\section{Performance} \subsection{Calibration} In this section, we describe the tests performed using light pulses of different colour, pulse shapes and intensities with the MAGIC calibration pulser box. \par The LED pulser system is able to provide fast light pulses of 3--4\,ns FWHM with intensities ranging from 3--4 photo-electrons to more than 500 in one inner pixel of the camera. These pulses can be produced in three colours $green$, $blue$ and $UV$. \begin{table}[htp] \centering \begin{tabular}{|c|c|c|c|c|c|} \hline \hline \multicolumn{6}{|c|}{The possible pulsed light colours} \\ \hline \hline Colour & Wavelength & Spectral Width & Min. Nr. & Max. Nr. & Secondary \\ & [nm] & [nm] & Phe's & Phe's & Pulses \\ \hline Green & 520 & 40 & 6 & 120 & yes \\ \hline Blue & 460 & 30 & 6 & 500 & yes \\ \hline UV & 375 & 12 & 3 & 50 & no \\ \hline \hline \end{tabular} \caption{The pulser colours available from the calibration system} \label{tab:pulsercolours} \end{table} Table~\ref{tab:pulsercolours} lists the available colours and intensities and figures~\ref{fig:pulseexample1leduv} and~\ref{fig:pulseexample23ledblue} show exemplary pulses as registered by the FADCs. Whereas the UV-pulse is very stable, the green and blue pulses show sometimes smaller secondary pulses after about 10--40\,ns from the main pulse. One can see that the very stable UV-pulses are unfortunately only available in such intensities as to not saturate the high-gain readout channel. However, the brightest combination of light pulses easily saturates all channels in the camera, but does not reach a saturation of the low-gain channel. \par Our tests can be classified into three subsections: \begin{enumerate} \item Un-calibrated pixels and events: These tests measure the percentage of failures of the extractor resulting either in a pixel declared as un-calibrated or in an event which produces a signal ouside of the expected Gaussian distribution. \item Number of photo-electrons: These tests measure the reconstructed numbers of photo-electrons, their spread over the camera and the ratio of the obtained mean value for outer and inner pixels. \item Linearity tests: These test the linearity of the extractor with respect to pulses of different intensity and colour. \item Time resolution: These tests show the time resolution and stability obtained with different intensities and colours. \end{enumerate} \begin{figure}[htp] \centering \includegraphics[height=0.25\textheight]{1LedUV_Pulse_Inner.eps} \includegraphics[height=0.25\textheight]{1LedUV_Pulse_Outer.eps} \caption{Example of a calibration pulse from the lowest available intensity (1\,Led UV). The left plot shows the signal obtained in an inner pixel, the right one the signal in an outer pixel. Note that the pulse height fluctuates much more than suggested from these pictures. Especially, a zero-pulse is also possible.} \label{fig:pulseexample1leduv} \end{figure} \begin{figure}[htp] \centering \includegraphics[height=0.25\textheight]{23LedsBlue_Pulse_Inner.eps} \includegraphics[height=0.25\textheight]{23LedsBlue_Pulse_Outer.eps} \caption{Example of a calibration pulse from the highest available intensity (23\,Leds Blue). The left plot shows the signal obtained in an inner pixel, the right one the signal in an outer pixel. One the left side, the (saturated) high-gain channel is visible, on the right side, the delayed low-gain pulse appears. Note that on the left side, there is a secondary pulses visible in the tail of the high-gain pulse. } \label{fig:pulseexample23ledblue} \end{figure} We used data taken on the 7$^{th}$ of June, 2004 with different pulser LED combinations, each taken with 16384 events. The corresponding run numbers range from nr. 31741 to 31772. This data was taken before the latest camera repair access which replaced about 2\% of the pixels known to be mal-functionning at that time. Thus, there is a lower limit to the number of un-calibrated pixels of about 1.5--2\%. \par Although, we had looked at and tested all colour and extractor combinations resulting from these data, we refrain ourselves to show here only exemplary behaviour and results of extractors. All plots, including those which are not displayed in this TDAS, can be retrieved from the following locations: \begin{verbatim} http://www.magic.ifae.es/~markus/pheplots/ http://www.magic.ifae.es/~markus/timeplots/ \end{verbatim} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \subsubsection{Un-Calibrated Pixels and Events} The MAGIC calibration software incorporates a series of checks to sort out mal-functionning pixels. Except