Name:_____________________________________________________________ Due Date:_________ Score: ________ / 30

Astronomy 480 - IRAF Exercise I
Introduction

You will hear astronomers talk about taking an image. You will also hear the terms flatfield frames (flats), dark frame (darks), bias frames (biases). What’s the difference between a frame and an image? For our purposes, we will define the frame as the entire read-out from a chip, including any overscan regions. We will define the image as that portion of the frame that will have the information that we want, the objects that we are observing. So, in the case of a flat, dark, or bias, the image part of the frame would be the same pixel ranges as that which would contain the science. At the right is a copy of what the DS9 tool displayed for test-f2.fits. The smeared region can be seen at the top-left. There appears to be at least 1 bad column. The scaling has ben adjusted to highlight the image area (light grey) and the overscan region (black). In this CCD, there is two overscan regions: one vertical and one horizontal.

Part 1 – Examining test-f1.fits

Bring up the image test-f1.fits on the DS9 tool, opening it using the DS9 drop-down menu. Find a nice region in the overscan part of the frame that has no defects. The region around [1040:1140,500:600] looks good:
imstat test-f1[1040:1140,500:600].

1. <2 pts> Use imstat to determine the mean and standard deviation of a region containing about 10,000 pixels within the overscan region of the device. Use imstat to determine the mean and standard deviation of a region containing about 10,000 pixels within the imaging region of the device. Be sure to avoid bad columns and any cosmic rays that would distort the statistics.

2. <1 pt>Use imhist to plot the histogram of the pixel values for each of these regions. You should either epar imhist or use the command line argument lo- to suppress log scaling on the y-axis (You can also change the number of bins used.):
   
   ecl>epar imhist
   OR
   ecl>imhist lo-
   Show your plot to your instructor or TA and get your efforts initialled here: __________

3. <3 pts> Does the plot of the overscan region look like a Gaussian or a Poisson distribution? How about the plot of the image region? Compare thte two plots and explain the difference. Are these what you might have expected?

Part II – Examining test-f2.fits

Display the image test-f2.fits in another DS9 frame. You will need to take a look at the image header.

4. <1 pt> Where was this image taken, with what size of a telescope, and with what instrument and detector?
   
   
5. <1 pt> On what date was the observation made?
   
   
6. <1 pt> How long was the exposure (exposure times are in seconds)?
   
   
7. <1 pt> How many rows are there in the image? ______ How many are there in the frame? ________
   
   
8. <1 pt> How many columns are there in the image? ______ How many are there in the frame? ________
   
   
9. <1 pt> For the image part of this CCD, what are the first and last pixels read out? Convention: [column (x), row (y)] coordinates

First one read out: ___________ Last one read out: ___________

10. <2 pts> Use imstat to find the total number of pixels. Does this number correspond to the image part or the entire frame? Is this number confirmed in the image header?
    
    
11. <1 pt> There are "overscan" pixels in this frame, pixels which were never exposed to light during the exposure (and that do not physically even exist). How many overscan pixels are at the end of each row? How many overscan rows occupy the top of the image?
    

Overscan pixels per row: _________ Number of overscan rows: __________

12. <1 pt> There is a region on this detector where the charge is "smeared" out due to poor charge transfer efficiency. What general region (specify columns) is afflicted the worst?
    
    
13. <2 pts> The average value in the overscan region is called the ‘bias" level. Use the "c" and "l" utilities in imexamine to determine how much the bias value varies in the overscan region. Do you think it could be subtracted as a simple scalar value from the entire array, or should it be determined and subtracted row by row? Explain your logic.
    
    
14. <3 pts> You can get a sense of the charge transfer efficiency (CTE) by looking at how rapidly the intensity falls in the overscan region. On this particular detector, is the parallel (between rows) or serial (between columns) CTE better? How can you tell, and, specifically, why would this be?
    
    

Part III – Examining photo1.fits and bias_ave_050206.fits

15. <3 pts> Display photo1.fits. Examine the stars at (34,785), (114,852), and (331,364). Comment on the stellar profiles. Explain why one profile is "weird-looking" based upon the fact that this is a 16-bit detector.
    
    
16. <1 pt> The biases that were averaged to form bias_ave_050206.fits were takenusing our setup on the A-Wing deck observatory and an SBIG ST8-XE camera. How many bias frames were averaged?
    
    
17. <2 pts> Display the bias frame. Using the methods described in Part I, state whether or not the bias for this chip is Gaussian. What may be the cause of the bias not being "flat" across the chip (consult Howell if necessary)?
    
    
18. <3 pts> You can view the image header within the DS9 window. What are the axes lengths, in pixels? Is there an overscan region on this chip? What steps would you take to determine the bias level for this chip?