Evaluating the Sensitivity of the Age Inferences of Red Giant Stars to Machine Learning Methodology
Jamie Tayar, Carli Mankowski, Lara Tunca, Dante Jordan, Mia Severino, Sydney McArthur, Zeina Benton, Sophia Armstrong, Alexa Leddy, Emily Bower, Zabdiel Sanchez, Colin Avery, Emily Cummings, Joshua Donley, Rachel Freeman, David R. Fulcher, Vanessa Hervie, James Ivey, Hyde Kenney, William MacMillan, Jake Mahoney, Eve Maramba, Erin Philip, Yazmeen Simpson, Ethan Strojie
astro-ph.SR, astro-ph.GA, astro-ph.IM
Submitted: 2026-06-23
Comments: 17 pages, 17 figures, submitted to AAS Journals
Code: https://github.com/jtayar/2025
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Deep Learning using Rectified Linear Units (ReLU)
- StelNet: Hierarchical Neural Network for Automatic Inference in Stellar Characterization
- Testing the Limits of Precise Subgiant Characterization with APOGEE and Gaia: Opening a Window to Unprecedented Astrophysical Studies
- The SkyMapper-Gaia RVS view of the Gaia-Enceladus-Sausage -- an investigation of the metallicity and mass of the Milky Way's last major merger
- Evolved stars with inconsistent age estimates: Abundance outliers or mass transfer products?
- TESS Asteroseismology of Red Giants in the Old Metal-Rich Open Clusters NGC 188 & NGC 6791
- Adam: A Method for Stochastic Optimization
- LSST Science Book, Version 2.0
- Expanding Asteroseismic Studies in Star Clusters Using NASA's TESS and ESA's Gaia Missions
- The Two-infall Model Revisited: Constraints on Milky Way Bulge Assembly from >30,000 Galactic Chemical Evolution Models and Machine Learning
- Model Choice Matters for Age Inference on the Red Giant Branch
- Roman Observations Time Allocation Committee: Final Report and Recommendations
- The YREC Stellar Evolution Code: Public Data Release
- The Nineteenth Data Release of the Sloan Digital Sky Survey
- Modeling Asteroseismic Yields for the Roman Galactic Bulge Time-Domain Survey
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