for the software bug searching criteria, the following exclusion reasons can apply: \begin{enumerate} \item The reconstructed mean signal is less than 2.5 times the extractor resolution $R$ from zero. (2.5 Pedestal RMS in the case of the simple fixed window extractors). This criterium cuts out dead pixels. \item The reconstructed mean signal error is smaller than its value. This criterium cuts out signal distributions which fluctuate so much that their RMS is bigger than its mean value. This criterium cuts out ``ringing'' pixels or mal-functionning extractors. \item The reconstructed mean number of photo-electrons lies 4.5 sigma outside the distribution of photo-electrons obtained with the inner or outer pixels in the camera. \item All reconstructed negative mean signal, signal sigma's and mean numbers of photo-electrons smaller than one. \end{enumerate} Moreover, the number of events are counted which have been reconstructed outside a 5 sigma region from the mean signal. These events are called ``outliers''. Figure~\ref{fig:outlier} shows a typical outlier obtained with the digital filter. \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{Outlier.eps} \caption{Example of an event classified as ``un-calibrated''. The histogram has been obtained using the digital filter (extractor \#32) applied to a high-intensity blue pulse (run 31772). The event marked as ``outlier'' clearly has been mis-reconstructed. It lies outside the 5 sigma region from the fitted mean.} \label{fig:outlier} \end{figure} The following figures~\ref{fig:unsuited:5ledsuv},~\ref{fig:unsuited:1leduv},~\ref{fig:unsuited:2ledsgreen} and~\ref{fig:unsuited:23ledsblue} show the resulting numbers of un-calibrated pixels and events for different colours and intensities. \par \begin{figure}[htp] \centering \includegraphics[height=0.95\textheight]{UnsuitVsExtractor-5LedsUV-Colour-13.eps} \caption{Uncalibrated pixels and pixels outside of the Gaussian distribution for a typical calibration pulse of UV-light which does not saturate the high-gain readout.} \label{fig:unsuited:5ledsuv} \end{figure} \begin{figure}[htp] \centering \includegraphics[height=0.95\textheight]{UnsuitVsExtractor-1LedUV-Colour-04.eps} \caption{Uncalibrated pixels and pixels outside of the Gaussian distribution for a very low intensity pulse.} \label{fig:unsuited:1leduv} \end{figure} \begin{figure}[htp] \centering \includegraphics[height=0.95\textheight]{UnsuitVsExtractor-2LedsGreen-Colour-02.eps} \caption{Uncalibrated pixels and pixels outside of the Gaussian distribution for a typical green pulse.} \label{fig:unsuited:2ledsgreen} \end{figure} \begin{figure}[htp] \centering \includegraphics[height=0.95\textheight]{UnsuitVsExtractor-23LedsBlue-Colour-00.eps} \caption{Uncalibrated pixels and pixels outside of the Gaussian distribution for a high-intensity blue pulse.} \label{fig:unsuited:23ledsblue} \end{figure} One can see that in general, big extraction windows raise the number of un-calibrated pixels and are thus less stable. Especially for the very low-intensity $1LedUV$-pulse, the big extraction windows summing 8 or more slices, cannot calibrate more than 50\% of the inner pixels (fig.~\ref{fig:unsuited:1leduv}). This is an expected behavior since big windows add up more noise which in turn makes the for the small signal more difficult. \par In general, one can also say that all ``sliding window''-algorithms (extractors \#17-32) discard less pixels than the ``fixed window''-ones (extractors \#1--16). The digital filter with the correct weights (extractor \#32) discards the least number of pixels, but is also robust against slight modifications of its weights (extractors \#28--31). Also the ``spline'' algorithms on small windows (extractors \#23--25) discard less pixels than the previous extractors, although slightly more then the digital filter. \par In the low-gain, there is one extractor discarding a too high amount of events which is the MExtractFixedWindowPeakSearch. The reason becomes clear when one keeps in mind that this extractor defines its extraction window by searching for the highest signal found in a sliding peak search window looping only over {\textit non-saturating pixels}. In the case of an intense calibration pulse, only the dead pixels match this requirement and define thus an alleatory window fluctuating like the noise does in these channels. It is clear that one cannot use this extractor for the intense calibration pulses. \par It seems also that the spline algorithm extracting the amplitude of the signal produces an over-proportional number of excluded