Summer research season is underway for me! This year, I am
working with Mike Brown on an observational astronomy project. I’ll be using
some of the data collected on the Keck Telescope last winter to study Jupiter’s
Trojan asteroids.
Observational astronomy is probably what most people imagine
when they picture an astronomer’s work, although the exact image in mind might
be a bit outdated. Today’s astronomers are more likely sitting behind a
computer screen than behind the eyepiece of a telescope, even in work that
isn’t strictly computational or theoretical. That’s because astronomy, like
many aspects of modern life, has gone digital.
Astronomers first recorded their observations on paper, by
hand, until the invention of photography. By the early twentieth century,
ground breaking discoveries, such as Edwin Hubble’s discovery of other galaxies
and the expansion of the universe, were being made with the assistance of
photographic plates. As photography evolved, so did astronomy. Today, digital
cameras use sensors called CCDs to capture images, as do most telescopes. Now,
astronomers can affix sensors to the foci of their telescopes in order to
collect high-quality data.
How do CCDs capture astronomical images, assuming you have a
telescope and a target for your observations? CCD stands for charge coupled device, a name that gives
a hint of how it works. A CCD is sectioned into pixels, or bins, and when exposed
to light, the bins gain a charge. The charge on each bin is proportional to the
amount of light that it received, so the more charge each bin has, the more
light it was exposed to, the brighter the area of the sky it observed. When the
exposure is finished, the charge on each bin is read out and converted into a
number (count) that represents how much charge built up in each bin. This
transforms the image into an array of counts that represents how much light was
detected in each pixel of the CCD.
Arrays, simple lists of numbers, are very easy for computers
to store, transfer, and manipulate, so they are a useful format for
astronomical data. Conversion of images to numbers just isn’t possible with
sketches and photographic plates, and opens up new possibilities for handling
data, since computers can very easily handle manipulating lists of that form.
Some astronomers today work on “training” computers to perform automatic
analyses of arrays, so computers can quickly accomplish basic tasks identifying
variable stars or Kuiper Belt Objects. Such computer programs are useful,
especially with the rise of large scale digital sky surveys that produce
enormous quantities of data on a nightly basis.
A small part of a typical array might look like this. While
useful to a computer, it’s very difficult for a human brain to figure out
what’s going on without some help. In order to understand what’s going on, we
can rearrange the numbers a bit. To make things even clearer, we can map count
numbers to colors. I’ll pick greyscale, so that we can keep in mind that more
counts corresponds to more light.
Unfortunately, CCDs, as powerful and useful as they are, do
introduce their own biases into the data, so our image doesn’t look very clean
right now. This problem is easy to correct, as long as you are prepared to
encounter it. The CCD-introduced bias can be fixed by taking two specific types
of pictures, known as darks and flats, which act like a control in a scientific
experiment.
The first type of control picture, the dark, is necessary
due to thermal noise in the CCD chip. Thermal noise is caused by the heat
radiation from the sensor itself, since CCDs are sensitive to infrared light
(heat). CCDs in telescopes are often cooled to low temperatures to reduce the
effect of this noise, which is present as long as the instrument has a
temperature, so it cannot be eliminated completely. To combat this problem,
astronomers prepare a dark, which is an exposure of the CCD to a completely
lightless environment, a bit like taking a picture with a camera that still has
the lens cap attached. This way, the CCD is only exposed to the thermal noise
originating from the instrument itself. Here is what a dark might look like:
The second type of image, the flat, is an image taken of a
flat field of uniform light. This could be an evenly illuminated surface. Many
astronomers will take flats during sunset when the evening sky is bright enough
to wash out the background stars, but not so bright that the sensors are
overloaded. Since we know the image should
be evenly lit, the flat field allows astronomers to pick up systematic defects
in the CCD. Due to tiny imperfections during manufacturing, some pixels may be
more or less sensitive than average, or the telescope itself might have lens
imperfections that concentrate light in different areas of the image. Flat
field images let astronomers discover and correct for these effects. A typical
flat might look like:
Now that we have our image, dark, and flat field, we can
begin to process the data. First, we subtract the dark from the image of the
object:
And from that image, we subtract the flat field, giving a
nice, clear picture of our target object:
Now that we’ve done initial processing of the image to
correct for bias, we can start to do more interesting analyses of the data. One
very basic thing we can do is use this image to figure out how bright the
object we are looking at is. We can sum up the counts that belong to the object
to get a total brightness. In this case, the sum of the object counts is 550.
But this number doesn’t mean very much on its own. The object might actually be
quite dim, but appears bright because a long exposure was taken, and the CCD
had more time to collect light. Or, we could have taken a very short exposure
of a very bright object. So, we need to find a reference star of known
brightness in our image, and measure that. If we know how bright the object
appears compared to the reference star in our images, and we know how bright
the reference star is, we can infer the brightness of the object.
If we have taken a picture of the same object in different
filters, we can also create false-color images. Filters can be placed in the
telescope aperture in order to restrict which wavelengths can pass through the
telescope. Using filters allows
astronomers to choose which colors of light will reach the CCD and be counted.
To make a false color image, astronomers combine images from two or more
different filters. Each separate image is assigned a color according to which
filter it was taken in (perhaps blue for ultraviolet light, green for visible
light, and red for infrared light), then the images are combined into one.
False color images are useful because the color coding for
each filter help draw attention to important differences between the individual
images while still allowing astronomers to see the structure of the object in
many different filters at once. In planetary science, for instance, different
colors in an image might reflect differences in the composition of the surface
of a planet, revealing regions of strikingly different geological histories
across the whole planet. Images can also be combined to produce “true color”
images using filters for different wavelengths of visible light in order to
produce pictures that mimic closely what different astronomical objects would
look like to human eyes. CCD technology has brought astronomy down to earth, quite literally, by producing images that reveal what the cosmos would look like, if only we could see it as well as our telescopes.
