Modeling Keplerian Orbits of Stars, Brown Dwarfs, and Planets

Grade Level at Time of Presentation

Senior

Major

Physics, Applied Mathematics

Minor

Astronomy, Computer Science

Institution

Northern Kentucky University

KY House District #

69

KY Senate District #

11

Department

Department of Physics, Geology, and Engineering Technology

Abstract

Any companion object (Star, Brown Dwarf, or Planet) that orbits a star follows a Keplerian Orbit. The APO Galactic Evolution Experiment surveys (APOGEE-1 and APOGEE-II) in data release 15 took spectroscopy of 263,444 stars and produced stellar radial velocity data of order 100 m/s precision. The combined surveys cover a base line of over 6 years (~2000 days). In our project, we used a mock catalog of companions that was designed to mimic the APOGEE surveys. The goal of our project was to compare the effectiveness of Markov-Chain Monte Carlo (MCMC) techniques with more traditional orbital fitting methods for deriving correct companion orbits from APOGEE-like radial velocity data. We investigated not only how well we could recover orbital parameters as a function of parameter space, but we also investigated the practical limitations of each method. In particular, we focused on using these techniques with large data sets, and the trade-offs between precision and computational time.

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Modeling Keplerian Orbits of Stars, Brown Dwarfs, and Planets

Any companion object (Star, Brown Dwarf, or Planet) that orbits a star follows a Keplerian Orbit. The APO Galactic Evolution Experiment surveys (APOGEE-1 and APOGEE-II) in data release 15 took spectroscopy of 263,444 stars and produced stellar radial velocity data of order 100 m/s precision. The combined surveys cover a base line of over 6 years (~2000 days). In our project, we used a mock catalog of companions that was designed to mimic the APOGEE surveys. The goal of our project was to compare the effectiveness of Markov-Chain Monte Carlo (MCMC) techniques with more traditional orbital fitting methods for deriving correct companion orbits from APOGEE-like radial velocity data. We investigated not only how well we could recover orbital parameters as a function of parameter space, but we also investigated the practical limitations of each method. In particular, we focused on using these techniques with large data sets, and the trade-offs between precision and computational time.