With the increasingly advanced development of artificial intelligence (AI) and machine learning, it is not uncommon for us to see them being applied in many areas and even in space and beyond our stratosphere. And speaking of the stars, what some researchers from the University of Leeds have achieved is to discover thousands of stars with the help of AI .
Something that they have achieved thanks to the observations of Gaia , a satellite of the European Space Agency (ESA) whose mission is to map the sky to complete the star map. In fact, on his resume he already has the most complete map of the Milky Way ever made , and what they hope is that by pulling AI “his eyes” can see even more.
Processing “mountains of data”
Specifically, they have discovered something like “star babies”, since as explained by the team in the university’s publication with the AI-based tool they have managed to create a list of 2,226 proto-stars . They are probably also of the Herbig Ae / Be type, a type of young star with a mass of between two and eight solar masses.
The information was validated in observatories in Chile and Spain, where they were able to measure the light emitted by these stars. With this they saw that the AI tool can predict which stars are of this type and above all that it allows to expand their discoveries, since it has gone from having cataloged about 100 stars of this type to those more than 2,000.
What they hope with this, as explained by Miguel Vioque (chief researcher of this project), is that combining this type of newer technologies can be processed more agilely “the mountain of data” produced by the telescope, seeing that in this case they started out of a total of 4.1 million stars to review . In addition, they are focusing on these types of stars, what they hope is to have more data on how the Milky Way could have formed , as they are growing stars.
Given the immensity of information that must be processed when talking about spatial observation , it will not be strange that we will see similar applications in other projects, which in the end are still Big