Changeset 6666


Ignore:
Timestamp:
02/23/05 16:33:26 (20 years ago)
Author:
hbartko
Message:
*** empty log message ***
Location:
trunk/MagicSoft/TDAS-Extractor
Files:
2 edited

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  • trunk/MagicSoft/TDAS-Extractor/Calibration.tex

    r6650 r6666  
    9090\par
    9191Although we had looked at and tested all colour and extractor combinations resulting from these data,
    92 we refrain ourselves to show here only exemplary behaviour and results of extractors.
     92we restrict ourselves to show here only exemplary behaviour and results of extractors.
    9393All plots, including those which are not displayed in this TDAS, can be retrieved from the following
    9494locations:
     
    107107
    108108\begin{enumerate}
    109 \item The reconstructed mean signal is less than 2.5 times the extractor resolution $R$ from zero.
     109\item The reconstructed mean signal $\widehat{Q}$ is less than 2.5 times the extractor resolution $R$: $\widehat{Q}<2.5\cdot R$.
    110110(2.5 Pedestal RMS in the case of the simple fixed window extractors, see section~\ref{sec:pedestals}).
    111111This criterium essentially cuts out
    112112dead pixels.
    113 \item The reconstructed mean signal error is smaller than its value. This criterium cuts out
     113\item The error of the mean reconstructed signal $\delta \widehat{Q}$ is larger than the mean reconstructed signal $\widehat{Q}$:
     114 $\delta \widehat{Q} > \widehat{Q}$. This criterion cuts out
    114115signal distributions which fluctuate so much that their RMS is bigger than its mean value. This
    115116criterium cuts out ``ringing'' pixels or mal-functioning extractors.
     
    121122\item All pixels with reconstructed negative mean signal or with a
    122123mean numbers of photo-electrons smaller than one. Pixels with a negative pedestal RMS subtracted
    123 sigma occur, especially when stars are focused onto that pixel during the pedestal taking (resulting
     124sigma occur, especially when stars are focused onto that pixel during the pedestal run (resulting
    124125in a large pedestal RMS), but have moved to another pixel during the calibration run. In this case, the
    125126number of photo-electrons would result artificially negative. If these
     
    129130
    130131Moreover, the number of events are counted which have been reconstructed outside a 5$\sigma$ region
    131 from the mean signal. These events are called ``outliers''. Figure~\ref{fig:outlier} shows a typical
     132from the mean signal $<\widehat{Q}>$. These events are called ``outliers''. Figure~\ref{fig:outlier} shows a typical
    132133outlier obtained with the digital filter applied on a low-gain signal, and figure~\ref{fig:unsuited:all}
    133134shows the average number of all excluded pixels and outliers obtained from all 19 calibration configurations.
     
    229230
    230231\begin{equation}
    231 Var(S) = F^2 \cdot Var(N_{phe}) \cdot \frac{<S>^2}{<N_{phe}>^2}
     232Var[S] = F^2 \cdot Var[N_{phe}] \cdot \frac{<S>^2}{<N_{phe}>^2}
    232233\label{eq:excessnoise}
    233234\end{equation}
     
    236237and assuming that the variance of the number of photo-electrons is equal
    237238to the mean number of photo-electrons (because of the Poisson distribution),
    238 one obtains an expression to retrieve the mean number of photo-electrons  impinging on the photo-multiplier from the
     239one obtains an expression to retrieve the mean number of photo-electrons  released at the photo-multiplier cathode from the
    239240mean extracted signal, $\widehat{S}$, and the RMS of the extracted signal obtained from
    240241pure pedestal runs $R$ (see section~\ref{sec:ffactor}):
    241242
    242243\begin{equation}
    243 <N_{phe}> \approx F^2 \cdot \frac{<\widehat{S}>^2}{Var(\widehat{S}) - R^2}
     244<N_{phe}> \approx F^2 \cdot \frac{<\widehat{S}>^2}{Var[\widehat{S}] - R^2}
    244245\label{eq:pheffactor}
    245246\end{equation}
     
    247248In theory, eq.~\ref{eq:pheffactor} must not depend on the extractor! Effectively, we will use it to test the
    248249quality of our extractors by requiring that a valid extractor yields the same number of photo-electrons
    249 for all pixels of a same type and does not deviate from the number obtained with other extractors.
     250for all pixels individually and does not deviate from the number obtained with other extractors.
    250251As the camera is flat-fielded, but the number of photo-electrons impinging on an inner and an outer pixel is
    251252different, we also use the ratio of the mean numbers of photo-electrons from the outer pixels to the one
     
    265266There is a considerable difference for all shown non-standard pulses. Especially the pulses from green
    266267and blue LEDs
    267 show a clear dependency  of the number of photo-electrons on the extraction window. Only the largest
     268show a clear dependence  of the number of photo-electrons on the extraction window. Only the largest
    268269extraction windows seem to catch the entire range of (jittering) secondary pulses and get the ratio
    269270of outer vs. inner pixels right. However, they (obviously) over-estimate the number of photo-electrons
     