pixels in the low-gain. The same, however in a less significant manner, holds for the digital filter with high-low-gain inverted weights. The limit of stability with respect to changes in the pulse form seems to be reached, there. \par Concerning the numbers of outliers, one can conclude that in general, the numbers are very low never exceeding 0.25\%. There seems to be the opposite trend of larger windows producing less outliers. However, one has to take into account that already more ``unsuited'' pixels have been excluded thus cleaning up the sample somewhat. It seems that the ``digital filter'' and a medium-sized ``spline'' (extractors \#25--26) yield the best result except for the outer pixels in fig~\ref{fig:unsuited:5ledsuv} where the digital filter produces a worse result than the rest of the extractors. \par In conclusion, one can say that this test excludes all extractors with too big window sizes because they are not able to extract small signals produced by about 4 photo-electrons. The excluded extractors are: \begin{itemize} \item: MExtractFixedWindow Nr. 3--5 \item: MExtractFixedWindowSpline Nr. 6--11 \item: MExtractFixedWindowPeakSearch Nr. 14--16 \item: MExtractTimeAndChargeSlidingWindow Nr. 21--22 \item: MExtractTimeAndChargeSpline Nr. 27 \end{itemize} The best extractors after this test are: \begin{itemize} \item: MExtractFixedWindow Nr. 1--2 \item: MExtractFixedWindowPeakSearch Nr. 13 \item: MExtractTimeAndChargeSlidingWindow Nr. 17--19 \item: MExtractTimeAndChargeSpline Nr. 24--25 \item: MExtractTimeAndChargeDigitalFilter Nr. 28--32 \end{itemize} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \subsubsection{Number of Photo-Electrons} Assuming that the readout chain is clean and adds only negligible noise with respect to the one introduced by the photo-multiplier itself, one can make the assumption that variance of the true (non-extracted) signal $ST$ is the amplified Poisson variance on the number of photo-electrons, multiplied with the excess noise of the photo-multiplier, characterized by the excess-noise factor $F$. \begin{equation} Var(ST) = F^2 \cdot Var(N_{phe}) \cdot \frac{^2}{^2} \label{eq:excessnoise} \end{equation} After introducing the effect of the night-sky background (eq.~\ref{eq:rmssubtraction}) in formula~\ref{eq:excessnoise} and assuming that the number of photo-electrons per event follows a Poisson distribution, one can get an expression to retrieve the mean number of photo-electrons impinging on the pixel from the mean extracted signal $$, its variance $Var(SE)$ and the RMS of the extracted signal obtained from pure pedestal runs $R$ (see section~\ref{sec:determiner}): \begin{equation} \approx F^2 \cdot \frac{Var(SE) - R^2}{^2} \label{eq:pheffactor} \end{equation} Equation~\ref{eq:pheffactor} must not depend on the extractor! Effectively, we will use it to test the quality of our extractors by requiring that a valid extractor yields the same number of photo-electrons for all pixels of a same type and does not deviate from the number obtained with other extractors. As the camera is flat-fielded, but the number of photo-electrons impinging on an inner and an outer pixel is different, we also use the ratio of the mean numbers of photo-electrons from the outer pixels to the one obtained from the inner pixels as a test variable. In the ideal case, it should always yield its central value of about 2.4--2.8. \par In our case, there is an additional complication due to the fact that the green and blue coloured pulses show secondary pulses which destroy the Poisson behaviour of the number of photo-electrons. We will thus have to split our sample of extractors into those being affected by the secondary pulses and those without showing any effect. \par Figures~\ref{fig:phe:5ledsuv},~\ref{fig:phe:1leduv},~\ref{fig:phe:23ledsblue}~and~\ref{fig:phe:2ledsgreen} show some of the obtained results. Although one can see an amazing stability for the standard 5Leds UV pulse, there is a considerable difference for all shown non-standard pulses. Especially the pulses from green and blue LEDs show a clear dependency on the extraction window of the number of photo-electrons. Only the largest extraction windows seem to catch the entire range of (jittering) secondary pulses and get also the ratio of outer vs. inner pixels right. \par The strongest discrepancy is observed in the low-gain extraction (fig.