Change log: PM 11/04/19 This is a first to introduce the principles of CCD data reduction and analysis (i.e. photometry). Includes a rough tutorial to do basic reduction steps with IRAF. Feel free to add comments.

A quick guide to data analysis

Data reduction

Why the data need calibration

Images of an astronomical object taken with a CCD camera will include many unwanted signals of various origin. The goal of the calibration is to remove these effects, so that the pixel values of the calibrated images are an accurate representation of the sky light that fell on the camera during your observations.

This quick tutorial will work you through the standard reduction steps, with an example of analysis with IRAF.

Effects to correct

Please comments if the level of details is too low or too high

• Bias When the CCD images are read, a small voltage is applied to all pixels. This electrical offset is called bias. It has to be subtracted, so that the zero points of the CCD output and the pixel-value scales coincide.

• Dark Current The thermal agitation of silicon in CCD produce electrons, even when no light fall on the CCD (hence the name 'dark' current). Dark current is always present, i.e. also in your sky images. It scales linearly with exposure time, at a rate dependent on the CCD temperature, and needs to be subtracted

• Non-uniformity (flat-fielding) The conversion of light to electrical signal on the camera varies with position, both on small scales (pixel-to-pixel), due to changing quantum efficiency of individual pixels, and on larger scales, because of vignetting and dust shadowing. To correct these effects, we need to divide the data by the normalised sensitivity of each pixel. This is estimated by observing a (theoretically) uniform source of light. The variations observed in this exposure, called a flat-field, are a measure of the non-uniformities of the camera. Note that the flat-field(s) need to be first corrected for the two effects described above.

• Cosmic rays Cosmic rays (CR) produce a stream of high-energy particles that interact with the camera, leaving bright spots or tracks in the images. By combining multiple images using the average, or better, the median of the pixel values at each pixel, the extreme values produced by CR hits are easily spotted and removed. The image combinations are often done with a rejection algorithm to remove extreme variations. If an obvious CR track remains in a combined image, it is better to find out from which individual image it originate, and remove the CR prior to combining the images.

What do you need for data reduction

T.B.D.: Describe which calibration frames to obtain (bias, dark, flat-field)

In practice: an example of calibration with IRAF

T.B.D.: Show working example of image calibration with iraf, with commented commands and results (use verbatim ?)

Photometry

T.B.D.