H Yepes, C Bigongiari, J Zuñiga, JdD Zornoza IFIC (CSIC - Universidad de Valencia) STATUS OF THE ABSORPTION LENGTH MEASUREMENT WITH THE OB SYSTEM ANTARES COLLABORATION MEETING NOVEMBER 2009, GANDIA (SPAIN)

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) OUTLINE A reminder of the experimental procedure Quality runs selection for the study of optical properties Analysis based on “Golden runs” Conclusions

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) A REMINDER OF THE EXPERIMENTAL PROCEDURE F2 One single LED of the top group of the lowest LED Beacon in the line (F2) flashes Measure the amount of light collected by OMs of the upper storeys in the same line EXPONENTIAL FIT Plot the collected charge (Q) as a function of the distance (R)  Skip all points at R < R min to avoid the electronic dead time effects  “phe level”  Skip all points at R > R max to avoid fake signals due to noise fluctuations.

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) A REMINDER OF THE EXPERIMENTAL PROCEDURE THE COLLECTED CHARGE: The collected charge (Q) is a convolution of: PHYSICS: Absorption length (L abs ) Scattering (L sca and  =  (  )) DETECTOR: OB – OM relative orientation OM efficiency ARS token ring dead time Charge resolution To minimize the effects of the detector: Consider only OMs in the same line of the OB Consider only the region (R min, R max ) where signal < spe but well above background TIME DISTRIBUTION: Q noise T max T min Q signal Determine the peak  Gaussian fit Choose a fixed time window [T min, T max ] and select the hits: T min = T peak – 3  T max = T peak ns Calculate their overall charge Q tot and the signal hits.

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) A REMINDER OF THE EXPERIMENTAL PROCEDURE NOISE CONTRIBUTION:  Substract the noise contribution (Q noise ): Q signal = Q tot – Q noise  Fit a constant in the [-1000, -50] ns range (B level ): Q noise = B level (T min – T max ) NOISE LEVEL CHARGE LOSSES: Some hits are lost due to the electronic dead time from the readout of the ARSs. Consider only the region where the probability to get more than one photoelectron is negligible (i.e. < 1 %). Electronics dead time effects related to R min to fit.

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) A REMINDER OF THE EXPERIMENTAL PROCEDURE PMT RELATIVE NOISE EFFICIENCY CORRECTION: PMTs don’t have the same efficiency (  PMT ): Assume that the Q noise ~  PMT. Normalize PMTs signal charge to their own noise charge : Efficiency correction by noise is not enough for some cases Alternative way for efficiency correction based on 40 K analysis  relative OMs “sensitivities” (Dmitry Zaborov):

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) A REMINDER OF THE EXPERIMENTAL PROCEDURE NOISE FLUCTUATIONS:  At large distances the signal can be confused with noise fluctuations.  Consider the region where Q signal >Q noise  The maximum distance R max to fit is related to the noise fluctuations at higher distances. MEASUREMENT OF ERRORS:  Statistical and dispersion errors are considered (data):

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) QUALITY RUNS SELECTION FOR OPTICAL PROPERTIES 1.DEAD CHANNELS CLEANING: A useful tool to check dead channels for our analysis is available at: Entry the line number and date we are considering Check available OMs for a specific date Check that our codes are not considering them, if there is any … reject it !

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) QUALITY RUNS SELECTION FOR OPTICAL PROPERTIES 2.LOW EFFICIENCY OMs CLEANING: We have seen obvious low efficiency OMs for different runs, e.g:  OM2 (F5), OM0 (F11), OM1 (F13)  Are they unknown dead channels? Compute hits projections. Fit a Gaussian. Consider only OMs between: (  +3 ,  -3  ). OM_0 OM_1 OM _2

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) QUALITY RUNS SELECTION FOR OPTICAL PROPERTIES 3.THE BACKGROUND FLATNESS AS A QUALITY FACTOR: Noise efficiency correction is affected by noise fluctuations along the line  A “flat” level noise along the line is required. The background level flat shape along the line is correlated with low rates  Special runs request at low mean background rates: E-LOG entry: 4126 USER Line 1-12 LED Beacon - Optical properties MI - V3.1 USER Line 1-12 LED Beacon - Optical properties HI - V3.1

