Houk and Wheeler also provide compelling computational evidence for the importance of direct interaction in pi stacking.  In their analysis of substituted benzene dimers in a sandwich conformation, they were able to recapitulate their findings using an exceedingly simple model where the substituted benzene, Ph-X, was replaced by H-X. Remarkably, this crude model resulted in the same trend in relative interaction energies, and correlated strongly with the values calculated for Ph-X. This finding suggests that substituent effects in the benzene dimer are due to direct interaction of the substituent with the aromatic ring, and that the pi system of the substituted benzene is not involved. This latter point is expanded upon below.
Now we have fifty photos of the sky and fifty photos of the inside of your camera's eyelids. What next?
Well, if you're using software like RotAndStack or DeepSkyStacker, download your photos to your computer, remove any you don't want (if they have clouds on them, trails from aeroplanes flying overhead or other things you don't want) and open them with the software. It does all the tedious alignment, stacking and other bits and pieces for you. All you will have to do is to tweak some settings for the best results, and edit the levels once the stacking has been done for the best brightness balance.
The software is doing a few tasks that you can do by hand, but it's incredibly tedious. First it aligns all the photos so that the stars are in the same place. Good stacking software will save copies of your photos once it's aligned them so you can play with them in Photoshop if you want to by opening all the photos as layers.
Next, it does dark field subtraction . Sensor noise isn't entirely random- your camera's sensor will have a pattern to where the noise appears. On my camera, the noise tends to be brighter in the middle, fading to darker at the sides with a brighter patch at the bottom- see the image. Your stacking software will work our your camera's noise profile from the dark photos you took with the lens cap on. Subtracting this from the image means that whatever is left should be truly random noise distributed evenly over the image, so your end photo won't have brighter and darker regions.
Lastly it stacks all the photos up and takes the average of each pixel. This is the statistical wizardry that finds stars too dim to make out in any single exposure by reducing background noise. It may also save an image showing the brightest value seen for each pixel- this is usually a compromise, more speckly than the averaged image but with more faint stars visible.
At this point you have an averaged image which contains as much detail as you are going to get from your raw photos. It's now up to you to tweak the light levels of your stack to make your image look better. Tthe aim is to adjust the levels so that the background grey in the image is just darkened to black, and all levels above that are lightened to make the stars more visible. You can do this in your favourite image editor, where the Curves operator comes in very handy, but it's out of the scope of this Instructable to explain that.
Finally, I can't leave out a mention of GuiltyPixel's instructable on astrophotography . He goes into way more detail than I have here, and if you want to know more about the subject it's well worth a read. Incidentally, I was just about to publish this Instructable last November when his was published first, and I was so dispirited by how much better it was that I put off publishing mine until now :)