Neural networks predict planet mass

To find out how planets form astrophysicists run complicated and time consuming computer calculations. Members of the NCCR PlanetS at the University of Bern have now developed a totally novel approach to speed up this process dramatically. They use deep learning based on artificial neural networks, a method that is well known in image recognition. Planets grow in stellar disks accreting solid material and gas. Whether they become bodies like Earth or Jupiter depends on different factors like the properties of the solids, the pressure and temperature in the disk and the already accumulated material. With computer models the astrophysicists try to simulate the growth process and determine the interior planetary structure. For given boundary conditions they calculate the masses of the gas envelope of a planet.