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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