Supernovae, which are exploding stars, play a pivotal role in galaxy formation and evolution. However, simulating these phenomena accurately and efficiently has been a significant challenge. For the first time, a team including researchers from the University of Tokyo has utilized deep learning to enhance supernova simulations. This advancement accelerates simulations, crucial for understanding galaxy formation and evolution, as well as the evolution of chemistry that led to life.
When you hear about deep learning, you might think of the latest app that sprung up this week to do something clever with images or generate humanlike text. Deep learning might be responsible for some behind-the-scenes aspects of such things, but it’s also used extensively in different fields of research. Recently, a team at a tech event called a hackathon applied deep learning to weather forecasting. It proved quite effective, and this got doctoral student Keiya Hirashima from the University of Tokyo’s Department of Astronomy thinking.
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