A tomographic spherical mass map emulator of the KiDS-1000 survey using conditional generative adversarial networks

Understand

Large sets of matter density simulations are becoming increasingly important in large-scale structure cosmology.

• Matter power spectra emulators, such as the Euclid Emulator and CosmicEmu, are trained on simulations to correct the non-linear part of the power spectrum.
• Map-based analyses retrieve additional non-Gaussian information from the density field, whether through human-designed statistics such as peak counts, or via machine learning methods such as convolutional neural networks.
• The simulations required for these methods are very resource-intensive, both in terms of computing time and storage.