André Blair — July 9, 2019
Galaxy clusters are among the most massive structures in the universe, also complicated to identify. To make things easier, scientists have now come with the idea to use artificial intelligence along with their research. The technology they plan to use is called Deep-CEE (Deep Learning for Galaxy Cluster Extraction and Evaluation), deep learning machinery that speeds up the search for galaxy clusters.
The research suggesting the method and the software were presented by Matthew Chan, a doctoral researcher at Lancaster University, at the Royal Astronomical Society’s National Astronomy meeting on July the 4th.
Galaxy clusters are pretty rare in the cosmos. The majority of the galaxies are located in low-density habitats, also known as ‘the fields,’ or in small groups, just like the Milky Way and the Andromeda. Even though the galaxy clusters are rare, they hold the most severe environments for star systems to thrive in. Observing them could open some of the world’s most intangible hypothesizes about the universe, dark matter, and dark energy.
Deep-CEE Artificial Intelligence Helps Astronomers Spot Galaxy Clusters
A high-tech AI model has been trained as a virtual astronomer to observe color images and particularly select galaxy clusters from the bunch. The machinery uses neural networks, which mirror the way human brain identifies objects, using particular neurons that can see patterns and colors.
In a first study which examined the AI’s abilities, the technology managed to identify and label galaxy clusters in images that include many other cosmic bodies. The results were promising, Royal Astronomy Society stated. This new automation of the identification process enables researchers to rapidly scan several images and receive accurate predictions with minimal human work.
Approaches such as the Deep-CEE are adding power and bring advancement to the discovery process and helps ease the tasks astronomers have by automating some of the most challenging and ordinary sequences of the process.