Download 1 LABORATORY 1: DIGITAL IMAGING WITH DS9 MATERIALS

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LABORATORY 1: DIGITAL IMAGING WITH DS9
MATERIALS:
• Network-ready PC running Windows, equipped with web browser. These are
available in the student laboratories on the third floor in the Chester F. Carlson
Center for Imaging Science (Building 76) and in Room 76-2205 (enter through
76-2125). If the small 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 MacOSX
(darwin). All versions and platforms support a consistent set of GUI and functional
capabilities. You may download DS9 and run it on your own computer.
PROCEDURE:
Part I: Select a cluster and download the image data:
1. Make a small list of names of 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 “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. 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. Globular clusters are older, farther
away, and crammed tightly together, so it will be difficult find individual resolved
stars.
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
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has lots of useful information. Their website is hosted by the Lunar and
Planetary Laboratory (LPL), whose site is http://www.lpl.arizona.edu/.
2. 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 images were created by digitizing
photographic plates on a 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 first blue (λ = 400 nm) and then red
(λ = 600 nm) images 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.
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.
To 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 of individual pixels using the real-time display at the
top of DS9.
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. Load two images at once: 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 is fine).
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Part II: Image Analysis
1. Determine the pixel scale and field of view of each image by measuring the
vertical size of the image in pixels and comparing it to the known size of the field
available from the download site.
2. Measure the peak pixel intensities (values) of at least 10 stars (preferably 30-50
stars) on each image. 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
value of the sky near each star’s image.
a. Measure the gray value Pp of the maximum pixel of the star
b. Measure the average gray value of the surrounding sky pixels Ps.
c. The value to be plotted is ∆P = Pp — Ps.
3. Pick the same stars on each image; try your best to choose stars that you think are
part of the cluster, yet are not saturated (overexposed) in either image. 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.
4. Make a table for each set of measurements (one table for each image), listing the
[x,y] pixel values for each star you picked, the peak pixel value, the pixel value of
nearby sky, and the difference (star minus sky), and the logarithm (base-10) of
these pixel values. It is easiest to make this table in a spreadsheet program, such
as Excel. Your laboratory assistant can show you how to do this if you have not
done it before.
5. Graph 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. That is, plot the measured red value
on the x-axis, and the ratio of red/blue on the y-axis. That is, plot
⎡ ∆P ⎤
log10 ⎢ red ⎥ vs. log10 [ ∆Pred ]
⎣ ∆Pblue ⎦
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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 parts in the report are:
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 10 stars)
d. Graph of red/blue image intensity ratio vs. red image value for your
(minimum of) 10 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?