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EVEREST: Tools for de-trending stellar photometry

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Ada Coda
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EVEREST: Tools for de-trending stellar photometry

Postby Ada Coda » Tue Jul 31, 2018 3:18 am

EVEREST: Tools for de-trending stellar photometry

Abstract: EVEREST (EPIC Variability Extraction and Removal for Exoplanet Science Targets) removes instrumental noise from light curves with pixel level decorrelation and Gaussian processes. The code, written in Python, generates the EVEREST catalog and offers tools for accessing and interacting with the de-trended light curves. EVEREST exploits correlations across the pixels on the CCD to remove systematics introduced by the spacecraft’s pointing error. For K2, it yields light curves with precision comparable to that of the original Kepler mission. Interaction with the EVEREST catalog catalog is available via the command line and through the Python interface. Though written for K2, EVEREST can be applied to additional surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets.

Credit: Luger, Rodrigo; Agol, Eric; Kruse, Ethan; Barnes, Rory; Becker, Andrew; Foreman-Mackey, Daniel; Deming, Drake

Site: https://rodluger.github.io/everest/
https://ui.adsabs.harvard.edu/#abs/2017arXiv170205488L

Bibcode: 2018ascl.soft07029L

Preferred citation method: https://ui.adsabs.harvard.edu/#abs/2016AJ....152..100L and https://ui.adsabs.harvard.edu/#abs/2017arXiv170205488L

ID: ascl:1807.029
Last edited by Ada Coda on Mon Oct 01, 2018 11:56 pm, edited 1 time in total.
Reason: Updated code entry.

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