Speaker
Description
The analysis of stellar surface oscillations provides a unique window into stellar interiors, enabling precise determination of fundamental properties of solar-type stars, such as radius, mass, and age. Among these properties, age estimation is particularly crucial, serving as a cornerstone for understanding galactic dynamics by offering insights into the timescales of star formation and chemical enrichment. Despite its importance, determining robust stellar ages remains challenging . This difficulty arises because age is a highly model-dependent parameter, significantly influenced by the various input physics used in stellar models, e.g. mixing-length parameter. Using a sample of 32 main-sequence stars, we present a stellar modeling approach in which we scale down the accepted models obtained through forward-modeling procedures to only those that better represent the core chemical composition of each star, i.e. central hydrogen abundance. This is achieved through an additional process of comparing specific observed frequency separations for each star to the ones derived from the acceptable models. Our approach demonstrates a significant improvement in age precision achieving 8% compared to the 15-20% typical of other techniques, thus establishing the stars' precise evolutionary states and ages. Furthermore, we reveal that a single solar mixing length parameter is only reliable for modeling spectroscopic solar twins, and it's insufficient for other stars.
| Stream | Science or Engineering |
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