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eleanor: An Open-source Tool for Extracting Light Curves from the TESS Full-frame Images

Feinstein, Adina D. and Montet, Benjamin T. and Foreman-Mackey, Daniel and Bedell, Megan E. and Saunders, Nicholas and Bean, Jacob L. and Christiansen, Jessie L. and Hedges, Christina and Luger, Rodrigo and Scolnic, Daniel and de Miranda Cardoso, José Vinícius (2019) eleanor: An Open-source Tool for Extracting Light Curves from the TESS Full-frame Images. Publications of the Astronomical Society of the Pacific, 131 (1003). Art. No. 094502. ISSN 0004-6280. doi:10.1088/1538-3873/ab291c. https://resolver.caltech.edu/CaltechAUTHORS:20190815-132553119

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Abstract

During its two-year prime mission, the Transiting Exoplanet Survey Satellite (TESS) will perform a time-series photometric survey covering over 80% of the sky. This survey comprises observations of 26 24° × 96° sectors that are each monitored continuously for approximately 27 days. The main goal of TESS is to find transiting planets around 200,000 pre-selected stars for which fixed aperture photometry is recorded every two minutes. However, TESS is also recording and delivering full-frame images (FFIs) of each detector at a 30-minutes cadence. We have created an open-source tool, eleanor, to produce light curves for objects in the TESS FFIs. Here, we describe the methods used in eleanor to produce light curves that are optimized for planet searches. The tool performs background subtraction; aperture and point-spread function photometry; decorrelation of instrument systematics; and cotrending using principal component analysis. We recover known transiting exoplanets in the FFIs to validate the pipeline and perform a limited search for new planet candidates in Sector 1. Our tests indicate that eleanor produces light curves with significantly less scatter than other tools that have been used in the literature. Cadence-stacked images, and raw and detrended eleanor light curves for each analyzed star will be hosted on Mikulski Archive for Space Telescopes, with planet candidates on ExoFOP-TESS as Community TESS Objects of Interest. This work confirms the promise that the TESS FFIs will enable the detection of thousands of new exoplanets and a broad range of time domain astrophysics.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1088/1538-3873/ab291cDOIArticle
https://arxiv.org/abs/1903.09152arXivDiscussion Paper
ORCID:
AuthorORCID
Feinstein, Adina D.0000-0002-9464-8101
Montet, Benjamin T.0000-0001-7516-8308
Foreman-Mackey, Daniel0000-0002-9328-5652
Bedell, Megan E.0000-0001-9907-7742
Saunders, Nicholas0000-0003-2657-3889
Bean, Jacob L.0000-0003-4733-6532
Christiansen, Jessie L.0000-0002-8035-4778
Hedges, Christina0000-0002-3385-8391
Luger, Rodrigo0000-0002-0296-3826
Scolnic, Daniel0000-0002-4934-5849
de Miranda Cardoso, José Vinícius0000-0001-5410-5551
Additional Information:© 2019 The Astronomical Society of the Pacific. Received 2019 March 21; accepted 2019 June 12; published 2019 July 31. We thank Doug Caldwell, Michael Fausnaugh, Jon Jenkins, and Roland Vanderspek for valuable discussions. We thank Patrick Vallely for his direction to recovering known supernovae in the TESS field of view. We thank the referee for the helpful comments which improved the quality of this paper. Work by B.T.M. was performed under contract with the Jet Propulsion Laboratory (JPL) funded by NASA through the Sagan Fellowship Program executed by the NASA Exoplanet Science Institute. We would like to acknowledge the live animal webcams of the Kansas City Zoo, and especially the emotional support of Elvis the emperor penguin during our hack weeks. This work was funded in part through the NASA TESS Guest Investigator Program, as a part of Program G011237 (PI Montet). This paper includes data collected by the TESS mission, which are publicly available from the Mikulski Archive for Space Telescopes (MAST). Funding for the TESS mission is provided by NASA's Science Mission directorate. This project was developed in part at the Building Early Science with TESS meeting, which took place in 2019 March at the University of Chicago. Software: numpy (Van Der Walt et al. 2011), matplotlib (Hunter 2007), scipy (Jones et al. 2001) tensorflow (Abadi et al. 2015), lightkurve,12 photutils,13 astropy (Astropy Collaboration et al. 2013; Price-Whelan et al. 2018), eleanor,14 sklearn (Pedregosa et al. 2012). Facility: TESS. -
Group:Infrared Processing and Analysis Center (IPAC)
Funders:
Funding AgencyGrant Number
NASA Sagan FellowshipUNSPECIFIED
NASAG011237
Subject Keywords:binaries: eclipsing – methods: data analysis – planets and satellites: detection – techniques: image processing – techniques: photometric
Issue or Number:1003
DOI:10.1088/1538-3873/ab291c
Record Number:CaltechAUTHORS:20190815-132553119
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190815-132553119
Official Citation:Adina D. Feinstein et al 2019 PASP 131 094502
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97926
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:15 Aug 2019 20:34
Last Modified:16 Nov 2021 17:35

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