k-Means Aperture Optimization Applied to Kepler K2 Time Series Photometry of Titan. (arXiv:1906.04220v1 [astro-ph.EP])
<a href="http://arxiv.org/find/astro-ph/1/au:+Parker_A/0/1/0/all/0/1">Alex H. Parker</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Horst_S/0/1/0/all/0/1">Sarah M. Hörst</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ryan_E/0/1/0/all/0/1">Erin L. Ryan</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Howett_C/0/1/0/all/0/1">Carly J. A Howett</a>
Motivated by the Kepler K2 time series of Titan, we present an aperture
optimization technique for extracting photometry of saturated moving targets
with high temporally- and spatially-varying backgrounds. Our approach uses
$k$-means clustering to identify interleaved families of images with similar
Point-Spread Function and saturation properties, optimizes apertures for each
family independently, then merges the time series through a normalization
procedure. By applying $k$-means aperture optimization to the K2 Titan data, we
achieve $leq$0.33% photometric scatter in spite of background levels varying
from 15% to 60% of the target’s flux. We find no compelling evidence for
signals attributable to atmospheric variation on the timescales sampled by
these observations. We explore other potential applications of the $k$-means
aperture optimization technique, including testing its performance on a
saturated K2 eclipsing binary star. We conclude with a discussion of the
potential for future continuous high-precision photometry campaigns for
revealing the dynamical properties of Titan’s atmosphere.
Motivated by the Kepler K2 time series of Titan, we present an aperture
optimization technique for extracting photometry of saturated moving targets
with high temporally- and spatially-varying backgrounds. Our approach uses
$k$-means clustering to identify interleaved families of images with similar
Point-Spread Function and saturation properties, optimizes apertures for each
family independently, then merges the time series through a normalization
procedure. By applying $k$-means aperture optimization to the K2 Titan data, we
achieve $leq$0.33% photometric scatter in spite of background levels varying
from 15% to 60% of the target’s flux. We find no compelling evidence for
signals attributable to atmospheric variation on the timescales sampled by
these observations. We explore other potential applications of the $k$-means
aperture optimization technique, including testing its performance on a
saturated K2 eclipsing binary star. We conclude with a discussion of the
potential for future continuous high-precision photometry campaigns for
revealing the dynamical properties of Titan’s atmosphere.
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