Today I did some tests with my 2year old ATIK383L+ CCD camera. I am using the camera regularly and you can find some results at my astrophotography page. The camera uses the wellknown KAF8300 17.6mmx13.52m CCD chip with a resolution of 3362×2504 pixels and a pixel size of 5.40µmx5.40µm. The manufacturer promotes it as a camera with very low readnoise of 7electrons, great linearity and with ideal Gaussian shaped bias frames.
So let’s see if that is true for my model.
Linearity
This is the easiest of the performed tests. Thereby the camera was mounted on the focuser of my telescope and the aperture was illuminated with my Flatfield panel. Then several images were taken with increasing exposure times as seen in the table below. Subsequently, the so gained flatfields were corrected for bias and darkcurrent contributions. The resulting mean counts in each individual image were tabulated and plotted against the exposure times showing the linearity of the CCD.
Exp
Time [s] 
ADU 
Poisson
Error [%] 
Fit 1
Error [%] 
Fit2
Error [%] 
Fit3
Error [%] 
Fit4
Error [%] 
1 
650 
3,92 
135,0 



2 
1222 
2,86 
61,7 



3 
1598 
2,50 
51,8 



4 
2108 
2,18 
36,4 



5 
2611 
1,96 
27,4 



6 
3106 
1,79 
21,5 



8 
4111 
1,56 
13,7 
15,8 


10 
5098 
1,40 
9,3 
11,3 


14 
7073 
1,19 
4,2 
6,1 


18 
9045 
1,05 
1,4 
3,2 
7,3 

22 
11009 
0,95 
0,4 
1,4 
4,6 

28 
13911 
0,85 
1,8 
0,0 
2,3 
4,1 
36 
17771 
0,75 
2,9 
1,2 
0,5 
1,8 
44 
21635 
0,68 
3,6 
1,9 
0,7 
0,2 
52 
25353 
0,63 
3,5 
1,8 
1,0 
0,2 
60 
29083 
0,59 
3,5 
1,9 
1,3 
0,6 
70 
33737 
0,54 
3,5 
1,8 
1,5 
1,0 
80 
38357 
0,51 
3,4 
1,7 
1,5 
1,1 
90 
42887 
0,48 
3,1 
1,5 
1,4 
1,1 
95 
45068 
0,47 
2,8 
1,1 
1,1 
0,9 
100 
47214 
0,46 
2,5 
0,8 
0,8 
0,6 
105 
49310 
0,45 
2,1 
0,4 
0,4 
0,2 
110 
51431 
0,44 
1,7 
0,0 
0,2 
0,0 
115 
53484 
0,43 
1,3 
0,4 
0,2 
0,4 
120 
55549 
0,42 
0,9 
0,8 
0,6 
0,7 
125 
57491 
0,42 
0,4 
1,4 
1,1 
1,2 
130 
59456 
0,41 
0,1 
1,9 
1,6 

150 
61486 
0,40 
11,4 



<error> [%] 

14,70 
2,68 
1,56 
0,95 
ATIK383L+ linearity measurement. Linear regression was performed iteratively narrowing down the datarange. Best photometric performance was found in the range above 15000 ADU and below 55000 ADU.
A Linear regression was performed iteratively narrowing down the count range (ADU) in order to find typical errors introduced due to nonlinearity of the CCD. A fit to all data points (red) gives a poor result, as expected, with a typical error of roughly 15 percent (see last row in table above). When limiting the range to values above 1000 ADU and below 60000 ADU a correlation coefficient R of 0.9996 (orange data; note that the value in the plot is R^{2}) is found, which is still worse than the number given by the manufacturer (0.9998). Thus, I definitely cannot recommend doing photometry within the full range of 1000 to 64000 ADU as suggested on the ATIK website. Nevertheless, the linearity seems to be good within a range of 10000 to 60000 ADU (yellow). In that range typical errors are below 2 percent only. The best performance is found between 15000 ADU and 55000 ADU, which is the range I would consider as the photometric one.
Thus, highest photometric precision is possible for countrates above 15000 ADU and below 55000 ADU.
Gain Measurement
There are several methods available to measure the gain. I have chosen the method described by Michael Richmond. So the following steps were performed:
1) a pair of Lflats was taken with varying exposure times (2,4,8,16,32,64 sec)
2) a set of 3 dark frames with the same exposure time was taken
3) individual darks were combined using the average value (masterdarks)
4) masterdarks were subtracted from the appropriate flats
5) sum of each pair of flats was calculated and devided by 2: sum*.fits
6) difference of each pair of flats was calculated: diff*.fits
7) gain is the inverse of the slope of the plot: mean vs. variance, where the variance is: RMS^{2}/2.
IMAGE 
Mean 

