Systematics in asteroseismic modelling: application of a correlated noise model for oscillation frequencies
The detailed modelling of stellar oscillations is a powerful approach to
characterizing stars. However, poor treatment of systematics in
theoretical models leads to misinterpretations of stars. Here,
we propose a more principled statistical treatment for the
systematics to be applied to fitting individual mode frequencies
with a typical stellar model grid. We introduce a correlated
noise model based on a Gaussian process (GP) kernel to describe
the systematics given that mode frequency systematics are
expected to be highly correlated. We show that tuning the GP
kernel can reproduce general features of frequency variations
for changing model input physics and fundamental parameters.
Fits with the correlated noise model better recover stellar
parameters than traditional methods that either ignore the
systematics or treat them as uncorrelated noise.