    384385Figure~\ref{fig:linear:phevscharge4} shows the conversion factor $c_{phe}$ obtained for different light intensities
    385386and colours for three exemplary inner and three exemplary outer pixels using a fixed window on
    386 8 FADC slices. The conversion factor seems to be linear to a good approximation,
    387 except for two cases:
     3878 FADC slices. The conversion factor seems to be linear to a good approximation, with the following restrictions:
    388388\begin{itemize}
    389389\item The green pulses yield systematically low conversion factors
     
    394394\end{itemize}
    395395
    396 We conclude that, apart from the two reasons above,
     396We conclude that, with the above restrictions,
    397397the fixed window extractor \#4 is a linear extractor for both high-gain
    398398and low-gain regions, separately.
     
    402402using an integrated spline and a fixed window with global peak search, respectively, over
    403403an extraction window of 8 FADC slices. The same behaviour is obtained as before. These extractors are
    404 linear to a good approximation, except for the two cases mentionned above.
     404linear to a good approximation, except for the two cases mentioned above.
    405405\par
    406406
     
    447447\par
    448448Figure~\ref{fig:linear:phevscharge20} shows the conversion factors using a sliding window of 6 FADC slices.
    449 The linearity is maintained like in the previous examples, except for the smallest signals the effect
     449The linearity is maintained like in the previous examples, except that for the smallest signals the effect
    450450of the bias is already visible.
    451451\par
     
    463463Figure~\ref{fig:linear:phevscharge23} shows the conversion factors using the amplitude-extracting spline
    464464(extractor \#23).
    465 Here, the linearity is worse than in the previous sample. A very clear difference between high-gain and
     465Here, the linearity is worse than in the previous examples. A very clear difference between high-gain and
    466466low-gain regions can be seen as well as a bigger general spread in conversion factors. In order to investigate
    467467if there is a common, systematic effect of the extractor, we show the averaged conversion factors over all
     
    514514
    515515Looking at figure~\ref{fig:linear:phevscharge25}, one can see that raising the integration window
    516 to two  effective FADC slices in the high-gain and three effective FADC slices in the low-gain
     516by two  effective FADC slices in the high-gain and three effective FADC slices in the low-gain
    517517(extractor \#25), the stability is completely resumed, except for
    518518a systematic increase of the conversion factor above 200 photo-electrons.
     
    545545expected one. The effect is not as problematic as it may appear here, because the actual calibration
    546546will not calculate the number of photo-electrons (with the F-Factor method) for every signal intensity.
    547 Thus, one possible reason for the instability falls away in the cosmics analysis. However, the limits
     547Thus, one possible reason for the instability is not relevant in the cosmics analysis. However, the limits
    548548of this extraction are visible here and should  be monitored further.
    549549
     
    590590
    591591The calibration LEDs
    592 deliver a fast-rising pulses, uniform over the camera in signal size and time.
    593 We estimate the time-uniformity to better
    594 than 300\,ps, a limit due to the different travel times of the light between inner and outer parts of the
    595 camera.
    596 
     592deliver fast-rising pulses, uniform over the camera in signal size and time.
     593We estimate the time-uniformity to as good as about~30\,ps, a limit due to the different travel times of the light
     594from the light source to the inner and outer parts of the camera. For cosmics data, however, the staggering of the
     595mirrors limits the time uniformity to about 600\,ps.
     596\par
    597597The extractors \#17--33 are able to compute the arrival time of each pulse.
    598598Since the calibration does not permit a precise measurement of the absolute arrival time, we measure
     
    609609systematic delays in the signal travel time, and a sigma $\sigma(\delta t_i)$, a measure of the
    610610combined time resolutions of pixel $i$ and pixel 1. Assuming that the PMTs and readout channels are
    611 of a same kind, we obtain an approximate time resolution of pixel $i$:
     611of the same kind, we obtain an approximate time resolution of pixel $i$:
    612612
    613613\begin{equation}
     
    649649(fig.~\ref{fig:reltimesinnerledblue2} bottom), the distribution is perfectly Gaussian and the resolution good,
    650650however a rather slight change from the blue calibration pulse weights to cosmics pulses weights (top)
    651 adds a secondary peak of events with mis-reconstructed arrival times.
     651adds a secondary peak of events with mis-reconstructed arrival times. In principle, the $\chi^2$ of the digital filter
     652fit gives an information about whether the correct shape has been used.
    652653
    653654\begin{figure}[htp]
  • trunk/MagicSoft/TDAS-Extractor/Criteria.tex

    r6640 r6666  
    3030\subsection{Bias and Mean-squared Error}
    3131
    32 Consider a large number of same signals $S$. By applying a signal extractor
     32Consider a large number of identical signals $S$, corresponding to a fixed number of photo-electrons. By applying a signal extractor
    3333we obtain a distribution of estimated signals $\widehat{S}$ (for fixed $S$ and
    3434fixed background fluctuations $BG$). The distribution of the quantity
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