Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov–Arnold Network (CKAN), which sheds new light on the properties of dark matter at galaxy-cluster scales.