Planet Formation

Planet formation research focuses on understanding how planets form from dust and gas within protoplanetary disks, aiming to explain the observed diversity of exoplanet systems. Current research heavily utilizes machine learning, particularly neural networks and support vector regression, to accelerate computationally expensive simulations of giant impacts and dust coagulation, improving the accuracy and speed of modeling planetary evolution. These advancements enable more comprehensive analyses of exoplanet populations, revealing correlations between planetary properties (like mass and radius) and stellar characteristics, ultimately refining our understanding of planetary system formation and evolution.