Perhaps someday in the near future the first signal from an alien intelligence will be detected by artificial intelligence. The future of artificial intelligence (AI) algorithms for finding exoplanets hidden in datasets was paved by one such algorithm developed by the University of Texas at Austin in partnership with Google in 2019 to probe the entire Kepler 2 data set of approximately 300,000 stars. The method is equally applicable to Kepler’s successor planet-hunting mission, TESS, which launched in April 2018.
“Telescopes like TESS are producing so much data,” NASA Sagan fellow at UT Austin Andrew Vanderburg told The Daily Galaxy, “we need AI methods to search through it all. We’re rapidly moving towards a future where most, if not all planets, will be inspected by some AI algorithm before being confirmed.”
“In the last few years, artificial intelligence has slowly gained recognition in the field of exoplanets as a powerful tool to handle and interpret ever larger astronomical data sets,” Andrew Mayo at UC Berkeley wrote in an email to The Daily Galaxy. “Neural networks and other types of AI will hopefully further enable the detection of new exoplanets, aid in the characterization of exoplanet atmospheres, help sift through large batches of data for unusual or miniscule signals (such as exomoons), and more.”
The University of Texas astronomers used AI to uncover two transiting planets in the Kepler space telescope K2 extended mission archive. The technique shows promise for identifying many additional planets that traditional methods could not catch. The planets discovered were from the K2 mission.
To find them, the team, led by an undergraduate at UT Austin, Anne Dattilo, created an algorithm that sifts through the data taken by Kepler to ferret out signals that were missed by traditional planet-hunting methods. Long term, the process should help astronomers find many more missed planets hiding in Kepler data. The discoveries have been accepted for publication in an upcoming issue of The Astronomical Journal.
Other team members included Vanderburg and Google engineer Christopher Shallue. In 2017, Vanderburg and Shallue first used AI to uncover an additional transiting planet around a Kepler star—one already known to harbor seven planets. The discovery made that solar system the only one known to have as many planets as our own.
Dattilo explained that this project necessitated a new algorithm, as data taken during Kepler’s extended mission K2 differs significantly from that collected during the spacecraft’s original mission.
“K2 data is more challenging to work with because the spacecraft is moving around all the time,” Vanderburg explained. “This change came about after a mechanical failure. While mission planners found a workaround, the spacecraft was left with a wobble that AI had to take into account.”
The main Kepler mission stared at the same group of 200,000 stars for nearly four years, while the K2 mission had to hop from stellar field to field every month. The loss in pointing accuracy and the shorter durations of the observations necessitated a different algorithm for detecting transiting planets.
The Kepler and K2 missions have already discovered thousands of planets around other stars, with an equal number of candidates awaiting confirmation. So why do astronomers need to use AI to search the Kepler archive for more?
“AI will help us search the data set uniformly,” Vanderburg said. “Even if every star had an Earth-sized planet around it, when we look with Kepler, we won’t find all of them. That’s just because some of the data’s too noisy, or sometimes the planets are just not aligned right. So, we have to correct for the ones we missed. We know there are a lot of planets out there that we don’t see for those reasons.”
“If we want to know how many planets there are in total, we have to know how many planets we’ve found, but we also have to know how many planets we missed. That’s where this comes in,” he explained.
The two planets Dattilo’s team found “are both very typical of planets found in K2,” she said. “They’re really close in to their host star, they have short orbital periods, and they’re hot. They are slightly larger than Earth.”
Of the two planets, one is called K2-293b and orbits a star 1,300 light-years away in the constellation Aquarius. The other, K2-294b, orbits a star 1,230 light-years away, also located in Aquarius.
Once the team used their algorithm to find these planets, they followed up by studying the host stars using ground-based telescopes to confirm that the planets are real. These observations were done with the 1.5-meter telescope at the Smithsonian Institution’s Whipple Observatory in Arizona and the Gillett Telescope at Gemini Observatory in Hawaii.
Image credit: a panorama of the northern sky is composed of 208 images taken by TESS in the second year of its mission. NASA/MIT/TESS and Ethan Kruse (USRA)