In a widely published story today, NASA and Google have used a neural
network developed at Google to crunch through data from the Kepler space
telescope and in the process discovered two new exoplanets.
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Originally Posted by Ry Crozier, IT News
The neural model runs using Google-developed TensorFlow technology and was trained on a dataset of 15,000 - out of a possible 35,000 - suspected planetary “signals”.
These signals are in the light readings recorded by Kepler - what NASA says are “minuscule changes in brightness captured when a planet passed in front of, or transited, a star".
“The measured brightness of a star decreases ever so slightly when an orbiting planet blocks some of the light,” Google said.
“The Kepler space telescope observed the brightness of 200,000 stars for 4 years to hunt for these characteristic signals caused by transiting planets.”
The TensorFlow model was trained to “detect the pattern of a transiting exoplanet”, and when the model was shown to work on a new sample of data, “the researchers directed their model to search for weaker signals in 670 star systems that already had multiple known planets".
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Story here :-
https://www.itnews.com.au/news/nasa-...planets-479890