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) QUALITY RUNS SELECTION FOR OPTICAL PROPERTIES  Run selection criterion: A flat shape for the background.  Optical properties runs (previous criterion applied): Updated 17/11/2009 TOTAL RUNsGOLDENSILVERCOPPER GOLDEN RUNS FOR OPTICAL PROPERTIES RUNDATELINESTOREYINTENSITY /05/200822H /05/200822H /05/200822H /05/200822H /05/200822H /05/200822H /10/200842H /10/200842H /10/200842H /10/200842H /10/200842H /10/200842H /10/200882H /12/200812H /02/200982L (DP) /02/200982H /02/200982L /02/200982L /11/200922H /11/200922M /11/200922M /11/200922H

BACKGROUND LEVELL USING CHARGEL USING HITS

To avoid the sensitive region where we are loosing charge (R min ). To check the noise fluctuations region (R max ). Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS” 1.L ESTIMATION FOR GOLDEN RUNS:  OM efficiency corrected by noise.  Statistical and dispersion errors taken into account.  Fixed limits on the fit range: High intensity runs  R min (H) = 135 m R max (H) = 275 m Low intensity runs  R min (L) = 85 m R max (L) = 200 m  Photoelectron region is kept ! 

High intensity (hits)Low intensity (hits)Noise dependence H and L (hits) Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS” L distributions computed with hits at high and low intensity. Noise level dependence  Solid: high intensity runs. No solid: low intensity runs.

3.CORRELATIONS BETWEEN L VALUES FOR CHARGE AND HITS: We can see a slight correlation between L values measured with charge or hits and between L values computed with both considered efficiencies, noise and Dmitry. Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS” Correlations between L values measured with charge and hits distributions Correlations between L values measured with noise and Dmitry efficiencies (for hits)

4.CORRELATIONS BETWEEN DMITRY EFFICIENCY AND NOISE EFFICIENCY FOR THE “BEST” AND THE “WORST” CASE: We have considered one of the best “Golden” runs and one of the worst “copper” runs: “GOLDEN” RUN (33983) “COPPER” RUN (40123) Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS”

5.INFLUENCE OF THE FITS LIMITS IN THE L ESTIMATION:  Reference case  correction by noise efficiency: Remember !  limits for high intensity (H) runs ≠ limits for low intensity (L) runs: High intensity runs  R min (H) = 135 m R max (H) = 275 m Low intensity runs  R min (L) = 85 m R max (L) = 200 m  How does the L value changes if we move the first point and the last point of the fit? Some examples: (0F, 0F)  Reference fit (not moved) The following cases have been analyzed: (  2F,0F) Range  R max changes while R min is kept fixed (0F,  1F) Range  R max is kept fixed while R min changes Random range  R max, R min not fixed Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS”

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) -1F (F20) 0F (F21) +1F (F22) -2F (F10)-1F (F11) 0F (F12)+1F (F13)+2F (F14) Mean = 55.2  = 2.40 FOR HITS (last 4 runs not included)

R max R min -2F (F10)-1F (F11)0F (F12)+1F (F13)+2F (F14) -1F (F20) F (F21) F (F22)  Taking different choices, we have for high intensity runs (most population) and for hits:  The value for L is stable close to the reference case.  If R min decreases  We go out from the photoelectron region  L increases. If R min increases  Scattering effects are most remarkable  L decreases.  The effect from the electronics will appear just when we take risky distances out from the photoelectron region ! Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS” FOR HITS

 In green  All available runs: golden, silver and copper  In red  Golden and silver runs  In black  Golden runs  Solid points  High intensity runsNon-solid points  Low intensity runs Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS” L IS STABLE ONCE GOLDEN RUNS CRITERION IS APPLIED !

