Machine Learning and Cosmology
It addresses the integration of machine learning into cosmology to improve research methods and foster collaboration, but it is incremental as it summarizes existing developments rather than presenting new findings.
This white paper reviews the application of machine learning in cosmology, highlighting its impact on computational tools, data analysis, and community development, and provides recommendations to enhance scientific impact over the next decade.
Methods based on machine learning have recently made substantial inroads in many corners of cosmology. Through this process, new computational tools, new perspectives on data collection, model development, analysis, and discovery, as well as new communities and educational pathways have emerged. Despite rapid progress, substantial potential at the intersection of cosmology and machine learning remains untapped. In this white paper, we summarize current and ongoing developments relating to the application of machine learning within cosmology and provide a set of recommendations aimed at maximizing the scientific impact of these burgeoning tools over the coming decade through both technical development as well as the fostering of emerging communities.