Changeset 5884 for trunk/MagicSoft/TDAS-Extractor
- Timestamp:
- 01/18/05 17:42:12 (20 years ago)
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trunk/MagicSoft/TDAS-Extractor/Performance.tex
r5789 r5884 353 353 \par 354 354 Moreover, 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 correctlyfor the green and blue pulses.355 photo-electrons correctly between outer to inner pixels for the green and blue pulses. 356 356 \par 357 357 The extractor MExtractTimeAndChargeDigitalFilter seems to be stable against modifications in the … … 360 360 hold any more for the low-gain, as can be seen in figure~\ref{fig:phe:23ledsblue}. There, the application 361 361 of 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 perinner pixels.362 and also a too low ratio of outer vs. inner pixels. 363 363 \par 364 364 All sliding window and spline algorithms yield a stable ratio of outer vs. inner pixels in the low-gain, 365 365 however 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 r aises by about a factor 1.4,366 Note that in figure~\ref{fig:phe:23ledsblue}, the number of photo-electrons rises by about a factor 1.4, 367 367 which is slightly higher than in the case of the high-gain channel (figure~\ref{fig:phe:2ledsgreen}). 368 368 \par 369 Concluding, there is no wfixed window extractor yielding the correct number of photo-electrons369 Concluding, there is no fixed window extractor yielding the correct number of photo-electrons 370 370 for the low-gain, except for the largest extraction window of 10 low-gain slices. 371 371 Either the number of photo-electrons itself is wrong or the ratio of outer vs. inner pixels is 372 372 not 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 not374 stable against exchanging the pulse form to match the slimmer high-gain pulses, though.373 account the after-pulse behaviour of the light pulser itself. The digital filter seems to be 374 unstable against exchanging the pulse form to match the slimmer high-gain pulses, though. 375 375 376 376 377 377 \subsubsection{Linearity Tests} 378 378 379 In this section, we test the lineary of the extractors. As the photo-multiplier is a linear device over a 379 In this section, we test the lineary of the extractors. As the photo-multiplier and the subsequent 380 optical transmission devices~\cite{david} is a linear device over a 380 381 wide dynamic range, the number of photo-electrons per charge has to remain constant over the tested 381 382 linearity region. We will show here only examples of extractors which were not already excluded in the 382 383 previous section. 383 384 \par 384 A first test concerns the stability of the conversion factor photo-electrons per FADC counts over the 385 tested intensity region. 385 A first test concerns the stability of the conversion factor: mean number of averaged photo-electrons 386 per FADC counts over the 387 tested intensity region. A much more detailed investigation on the linearity will be shwon in a 388 separate TDAS~\cite{tdas-calibration}. 386 389 387 390 … … 459 462 \subsubsection{Time Resolution} 460 463 461 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 464 The extractors \#17--32 are able to extract also the arrival time of each pulse. The calibration 465 delivers a fast-rising pulse, uniform over the camera in signal size and time. 466 We estimate the time-uniformity to better 463 467 than 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 measure465 the relative arrival time , i.e.468 camera. Since the calibraion does not permit a precise measurement of the absolute arrival time, we measure 469 the relative arrival time for every channel with respect to a reference channel (usually pixel Nr.\,1): 466 470 467 471 \begin{equation} … … 470 474 471 475 where $t_i$ 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 476 arrival time of the reference pixel nr. 1 (software numbering). For one calibration run, one can then fill 477 histograms of $\delta t_i$ for each pixel and fit them to the expected Gaussian distribution. The fits 478 yield a mean $\mu(\delta t_i)$, comparable to 479 systematic offsets in the signal delay, and a sigma $\sigma(\delta t_i)$, a measure of the 475 480 combined time resolutions of pixel $i$ and pixel 1. Assuming that the PMTs and readout channels are 476 481 of a same kind, we obtain an approximate absolute time resolution of pixel $i$ by: 477 482 478 483 \begin{equation} 479 t res_i \approx \sigma(\delta t_i)/sqrt(2)484 t^{res}_i \approx \sigma(\delta t_i)/sqrt(2) 480 485 \end{equation} 481 486 482 Figures~\ref{fig:reltimesinner10leduv} and~\ref{fig:reltimesouter10leduv} show distributions of $ <\delta t_i>$487 Figures~\ref{fig:reltimesinner10leduv} and~\ref{fig:reltimesouter10leduv} show distributions of $\delta t_i$ 483 488 for 484 489 one typical inner pixel and one typical outer pixel and a non-saturating calibration pulse of UV-light,
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