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FUNDAMENTALS OF ASTRONOMICAL IMAGING 1 LABORATORY 1: DIGITAL IMAGING WITH DS9 MATERIALS and EQUIPMENT: • DS9 astronomical imaging software for your platform (available from the website http://hea-www.harvard.edu/RD/ds9) This software is available for Windows XP/NT/2000, Macintosh OSX, Linux, and Solaris. It was formerly known as SAOImage, and is a free and quite powerful standard imaging program for astronomy. • We will run network-ready Windows-based personal computers equipped with web browsers. These are available in the individual student imaging laboratories on the third floor in the Chester F. Carlson Center for Imaging Science (Building 76) and in the Imaging Science Computing Complex in Room 76-2205 (enter through 76-2125). If the individual laboratories are not in use, you may sign them out at room 76-3211. • DS9 software (available from the website http://hea-www.harvard.edu/RD/ds9) • Images to view and process. Many are available from the Space Telescope Science Institute “Digitized Sky Survey”, which is part of the MAST project (Multimission Archive at Space Telescope), which accesses several astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST provides search tools and retrieval support for the following missions at the website: http://archive.stsci.edu/dss/dss_form.html INTRODUCTION: This first lab is intended to familiarize you with the image archive and imaging software. The full laboratory is expected to run for two weeks. DS9 is the latest iteration of the astronomical data visualization program “SAOImage”, which is published by the Smithsonian Astrophysical Observatory in Cambridge MA. It accepts images in the “standard” FITS image format (Flexible Image Transport System), which was developed in the late 1970s as a standard format for interchanging astronomical image data. The format includes a header that contains the relevant “metadata” pertaining to each image, such as the object, telescope used, resolution, plate scale, etc. The format is maintained by a working group of the International Astronomical Union (IAU).http://www.inasan.rssi.ru/iau/iau5/wgfits.html DS9 is available for free for several operating systems: Sun Solaris, Sun Solaris64, Linux, LinuxPPC, SGI, DEC Alpha, Windows 98/ME/NT/2000/XP, and Macintosh OS X (darwin). All versions and platforms support a consistent set of graphical user interface commands and functional capabilities. You may download DS9 yourself and run it on your own computer. FUNDAMENTALS OF ASTRONOMICAL IMAGING 2 PROCEDURE: Part I: Select a cluster and download the image data: 1. Make a small list of the names of “open” star clusters from the on-line catalog of Messier objects: http://www.seds.org/messier. (click on “look at star clusters” which is on the left below the heading “Messier Object of the Week” and “Look at Nebulae”). There are two types of clusters listed: open and globular clusters. We are interested in the open clusters, which typically are “closer” to Earth than the other “globular” clusters. The stars in an open cluster are gravitationally linked and “move” as a group, but the angular separations between individual stars are still rather large so that the individual stars may be separated (“resolved”). Globular clusters are older, farther away, and the stars are crammed tightly together, so it is generally not possible to locate and measure individual resolved stars. You will be looking at TWO DIFFERENT open clusters. a. This website is maintained by the Students for the Exploration and Development of Space, which began at the University of Arizona; you might also want to surf around their website (http://www.seds.org), which has lots of useful information about many types of astronomical objects. Their website is hosted by the Lunar and Planetary Laboratory (LPL), whose website is http://www.lpl.arizona.edu/. 2. After selecting the star clusters, go to the Space Telescope Science Institute’s Digitized Sky Survey (DSS) website, http://archive.stsci.edu/dss/dss_form.html, and fill in the form to obtain the images of a star cluster from your list. The digital images in the survey were created by digitizing photographic plates on an image scanner. To fill in the form and download images: 1. Enter name of the cluster, e.g., “Pleiades” or “M45”, in the “object name” box, and click on “get coordinates”. The Pleiades, also known as the “Seven Sisters” is probably the best known open cluster. It is visible in the winter as the shoulder of Taurus (the bull), rising in the east on December evenings. Most people can see six of the seven brightest stars, but some people can see as many as 13. As an aside, the Japanese name for the Pleiades is “Subaru” – compare the hood ornament of a Subaru to the pattern of the Pleiades. 2. Choose a sky survey to search, and download images in blue light (λ = 400 nm) and in red light (λ = 600 nm) of the star cluster. (You may need to repeat these steps until you find a cluster for which both blue and red images are available.) 3. Choose the “display” option to preview the available images for the cluster. 4. Once you have decided on a cluster to analyze, specify that you want the images in FITS format (the default), and that you want to “download” (rather than “display”) the images. “FITS” is the acronym for “Flexible Image Transport System” which is the standard format for astronomical images (http://fits.gsfc.nasa.gov/). 5. Click “retrieve images” and specify the file name and directory where you want to put the image. Repeat for the second image of the cluster. FUNDAMENTALS OF ASTRONOMICAL IMAGING 3 Part II: Process the Images: 1. Start up DS9 and read in one of the images you just downloaded. 