~\ref{fig:phe:23ledsblue}) where all fixed window extractors \begin{figure}[htp] \centering \includegraphics[height=0.92\textheight]{PheVsExtractor-5LedsUV-Colour-13.eps} \caption{Number of photo-electrons from a typical, not saturating calibration pulse of colour UV, reconstructed with each of the tested signal extractors. The first plots shows the number of photo-electrons obtained for the inner pixels, the second one for the outer pixels and the third shows the ratio of the mean number of photo-electrons for the outer pixels divided by the mean number of photo-electrons for the inner pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:phe:5ledsuv} \end{figure} \begin{figure}[htp] \centering \includegraphics[height=0.92\textheight]{PheVsExtractor-1LedUV-Colour-04.eps} \caption{Number of photo-electrons from a typical, very low-intensity calibration pulse of colour UV, reconstructed with each of the tested signal extractors. The first plots shows the number of photo-electrons obtained for the inner pixels, the second one for the outer pixels and the third shows the ratio of the mean number of photo-electrons for the outer pixels divided by the mean number of photo-electrons for the inner pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:phe:1leduv} \end{figure} \begin{figure}[htp] \centering \includegraphics[height=0.92\textheight]{PheVsExtractor-2LedsGreen-Colour-02.eps} \caption{Number of photo-electrons from a typical, not saturating calibration pulse of colour green, reconstructed with each of the tested signal extractors. The first plots shows the number of photo-electrons obtained for the inner pixels, the second one for the outer pixels and the third shows the ratio of the mean number of photo-electrons for the outer pixels divided by the mean number of photo-electrons for the inner pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:phe:2ledsgreen} \end{figure} \begin{figure}[htp] \centering \includegraphics[height=0.92\textheight]{PheVsExtractor-23LedsBlue-Colour-00.eps} \caption{Number of photo-electrons from a typical, high-gain saturating calibration pulse of colour blue, reconstructed with each of the tested signal extractors. The first plots shows the number of photo-electrons obtained for the inner pixels, the second one for the outer pixels and the third shows the ratio of the mean number of photo-electrons for the outer pixels divided by the mean number of photo-electrons for the inner pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:phe:23ledsblue} \end{figure} One can see that all extractor using a large window belong to the class of extractors being affected by the secondary pulses. The only exception to this rule is the digital filter which - despite of its 6 slices extraction window - seems to filter out all the secondary pulses. \par Moreover, one can see in fig.~\ref{fig:phe:1leduv} that all peak searching extractors show the influence of the bias at low numbers of photo-electrons. \par The extractor MExtractFixedWindowPeakSearch at low extraction windows apparently yields chronically low numbers of photo-electrons. This is due to the fact that the decision to fix the extraction window is made sometimes by an inner pixel and sometimes by an outer one since the camera is flat-fielded and the pixel carrying the largest non-saturated peak-search window is more or found by a random signal fluctuation. However, inner and outer pixels have a systematic offset of about 0.5 to 1 FADC slices. Thus, the extraction fluctuates artificially for one given channel which results in a systematically large variance and thus in a systematically low reconstructed number of photo-electrons. This test thus excludes the extractors \#11--13. \par Moreover, one can see that the extractors applying a small fixed window do not get the ratio of photo-electrons from outer to inner pixels correctly for the green and blue pulses. \par The extractor MExtractTimeAndChargeDigitalFilter seems to be stable against modifications in the exact form of the weights in the high-gain readout channel since all applied weights yield about the same number of photo-electrons and the same ratio of outer vs. inner pixels. This statement does not hold any more for the low-gain, as can be seen in figure~\ref{fig:phe:23ledsblue}. There, the application of high-gain weights to the low-gain signal (extractors \#30--31) produces a too low number of photo-electrons and also a too low ratio of outer per inner pixels. \par All sliding window and spline algorithms yield a stable ratio of outer vs. inner pixels in the low-gain, however the effect of raising the number of photo-electrons with the extraction window is very pronounced. Note that in figure~\ref{fig:phe:23ledsblue}, the number of photo-electrons raises by