450103 SE COSMOS Topic Seminar: A Bayesian Toolkit and Stellar Cluster Dynamics (PI) (2021S)

This seminar has a dual concept. In two intertwining strands, students will learn about (a) tools for Bayesian inference, and (b) the dynamics of stellar clusters. The two strands will support one another: throughout the seminar, inference tools will be applied to data from stellar clusters (both simulated and real). The course is suitable for Astronomy and COSMOS PhD students, and final year Astronomy Masters students.

AIMS - By the end of this seminar, students will understand modern concepts in Bayesian inference and gain the knowledge to apply software tools for inference to a variety of problems. Moreover, students will be able to describe the current status of research into the dynamics of stellar clusters, and to identify the main open problems.

CONTENTS - Introduction to stellar clusters: general properties and open problems, types of data available and observable properties - Dynamical models of stellar clusters - Introduction to Bayesian inference - Overview of inference techniques and software - Inference with real datasets

METHODS - The content outlined above will be presented by means of dedicated slides prepared for each session and made available to the students on Moodle. During the seminar, students will write computer programs to manipulate data, compute dynamical models, and perform inference on these models given observed data. They will also present their results, putting them into the general context of the field, compare their results with those of their peers, and discuss them in the context of the research field presented in the course.