Download Spectroscopy

Spectroscopy
This exercise will give you an idea of how to extract a spectrum from an image obtained
with a spectrograph. Spectra enable us to learn of the composition of the atmospheres of
stars, planets, comets, and other astronomical objects.
Spectroscopy is a very important branch of astronomy. We can’t obtain an actual sample
of any distant astronomical object. The only method we have to study these objects is
through their light output. Fortunately, photons carry a great deal of information.
When one studies the light from an astronomical object, one is looking at two major
things. The first is the distribution of the light with wavelength. This is called the
“continuum”. Any object that has a temperature will radiate light at some wavelength.
To put is simply, hotter objects are bluer (shorter wavelength) and cooler objects are
redder (longer wavelength). This simple relation works for stars, too.
Step 1: Load the image in your computer’s spectroscopy folder called vegaspectrum.fits.
This is a spectrum of Vega, an A0V (astronomical designation of type that means that it
is more massive and hotter than the sun) star in the constellation Lyra. Lyra is a summer
constellation and so cannot be seen now. The file is already calibrated and so you don’t
have to subtract the bias and dark frame, or divide by the flat field.
Use the “stretch” button to best view the image.
1) How would you describe the spectrum? Is one end brighter than the other?
2) Are there dark features? How many?
Step 2: Click on Measure ->Spectroscopy. The spectroscopy menu will appear.
Step 3: Select the region of the image containing the spectrum. There are text boxes and
sliders to define the background sky above the spectrum, the region of the spectrum itself,
and the background sky below the spectrum. The spectrum is the bright line across the
image, created by passing the star’s light through a prism or grating.
The program will subtract a median of the sky background from the spectrum itself.
Move the sliders “Spect Top and Spect Bot” to define the region of the spectrum itself.
Choose sky background that does not have any visible star contribution.
Step 4: Select the spectrometer mode. This image was taken with an objective prism.
Select “Objective” mode. (there are differences in how the sky contribution is calculated
for objective prism spectra and slit spectra).
Step 5: Select the Vertical Scale type. You have the option of displaying the spectral
amplitude in either linear or logarithmic mode. Choose linear for your first try.
Step 6: When you think everything is okay, click “OK”. The spectrum will be
displayed.
Step 7: Look at your spectrum. The dips in the spectrum are called “absorption lines”.
They are created by the atoms of different elements in the atmosphere of Vega. Record
as best you can the wavelengths of the absorption lines. The shape of the spectrum is
also important. The overall shape can tell us much about what type of object this is. This
spectrum is a characteristic stellar spectrum. The highest point also tells us the
temperature of the object (using something called Wien’s Law). Which pixel marks the
highest point of the spectrum?
Step 8: Click the “Save” button to save your spectrum to a file. The file can be loaded
into Microsoft Excel.
Step 9: Repeat steps 1-8, this time choosing a logarithmic mode to display your
spectrum.
1) Does this type of display help you to view detail? Why?
Step 10: Repeat steps 1-8 using the file called “wd1728.fits”. This
is a spectrum of a white dwarf star. This spectrum covers 1294-1348 Angstroms.
1) How does it differ from the spectrum of Vega?
2) There are 500 pixels in this image. How many angstroms does each pixel cover?
Step 11: Repeat steps 1-8 usisng the file called “procyonb.fits”. This is the spectrum of
the white dwarf companion to Procyon, taken with the Hubble Space Telescope. How
does it differ from the spectra of the other two stars?
1) How does this spectrum differ from the other two spectra?
2) This spectrum covers 2130-3066 Angstroms. There are 500 pixels in this
image. How many angstroms does each pixel cover?