After eliminating obvious cosmic rays (I am using the term 'Cosmic Rays' as an all-embracing term of abuse) the dark images dark, 11ba, 11bb, 1b-26a, d142355, d142359, d150004 etc, appear more or less indistinguishable from gaussian noise. There is, as Tom pointed out, a bit of a ramp at the start of each image but this is small and appears consistent from image to image and should be completely eliminated by any sort of dark subtraction so there is no need to fix it.
After much manipulation, I have come up with various estimates
of the electronic noise ... the best ones agree pretty well with
Tom's. Damn! All that effort and not even anything to argue about.
Bennett: 12.2 electrons.
Tom: 12.3 electrons.
See Chapter and Verse below
With the eye of faith, optimum contrast and strategic use of peripheral vision, I have almost convinced myself there is something consistent with a period of 4 pixels. I propose to spend the next month getting my FFT routines to run on image data so I can really get nit-picky. Whatever it is, it is at such a low level that it will have no effect in the real world. Congratulations, Tom! I think you got things grounded!
The other 2 images (11fa, 11fb) from which Tom calculated the gain are a different story. The following clip is from 11fa and has been put through a logarithmic compression to bring up the contrast in the noise. OK - I could have done a better job. Next time.
Yes - those things are the dreaded frost crystals. I felt sure when I calculated the rms difference between the full images and got an answer that agreed with Tom's that we must both be wrong! But painstaking avoidance of all the icefloes gave exactly the same answer and the final removal of one last cosmic ray reduced the rms by half a percent giving a final reciprocal gain estimate of:
Bennett: 3.0 electrons/e- (actually 2.96 but I rounded it up)
Tom: 2.9
There! Hard work pays off.
The statistics are not as straightforward for these bright images; histograms show strong odd/even bias or in another case a pattern with a period of 4 adu. Not to be confused with the spatial period of 4 pixel mentioned above. There is also more than a hint of a spatial pattern at 16 pixels at right angles to the 4 pixel one. Lots of scope for future nit-picking. On the other hand, the pixels appear pretty uniform. One interpretation of the statistics is that pixel sensitivity is random with an rms variation of around 1% which ain't too bad. We are going to need good flats with less ice.
The bad new is that the cosmic rays are mostly not single pixels. In the main, they look just like well focussed stars or like galaxies or close pairs. This means that it is going to be very difficult to get rid of them without losing several classes of real objects that we are supposed to be looking for. Ouch!
Part of 11ba. Ok - this doesn't come out too well. I got some
improvement by jiggling the brightness and contrast on my monitor.
Take the image away and look at it with some real software.
The images started out as TIF and had to be JPEG'd to get them
on the Net. Minimum compression has left them bearing a slight
resemblance to the original. If you want the real thing, I will
e-mail it.
The same part of 11bb.
The difference between the two previous images. Mid grey means
no difference. The white dots are cosmic rays from image 11ba and
the black ones are from image 11bb. Even on this scale, I can
tell on my display that at least the black ones are blobs
rather than dots. I used bidirectional logarithmic compression
to bring up the noise.
Selected regions, no large cosmic rays
Image Mean var sd d142359 62.0 7.9 d150004 42.0 6.5 Difference 84.6 9.2
If we now scale the variance of the difference in the ratio of the separate variances (a hairy process!):
Scaled var sd
d142359 50.4 7.1
d150004 34.1 5.8
Now extrapolate to zero dark current assuming d142359 got two units and d150004 got 1 unit (OK - it should be 100:51 with a readout time of 50 seconds but I'm too lazy to go back to the spreadsheet and fix the factor) (Method 1 below)
var sd
Extrapolated 17.8 4.2 = 12.2 electrons taking gain as 2.9 adu/e-
Compare Tom's estimate of 12.3 using files 11ba and 11bb
Wow! The same answer from a different data set. Too good to be true.
Alternatively, (Method 2 below) using gain = 2.9
Mean variance from Difference 42.3 Estimated dark current noise 17.4 Electronic var 24.9 sd 5.0 = 14.4 electrons
Which is not very different.
Dark current noise variance is estimated as 1.5 ((1+2)/2) times change in mean (adu) times gain (adu/electron - the reciprocal of the "gain" Tom used).
Using the whole images, cosmic rays on both 11ba and 11bb plus icicles all over 11fa and 11fb
Average var sd Average sd
11ba -24650.7 39.4 6.3 11fa -3066.8 478
11bb -24637.1 27.5 5.2 11fb -3006.7 482
Diff. -13.6 65.7 8.1 Diff. -60.1 121
R 0.0175 R 0.9682
The low value of the correlation, R, for 11ba and11bb is excellent news - there isn't much there except uncorrelated noise. The high value for 11fa and 11fb says that in this case most of the junk is fixed: the icicles didn't move much between the exposures.
Estimating the dark current noise as above - assuming the exposures are the same:
Mean variance from Diff. 32.8 Estimated dark current noise 7.1 Electronic var 25.8 sd 5.1 = 14.7 electrons
Using selected bits avoiding most cosmic rays
Average var sd Average sd
11ba -24650.8 23.1 4.8 11fa -3014.3 238
11bb -24637.1 29.7 5.5 11fb -2952.3 239
Diff. 51.7 7.2 121
R 0.0197 R 0.8707
The correlation between 11fa and 11fb is still high. Most of the signal is variation in pixel sensitivity.
For dark files, 11ba and 11bb:
Mean variance from Diff. 25.9 adu^2 Estimated dark current noise 7.1 Electronic var 18.8 sd 4.3 = 12.6 electrons
So getting clear of (most of) the cosmic rays brings the answer back pretty close to Tom's.
The major difference in going to the selected, cleaner, area is a big reduction in the variance of the individual flat files. The variance of the difference is essentially unchanged - a coincidence. Modelling the total noise as the sum of random variation in pixel sensitivity plus the root n electron noise plus the electronic noise we can estimate:
For flat files, 11fa and 11fb:
Total variation 238 digits Pixel variation 222 digits = 1.03% rms Noise part 86 digits
Estimating (reciprocal) gain as change in average value between the dark files and the illuminated ones divided by change in variance gives 2.96 e-/adu which rounds up to 3.0. Hooray! A different answer from Tom's 2.9.
The noise is modelled as a random superposition of electronic
noise plus the random fluctuations in the dark and photoelectric
charge. If the total charge is on average n electrons, the variance
is taken as n electrons and the standard deviation as root(n).
Define
d dark electrons in unit time: 2d in twice the time f photoelectrons in unit time for the flat image e electronic noise A Gain, digits per electron V0 Digits out for zero electrons
Then
Case Mean digits Variance digits^2 Dark d V0+Ad d+e A^2(d+e) Dark x2 2d V0+2Ad 2d+e A^2(2d+e) Flat d+f V0+A(d+f) d+f+e A^2(d+f+e)
So from the digitized output one can estimate
A = (var(Flat) - var(Dark))/((mean(Flat) - mean(Dark)) e = (2var(Dark) - var(Dark x2))/A^2
which is the first method used above. Since the variances are not that well determined, especially with the odd cosmic ray, this is not the best method. Alternatively one can proceed as follows giving the second method used above.
Ad = mean(Dark x2) - mean(Dark)
A^2(1.5d+e) = (var(Dark) + var(Dark x2))/2
e = {(var(Dark) + var(Dark x2))/2
- 1.5A(mean(Dark x2) - mean(Dark))}/A^2