2. Experiment with manipulating the images using DS9. For example: a. Move the cursor across the image, and note how you can measure the locations and intensities (“brightness”) of individual pixels using the real-time display at the top of the user interface. b. Change the image display intensity and contrast, by holding down the right mouse button while moving the cursor on the image. c. Change various attributes of the image display (zoom, scale, color) using the buttons at the top of the image. d. Now load a second image so that you have two images in memory at the same time. The “frame” option on the top row allows you to read in a second image and display it next to the first. This is a handy way to compare red and blue images of the same star cluster side-by-side. Load the second image via “Frame→Tile→New”. Click on the empty half of the screen and open the second image. e. Print each image to a laser or inkjet printer; B&W prints are fine. The images are in Postscript format, which not all printers can handle, but you can convert them to Adobe Acrobat format (“.pdf”) using Acrobat Distiller, which is available on the Imaging Science lab computers. You should convert the images to “negatives” (black stars on white), as it makes the images easier to annotate and saves ink or toner when printing. Part III: Analyze the Images 1. Determine the pixel scale and field of view of each image. The pixel scale is the number of arcseconds subtended by a pixel (60 arcseconds in 1 arcminute, 60 arcminutes in one angular degree). The scale may be computed by measuring the dimensions of the image in pixels and comparing them to the known angular size of the field that was listed in the catalog of the original image. 2. Pick the same stars on the two images (red and blue light); try your best to choose stars that you think are part of the cluste. A saturated image of a star may be distinguished by noting the “gray values” (“brightnesses”) of several pixels in the brightest part of the star. If these all have the same gray value, then you can assume that the image is saturated. A plot illustrating saturation in shown in the Figure. FUNDAMENTALS OF ASTRONOMICAL IMAGING 4 3. Measure the peak pixel intensities (values) of the same stars (at least 10 and preferably 30-50 stars) on each pair of images. Note that the gray values of pixels in the “black sky” are not zero – to get a good measure of the brightness of that star, you must subtract the gray value of the sky measured near the image of each star. This is done by following this procedure: a. Measure the gray value Pp of the pixel with the maximum value for each star; this value should be less than the maximum possible value, which ensures that the image is not overexposed (“saturated”). b. Measure the average gray value of the surrounding sky pixels Ps. c. The value to be plotted is ∆P = Pp - Ps. 4. Make a table for the measurements for each cluster (one table for each cluster). The table will list the coordinates of the star locations (the [x,y] values) for each star you selected, the peak pixel value for that star, the average of the pixel values of nearby sky, and the difference (“star minus sky”), and the logarithm (base-10) of these two numerical values. It is easiest to make this table in a spreadsheet program, such as Excel, which can also evaluate the logarithm; Excel also is available on the laboratory computers. Your laboratory assistant can show you how to do this if you have not done it before. Do this for stars in two different clusters. 5. Compute the ratio of the logarithm of the (sky-subtracted) peak amplitude of the ratio of red-to-blue pixel values for each star to the logarithm of the (skysubtracted) peak pixel value in the red image. Do this for stars in at least two clusters. Plot the logarithm (base-10) of the measured red value on the x-axis and ⎡ ∆P ⎤ the logarithm of the ratio of red/blue on the y-axis: log10 ⎢ red ⎥ vs. log10 [ ∆Pred ] . ⎣ ∆Pblue ⎦ I suggest using a spreadsheet program (such as Excel) for the graph, but note that the graph you are generating is of “independent” points that have no order or sequence. Compare this to the graph of a function, such as y = x 2 + 4 x − 2 . The values on the x-axis listed in order with negative values on the left and positive values on the right. The points on this graph may be legitimately connected with a line. By contrast, the x-values of the points in this lab are determined for stars selected in random order, and thus it makes no sense to connect the data points by lines. Rather you want to just plot the points. The option to do this in Excel is called “XY-Scatter.” The result will be just the plot of the data points. Do this for both clusters ON THE SAME GRAPH, but plot the points for the stars in the two clusters with different colors and/or (preferably “and”) with different symbols. With luck, the actual colors of the stars in the two clusters will differ and thus appear in different regions of the plot. FUNDAMENTALS OF ASTRONOMICAL IMAGING 5 LABORATORY REPORT There is no fixed required length to a lab report; I sometimes (and only half-jokingly) say that a lab report “should be as long as necessary, but no longer.” For this lab, the necessary sections of the report should be: 1. Objective 2. Observations: a. Name of the cluster you chose, and the reason you chose it, aside from availability of both blue and red images (was it the concentration of stars in the image? Centering of the cluster in the image? Etc.). Include the basic data from the on-line Messier catalog here: Right ascension and declination, distance, apparent magnitude, and approximate angular size. b. The attributes of each image (wavelength, pixel scale, field of view) and how you determined these c. Overall description of the star cluster imaged (does it take up the whole field of the image? Roughly how many stars seem to be part of the cluster? How many of these are very bright [saturated]?) 3. Analysis and Results: a. Criteria for selecting 20-50 cluster candidate stars b. Hardcopy of both images, with selected stars marked and numbered on each c. Data table for each image (table of x,y peak pixel for AT LEAST 10 stars) d. Graph of red/blue image intensity ratio vs. red image value for your stars. 4. Conclusions: a. Do you think all of the stars you picked actually belong to the cluster? Why or why not? b. Is the color (red/blue intensity ratio) of a star related to its brightness? c. What errors or problems in measurement may have affected your results?