contribution of Rayleigh scattering

Particle scattering (Mie) Strong forward peaked (<cos>Mie=0.924)

effscatabs

effatt

111

Attenuation Length (COLIMATED BEAM)

Effective Attenuation Length (ISOTROPIC SOURCE)

Absorption lengthAbsorption length Scattering LengthScattering Length

scatabsatt 111

Mie

scatscateffscat

cos)1(1cos1

924.0cos Mie

Scattering length wavelength dependence

(Kopelevich parameterization)

][550

312.0550

34.1550

0017.0 13.07.13.4

mvvb ls

scat

b1

b = scattering coefficient.

vs, vl = scattering centers.<Cos> = Average cosine of the global distribution

Petzold values for particle scattering

)()1()()( *** MieRay

SimulationSimulationSimulationSimulation


A set of water properties inputs reliable for study:

• AIM production of the absorption and scattering spectrum for different water models for muons and neutrinos, in agreement to the water models proposed for the data/MC CALIBOB comparison for optical beacon data (J Ruiz-Rivas, Collaboration Meeting in Paris 2010).

• Ten different water models (two runs each, just for a first approach) for muons and neutrinos (20 files for muons, 20 files for neutrinos).



abs [m] Vs, Vl (scattering centers) [ppm] scat at 470 nm [m]

55 0.0075 53 0.17

55 0.01 41 0.17

55 0.02 22 0.17

55 0.01 41 0.11

55 0.02 22 0.02

63 0.0075 53 0.17

63 0.01 41 0.17

63 0.02 22 0.17

63 0.01 41 0.11

63 0.02 22 0.02

• Three runs with the same value and different scattering spectrum for a given absorption length.

• Three runs with different values, but is computed in such a way that the three runs will have the same effective scattering length at 470 nm, for a given absorption length.

• Three common models for comparisons (muons abs55-abs63, neutrinos abs55) with previous Monte Carlo productions.

• OM Angular acceptance of June 2009 (Genova Meeting 2009).



GENGENWATER MODEL:

•Photon tables production (water tables) Water tables (hbook files) + Description files (ASCII files).

HITHITOM PARAMETERS:

• Hit probability computation from the water tables for a given OM parameters Hit tables (hbook files) + Description files (ASCII files).

KM3KM3SIMULATED EVENTS: GEOMETRY + KINEMATICS

• Physics events reading and OM hits production based on event geometry and hit probability tables Detector events: Signal hits (muons, not tracks from hadronic showers), physical background.

GEASIMGEASIM

MCEWMCEW

TETE

RECORECO

SIMULATIONS OF ATMOSPHERIC NEUTRINO INTERACTIONS.

• Process (and evaluation) tracks from particles coming from the hadronic showers (also muons from KM3).

TRANSLATION OF INFO ASCII FILES INTO ROOT FORMAT.

FORMAT CONVERSION TO “LOOK LIKE DATA”: electronics smearing effects (calibration, ARS response) and optical background.

RECONSTRUCTION: Reconstruction of track direction (AAfit) and ntuples information arrangement as number of hits, zenith distribution…(AntDST).

Simulation chain:



Main options and software versions in muons and neutrinos simulation:

CODE/INPUT OPTIONS/VERSIONS

GEN v3r7

HIT v3r7

KM3 v3r7

DETECTOR r12_c00_s01

GEASIM v4r10

MCEW -

TriggerEfficiency Gaussian ARS threshold file: threshold_gaus_0.33_0.08_0.1.txt

SoS file: noise_basic_harold.root (Thanks to C Bogazzi)

-n 10000000 –t 104.858 –C3 – p 0.035

-t 104.858 Frame time in ms. To determine the number of background hits to be generated in case the summary data are used.

-C3 Hit generator type: 3, Gaussian, according observed charge distribution, with time-dependent contribution of after pulses.

2010-09-23 version

Aafit v0r6

AntDST v1r1



Methodology: runs selection, lifetime computations and weights

1. Data subsample: “Point source search with 2007 and 2008 data” (ANTARES-PHYS-2010-008).

3. Lifetime and scaling for MC:

• Lifetime for neutrinos: 365 days.

• Lifetime for muons: 2*8320/86400 = 0.19 days.

4. Weights:

• Neutrinos: w3*(1.0/2*1.0e+10).

• 1044 files (12 lines detector) [08/05/2008-30/12/2008].

• Lifetime data: 76.77 days.

• ntuples from JP Gomez-Gonzales (thanks!!!).

2. MC sampling:

• SoS file prepared by C Bogazzi (thanks!!!) from the data subsample (noise_basic_harold.root): time slices taken from all different acquisition conditions.

• Mupage for muons.

• Geasim for neutrinos.

Thanks to Annarita and Carla also for the codes used as starting point and their support !!!

Thanks also to Patrick, Maarten and Aart from NIKHEF for their appropriate help about software details !!!

“Different” water tables – Same SoS file

“Different” water tables – Different SoS file

Same water tables – Same SoS file

Remarks:

1.Water tables produced by Annarita to Juan Pablo and the mine ones, are equivalent (absorption length 63 m).

2.Reproducibility of the simulation chain and equivalence among scripts are OK (just one run considered).

