4564015
doi
10.5281/zenodo.4564015
oai:zenodo.org:4564015
user-coolstars20half
Wolk, Scott
Lingg, Ryan
Western Washington University
Kounkel, Marina
Western Washington University
Covey, Kevin
Western Washington University
Hutchinson, Brian
Western Washington University
Sagitta: a Neural Network Approach to Identifying and Predicting Ages of YSOs
McBride, Aidan
Western Washington University
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Young stars
Stellar systems, clusters, and associations
<p>A reliable census of of pre-main sequence stars with known ages is critical to our understanding of early stellar evolution, but historically there has been difficulty in separating such stars from the field. We present a trained neural network model, Sagitta, that relies on Gaia DR2 and 2MASS photometry to identify pre-main sequence stars and to derive their age estimates. Our model successfully recovers populations and stellar properties associated with known star forming regions up to five kpc. Furthermore, it allows for a detailed look at the star-forming history of the solar neighborhood, particularly at age ranges to which we were not previously sensitive. In particular, we observe several bubbles in the distribution of stars, the most notable of which is a ring of stars associated with the Local Bubble, which may have common origins with the Gould's Belt.</p>
Zenodo
2021-02-26
info:eu-repo/semantics/conferencePoster
4564014
user-coolstars20half
1614347089.133992
5104300
md5:597d6c9cbd71222cbb85b8e5c0b72a72
https://zenodo.org/records/4564015/files/CoolStars2021Poster.pdf
public
10.5281/zenodo.4564014
isVersionOf
doi