Many scientists at the University of Georgia have created new ways to discover and classify new worlds far from Earth. They encountered an exoplanet using machine learning, the wings of artificial intelligence (AI).
A recent study showed that AI can pinpoint the presence of exoplanets by examining protoplanetary disks (gas around newly created stars). The newly published results represent the first step towards using machine learning to recognize previously bypassed exoplanets.
The lead author of the study, Jason Terry, said in a message:
“Applying the model to a series of older observations identified a disk that had already been analyzed but was not known to contain planets. As with previous discoveries, we performed simulations of the disk. and discovered that planets could re-form, making observations.”
According to Terry, the model detected the presence of a planet and was characterized by multiple photographs that enthusiastically highlighted specific parts of the disk that were found to have specific signatures of the planet-around the planet. Abnormal changes in gas velocity.
Cassandra Hall, Assistant Professor of Computational Astrophysics and Principal Investigator of UGA’s Exoplanets and Planet Formation Research Group, said: Now you can be sure that you can use it for brand discovery.
“This demonstrates the ability of our models, and machine learning in general, to quickly and accurately identify important information that people may miss. Subsequent theoretical insights can be dramatically sped up,” said Terry.
“It only took about an hour to analyze that entire catalog and find strong evidence of a new planet at a particular location, so as the dataset grows ever larger, more important locations for these types of techniques become apparent. I think there is.”
