Here's how artificial intelligence is assisting astronomers

 Here's how artificial intelligence is assisting astronomers

The analysis of all data is one of the most difficult tasks facing the future generation of astronomers. Astronomers are using machine learning and artificial intelligence (AI) to construct new tools to quickly search for the next significant breakthroughs in order to meet the difficulties.According to news agency PTI, research by Ashley Spindler of the University of Hertfordshire's Department of Astrophysics has shed light on this.

 

Here are four ways that artificial intelligence is assisting astronomers.

 

1. Planet hunting: There are a few approaches to find a planet, but researching transits has proven to be the most successful. Exoplanets obscure some of the light that humans can see when they pass in front of their parent star.

Astronomers develop a picture of the dips in the light by observing multiple orbits of an exoplanet, which they can use to identify the planet's features.

 

2. Gravitational waves: Time-series models aren't just useful for locating exoplanets; they're also ideal for detecting the signals of the universe's most catastrophic events.

When dense things collide, ripples in space-time are created, which can be detected by analysing tiny signals on Earth.

 

3. The changing sky: When the Vera Rubin Observatory, which is now under construction in Chile, is completed, it will survey the entire night sky every night, collecting over 80 terabytes of data in one go, to examine how the universe's stars and galaxies change over time. 8,000,000,000,000 bits make up a terabyte.

 

4. Strong gravitational lenses are a celestial phenomenon that many astronomers are fascinated by. When two galaxies align in our line of sight, the gravity of the closest galaxy works as a lens, magnifying the more distant object, resulting in rings, crosses, and double images.

The winner of this competition utilised a model called a convolutional neural network, which learns to break down pictures using multiple filters until it can identify them as including a lens or not.