Changeset 6519
- Timestamp:
- 02/16/05 14:16:05 (20 years ago)
- File:
-
- 1 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/MagicSoft/TDAS-Extractor/Calibration.tex
r6517 r6519 116 116 \item The reconstructed mean number of photo-electrons lies 4.5 sigma outside 117 117 the distribution of photo-electrons obtained with the inner or outer pixels in the camera, respectively. 118 This criterium cuts out pixelschannels with apparently deviating (hardware) behaviour compared to118 This criterium cuts out channels with apparently deviating (hardware) behaviour compared to 119 119 the rest of the camera readout\footnote{This criteria is not applied any more in the standard analysis, 120 although here, we kept using it}.120 although we kept using it here}. 121 121 \item All pixels with reconstructed negative mean signal or with a 122 122 mean numbers of photo-electrons smaller than one. Pixels with a negative pedestal RMS subtracted … … 128 128 \end{enumerate} 129 129 130 Moreover, the number of events are counted which have been reconstructed outside a 5 sigmaregion130 Moreover, the number of events are counted which have been reconstructed outside a 5$\sigma$ region 131 131 from the mean signal. These events are called ``outliers''. Figure~\ref{fig:outlier} shows a typical 132 outlier obtained with the digital filter applied to a low-gain signaland figure~\ref{fig:unsuited:all}132 outlier obtained with the digital filter applied on a low-gain signal, and figure~\ref{fig:unsuited:all} 133 133 shows the average number of all excluded pixels and outliers obtained from all 19 calibration configurations. 134 134 One can already see that the largest window sizes yield a high number of un-calibrated pixels, mostly … … 162 162 and~\ref{fig:unsuited:23ledsblue} show the resulting numbers of un-calibrated pixels and events for 163 163 different colours and intensities. Because there is a strong anti-correlation between the number of 164 excluded channels and the number of outliers per event, we have chosen to show these numbers together.164 excluded pixels and the number of outliers per event, we have chosen to show these numbers together. 165 165 166 166 \par … … 198 198 One can see that in general, big extraction windows raise the 199 199 number of un-calibrated pixels and are thus less stable. Especially for the very low-intensity 200 \textit{\bf 1 Led\,UV}-pulse, the big extraction windows summing 8 or more slices,cannot calibrate more201 than 50\% 202 of the inner pixels (fig.~\ref{fig:unsuited:1leduv}).This is an expected behavior since big windows203 addup more noise which in turn makes the search for the small signal more difficult.200 \textit{\bf 1\,Led\,UV}-pulse, the big extraction windows -- summing 8 or more slices -- cannot calibrate more 201 than 50\% of the inner pixels (fig.~\ref{fig:unsuited:1leduv}). 202 This is an expected behavior since big windows 203 sum up more noise which in turn makes the search for the small signal more difficult. 204 204 \par 205 205 In general, one can also find that all ``sliding window''-algorithms (extractors \#17-32) discard 206 206 less pixels than the corresponding ``fixed window''-ones (extractors \#1--16). The digital filter with 207 207 the correct weights (extractors \#30-33) discards the least number of pixels and is also robust against 208 slight modifications of its weights (extractors \#28--30). The robustness gets lost when the high-gain and 209 low-gain weights are inverted (extractors \#31--39, see fig.~\ref{fig:unsuited:23ledsblue}). 208 slight modifications of its weights (extractors \#28--30). 210 209 \par 211 210 Also the ``spline'' algorithms on small
Note:
See TracChangeset
for help on using the changeset viewer.