The universe is still a wonder to humans, and so is AI. AI has modified how we worked and played a massive role in making our life easier. It has aided our quest to understand the universe. Astronomers across the world are thankful for the developments in AI. 2022 was indeed a milestone year in space exploration, and the role of AI should be addressed. Here are four instances where AI played a vital role in opening a new portal in understanding the universe, we live in. 

Morpheus: Some things are beyond the reach of humans, and this is where computers step in. This is the core idea that birthed project Morpheus, which took around two years to come to fruition. With AI software such as Morpheus, it is possible to 'snap' objects with higher accuracy and gather critical data on the evolution of galaxies.   

Morpheus leverages deep learning and applies computer vision algorithms to classify objects based on the raw data streaming out of telescopes. Furthermore, it enables pixel-by-pixel classifications and brings a semantic segmentation of spatial objects to life, irrespective of their shape.    

Click here to know more about Morpheus. 

Studying Quark Guon Plasma: According to researchers, immediately after the Big Bang, the entire universe was in a state called the 'quark-gluon plasma'. Tiny particles whir around widely with extremely high energy. Countless interactions occur in the tangled mess of quantum particles.  

A process like this can only be studied through a high-performance computer. Hence, using AI and ML for this purpose was the obvious idea scientists could think of. The mathematical properties of particle physics require a very special structure of neural networks.  

Click here to know more about studying Quark Guon Plamsa. 

SNlascore: A group of Caltech astronomers have recently used an ML algorithm SNlascore to classify 1000 supernovae completely autonomously. The algorithm was applied to data captured by the Zwicky Transient facility or ZTF, a sky survey instrument based at Caltech's Palomar Observatory.  

ZFT scans the night skies every night to look for changes called transient events. However, due to the massive load of data generated by ZFT, team members cannot sort through independently. They developed SNlascore for the task of classifying candidate supernovae. Currently, SNlascore can classify 'Type las' supernovae which occur due to the dying of a star. In addition, it allows astronomers to measure the expansion of the universe.   

Click here to know more about SNlascore.  

ISRO Initiatives: ISRO is proven to be one of the most elite space organizations. They are nourishing their space missions with AI. ISRO's research on AI for observational purposes, satellite navigation, meteorology and space assistance started in November 2018. They published a synopsis to the universities regarding their study.  

Click here to know more about ISRO's work with AI.