Asteroseismology with the Roman Galactic Bulge Time-Domain Survey
Daniel Huber, Marc Pinsonneault, Paul Beck, Timothy R. Bedding, Joss, Bland-Hawthorn, Sylvain N. Breton, Lisa Bugnet, William J. Chaplin, Rafael A., Garcia, Samuel K. Grunblatt, Joyce A. Guzik, Saskia Hekker, Steven D., Kawaler, Stephane Mathis, Savita Mathur, Travis Metcalfe

TL;DR
The paper discusses how the Roman Galactic Bulge Time-Domain Survey can enable asteroseismology of red giant stars, providing new insights into stellar populations in the Milky Way's bulge through precise photometry and complementary data.
Contribution
It identifies key photometric requirements and observational strategies for effective asteroseismology with Roman, highlighting its potential to study stellar populations in the Galactic bulge.
Findings
Photometric precision of 1 mmag per 15 min enables red clump star detection.
Repeat observations can improve data quality or expand stellar sample.
Synergies with Gaia and exoplanet studies enhance scientific returns.
Abstract
Asteroseismology has transformed stellar astrophysics. Red giant asteroseismology is a prime example, with oscillation periods and amplitudes that are readily detectable with time-domain space-based telescopes. These oscillations can be used to infer masses, ages and radii for large numbers of stars, providing unique constraints on stellar populations in our galaxy. The cadence, duration, and spatial resolution of the Roman galactic bulge time-domain survey (GBTDS) are well-suited for asteroseismology and will probe an important population not studied by prior missions. We identify photometric precision as a key requirement for realizing the potential of asteroseismology with Roman. A precision of 1 mmag per 15-min cadence or better for saturated stars will enable detections of the populous red clump star population in the Galactic bulge. If the survey efficiency is better than…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Adaptive optics and wavefront sensing