7.EVOLUTION IN TIME FOR HIGH AND LOW INTENSITY RUNS: ( The latests 4 Golden RUNs included! )  We can see the stability on time for the golden runs selected  A strong reason to follow taking runs under the requirements requested !  The mean value for L for high intensity runs is around 55.2 (hits)  Remind that this must be taken as a lower limit for the absorption length. All runs (high and low intensity) Golden runs (high and low intensity) Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS”

For integration gate over 500 ns, the value for L doesn’t depend of the integration gate. T max ↑ L → abs MC PRODUCTION Water model: ( bug in hit KM3 routine not corrected ! ) abs = 60 m fixed  = 0.17, 0.05 scat = 30, 40, 50, 60, 70 m abs = 60 m Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS”    L 1000 IS A LOWER LIMIT FOR THE abs 

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) CONCLUSIONS The preliminary procedure to classify optical properties runs has been presented. This selection is based on the stability of the background rate along the detector line. The OM efficiencies calculated with two different techniques are correlated for golden runs. For golden runs, the values of L are stable along the period under study (one year and a half). High intensity runs are less sensitive to the level of background than low intensity runs. The L value for high intensity runs is very stable  mean = 55.2 m, sigma = 2.40 m. Low intensity runs are less stable and more runs at low background are required. More runs of low/medium intensity are needed to help to disentangle between absorption and scattering (although high intensity runs are still need to check the reproducibility of our results).

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) A REMINDER OF THE EXPERIMENTAL PROCEDURE 40 K OM EFFICIENCY CORRECTION: Alternative way for efficiency correction based on 40 K analysis  relative OMs “sensitivities” (Dmitry Zaborov): If 3 OMs are working: efficiencies extracted from 3 equations and 3 unknowns. If 1 OM is dead: assume that the other 2 OMs have the same efficiency (1 equation, 1 unknown). If 2 OMs are dead: set all efficiencies to 0.

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) A REMINDER OF THE EXPERIMENTAL PROCEDURE MEASUREMENT OF ERRORS: The errors have been computed using the fitter seetings of ROOT (best error option used “E”) (fit). Statistical and dispersion errors are considered (data):

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) BACKUP SLIDES ROOT BEST ERRORS: ( MINUIT Tutorial-Function Minimization. Fred JAMES (CERN, Geneva). June 16, 2004 ) Best errors estimation by using the Minos technique: MINOS is a minimization (minimize the difference “  2” between theory and experimental data) algorithm implemented in MINUIT, it takes into account non-parabolic behaviour of the minimized function in the vicinity of the minimum, so the errors it reports are asymmetric (different positive and negative errors). MINUIT is conceived as a tool to find the minimum value of a multi-parameter function and analyze the shape of the function around the minimum. The principal application is foreseen for statistical analysis, working on chisquare or log-likelihood functions, to compute the best-fit parameter values and uncertainties, including correlations between the parameters. It is especially suited to handle difficult problems, including those which may require guidance in order to find the correct solution. Nonparabolic likelihood  non-parabolic log-likelihood ≡ nonparabolic chi-square. In case of ROOT histograms, the fit function defines the MINUIT fitting function as being H1FitChisquare or H1FitLikelihood depending on the options selected. H1FitChisquare calculates the chisquare between the user fitting function and the data for given values of the parameters. It is the task of MINUIT to find those values of the parameters which give the lowest value of chisquare.

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) BACKUP SLIDES ( noise efficiency, fixed limits )

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain)

Only high intensity runs, charge, expo fit

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) Only high intensity runs, hits, expo fit

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) H and L intensity, silver runs, charge, expo fit

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) H and L intensity, silver runs, hits, expo fit

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) Low intensity, silver runs, charge, expo fit

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) Low intensity, silver runs, hits, expo fit

Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) -1F (F20) 0F (F21) +1F (F22) -2F (F10)-1F (F11) 0F (F12)+1F (F13)+2F (F14) FOR CHARGE

 Taking different choices we have for high intensity runs (most population) and for charge: Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS” R max R min -2F (F10)-1F (F11)0F (F12)+1F (F13)+2F (F14) -1F (F20) F (F21) F (F22) FOR CHARGE

 The procedure implies: a more strong cut for R min    Take as much charge as we can, for one particular RUN (33999): -2F-1F0F-3F Harold Yepes ANTARES Collaboration Meeting November 2009, Gandía (Spain) ANALYSIS BASED ON “GOLDEN RUNS” ( noise efficiency, fixed limits )

High Intensity Runs Compatible results within errors About 5% error on L OW method still more fragile Outliers Fixed Window method Optimized Window method