IMAGE 
RMS 
Variance 
sum2.fits 
1524 

diff2.fits 
89.0 
3957.8 
sum4.fits 
2747 

diff4.fits 
114.1 
6509.4 
sum8.fits 
5516 

diff8.fits 
159.5 
12720.1 
sum16.fits 
10975 

diff16.fits 
218.5 
23871.1 
sum32.fits 
21841 

diff32.fits 
306.0 
46818.0 
sum64.fits 
43342 

diff64.fits 
426.4 
90908.5 
ATIK383L+ gain measurement. A linear regression (green curve) was conducted on the measurements of the mean response in ADU vs. the variance. The gain is then the inverse of the slope.
The gain is then the inverse of the slope when doing a linear regression of the mean vs. variance plot.
A gain of 0.48 e^{–}/ADU was found for the ATIK383L+.
ReadoutNoise
In order to measure the readoutnoise of the CCD camera, bias frames taken throughout several hours of observations were used. The readnoise was measured following the procedure described here:
1) 9 bias frames were taken and combined using the median (masterbias)
2) the masterbias was subtracted from each individual bias: Rdnoise*.fits
3) readnoise is the standard deviation in these images (see table)
4) finally the masterbias was analysed using the histogram and a Fast Fourier Transform (FFT)
IMAGE 
NPIX 
MEAN 
STDDEV 
MIN 
MAX 
Rdnoise1.fits 
8529394 
0,6629 
19,56 
124,5 
1885 
Rdnoise2.fits 
8529394 
3,382 
19,84 
123,5 
1046 
Rdnoise3.fits 
8529394 
2,212 
19,49 
262 
644 
Rdnoise4.fits 
8529394 
1,562 
19,57 
129 
5063 
RdnoiseB1.fits 
8529394 
0,4971 
20,17 
118 
9360 
RdnoiseB2.fits 
8529394 
0,7299 
19,89 
122 
518 
RdnoiseB3.fits 
8529394 
0,8872 
19,95 
163 
426 
RdnoiseB4.fits 
8529394 
0,467 
19,89 
114 
523 
RdnoiseB5.fits 
8529394 
1,106 
19,95 
116 
709 
I noticed that the biaslevel can vary slightly (order of 20 ADU) during several hours of observations. Therefore, it is the best to keep track on the bias level and take some bias once an hour. For this test, I had to create two individual masterbias frames in order to extract the correct readoutnoise. The result is not affected by that.
The average value of the readoutnoise for my ATIK383L+ is: 19.8 ADU. Using the gain calculated before, a readnoise of 10 electrons was measured.
Thus, the level of the readoutnoise is indeed very low with only 10 e^{–}. However, it is not as low as promoted by the manufacturer.
In a next step, the quality and homogeneity of the masterbias was examined using the histogram and a FFT (see below).
Histogram of the masterbias showing a Gaussianlike and thus random noise dominated distribution
Masterbias image (left) and FFT of the masterbias (right). A column of an increased bias level can be easily identified in the image. Additionally, the FFT indicates the existence of a nonrandom largescale noise pattern.
An examination of the historgram reveals that the bias is of course not an ideal Gaussian as promoted by the manufacturer. However, it is Gaussianlike and thus noise dominated. Furthermore, a column of increased bias level can be identified in the image and after performing a Fourier Transform, it can be seen that some nonrandom pattern exists. This is indicated by the “cross” in the middle of the FFT image. However, the relative value of the pattern is very low.
I would conclude that the camera’s bias indeed is noisedominated and very smooth, certainly allowing for faint details to be detected.
Finally the performed measurements show that the ATIK383L+ is a CCD camera that can be used for scientific photometric applications when limiting the linearity range as suggested. Due to its smooth bias it is furthermore an excellent tool for high quality astrophotography.