The remarkable progress in cosmology over the last decades has been driven by the close interplay between theory and observations. Observational discoveries have led to a standard model of cosmology with ingredients that are not present in the standard model of particle physics – dark matter, dark energy, and a primordial origin for cosmic structure. Their physical nature remains a mystery, motivating a new generation of ambitious sky surveys. However, it has become clear that formidable modelling and analysis challenges stand in the way of establishing how these ingredients fit into fundamental physics. The speaker will discuss progress in harnessing advanced machine-learning techniques to address these challenges, giving some illustrative examples. She will highlight the particular relevance of interpretability and explainability in this field.
頻道：(網上講授)Zoom ID:942-338-0685 ← gravity
講者：Hiranya Peiris(University College London & Stockholm University)
“Copernicus Webinar and Colloquium Series”: To promote scientific discussions during this pandemic, they are organizing an online seminar series, i.e. Copernicus Webinar Series, seeking the most outstanding speakers to introduce innovative ideas and important progress in the field of gravity and cosmology. This series is named after the famous Polish Astronomer, Nicolaus Copernicus, whose discovery eventually marked the dawn of modern science.