Yesterday, scientists from NASA’s Kepler team added a whopping 1,284 planets to the official list of planets we’ve found outside of our solar system. Credit for the large number of new exoplanets being added at the same time goes to a new, automated technique for analyzing planet-like signals and verifying that they actually are from planets.
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| An artist’s concept of select planetary discoveries made by NASA’s Kepler space telescope. Image Credit: NASA/W. Stenzel |
The Kepler Space Telescope was launched in 2009 to search for Earth-sized planets in the habitable “Goldilocks” zone. This zone describes the area around a star within which a planet could contain liquid water, and therefore sustain life as we know it. It’s an important step in exploring whether or not we are alone in the universe.
More broadly, the Kepler Mission aims to describe the distribution of planets, their orbits, and their star systems using data collected by surveying about 150,000 stars within our region of the Milky Way. From 2009-2013, Kepler collected data for its primary mission, and analysis is ongoing, although winding down as NASA prepares for the next stage of exoplanet exploration. (Kepler does have an ongoing K2 mission, which you can read about here.)
As of yesterday, a total of 3,264 exoplanets have been detected and verified, and Kepler is responsible for 2,326 of these. Twenty-one of these are roughly Earth-sized (no more than twice the size of the Earth) and fall within the habitable zone of the star they orbit. Nine of the 21 were added with yesterday’s announcement.
Kepler detects planets using the transit method. If you caught any of the transit of Mercury on Monday, this method will be familiar. A transit occurs when a planet passes between us and a star. We see the transit as a dark dot that moves along the surface of the star with time.
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| The transit of Mercury on May 9 shown with a composite image from the Solar Dynamics Observatory. Image Credit: NASA’s Goddard Space Flight Center/SDO/Genna Duberstein. |
Kepler detects planets by looking for dimming in starlight that is characteristic of a transit. This little bit of data can be unraveled into a whole lot of information—information on the size of the planet’s orbit, the mass of the star, and the size of the planet.
One of the main challenges with this method is verifying that the transit signal you see is actually from a planet. Certain configurations of star systems, like two stars that rotate around one another, can produce similar “imposter” signals, which Kepler scientists call false positives. For this reason, all characteristic signals represent candidates for exoplanets at first – a transiting object isn’t hailed as new exoplanet until it has been verified in another way.
The verification process is time and resource intensive, and involves examining the systems one-by-one, usually with ground based observational data.
With this announcement, however, the Kepler team presented data from a fast and automated new method for calculating the statistical probability that a transiting object is a planet. The method was developed by Timothy Morton, associate research scholar at Princeton University in New Jersey, and combines information from two types of simulations. The first is a simulation of the detailed shape of transit signals from planets and imposter stars, and the second is a simulation of the prevalence of imposter systems. Using this information, the technique provides a statistical likelihood that any given signal is from an exoplanet. Anything that received a statistical likelihood of 99% or greater has been designated an exoplanet.
This technique builds on past analysis methods used on Kepler data based on statistical probabilities, but is the first fully automated technique that can batch process candidates.
After applying this technique to about 4,300 planet candidates identified in a catalog of Kepler objects from July of 2015, the team verified 1,284 new exoplanets. In addition, the new technique verified nearly 1,000 others that had been verified previously using other methods. Similarly, candidates designated as false positives previously with other methods were identified as such with this new technique.
Many of the remaining candidates are likely to be planets as well, but fell below the 99% cut and will be further explored in follow-up work.
This is an exciting result—not only because of the new planets, but because it adds so much more information to the statistical picture of how planets are distributed around stars. Of course, just knowing that a star has a planet, even one in its habitable zone, does not mean that the system can support life. This will be further explored in future NASA missions, such as the James Webb Space Telescope, which will collect information on the atmospheres of exoplanets and the Transiting Exoplanet Survey Satellite, which will look for exoplanets in our neighborhood.
—Kendra Redmond