Sky map of the XMM-Newton Source Catalogue.
Credit: ESA/XMM-Newton/EPIC/M. Watson (University of Leicester)
In astronomy, the most reliable method to estimate how far from the earth a source, like a galaxy, lies is by studying its spectrum. Scientists search for features in the spectrum, like absorption and emission lines and compare the wavelength of each feature with that found in experiments on Earth. When an object is moving relative to the observer, its wavelength (or frequency) changes and this phenomenon is called Doppler effect. If the source is moving away from the observer then it is redshifted, whereas when it moves towards the observer the source is blueshifted. Therefore, studying the relative difference between the observed and emitted wavelengths of the lines in a spectrum, astronomers can estimate the distance of the objects. However, this technique requires a lot of telescope time and is expensive in resources. Thus, cannot be applied on hundreds of thousands or even millions of X-ray sources, that future X-ray satellites, like eROSITA and ATHENA will provide us in the near future.
An alternative method, and perhaps the most suitable to estimate redshifts for thousands of X-ray sources with an active supermassive black hole (AGN), is to calculate their distance using machine-learning techniques. In these methods an algorithm is trained using a sample with known spectroscopic redshifts and then is applied on a sample of sources with unknown distances. Such a method was recently used on the largest X-ray catalogue currently available, the 3XMM catalogue.
3XMM numbers about 370,000 unique X-ray sources, observed with ESA’s XMM-Newton satellite and covers an area of 800 square degrees on the sky. The huge potential of this catalogue, though, remains practically untapped because of the lack of the redshift. Using TPZ, a machine learning technique, astronomers from the X-ray group of the National Observatory of Athens, estimated distances for about 90,000 X-ray sources with at least optical photometry available. The catalogue is available to the astronomical society and will allow the full exploitation of the 3XMM dataset and help us study the environment of AGN!