Sarah Jiang

Planet Finder Academy Instructional Resources

As instructional content for the Planet Finder Academy, I created several worksheets and Jupyter notebooks designed to teach students the fundamentals of Python for scientific programming and the basics of the RV method for detecting exoplanets. These worksheets/tutorials are designed to be completed in the order that they are listed below, but they can be adapted to work as standalone activities.

Please feel free to use any of the following resources with appropriate credit. If you have any questions about the content or use of these resources, please feel free to email me.

Discovering Exoplanetary Characteristics with RV (and Transit) Data: This worksheet is a pen-and-paper exercise intended to guide students through the building blocks of the RV method. They are given ten different observations of a section of a star’s spectrum over time and asked to manually measure the Doppler shift and calculate the RVs. Then, using the parameters of the star (assumed to be the Sun), they are asked to calculate various other parameters of the planet and its orbit. Finally, they are asked to reflect on what they can learn about a system using RV data and how the parameters of both the star and the planet can affect the strength of RV signals. (Spoiler alert: in order to produce shifts large enough to be measurable by hand, the planet in the worksheet is in fact a brown dwarf.)

You can find the 2022 version here and the 2023 version (modified with a reflection between Exercises 2 and 3) here.

DACE Tutorial with 51 Pegasi b: After manually measuring, plotting, and estimating orbital period and semi-amplitude from RV plots in the pen-and-paper exercise above, we used the University of Geneva’s Data & Analysis Center for Exoplanets (DACE) interface to show students how, especially in modern science as the volume of data grows larger and larger, automated methods are generally used to identify planetary signals. This tutorial introduces students to the concept of a periodogram and guides them through using the DACE interface’s RV time series data for 51 Pegasi to “discover” 51 Pegasi b. This tutorial was adapted from DACE’s “Searching for planets in radial velocity time series” tutorial. You can find the tutorial here.

Fitting RV Data with Python (51 Pegasi b): This Jupyter notebook essentially goes through the same exercise as the DACE tutorial (fitting RV data for 51 Pegasi to find 51 Pegasi b), but using Python rather than DACE’s graphic user interface. The notebook is built off of the exoplanet package and utilizes the bgls code developed by Mortier et al.. The tutorial guides the user through the steps of plotting an RV time series, analyzing its periodogram generated by bgls, and fitting an RV time series using the exoplanet package. This tutorial assumes that the user has a very basic knowledge of Python, but most of the code is written already and does not require the user to create the functions and models themselves; however, it does prompt the user to fill in the blanks with formulas and initial guesses for period and semi-amplitude in certain places.

The tutorial notebook, data, and bgls.py file are located here. You can also access this tutorial on Kaggle, a web-based notebook service, here.

Fitting RV Data with Python (Random Systems): This notebook uses the same code and methods as the tutorial, but instead of a known system and exoplanet, the students are given RV data from one of nine random fictional systems. The students are given the stellar parameters of the star (based off of real stars), but no information about the planet(s) in the system. Using the RV data given, they are asked to fit for periodicities and search for planets in their system, much like they did with 51 Pegasi b. The notebook guides students through fitting for planets in systems that they have no prior knowledge of and prompts them to use what they’ve learned about the RV method to determine what conclusions they can make about the planets in their system. This notebook is designed to build upon the tutorial by allowing them to apply the skills they’ve learned to finding a “real” exoplanet and to give students an introduction to the complexities of searching for planetary signals in RV data.

The notebook, data for all nine systems (and the Solar System as a bonus system), answer key for all systems (listing the real stars and planets the systems were constructed from), and bgls.py file are located here. You can also find these files (minus the answer key and the Solar System data) hosted on Kaggle here.