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01/18/05 17:42:12 (20 years ago)
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gaug
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  • trunk/MagicSoft/TDAS-Extractor/Performance.tex

    r5789 r5884  
    353353\par
    354354Moreover, one can see that the extractors applying a small fixed window do not get the ratio of
    355 photo-electrons from outer to inner pixels correctly for the green and blue pulses.
     355photo-electrons correctly between outer to inner pixels for the green and blue pulses.
    356356\par
    357357The extractor MExtractTimeAndChargeDigitalFilter seems to be stable against modifications in the
     
    360360hold any more for the low-gain, as can be seen in figure~\ref{fig:phe:23ledsblue}. There, the application
    361361of high-gain weights to the low-gain signal (extractors \#30--31) produces a too low number of photo-electrons
    362 and also a too low ratio of outer per inner pixels.
     362and also a too low ratio of outer vs. inner pixels.
    363363\par
    364364All sliding window and spline algorithms yield a stable ratio of outer vs. inner pixels in the low-gain,
    365365however the effect of raising the number of photo-electrons with the extraction window is very pronounced.
    366 Note that in figure~\ref{fig:phe:23ledsblue}, the number of photo-electrons raises by about a factor 1.4,
     366Note that in figure~\ref{fig:phe:23ledsblue}, the number of photo-electrons rises by about a factor 1.4,
    367367which is slightly higher than in the case of the high-gain channel (figure~\ref{fig:phe:2ledsgreen}).
    368368\par
    369 Concluding, there is now fixed window extractor yielding the correct number of photo-electrons
     369Concluding, there is no fixed window extractor yielding the correct number of photo-electrons
    370370for the low-gain, except for the largest extraction window of 10 low-gain slices.
    371371Either the number of photo-electrons itself is wrong or the ratio of outer vs. inner pixels is
    372372not correct. All sliding window algorithms seem to reproduce the correct numbers if one takes into
    373 account the after-pulse behaviour of the light pulser itself. The digital filter seems to be not
    374 stable against exchanging the pulse form to match the slimmer high-gain pulses, though.
     373account the after-pulse behaviour of the light pulser itself. The digital filter seems to be
     374unstable against exchanging the pulse form to match the slimmer high-gain pulses, though.
    375375
    376376
    377377\subsubsection{Linearity Tests}
    378378
    379 In this section, we test the lineary of the extractors. As the photo-multiplier is a linear device over a
     379In this section, we test the lineary of the extractors. As the photo-multiplier and the subsequent
     380optical transmission devices~\cite{david} is a linear device over a
    380381wide dynamic range, the number of photo-electrons per charge has to remain constant over the tested
    381382linearity region. We will show here only examples of extractors which were not already excluded in the
    382383previous section.
    383384\par
    384 A first test concerns the stability of the conversion factor photo-electrons per FADC counts over the
    385 tested intensity region.
     385A first test concerns the stability of the conversion factor: mean number of averaged photo-electrons
     386per FADC counts over the
     387tested intensity region. A much more detailed investigation on the linearity will be shwon in a
     388separate TDAS~\cite{tdas-calibration}.
    386389
    387390
     
    459462\subsubsection{Time Resolution}
    460463
    461 The extractors \#17--32 are able to extract also the arrival time of each pulse. In the calibration,
    462 we have a fast-rising pulse, uniform over camera also in time. We estimate the time-uniformity to better
     464The extractors \#17--32 are able to extract also the arrival time of each pulse. The calibration
     465delivers a fast-rising pulse, uniform over the camera in signal size and time.
     466We estimate the time-uniformity to better
    463467than 300\,ps, a limit due to the different travel times of the light between inner and outer parts of the
    464 camera. Since the calibraion does not have an absolute measurement of the arrival time, we measure
    465 the relative arrival time, i.e.
     468camera. Since the calibraion does not permit a precise measurement of the absolute arrival time, we measure
     469the relative arrival time for every channel with respect to a reference channel (usually pixel Nr.\,1):
    466470
    467471\begin{equation}
     
    470474
    471475where $t_i$ denotes the reconstructed arrival time of pixel number $i$ and $t_1$ the reconstructed
    472 arrival time of pixel number 1 (software numbering). For one calibration run, one can then fill
    473 histograms of $\delta t_i$ for each pixel which yields then a mean $<\delta t_i>$, comparable to
    474 systematic offsets in the signal delay and a sigma $\sigma(\delta t_i)$ which is a measure of the
     476arrival time of the reference pixel nr. 1 (software numbering). For one calibration run, one can then fill
     477histograms of $\delta t_i$ for each pixel and fit them to the expected Gaussian distribution. The fits
     478yield a mean $\mu(\delta t_i)$, comparable to
     479systematic offsets in the signal delay, and a sigma $\sigma(\delta t_i)$, a measure of the
    475480combined time resolutions of pixel $i$ and pixel 1. Assuming that the PMTs and readout channels are
    476481of a same kind, we obtain an approximate absolute time resolution of pixel $i$ by:
    477482
    478483\begin{equation}
    479 tres_i \approx \sigma(\delta t_i)/sqrt(2)
     484t^{res}_i \approx \sigma(\delta t_i)/sqrt(2)
    480485\end{equation}
    481486
    482 Figures~\ref{fig:reltimesinner10leduv} and~\ref{fig:reltimesouter10leduv} show distributions of $<\delta t_i>$
     487Figures~\ref{fig:reltimesinner10leduv} and~\ref{fig:reltimesouter10leduv} show distributions of $\delta t_i$
    483488for
    484489one typical inner pixel and one typical outer pixel and a non-saturating calibration pulse of UV-light,
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