A probabilistic deep learning model to distinguish cusps and cores in dwarf galaxies
Numerical simulations within a cold dark matter (DM) cosmology form halos whose density profiles have a steep inner slope (‘cusp’), yet observations of galaxies often point towards a flat central ‘core’. We develop a convolutional mixture density neural network model to derive a probability density function (PDF) of the inner density slopes of DM
Fecha de publicación:
12
2022