Teaching with Code: Globular Cluster Distance Lab

Modern astronomy is increasingly dependent on computational thinking. Although some astronomy courses for undergraduates use computing, high school astronomy courses often have little computing in the curriculum. Created as a part of a research experience for teachers in astronomy and another in computer science, this project leverages robotic telescope time-domain images and modern astronomical algorithms to determine the distance to a star cluster using variable stellar photometry. Students investigate Python and Jupyter Notebook to analyze real astronomical images to calculate the interstellar distance to a star cluster across the Milky Way from our solar system. They will learn how to write Python code that runs in a Jupyter Notebook such that the brightness of stars in an astronomical image can be determined. The real astronomical image data will be directly manipulated and analyzed by code the students create. Student project files and teacher solution files are provided. Classroom uses, technology requirements, and coding experience levels are discussed, as is the use of robotic telescopes in obtaining data. All code is open source, and materials are available for classroom use.