Exoplanets: Properties and Discovery | Artificial Intelligence in Astrophysics

Exoplanets are awesome. By definition, they are any planetary body that is located outside of our solar system (so a planet that is not Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, or Neptune).
Exoplanets have the basic, familiar properties of planets: they orbit stars and rotate on their axis. However, the diversity of exoplanets results in a wide variety of characteristics. Some exoplanets orbit their star (complete a year) in about an hour, whereas others take millions of years. Exoplanets have all sorts of densities, sizes, albedos, etc.
Most of the exoplanets we've discovered are located in the Milky Way Galaxy, though there are probably many throughout different galaxies. The way we discover exoplanets is pretty indirect, but also pretty cool.
When astronomers observe the sky with their telescopes, exoplanets are not visible. Being so far off, the light from the star that the exoplanet orbits obscures and outshines any sight of the exoplanet itself. But astronomers can still detect these exoplanets. By analyzing the light emitted from stars suspecting to have exoplanets orbit them, scientists can infer the presence of an exoplanet. If the light of the star is blocked in uniform time intervals, an exoplanet is likely passing by. The exoplanet is transiting in front of the star and blocking its light instantly each time it passes in front of (or transits) the star.
Detecting exoplanets this way is quite tedious. That's why many astrophysicists are researching machine learning and artificial intelligence to detect exoplanets. Since there are so many stars to analyze, machine learning programs could run through the light emission of these stars and use image recognition to identify transits and make a conclusion about an exoplanet.

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