An illustration of what some of the new exoplanets announced today may look like, along with their host stars. (credit: NASA)
It is one thing to observe the periodic dimming of a star’s light, as NASA’s Kepler Space Telescope has done for thousands of planet “candidates” since its launch in 2009. However, to confirm that such dimmings are in fact due to a planet passing in front of a star, as opposed to any number of false positives such as a binary star companion, requires intensive follow-up work with ground-based instruments, most often a measurement of radial velocity to determine the object’s mass.
To ease this workload, planetary astronomers have devised a few different statistical techniques, but none have been fully automated until now. Princeton University researcher Timothy Morton has developed software that can, within a few minutes, asses the orbital period and other data gathered by Kepler to assign a statistical probability that planet “candidates” are, or are not, planets. When tested on previously confirmed exoplanets and false positives, the new technique worked almost flawlessly.
Described in the Astrophysical Journal, this new method allowed scientists to rapidly assess Kepler’s planet candidate catalog from July, 2015, which identified 4,302 potential planets. Of these, the new technique found that 1,284 were planets at a confidence level of 99 percent or greater. An additional 1,327 are likely planets, but did not reach the 99 percent confidence threshold.
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