Next-generation Large-Scale Structure (LSS) and Cosmic Microwave Background (CMB) surveys will provide us with unprecedented levels of precision in the final constraints on our cosmological model. However, the computational challenges posed by these enormous datasets dangerously hinder their analysis within a Bayesian framework for rigorous uncertainty propagation – a condition necessary to...
Deep generative models including generative adversarial networks (GANs) are powerful unsupervised tools in learning the distributions of data sets. Various applications of GANs such as image generation, data/image to image translation, feature transfer, or super resolution could notably enhance astronomical data sets. Building a simple GAN architecture in PyTorch and training on the CANDELS...
Understanding dark matter halo formation is essential for understanding the formation of galaxies to test our cosmological model.
In the last decades, there has been a continued effort to investigate large-scale structure formation using the LSS surveys and large cosmological simulations.
Despite the success of newly developed simulations to predict halo formation, they usually lack the...
