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The researcher develops a new algorithm to help search for exoplanets

  SwRI researchers develop new algorithm to help the search for exoplanets
This artist's impression (not to scale) illustrates how common star annex planets can be in the Milky Way. A SwRI scientist has developed an algorithm to predict the likelihood of a star hosting giant planets, based on the composition of known star-exoplanet systems. Credit: ESO / M. Kornmesser

Inspired by movie streaming services such as Netflix or Hulu, a researcher from the Southwest Research Institute developed a technology for looking for stars that will likely host giant Jupiter planets outside our solar system. She developed an algorithm for identifying stars that can host giant exoplanets, based on the composition of stars known to have planets.

"My viewing habits have trained Netflix to recommend sci-fi movies that I might like ̵

1; based on what I've already seen. These collagen films are like the known star-exoplanet systems," says Dr. Natalie Hinkel. a planet astrophysicist at SwRI. "Then the algorithm looks for stars with even undiscovered planets, which are comparable to films I haven't watched – and foresee the likelihood that these stars have planets." Ingredients, stars need some elements to create giant planets, scientists can use spectroscopy, or how the light interacts with atoms in the star's upper layer, to measure a star's composition, which contains materials such as carbon, magnesium and silicon. to create a planet, because stars and planets are made simultaneously and from the same material, but while there are many ingredients r in your kitchen, do not hear all of them in a cake. Here comes the movie streaming algorithm, predicting planets based on the elements of stars.

"We found that the most influential elements in predicting the planet's host stars are coal, oxygen, iron and sodium," Hinkel said. "The funny thing was that we didn't expect sodium to be an important ingredient for predicting a planet. But it must be an important link between stars and planets, because it continued to appear, even when looking at different combinations of element." [19659005] Hinkel used Hypatia Catalog, a publicly available star database that she developed to educate and test the algorithm. It is the largest database of stars and their elements for the population within 500 light years of our Sun. In the case of distress, Hypatia had stellar element data for 6,193 stars, of which 401 are known to host planets. The database also catalogs 73 stellar elements from hydrogen to lead.

The algorithm, which will be available to the public, 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 saw various combinations of these ingredients to see how they affected the algorithm.

Hinkels team identified around 360 potential giant planet's host stars that have more than 90 percent probability of hosting a giant exoplanet. "We were happy, so we used archive telescope data to search for some signs of planets around these likely host stars," Hinkel said. "We identified possible planets of Jupiter size around three stars predicted by the algorithm."

When asked about how reliable her algorithm is, she explained that "we have no true negatives in our data, that is, stars we know do not have planets – so we hid some known planet-host stars in data to see what their prediction points would be. On average, they made more than 75 percent, which is good! It's probably a higher average than I like the sci-fi movies Netflix chooses for me. "

Moving forward, these results can revolutionize target star selection future research and clear role elements play in the giant planet's detection and formation. Hinkel is the leading author of the paper "A recommendation algorithm for predicting giant exoplanet host stars using stellar elemental abundance" which will be published in a forthcoming issue of The Astrophysical Journal .

Researchers develop database for stellar-exoplanet "exploration"

More information:
Natalie R. Hinkel, et al. A recommendation algorithm for predicting giant exoplanet value stars using Stellar Elemental Abundances. arXiv: 1805.12144v2 [astro-ph.EP]: arxiv.org/abs/1805.12144

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Southwest Research Institute

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Researchers develop new algorithm to help the search for exoplanets (2019, June 25)
June 25, 2019
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