The Bayesian Asteroseismology data Modeling pipeline and its application to $K\mathit{2}$ data

We present the Bayesian Asteroseismology data Modeling (BAM) pipeline, an automated asteroseismology pipeline that returns global oscillation parameters and granulation parameters from the analysis of photometric time-series. BAM also determines if a star is likely to be a solar-like oscillator. We have designed BAM to specially process $K\mathit{2}$ light curves, which suffer from unique noise signatures that can confuse asteroseismic analysis, though it may be used on any photometric time series — including those from $Kepler$ and $TESS$. We demonstrate the BAM oscillation parameters are consistent within $\sim 1.53\mathrm{\%}(\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{o}\mathrm{m})\pm 0.2\mathrm{\%}(\mathrm{s}\mathrm{y}\mathrm{s}\mathrm{t}\mathrm{e}\mathrm{m}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{c})$ and $1.51\mathrm{\%}(\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{o}\mathrm{m})\pm 0.6\mathrm{\%}(\mathrm{s}\mathrm{y}\mathrm{s}\mathrm{t}\mathrm{e}\mathrm{m}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{c})$ for ${\nu }_{\mathrm{m}\mathrm{a}\mathrm{x}}$ and $\mathrm{\Delta }\nu$ with benchmark results for typical ${\it K2}$redgiantstarsinthe${\it K2}$ Galactic Archaeology Program’s (GAP) Campaign 1 sample. Application of BAM to $13016$ $K\mathit{2}$ Campaign 1 targets not in the GAP sample yields $104$ red giant solar-like oscillators. Based on the number of serendipitous giants we find, we estimate an upper limit on the average purity in dwarf selection among C1 proposals is $\approx 99\mathrm{\%}$, which could be lower when considering incompleteness in BAM detection efficiency, and proper motion cuts specific to C1 Guest Observer proposals.