New machine learning methods for analyzing expanding stars in the Orion complex
- Author(s)
- Hannah Woodward, Elena D'Onghia, Kashika Mahajan, Moritz Münchmeyer, Cameren Swiggum, Joao Alves
- Abstract
In this poster we present results from applying new machine learning algorithms to stars in Orion. Using new data from Gaia DR3 and SDSS, positions, radial velocities, proper motions, parallaxes, and ages are assembled for available stars in the region. Stars in the sample are clustered into groups based on these characteristics. With current data, we are able to include more details than previous work, which will improve inferences about the past dynamics of stars in Orion.
- Organisation(s)
- Department of Astrophysics
- External organisation(s)
- University of Wisconsin, Madison, European Southern Observatory (Germany)
- Journal
- Bulletin of the American Astronomical Society
- Volume
- 56
- ISSN
- 0002-7537
- Publication date
- 07-2024
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 103003 Astronomy, 103004 Astrophysics
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/661dab34-3638-4e51-a7b1-3e4664e0d21a