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Tutorial 1a)
Your team from The Magic Next Telescope (TMNT) found a transiting exoplanet candidate using its photometric instrument Leonardo. Now it is your job to model it!
All codes available on GitHub.
You can run allesfitter in a graphical user interface and/or directly using its Python scripts. No need to choose, you can fluently mix & match to make your life easiest. For starters, we will explain the graphical user interface here. To skip ahead, check out Tutorial 1b.
Watch the video (engaging and cool)
Watch the video (engaging and cool)
Note: The video is a bit outdated by now, but still captures 99% of the workflow. The updated crash course on GitHub simplifies and speeds up the modeling.
Read the documentation (old and dusty)
Read the documentation (old and dusty)
You can download the data file here: Leonardo.csv
Your team's discovery report gives you a first guess for the transit signal:
Epoch: 1.09 +- 0.01 days after start of observations
Period: 3.41 +- 0.01 days
R_planet / R_star: 0.10 +- 0.01
(R_star + R_planet) / semi-major axis: somewhere between 0.1 and 0.3
(Your team is still unsure about the stellar parameters, so let us leave these undefined for now.)
Simply launch allesfitter’s graphical user interface (GUI) either
either via double click on the launch_allesfitter app (for Mac/Windows/Linux)
or by executing the following lines in a Python console:
import allesfitter
allesfitter.GUI()
Now fill out the fields step by step, hit the run button, and lean back. The fields should be relative self-explanatory; if not, please check the video.
Congratulations! Now that you successfully modeled the data, you can schedule follow-up observations with the rest of the TMNT network: Michelangelo (photometry), Donatello (RV) and Raphael (RV).
Now move on to the more advanced tutorials, which step by step introduce GPs, RV modeling, and much more.
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