The hunt for quasars can be simplified only if we develop a candidate screening process. Astronomers look at the sky using different types of telescopes. The difference is mostly in the range of wavelengths (band width) through which they look at the sky. The sky looks different in each observation based on the wavelength of the light that comes from each object. A filter is used to make sure that only specific bands are observed at a time. For example, if the filter is blue in colour, all blue objects will appear bright in that filter and the red objects may not be seen at all. Comparing this with that of a red filter allows one to filter out all the red objects in the sky. Since quasars are far away objects, due to redshift, they would be redder than others. However, red is also the colour of some dying stars which are relatively much nearer. When we try to make our judgment based on colours, this comes in as a source of contamination. To make things worse, the quasars themselves change colour from red to blue and then to green as they grow older.
Astronomers call the difference between the magnitudes in two filters as the colour of an object. If we have many filters, we can obtain different colours and plot a colour-colour diagram. A colour-colour diagram is nothing but a plot with different colours on the x and y axis. The interesting thing here is that each type of object, especially quasars (after correcting for redshifts) cluster together at a particular region in the colour plots. This simplifies the candidate selection process provided we know their redshifts.
We have seen that knowing the redshift even with spectra is a nontrivial process. However, the good news is that the clusters formed, even without the application of the correction for redshifts, have a majority of quasars in them. The use of colour-colour diagrams is like throwing a net to catch a particular type of fish in an area where they are in abundance and then later sorting out the right ones from it. Yes, it is much more efficient than randomly searching everywhere.
