Stellar variance for asteroseismic parameter estimation and inferences on the evolutionary state and binary population of red giant stars

Jones, Caitlin Dawn (2018). Stellar variance for asteroseismic parameter estimation and inferences on the evolutionary state and binary population of red giant stars. University of Birmingham. Ph.D.

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Abstract

The latest generation of space missions have performed large scale observations of stars and this has been revolutionary in the field of asteroseismology. The ability to characterise thousands of stars has been instrumental in understanding the interiors of stars and the evolution of the Galaxy. This thesis focuses on studying red giant stars, both on an individual basis and as a population, using a robust asteroseismic metric we define based on the bandpass filtered estimate of the stellar variance.
Here we present results of testing asteroseismic scaling relations, and the assumptions needed to create realistic simulated power spectra. The resulting synthetic datasets then inform three other investigations. We present the results of an investigation into determining the binary population of Kepler red giant branch stars using our variance metric. The inferred fraction of 57.4 +/- 2.5% is consistent with previous work on main sequence stars. Results of using our variance metric as part of an analysis pipeline, designed to automate the detection of solar-like oscillations and determine global asteroseismic parameters in K2 and CoRoT data are presented. Finally, we present a discussion of using ourvariance metric to highlight structural differences
between red giant branch and red clump stars.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):