Computers assist astronomers in classifying galaxies
ONE of the most specialised and tedious
jobs of an astronomer is classifying
galaxies after examining them through a
telescope. Now, computers are going to
help the scientists in this task, which is
important because specifying the type
of galaxy gives vital clues about its
origin and evolution (Science, Vol 267,
No 5199).
This is a new field for computer
usage because it means employing them
in what is a highly skilled job. This is
because galaxy classification is to a large
extent a subjective matter. What the
classification scheme gives you is the
correlation between certain morphological features (like the size of the central
bulge, or how tightly the spiral arms
wound around the core) and the type of
galaxy. But to place any given image
with certain characteristics into one or another
type is still a matter of
judgment. Fortunately
though, unlike insects or
plants, most of the galaxies are classified either as
spiral, like our own Milky
Way, or elliptical. However, within each classification, there are a few subclassifications.
Now, computer programmes called neural
networks, which come
closest to the human
brain, are being employed in the
time consuming and highly technical
job of galaxy classification. Neural
networks consist of interconnected processors where the processors
and the connections roughly mimic
the neurons and the synapses of human
brain. The property that makes these
models useful is that they can be made
to learn from experience.
Before using the neural networks to
classify galaxies, astronomers first train
the networks with some 500 images of
galaxies. The network classifies the
image according to some features of the
image and assigns different weights to
these features. The network is then
given the correct answer for each image
and it changes the Assignment of
weights so as to produce the answer
closest to that given it by
the trainer. The more positive reinforcement that a
network gets, the better it
is equipped to handle the
next image.
A competition between the trained electronic apprentices and their
astronomer trainers in
classifying galaxies showed encouraging results,
suggesting that the neural
networks could soon
become an indispensable
tool in astronomy.
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