Cosmology with Artificial Intelligence

Abstract: In recent years Artificial Intelligence methods have found multiple applications in cosmology. These methods are particularly well suited for the analysis of large scale structure, as they are capable of creating rich and complex models of non-linear data. In this talk I will present the cosmology constraints derived using deep convolutional neural networks from weak lensing data, achieving more constraining power than the equivalent analysis with conventional methods. This analysis relies on the training sets consisting of grids of precise simulations; I will present current efforts to create large grids for constraining cosmological models using AI methods. Generative AI models can also be used to aid the creation of simulations themselves, considerably speeding up simulation time. I will discuss the current and future directions for AI-accelerated simulations.