3.Run-dependent simulation effect is seen from the SoS Monte Carlo sampling (factor ~ 1.20).

4.Agreement data / MC should be independent of the SoS file. Confirmation in next slides MC Sampling with a SoS file based on 2008-2009 data subsample. Data/MC comparisons with the same data subsample.





My production (abs = 55 m)Juan Pablo (Amsterdam) (abs = 55 m)

• SoS File: noise_basic_harold.root

• Data ≈ MC (), Data > MC ().

• KM3 v3r7, Aafit v0r6.

• 2008 data.

• OM angular acceptance 09.

• SoS File: ?

• Data < MC (), Data ≈ MC ().

• KM3 v3r6, Aafit v0r6.

• 2007-2008 data.

• OM angular acceptance 08.

tcosth > 0 && beta < 1


Juan Pablo (CERN)

RED:

abs = 63 m



My production

RED:

abs = 63 m

• SoS File: noise_basic_harold.root

• MC > data.

• Aafit v0r6.

• SoS File: noiseblendL12-basic.root

• Data > MC.

• Aafit v0r6.

tcosth > 0 && beta < 1 tcosth > 0 && beta < 1



What kind of information we have:

1. Reconstructed data (muons + neutrinos):

• Absorption + scattering info:

• Reconstruction quality parameter.

• Number of hits used in the fit.

• Total amplitude of the hits used in the fit.

• Zenith distributions.

• Etc…(backup).

• Scattering info Time residuals.

• No reconstructed data has not been analyzed yet.

A quick look over some distributions

• Some extremes models could be discarded (i.e, blue line).

• Muons region seems to be specially in agreement for the cases at the same effective scattering length (lambda > -7).

• Neutrinos region for lambda > -4.5 have a nice agreement. MC Underestimation lambda < -4.5 .

ResultsResultsResultsResults


Reconstruction quality parameter ():


• Some extremes models could be discarded (i.e, grey line).

• Muons region seems to be in agreement most cases.

• Neutrinos region agreement at absorption 55 m is not enough clear as is seen for the models at 63 m. And peaks ..?





• Some distributions scales to the peak and others to the tail…



Number of hits used in the fit (Nhit):

tcosth < 1 && nhit > 5 && lambda > -5.4


• Scale to the peak is not seen as in the previous case, but a nice agreement seems to be for the tails of the green and light blue model.





• Some distributions scales to the peak (blue and magenta) and others to the tail (green and sky blue).



Total amplitude of the hits used in the fit (Ahit):





• Agreement to the tails for green and sky blue models, seems to be for light yellow also.


• Some extremes models could be discarded (i.e, blue line). Peaks ???

• Muons region agreement could be take place for distributions at same effective scattering length.

• Lack of neutrino events for most cases STATISTICS DEPENDENT (few runs to compare) SEE NEXT SLIDE.



Zenith angle of the fitted track (cos):

lambda > -5.4 && beta < 1



Stat

istic

s ef

fect

on

zeni

th d

istr

ibut

ions

:

abs

= 5

5 m

@ 4

70 n

m (f

rom

offi

cial

pro

duct

ions

)

• Some extremes models could be discarded (i.e, grey line). Peaks ???

• Muons region agreement could be take place for distributions at same effective scattering length.

• Lack of neutrino events again !!!



lambda > -5.4 && beta < 1



Time residuals (thit - texp):



CONCLUSIONS AND OUTLOOKCONCLUSIONS AND OUTLOOKCONCLUSIONS AND OUTLOOKCONCLUSIONS AND OUTLOOK


1. How much the correct model could matters?

2. What model could we trust on it?

3. P

4. L

5. A tentative “to do list”:

• Number of hits in the trigger.

• Total number of hits in the event.

• Arrival time of the hit on the PMT, before and after trigger.

• Detector performance: expect impact on effective areas and detector angular resolution.

MORE PLOTS CAN BE FOUND IN THE BACKUP OR:

http://ific.uv.es/~yepes/CM_MOSCOW_2011/finalPlots

1. How much the correct model could matters?

2. What model could we trust on it?

3. P

4. L

5. A tentative “to do list”:

• Number of hits in the trigger.

• Total number of hits in the event.

• Arrival time of the hit on the PMT, before and after trigger.

• Detector performance: expect impact on effective areas and detector angular resolution.

MORE PLOTS CAN BE FOUND IN THE BACKUP OR:




BACKUPBACKUPBACKUPBACKUP


5 parameters fit - 2 minimization: t0, , , x0, y0

cgctheory

k

v

kl

ctt

sin

1

tan

10

Reconstruction quality factor L:

• Linear prefit photon hit coordinates x, y, z, t

• Minimization with hit-charge weights.

• Maximum likelihood (L) fit computed from MC PDF of time residuals.

)1(log

solutionsdof

NN

L



Statistics effect on zenith distributions:

abs = 63 m @ 470 nm (official mupage production @ CERN)



Angular error ():





Azimuth:





Number of lines used in the fit (Nlines):





GLOSARY:

Time slices:

Documents

IMPACT OF WATER OPTICAL PROPERTIES ON TRACKS RECONSTRUCTION