5–7 Oct 2026
Konkoly Observatory, HUN-REN CSFK
Europe/Budapest timezone

What can mass loss observations and models tell us about the properties of mass-losing AGB stars?

5 Oct 2026, 16:50
25m
Konkoly Observatory, HUN-REN CSFK

Konkoly Observatory, HUN-REN CSFK

20 minute talk

Speaker

Henry Prager (University of Iowa)

Description

Asymptotic Giant Branch (AGB) stars are the near-end state of low-to-intermediate mass stars (we have focused on stars between $0.6\ \mathrm{M_{\odot}}$ and $2.0\ \mathrm{M_{\odot}}$). Through combined effects of opacity driven pulsations and dust formation, these stars develop a strong pulsation and dust driven stellar wind and consequently experience significant mass loss, ultimately losing their stellar envelopes and becoming white dwarfs. Surveys of nearby galaxies tell us the observable properties of these mass-losing stars, and ultimately we should be able to replicate the properties of these populations using atmospheric models.

We have been investigating the effects of modifying parameters of atmospheric models generated using George Bowen’s atmospheric pulsation code on the properties of the resulting grid of stellar of models. Initial results suggested extreme modifications to both the driving amplitude and dust properties were necessary to produce stars with the observed mass-loss rates at observed luminosities and pulsation periods. However, continued investigation has shown that modification of radius-mass-luminosity and pulsation-mass-radius relations to better match the results of dynamic 3D models of these stars significantly improves agreement between the properties of the modeled atmospheres and observations. Further, these modified constraints lead to self-consistent determinations of which stars should be losing mass from multiple methods. This implies we will need 3D models to correctly determine the relations between stellar mass, luminosity, radius, and pulsation period on the AGB.

Authors

Henry Prager (University of Iowa) Prof. Lee Anne Willson (Iowa State University)

Co-authors

Dr Joyce Guzik (Los Alamos National Laboratory) Prof. Michelle Creech-Eakman (New Mexico Institute of Mining and Technology) Dr Qian Wang (Iowa State University)

Presentation materials

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