Measure the Milky Way with Stars
For this maker challenge, students move through the engineering design process. They investigate Python and Jupyter Notebook to analyze real astronomical images in order to calculate the interstellar distance to a star cluster across the Milky Way from our own Solar System. They learn how to write Python code that runs in a Jupyter Notebook so they can determine the brightness of stars in an astronomical image. Next, students complete the functions in the project to determine how far away a single star in the cluster is from Earth. This is a chance to try hands-on astronomical research techniques in the field of aperture photometry. The real astronomical image data will be directly manipulated and analyzed by code the students create. Groups compare their final images and results to answer questions about the astronomy of stars and stellar distances within the Milky Way. Students experience their discoveries the same way Harvard scientist Harlow Shapley first learned the true size and shape of the Milky Way.
This cluster can help us measure the Milky Way!Copyright 2019 Jimmy Newland, Rice University RET
- A computer running Windows, Mac OS X, Linux, or Chrome OS
- Access to a web browser such as Chrome, Microsoft Edge, or Firefox
- At least one of the following (tested on all 3):
- Access to the internet and Microsoft Azure Notebook
- Install Anaconda Distribution of Python with Jupyter Notebook
- Access to Google Colaboatory (free access)
Contributors
Jimmy Newland
Supporting Program
Research Experience for Teachers, Office of STEM Engagement, Precise Advance Technologies and Health Systems for Underserved Populations and Department of Electrical and Computer Engineering, Rice University
Acknowledgements
This activity was developed as part of the Research Experience for Teachers through the Office of STEM Engagement and the Department of Electrical and Computer Engineering at Rice University supported by the National Science Foundation under grant number IIS 1730574. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or Rice University.
Copyright
2019 by Regents of the University of Colorado; original © 2019 Rice University
