A team of scientists, consisting of Professors Sudip Bhattacharya and Mr. Shivam Kumaran, from the Tata Institute of Fundamental Research in Mumbai and the Indian Institute of Space Science and Technology in Thiruvananthapuram, as well as Professor Sameer Mandal and Professor Deepak Mishra, used the machine to describe the machine. used learning techniques. Thousands of new celestial natures in X-ray waves. Machine learning is a branch of artificial intelligence.

Astronomy is undergoing a transformation as large amounts of astronomical data on millions of celestial bodies become readily available. This has been achieved through large-scale research and careful observation using world-class astronomical observatories, combined with a policy of open data availability.

Needless to say, this data holds great potential for many discoveries and new insights about the universe. However, manually examining data from all these objects is impractical and automated machine learning techniques are needed to extract information from this data. However, the application of such methods to astronomical data is still very limited and in its infancy.

Classification of the nature of unknown objects is equivalent to the detection of objects of certain classes. Thus, this research has focused on black holes, neutron stars, white dwarfs, stars, etc. This led to the possible discovery of thousands of cosmic objects from classes such as many new interesting objects.

This collaborative research has also been instrumental in creating a cutting-edge capacity to apply new machine learning techniques to basic research in astronomy, which will be critical to the scientific use of data from current and future observatories.