(ORDO NEWS) — Scientists from the Tata Institute for Basic Research (TIFR) and the Indian Institute of Space Science and Technology (IIST) have determined the nature of new space objects using machine learning techniques.
Astronomy is entering a new era as vast amounts of astronomical data from millions of space objects become available.
This is the result of planned observations using high-quality astronomical observatories, as well as an open data access policy.
Needless to say, these data hold enormous potential for many discoveries and new understandings of the universe.
However, manually examining the data from all these objects is impractical, and automated machine learning techniques are needed to extract information from this data.
But the application of such methods to astronomical data is still very limited and at a preliminary stage.
The TIFR-IIST team has applied machine learning techniques to hundreds of thousands of space objects observed in X-rays using the Chandra space observatory in the United States.
Astronomers have analyzed approximately 277,000 X-ray objects, the nature of most of which was unknown. The classification of the nature of unknown objects is equivalent to the detection of objects of certain classes.
Thus, this research led to the reliable discovery of many cosmic objects of various classes, such as black holes, neutron stars, white dwarfs and stars.
This collaborative study was also important in building a state-of-the-art capability to apply new machine learning techniques to basic research in astronomy, which will be critical to the scientific use of these observatories.
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