Astronomers are turning to machine learning and artificial intelligence (AI) to create new ventures to quickly spot the next big breakthrough. Here are four ways AI is helping astronomers:

First: Discovery of planets

There are a few methods of detecting planets, but the most successful of these is through their motion. When exoplanets (planets outside the solar system) pass through front of their parent star, they obstruct some of the amount of light that we can be noticed.

Astronomers have created an image based on the difference in light observed from the exoplanet's various orbits, from which they can determine the planet's status, such as its weight, size, and distance from its star. The technology in NASA's Kepler space telescope has been very successful, through which thousands of stars can be monitored at once, it also keeps an eye on the light produced by the stars. Humans are skilled at recognising distinctions, but this ability requires time to develop, which is where artificial intelligence comes in handy.

Second: Gravitational Waves 

The time-series model is valuable not just for identifying exoplanets, but also for detecting evidence of the universe's most catastrophic events, such as the collision of black holes and neutron stars. When this very dense object is pulled towards the black hole, they send waves into space that can be detected by weak signals coming to Earth.

Gravitational wave detectors collaborations 'LIGO' and 'Virgo', with the help of gravitational wave detection instruments, detect dozens of waves of these phenomena and this is done by machine learning. LIGO and the Virgo-based team can spot a possible event in seconds and can send a warning signal to astronomers around the world to point their telescopes in other directions.

Third: Change In The Sky

When the Vera C. Rubin Observatory in Chile is ready, it will survey the entire sky overnight—the observatory will collect about 80 terabytes of images at a time—to see what changes happens to the stars and galaxies in the universe over time.  There are 8,000,000,000,000 bits in a terabyte. Rubin will collect and analyze hundreds of petabytes of data over time, including planned operations, the legacy of space surveys. For reference, 100 petabytes means the equivalent of storing all photos on Facebook, or 700 years of continuous HD video.

Fourth: Gravitational Lens 

As we collect more and more data regarding the universe, sometimes we will also need to manage them and destroy the useless data. So how can we extract the scarce information from this pile of data?

There is a celestial phenomenon that excites many astronomers, and that is the gravitational lens. This occurs when two galaxies are in front of our vision and the gravity of the nearest galaxy acts as a lens and makes distant objects appear larger.

In the year 2018, astronomers from around the world joined the challenge of finding strong gravitational lenses in which they had to develop the best algorithm to detect these lenses automatically. Astronomers will collect data in petabytes, or thousands of terabytes, in the coming decade using instruments like the Vera Rubin Observatory.

Hence we come to know scientists are using artificial intelligence in the discovery of new planets, gravitational waves, changes in the sky, rare information related to gravitational lenses and data analysis.

Ashley Schipdler, Researcher, Astrophysics, University of Hertfordshire, made several new discoveries from the experiment. According to scientists, the universe is expanding and with it the information they are getting is also increasing, but the big challenge for the next generation of astronomers is how to study the data that they have collected. In such a situation, the use of artificial intelligence is very helpful to scientists.