The typical reduction procedure

If you read a paper in the technical astronomy journals, you'll often see the phrase "we applied the standard reduction procedure to our images." What does that mean? It means:

subtract a (master) dark frame
divide by a (master) flatfield frame

Today, your job is to carry out this standard task on a set of images taken on Sep 10, 2003. However, you'll have to do a little extra work first: you'll need to create the master dark and flatfield frames before you can apply them to the target frames.

Here's the overview -- you fill in the details and do the work:

clean out your own directory; remember that you can delete files with the rm command
copy over all the files in the sep10_2003 directory
look at several of the raw target images. Get a feeling for the quality of the pictures.
create a median master dark from the 1-second frames; you'll use this on the 1-second long flatfield images
create a median master dark from the 30-second dark frames; you'll use this on the target images
subtract the 1-second dark from all the flatfield images
create a master flatfield frame
subtract the 30-second dark from all YOUR target images

There are many frames with names like cyaqr_a-010v.fit. Each student should pick one set of 10 frames. Tell me which set you want, and I'll make sure that all 50 images are taken during the class period.
look at several of the dark-subtracted target images. Verify that the hot pixels are gone, and that the images look OK.
prepare to make the flatfield correction. You need to calculate the mean level in the master flatfield frame, so that we can normalize the division in a moment. If your master flatfield is called master_flat.fit, then run the mn command once, like so:
```
                mn master_flat.fit
  
```
The XVista program mn not only calculates the mean level, and prints that value to the screen; it also stores the mean value (and the stdev) into a secret place for future reference. You can peer into the secret place by typing the command xlet.
correct each dark-subtracted frame for the flatfield effect like so:
```
               div target_frame.fit master_flat.fit flat
   
```
where you replace "target_frame.fit" by the name of the target image, and "master_flat.fit" by the name of your master flat image. The keyword "flat" must appear after the names of the two images. It signals the div program to perform the division, pixel-by-pixel, but to multiply the result by the mean of the flatfield frame before storing the result back into the "target_frame.fit" image.
look at one of your images after you have divided by the flatfield frame. Verify that the average value is still roughly the same as it was before, and make sure that the overall pattern of brightness variations has decreased.
Actually, on this particular night (Sep 10, 2003), I wasn't able to acquire flatfield images. The frames you have used are taken from Sep 17, 2003. You will notice that they don't do a very good job of removing the variations in sensitivity...

Cleaned images

The result of your work should be a directory full of "clean" images: CCD frames from which the thermal contribution and variations in sensitivity have been removed. You should be ready to perform the next step in your analysis, whether it is photometry, astrometry, or just plain looking.

Before we move on to measuring the light of the stars in these images, let's figure out just what the subject is. As the image names proclaim, these are pictures of the star "CY Aqr". But -- so what?

make a finding chart of the field using the Aladin tool from SIMBAD
find the orientation of the images. Which way is North? East?
what is the pixel scale? That is, how many arcseconds does each pixel represent?
which star is CY Aqr?
what are the catalog magnitudes of the three or four brightest stars in the field?
just what sort of star is CY Aqr, anyway?

One way to look for information on a particular star is to use SIMBAD's list of stellar properties and references. Another way is to go to the Astrophysics Data Service Abstract Search site. Choose either the "Object name/position" or "Abstract Words/Keywords" box, and type the name of your object. Then click on the "Send Query" button.