about a factor 1.4, which is slightly higher than in the case of the high-gain channel (figure~\ref{fig:phe:2ledsgreen}). \par Concluding, there is now fixed window extractor yielding the correct number of photo-electrons for the low-gain, except for the largest extraction window of 10 low-gain slices. Either the number of photo-electrons itself is wrong or the ratio of outer vs. inner pixels is not correct. All sliding window algorithms seem to reproduce the correct numbers if one takes into account the after-pulse behaviour of the light pulser itself. The digital filter seems to be not stable against exchanging the pulse form to match the slimmer high-gain pulses, though. \subsubsection{Linearity Tests} In this section, we test the lineary of the extractors. As the photo-multiplier is a linear device over a wide dynamic range, the number of photo-electrons per charge has to remain constant over the tested linearity region. We will show here only examples of extractors which were not already excluded in the previous section. \par A first test concerns the stability of the conversion factor photo-electrons per FADC counts over the tested intensity region. \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{PheVsCharge-3.eps} \caption{Example of a the development of the conversion factor FADC counts to photo-electrons for two exemplary inner pixels (upper plots) and two exemplary outer ones (lower plots). A fixed window extractor on a window size of 6 high-gain and 6 low-gain slices has been used (extractor \#3). } \label{fig:linear:phevscharge3} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{PheVsCharge-8.eps} \caption{Example of a the development of the conversion factor FADC counts to photo-electrons for two exemplary inner pixels (upper plots) and two exemplary outer ones (lower plots). A fixed window spline extractor on a window size of 6 high-gain and 6 low-gain slices has been used (extractor \#8). } \label{fig:linear:phevscharge8} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{PheVsCharge-14.eps} \caption{Example of a the development of the conversion factor FADC counts to photo-electrons for two exemplary inner pixels (upper plots) and two exemplary outer ones (lower plots). A fixed window peak search extractor on a window size of 6 high-gain and 6 low-gain slices has been used (extractor \#14). } \label{fig:linear:phevscharge14} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{PheVsCharge-20.eps} \caption{Example of a the development of the conversion factor FADC counts to photo-electrons for two exemplary inner pixels (upper plots) and two exemplary outer ones (lower plots). A sliding window extractor on a window size of 6 high-gain and 6 low-gain slices has been used (extractor \#20). } \label{fig:linear:phevscharge20} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{PheVsCharge-25.eps} \caption{Example of a the development of the conversion factor FADC counts to photo-electrons for two exemplary inner pixels (upper plots) and two exemplary outer ones (lower plots). An integrating spline extractor on a sliding window and a window size of 2 high-gain and 3 low-gain slices has been used (extractor \#25). } \label{fig:linear:phevscharge25} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{PheVsCharge-27.eps} \caption{Example of a the development of the conversion factor FADC counts to photo-electrons for two exemplary inner pixels (upper plots) and two exemplary outer ones (lower plots). An integrating spline extractor on a sliding window and a window size of 6 high-gain and 7 low-gain slices has been used (extractor \#27). } \label{fig:linear:phevscharge27} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{PheVsCharge-32.eps} \caption{Example of a the development of the conversion factor FADC counts to photo-electrons for two exemplary inner pixels (upper plots) and two exemplary outer ones (lower plots). A digital filter extractor on a window size of 6 high-gain and 6 low-gain slices has been used (extractor \#32). } \label{fig:linear:phevscharge32} \end{figure} \subsubsection{Time Resolution} The extractors \#17--32 are able to extract also the arrival time of each pulse. In the calibration, we have a fast-rising pulse, uniform over camera also in time. We estimate the time-uniformity to better than 300\,ps, a limit due to the different travel times of the light between inner and outer parts of the camera. Since the calibraion does not have an absolute measurement of the arrival time, we measure the relative arrival time, i.e. \begin{equation} \delta t_i = t_i - t_1 \end{equation} where $t_i$ denotes the reconstructed arrival time of pixel number $i$ and $t_1$ the reconstructed arrival time of pixel number 1 (software numbering). For one calibration run, one can then fill histograms of $\delta t_i$ for each pixel which yields then a mean $<\delta t_i>$, comparable to systematic offsets in the signal delay and a sigma $\sigma(\delta t_i)$ which is a measure of the combined time resolutions of pixel $i$ and pixel 1. Assuming that the PMTs and readout channels are of a same kind, we obtain an approximate absolute time resolution of pixel $i$ by: \begin{equation} tres_i \approx \sigma(\delta t_i)/sqrt(2) \end{equation} Figures~\ref{fig:reltimesinner10leduv} and~\ref{fig:reltimesouter10leduv} show distributions of $<\delta t_i>$ for one typical inner pixel and one typical outer pixel and a non-saturating calibration pulse of UV-light, obtained with three different extractors. One can see that the first two yield a Gaussian distribution to a good approximation, whereas the third extractor shows a three-peak structure and cannot be fitted. We discarded that particular extractor for this reason. \begin{figure}[htp] \centering \includegraphics[width=0.3\linewidth]{RelArrTime_Pixel97_10LedUV_Extractor32.eps} \includegraphics[width=0.32\linewidth]{RelArrTime_Pixel97_10LedUV_Extractor23.eps} \includegraphics[width=0.32\linewidth]{RelArrTime_Pixel97_10LedUV_Extractor17.eps} \caption{Example of a two distributions of relative arrival times of an inner pixel with respect to the arrival time of the reference pixel Nr. 1. The left plot shows the result using the digital filter (extractor \#32), the central plot shows the result obtained with the half-maximum of the spline and the right plot the result of the sliding window with a window size of 2 FADC slices (extractor \#17). A medium sized UV-pulse (10Leds UV) has been used which does not saturate the high-gain readout channel.} \label{fig:reltimesinner10leduv} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.31\linewidth]{RelArrTime_Pixel400_10LedUV_Extractor32.eps} \includegraphics[width=0.31\linewidth]{RelArrTime_Pixel400_10LedUV_Extractor23.eps} \includegraphics[width=0.31\linewidth]{RelArrTime_Pixel400_10LedUV_Extractor17.eps} \caption{Example of a two distributions of relative arrival times of an outer pixel with respect to the arrival time of the reference pixel Nr. 1. The left plot shows the result using the digital filter (extractor \#32), the central plot shows the result obtained with the half-maximum of the spline and the right plot the result of the sliding window with a window size of 2 FADC slices (extractor \#17). A medium sized UV-pulse (10Leds UV) has been used which does not saturate the high-gain readout channel.} \label{fig:reltimesouter10leduv} \end{figure} Figures~\ref{fig:reltimesinner10ledsblue} and~\ref{fig:reltimesouter10ledsblue} show distributions of $<\delta t_i>$ for one typical inner and one typical outer pixel and a high-gain-saturating calibration pulse of blue-light, obtained with two different extractors. One can see that the first (extractor \#23) yields a Gaussian distribution to a good approximation, whereas the second (extractor \#32) shows a two-peak structure and cannot be fitted. \par \ldots {\it Unfortunately, this happens for all digital filter extractors in the low-gain. The reason is not yet understood, and has to be found by Hendrik... } \ldots \par \begin{figure}[htp] \centering \includegraphics[width=0.31\linewidth]{RelArrTime_Pixel97_10LedBlue_Extractor23.eps} \includegraphics[width=0.31\linewidth]{RelArrTime_Pixel97_10LedBlue_Extractor32.eps} \caption{Example of a two distributions of relative arrival times of an inner pixel with respect to the arrival time of the reference pixel Nr. 1. The left plot shows the result using the half-maximum of the spline (extractor \#23), the right plot shows the result obtained with the digital filter (extractor \#32). A medium sized Blue-pulse (10Leds Blue) has been used which saturates the high-gain readout channel.} \label{fig:reltimesinner10ledsblue} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.31\linewidth]{RelArrTime_Pixel400_10LedBlue_Extractor23.eps} \includegraphics[width=0.31\linewidth]{RelArrTime_Pixel400_10LedBlue_Extractor32.eps} \caption{Example of a two distributions of relative arrival times of an outer pixel with respect to the arrival time of the reference pixel Nr. 1. The left plot shows the result using the half-maximum of the spline (extractor \#23), the right plot shows the result obtained with the digital filter (extractor \#32). A medium sized Blue-pulse (10Leds Blue) has been used which saturates the high-gain readout channel.