The more the merrier: grid based modelling of Kepler dwarfs with 5-dimensional stellar grids

We present preliminary results of our grid based modelling (GBM) of the dwarf/subgiant sample of stars observed with Kepler including global asteroseismic parameters. GBM analysis in this work is based on a large grid of stellar models that is characterized by five independent parameters: model mass...

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Bibliographic Details
Main Authors: Serenelli Aldo, Chaplin William J., Huber Daniel
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:EPJ Web of Conferences
Online Access:https://doi.org/10.1051/epjconf/201716003011
Description
Summary:We present preliminary results of our grid based modelling (GBM) of the dwarf/subgiant sample of stars observed with Kepler including global asteroseismic parameters. GBM analysis in this work is based on a large grid of stellar models that is characterized by five independent parameters: model mass and age, initial metallicity (Zini), initial helium (Yini), and mixing length parameter (αMLT). Using this grid relaxes assumptions used in all previous GBM work where the initial composition is determined by a single parameter and that αMLT is fixed to a solar-calibrated value. The new grid allows us to study, for example, the impact of different galactic chemical enrichment models on the determination of stellar parameters such as mass radius and age. Also, it allows to include new results from stellar atmosphere models on αMLT in the GBM analysis in a simple manner. Alternatively, it can be tested if global asteroseismology is a useful tool to constraint our ignorance on quantities such as Yini and αMLT. Initial findings show that mass determination is robust with respect to freedom in the latter quantities, with a 4.4% maximum deviation for extreme assumptions regarding prior information on Yini – Zini relations and aMLT. On the other hand, tests carried out so far seem to indicate that global seismology does not have much power to constrain Yini – Zni relations of αMLT values without resourcing to additional information.
ISSN:2100-014X