In recent years, the field of astronomy has seen a surge in technological advances that have enabled researchers to explore further and deeper into space than ever before. One of the most exciting developments is the use of artificial intelligence (AI) to detect exoplanets outside our solar system. A team of scientists from around the world recently used AI to discover an exoplanet orbiting a star located about 300 light-years away from Earth.
The planet was detected using machine learning, a branch of AI that enables computers to learn from data without being explicitly programmed. The team trained their computer model on thousands of previously observed stars and then applied it to new observations taken by NASA’s Transiting Exoplanet Survey Satellite (TESS). After analyzing these observations, they were able to identify patterns associated with planets orbiting other stars.
This discovery marks an important milestone for astronomers as it demonstrates how powerful AI can be when used in conjunction with traditional methods for detecting exoplanets. It also shows how much progress has been made in this area over the past few years as more sophisticated algorithms are developed and deployed on larger datasets.
The newly discovered planet is roughly twice the size of Earth and orbits its host star every 37 days at a distance slightly closer than Mercury’s orbit around our Sun. While this makes it too hot for life as we know it, its proximity could make it ideal for studying planetary formation processes or even searching for signs of extraterrestrial life forms such as bacteria or microbes living beneath its surface layers.
This latest breakthrough highlights just how far technology has come in helping us understand our universe better and opens up many possibilities for future exploration beyond our own solar system. With continued advancements in both hardware and software technologies, there is no telling what else we may find out there!
|Researchers Use AI To Discover New Planet Outside Solar System|Technology|ScienceDaily