Astronomy programs
A vast range of statistical problems arise in modern astronomical and space sciences research, particularly due to the flood of data produced by both ground-based and space-based astronomical surveys at many wave-bands. A resurgence of interest in statistical and applied mathematical methods has emerged among astronomers and astrophysicists as they seek insights into the physical phenomena underlying such complex data. Researchers often confront problems for which the common approaches in astronomy either inadequately utilize known methods or require the development of new methods. Although, astronomy was responsible for many important statistical concepts and methods in the past few centuries, in contrast with the biological and social sciences, the statistical needs of physical scientists have been neglected during past decades.
To cope with the current and future needs of astronomy missions require concerted efforts by cross-disciplinary collaborations involving astronomers, computer scientists, mathematicians and statisticians. SAMSI is an ideal place from which to broadcast these issues and involve the wider statistical and applied mathematical communities. Astronomical themes will includes cosmology, exoplanets, gravitational waves and synoptic surveys. While astronomers typically specialize in one of these areas, the organizers have identified several common mathematical and statistical tools and challenges. For example, each of the astronomical sub-fields could benefit from improved time series analysis, hierarchical modeling, uncertainty quantification, reduced order modeling and inference with misspecified models.
By bringing together experts in each of these areas, the SAMSI program will accelerate the adoption of modern statistical and mathematical tools into modern astronomy. Astronomers will bring scientifically important problems and real datasets, statisticians and applied mathematicians will bring methodological expertise and will help translate these into computationally feasible algorithms. The program will provide multiple avenues for cross-disciplinary interactions, including several workshops, long-term visitors, and regular teleconferences, so participants can continue collaborations, even if they can only spend limited time in residence at SAMSI.