Learn more about the orbits of the outer planets using Orbit!

Spins! It is a program used in the scientific community to fit directly imaged exoplanet orbits. Sounds great, but what does that mean?

Most of the outer planets are us direct picture They lie far from their host star, which means they have very long periods. Since we cannot constantly observe these objects, we often get “astrometry” – x and y (or r and If you are working in polar coordinates) the positions relative to the star at each time of observation, along with their uncertainty. An example of an astronomy table is shown in Figure 1.

Figure 1. Table of Buller et al. 2020 from r and  theta (The separation angle and position (PA)) of the companion star HD 984 is called HD 984 B at different intervals.

Positions are useful to us because we can use them to estimate the orbits of the planets in 3D – they are the orbits EccentricOr more circular? What is a file Half of the main axis from orbit? Is it tilted orbit for us here on Earth? Since the live imaging method is relatively new, the community needed open source code that could help us answer these questions and better understand the orbits of these exoplanets. We want to learn more about the orbits of exoplanets because they can tell us a lot about how planetary systems are formed and how they will evolve over time.

Figure 2. 6 orbital elements which describe a three-dimensional orbit are the semi-major axis (a), skew (e), inclination (i), ascending node meridian ( Omega), the peristerone argument ( Omega) and the real anomaly (Not). This diagram has a different reference direction than that used in exoplanet science (our reference direction is usually going up).

Sarah Blunt, a graduate student at Caltech, has led an effort to write orbit-friendly code in Python that is open-source and straight-to-use, called Spin! (Yes, with an exclamation point!). It has since become a standard in the live imaging community for exoplanets. This code allows you to use planet positions to estimate the planet’s orbital parameters, using two main algorithms: Orbits For The Impatient (OFTI) and Markov-Chain Monte Carlo (MCMC). All six orbital parameters are shown in Figure 2.

In today’s post, we’ll learn how to download and use orbit! with the MCMC Functions to fit the probable orbits of the HD 984 B exoplanets (Discover it Mishkat and others 2015), as shown in Figure 3. (Note: This tutorial assumes that you have Python 3 installed on your computer, along with Python packages NumPy And the Matplotlib – If you don’t have it installed, please click the links to learn how to install it).

We’ll need to coordinate our astrometry correctly for it to spin! It can be read. Spins! It takes a CSV file (it can be written on Google Sheets or Excel) where the columns, respectively, should be as follows:

  • “Era” – this is the time of your astrological observation, in Julian’s History (Mg). You can use a file Online Converter To convert regular dates to MJD.
  • “Object” – This refers to the object for which your astronomy is measured. Here, since we are using the astrometry from the planet, we always put the values ​​”1″ in this angle.
  • “sep” – this is the separation of the body from the host star, in milliseconds (mas).
  • “sep_err” – This is the uncertainty of your object’s separation in mas.
  • “pa” – This is the angle in degrees of your planet’s position.
  • “pa_err” – This is your planet’s uncertainty angle in degrees.

Once the spreadsheet is formatted, you must download it as a CSV file.

Figure 4 shows an example of how this data is formatted, for the HD 984 B. For the sake of making this tutorial easier, I’ve uploaded this CSV file to GitHub, so you can access it from there by clicking this link.

Figure 4. Astronomy of HD 984 B that will be used in orbit!

Now that you have the file ready to go, we’ll move on to File Jupiter Notebook for the rest of the tutorial.

To access the tutorial on how to download and run orbitize!, please click here!

orbit! The documentation page contains a description of how to use a file OFTI The algorithm and how to modify the orbit to suit your needs more specifically. The great thing about open source code is that it allows scientists and developers to contribute using a standardized way of doing scientific research, which is free and publicly available. Hopefully, as we develop our scientific methods and algorithms, we can start using and writing more open source code that is accessible to the public and the community!

Edited by: Jana Schwer

Featured image credit: Orbit! cooperation

About Clarissa Do O

I am a second year Physics graduate student at the University of California, San Diego. I study the orbital dynamics of exoplanets and also work on exoplanet instruments. My current work upgrades the adaptive optics of the Gemini Planet Imager 2.0, a tool intended to directly image and characterize exoplanets.