Dark Energy Survey Year 3 results: Simulation-based $w$CDM inference from weak lensing and galaxy clustering maps with deep learning. I. Analysis design

The Dark Energy Survey Year 3 results are making waves in the field of cosmology, showcasing a groundbreaking simulation-based inference pipeline that leverages deep learning to analyze weak lensing and galaxy clustering maps. This innovative approach not only enhances our understanding of the universe's structure but also sets the stage for future analyses of survey data. By extracting non-Gaussian information, researchers are better equipped to tackle the mysteries of dark energy, which is crucial for understanding the universe's expansion and fate.