} \label{fig:reltimesouter10ledsblue} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResExtractor-5LedsUV-Colour-12.eps} \caption{Reconstructed arrival time resolutions from a typical, not saturating calibration pulse of colour UV, reconstructed with each of the tested arrival time extractors. The first plots shows the time resolutions obtained for the inner pixels, the second one for the outer pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:time:5ledsuv} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResExtractor-1LedUV-Colour-04.eps} \caption{Reconstructed arrival time resolutions from the lowest intensity calibration pulse of colour UV (carrying a mean number of 4 photo-electrons), reconstructed with each of the tested arrival time extractors. The first plots shows the time resolutions obtained for the inner pixels, the second one for the outer pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:time:1leduv} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResExtractor-2LedsGreen-Colour-02.eps} \caption{Reconstructed arrival time resolutions from a typical, not saturating calibration pulse of colour Green, reconstructed with each of the tested arrival time extractors. The first plots shows the time resolutions obtained for the inner pixels, the second one for the outer pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:time:2ledsgreen} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResExtractor-23LedsBlue-Colour-00.eps} \caption{Reconstructed arrival time resolutions from the highest intensity calibration pulse of colour blue, reconstructed with each of the tested arrival time extractors. The first plots shows the time resolutions obtained for the inner pixels, the second one for the outer pixels. Points denote the mean of all not-excluded pixels, the error bars their RMS.} \label{fig:time:23ledsblue} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResVsCharge-Area-21.eps} \caption{Reconstructed mean arrival time resolutions as a function of the extracted mean number of photo-electrons for the weighted sliding window with a window size of 8 FADC slices (extractor \#21). Error bars denote the spread (RMS) of the time resolutions over the investigated channels. The marker colours show the applied pulser colour, except for the last (green) point where all three colours were used.} \label{fig:time:dep20} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResVsCharge-Area-23.eps} \caption{Reconstructed mean arrival time resolutions as a function of the extracted mean number of photo-electrons for the half-maximum searching spline (extractor \#23). Error bars denote the spread (RMS) of the time resolutions over the investigated channels. The marker colours show the applied pulser colour, except for the last (green) point where all three colours were used.} \label{fig:time:dep23} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResVsCharge-Area-30.eps} \caption{Reconstructed mean arrival time resolutions as a function of the extracted signal for the digital filter with inverted high- and low-gain weights (extractor \#30). Error bars denote the spread (RMS) of the time resolutions over the investigated channels. The marker colours show the applied pulser colour, except for the last (green) point where all three colours were used.} \label{fig:time:dep30} \end{figure} \begin{figure}[htp] \centering \includegraphics[width=0.95\linewidth]{TimeResVsCharge-Area-32.eps} \caption{Reconstructed mean arrival time resolutions as a function of the extracted signal for the digital filter (extractor \#32). Error bars denote the spread (RMS) of the time resolutions over the investigated channels. The marker colours show the applied pulser colour, except for the last (green) point where all three colours were used.} \label{fig:time:dep32} \end{figure} \clearpage \subsection{Pulpo Pulses} \subsection{MC Data} \subsection{Cosmics Data?} The results of this subsection are based on the following runs taken on the 21st of September 2004. \begin{itemize} \item{Run 39000}: OffCrab11 at 19.1 degrees zenith angle and 106.2 azimuth. \item{Run 39182}: CrabNebula at 19.0 degrees zenith angle and 106.0 azimuth. \end{itemize} \subsection{Pedestals} %%% Local Variables: %%% mode: latex %%% TeX-master: "MAGIC_signal_reco" %%% TeX-master: "MAGIC_signal_reco." %%% TeX-master: "MAGIC_signal_reco" %%% TeX-master: "MAGIC_signal_reco" %%% TeX-master: "MAGIC_signal_reco" %%% TeX-master: "MAGIC_signal_reco" %%% End: