SwRI: Novel Algorithm to Aid Search for Exoplanets

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SwRI Scientist Develops Novel Algorithm to Aid Search for Exoplanets
Southwest Research Institute | 2019 Jun 25

Machine learning tool allows scientists to search stellar data for likely exoplanet host stars

This artist’s impression (not to scale) illustrates how common star-exoplanet systems may be in the Milky Way. An SwRI scientist has developed an algorithm to predict the likelihood that a star hosts giant planets, based on the composition of known star-exoplanet systems. Credit: ESO/M. Kornmesser

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Inspired by movie streaming services such as Netflix or Hulu, a Southwest Research Institute scientist developed a technique to look for stars likely to host giant, Jupiter-sized planets outside of our solar system. She developed an algorithm to identify stars likely to host giant exoplanets, based on the composition of stars known to have planets. ...

Just as a cake recipe includes some basic ingredients, stars need certain elements to make giant planets. Scientists can use spectroscopy, or the way that light interacts with atoms in the star’s upper layers, to measure a star’s composition, which includes materials such as carbon, magnesium and silicon. These elements are the ingredients for making a planet, because stars and planets are made at the same time and from the same materials. However, while there are a lot of ingredients in your kitchen, not all of them belong in a cake. This is where the movie-streaming algorithm comes in, predicting planets based on the elements in stars. ...

Hinkel used the Hypatia Catalog, a publicly available stellar database she developed, to train and test the algorithm. It’s the largest database of stars and their elements for the population within 500 light years of our Sun. At last count, Hypatia had stellar element data for 6,193 stars, 401 of which are known to host planets. The database also catalogs 73 stellar elements from hydrogen to lead.

The algorithm, which will be publicly available, has looked at more than 4,200 stars and assessed their likelihood of hosting planets, based solely on the elements, or ingredients, within the star. In addition, Hinkel looked at different combinations of those ingredients to see how they influenced the algorithm. ...

Star Tours: Astronomy Bot Speeds Up Search for Jupiter's Twins
University of California, Riverside | 2019 Jun 25

A Recommendation Algorithm to Predict Giant Exoplanet Host
Stars Using Stellar Elemental Abundances ~ Natalie R. Hinkel et al

• arXiv.org > astro-ph > arXiv:1805.12144 > 30 May 2018 (v1), 18 Jun 2019 (v2)