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1\section{Criteria for the Optimal Signal Extraction}
2
3The goal for the optimal signal reconstruction algorithm is to compute an unbiased estimate of the strength and arrival time of the
4Cherenkov signal with the highest possible resolution for all signal intensities. The MAGIC telescope has been optimized to
5lower the energy treshold of observation in any respect. Particularly the choice for an FADC system has been made with an eye on the
6possibility to extract the smallest possible signals from air showers. It would be inconsequent not to continue the optimization procedure
7in the signal extraction algorithms and the subsequent image cleaning.
8\par
9In the traditional image analysis, one takes the decision whether the extracted signal of a certain pixel is considered as signal or background.
10Those considered as signal are further used to compute the image parameters while the background ones are simply rejected. The calculation
11of the second moments of the image ``ellipse'' usually fails when applied to un-cleaned images, therefore the decision is yes or
12no\footnote{This restriction is not necessary any more in all advanced analyses using likelihood fits to the images or fourier transforms. Thereby any bias of the reconstructed signal leads to potentially wrong results.}.
13Moreover,
14already low contributions of mis-estimated background can degrade the resolution of the image parameters considerably. If one wants to
15lower the threshold for signal recognition, it is therefore mandatory to increase the efficiency with which the background is recognized as
16such. If the background resolution is bad, the signal threshold goes up and vice versa.
17
18Also an accurate determination of the signal arrival time may help to distinguish between signal and background. The signal arrival times vary smoothly from pixel to pixel while the background noise is randomly distributed in time.
19
20\par
21One cuts on the probability that the reconstructed charge is due to background. This yields a lower reconstructed signal limit for an event
22being considered as signal at all. The lower the limit (keeping constant the background probability), the lower the analyzed energy
23threshold.
24\par
25Furthermore, the algorithm must be stable with respect to changes
26in observation conditions and background levels and between signals obtained from gamma or hadronic showers or from muons.
27
28Also the needed computing time is of concern.
29
30\subsection{Bias and Mean-squared Error}
31
32Consider a large number of same signals $S$. By applying a signal extractor
33we obtain a distribution of estimated signals $\widehat{S}$ (for fixed $S$ and
34fixed background fluctuations $BG$). The distribution of the quantity
35
36\begin{equation}
37X = \widehat{S}-S
38\end{equation}
39
40has the mean $B$ and the Variance $R$ defined as:
41
42\begin{eqnarray}
43 B \ \ \ \ = \ \ \ \ \ \ <X> \ \ \ \ \ &=& \ \ <\widehat{S}> \ -\ S\\
44 R \ \ \ \ = \ <(X-B)^2> &=& \ Var[\widehat{S}]\\
45 MSE \ = \ \ \ \ \ <X^2> \ \ \ \ &=& \ Var[\widehat{S}] +\ B^2
46\end{eqnarray}
47
48The parameter $B$ is also called the {\textit{\bf BIAS}} of the estimator and $MSE$
49the {\textit{\bf MEAN-SQUARED ERROR}} which combines the variance of $\widehat{S}$ and
50the bias. Both depend generally on the size of $S$ and the background fluctuations $BG$,
51thus: $B = B(S,BG)$ and $MSE = MSE(S,BG)$.
52
53\par
54Usually, one measures easily the parameter $R$, but needs the $MSE$ for statistical analysis (e.g.
55in the image cleaning).
56However, only in case of a vanishing bias $B$, the two numbers are equal. Otherwise,
57the bias $B$ has to be known beforehand. Note that every sliding window extractor has a
58bias, especially at low or vanishing signals $S$.
59
60\subsection{Linearity}
61
62The reconstructed signal should be proportional to the total integrated charge in the FADCs
63due to the PMT pulse from the Cherenkov signal. A deviation from linearity is usually obtained in the following cases:
64
65\begin{itemize}
66\item At very low signals, the bias causes as too high reconstructed signal (positive $X$).
67\item At very high signals, the FADC system goes into saturation and the reconstructed signal becomes too low (negative $X$).
68\item Any error in the inter-calibration between the high- and low-gain acquisition channels yield an effective deviation from
69linearity.
70\end{itemize}
71
72The linearity is very important for the reconstruction of the shower energy and further the obtained energy spectra from the
73observed sources.
74
75\subsection{Low Gain Extraction}
76
77Because of the peculiarities of the MAGIC data acquisition system, the extraction of the low-gain pulse is somewhat critical:
78The low-gain pulse shape differs significantly from the high-gain shape. Due to the analogue delay line, the low-gain pulse is
79wider and the integral charge is distributed over a longer time window.
80
81The time delay between high-gain
82and low-gain pulse is small, thus for large pulses,
83mis-interpretations between the tails of the high-gain pulse and the low-gain pulse might occur. Moreover, the total recorded time window
84is relatively small and at late high-gain pulses, parts of the low-gain pulse might already reach out of the recorded FADC window.
85A good extractor must be
86stably extracting the low-gain pulse without being confused by the above points. This is especially important since the low-gain
87pulses are due to the large signals with a big impact on the image parameters, especially the size parameter.
88
89\subsection{Stability}
90
91
92
93
94
95\subsection{Treatment of Calibration Pulses}
96
97
98
99\subsection{Applicability for Different Sampling Speeds / No Pulse Shaping.}
100The current read-out system of the MAGIC telescope \cite{Magic-DAQ} with 300 MSamples/s is relatively slow compared to the fast pulses of about 2 ns FWHM of Cherenkov pulses. To acquire the pulse shape an artificial pulse shaping to about 6.5 ns FWHM is used. Thereby also more LONS is integrated that acts as noise.
101
102For 2 ns FWHM fast pulses a 2 GSamples/s FADC provides at least 4 sampling points. This permits a reasonable reconstruction of the pulse shape. First prototype tests with fast digitization systems for MAGIC have been successfully conducted \cite{GSamlesFADC}. The signals have been reconstructed within the common MAGIC Mars software framework.
103
104
105\ldots {\textit Some comments by Hendrik ...}
106
107\subsection{CPU Requirements}
108\ldots {\textit The needed CPU time for each extractor}
109
110
111
112
113\subsection{Pulpo Pulses}
114\subsection{Cosmics Data?}
115The results of this subsection are based on the following runs taken
116on the 21st of September 2004.
117\begin{itemize}
118\item{Run 39000}: OffCrab11 at 19.1 degrees zenith angle and 106.2
119azimuth.
120\item{Run 39182}: CrabNebula at 19.0 degrees zenith angle and 106.0 azimuth.
121\end{itemize}
122
123
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