LASR-guided stellar photometric variability subtraction

We develop a technique for removing stellar variability in the light curves of δ-Scuti and similar stars. Our technique, which we name the Linear Algorithm for Significance Reduction (LASR), subtracts oscillations from a time series by minimizing their statistical significance in frequency space. We...

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Veröffentlicht in:Astronomy and astrophysics (Berlin) 2018-07, Vol.615
Hauptverfasser: Ahlers, John P., Barnes, Jason W., Horvath, Sarah A., Myers, Samuel A., Hedman, Matthew M.
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container_title Astronomy and astrophysics (Berlin)
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creator Ahlers, John P.
Barnes, Jason W.
Horvath, Sarah A.
Myers, Samuel A.
Hedman, Matthew M.
description We develop a technique for removing stellar variability in the light curves of δ-Scuti and similar stars. Our technique, which we name the Linear Algorithm for Significance Reduction (LASR), subtracts oscillations from a time series by minimizing their statistical significance in frequency space. We demonstrate that LASR can subtract variable signals of near-arbitrary complexity and can robustly handle close frequency pairs and overtone frequencies. We demonstrate that our algorithm performs an equivalent fit as prewhitening to the straightforward variable signal of KIC 9700322. We also show that LASR provides a better fit to seismic activity than prewhitening in the case of the complex δ-Scuti KOI-976.
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subjects Algorithms
asteroseismology
Complexity
methods: data analysis
methods: numerical
Photometry
Prewhitening
Seismic activity
stars: variables: delta Scuti
Subtraction
techniques: polarimetric
Variability
title LASR-guided stellar photometric variability subtraction
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