TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys

Context. There have been many efforts to correct systematic effects in astronomical light curves to improve the detection and characterization of planetary transits and astrophysical variability. Algorithms such as the trend filtering algorithm (TFA) use simultaneously-observed stars to measure and...

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Detalles Bibliográficos
Autores: Ser Badia, Daniel del, Fors Aldrich, Octavi, Núñez de Murga, Jorge, 1955-
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/208020
Acceso en línea:https://hdl.handle.net/2445/208020
Access Level:acceso abierto
Palabra clave:Fotometria
Planetes
Estels
Photometry
Planets
Stars
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spelling TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveysSer Badia, Daniel delFors Aldrich, OctaviNúñez de Murga, Jorge, 1955-FotometriaPlanetesEstelsPhotometryPlanetsStarsContext. There have been many efforts to correct systematic effects in astronomical light curves to improve the detection and characterization of planetary transits and astrophysical variability. Algorithms such as the trend filtering algorithm (TFA) use simultaneously-observed stars to measure and remove systematic effects, and binning is used to reduce high-frequency random noise. Aims: We present TFAW, a wavelet-based modified version of TFA. First, TFAW aims to increase the periodic signal detection and second, to return a detrended and denoised signal without modifying its intrinsic characteristics. Methods: We modified TFA's frequency analysis step adding a stationary wavelet transform filter to perform an initial noise and outlier removal and increase the detection of variable signals. A wavelet-based filter was added to TFA's signal reconstruction to perform an adaptive characterization of the noise- and trend-free signal and the underlying noise contribution at each iteration while preserving astrophysical signals. We carried out tests over simulated sinusoidal and transit-like signals to assess the effectiveness of the method and applied TFAW to real light curves from TFRM. We also studied TFAW's application to simulated multiperiodic signals. Results: TFAW improves the signal detection rate by increasing the signal detection efficiency (SDE) up to a factor ̃2.5× for low S/R light curves. For simulated transits, the transit detection rate improves by a factor ̃2 - 5× in the low-S/R regime compared to TFA. TFAW signal approximation performs up to a factor ̃2× better than bin averaging for planetary transits. The standard deviations of simulated and real TFAW light curves are ̃40% better compared to TFA. TFAW yields better MCMC posterior distributions and returns lower uncertainties, less biased transit parameters and narrower (by approximately ten times) credibility intervals for simulated transits. TFAW is also able to improve the characterization of multiperiodic signals. We present a newly-discovered variable star from TFRM.EDP Sciences2024202420182024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion13 p.application/pdfhttps://hdl.handle.net/2445/208020Articles publicats en revistes (Física Quàntica i Astrofísica)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1051/0004-6361/201730671Astronomy & Astrophysics, 2018, vol. 619, num.A86, p. 1-13https://doi.org/10.1051/0004-6361/201730671(c) The European Southern Observatory (ESO), 2018info:eu-repo/semantics/openAccessoai:recercat.cat:2445/2080202026-05-29T05:05:01Z
dc.title.none.fl_str_mv TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
title TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
spellingShingle TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
Ser Badia, Daniel del
Fotometria
Planetes
Estels
Photometry
Planets
Stars
title_short TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
title_full TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
title_fullStr TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
title_full_unstemmed TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
title_sort TFAW: Wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
dc.creator.none.fl_str_mv Ser Badia, Daniel del
Fors Aldrich, Octavi
Núñez de Murga, Jorge, 1955-
author Ser Badia, Daniel del
author_facet Ser Badia, Daniel del
Fors Aldrich, Octavi
Núñez de Murga, Jorge, 1955-
author_role author
author2 Fors Aldrich, Octavi
Núñez de Murga, Jorge, 1955-
author2_role author
author
dc.subject.none.fl_str_mv Fotometria
Planetes
Estels
Photometry
Planets
Stars
topic Fotometria
Planetes
Estels
Photometry
Planets
Stars
description Context. There have been many efforts to correct systematic effects in astronomical light curves to improve the detection and characterization of planetary transits and astrophysical variability. Algorithms such as the trend filtering algorithm (TFA) use simultaneously-observed stars to measure and remove systematic effects, and binning is used to reduce high-frequency random noise. Aims: We present TFAW, a wavelet-based modified version of TFA. First, TFAW aims to increase the periodic signal detection and second, to return a detrended and denoised signal without modifying its intrinsic characteristics. Methods: We modified TFA's frequency analysis step adding a stationary wavelet transform filter to perform an initial noise and outlier removal and increase the detection of variable signals. A wavelet-based filter was added to TFA's signal reconstruction to perform an adaptive characterization of the noise- and trend-free signal and the underlying noise contribution at each iteration while preserving astrophysical signals. We carried out tests over simulated sinusoidal and transit-like signals to assess the effectiveness of the method and applied TFAW to real light curves from TFRM. We also studied TFAW's application to simulated multiperiodic signals. Results: TFAW improves the signal detection rate by increasing the signal detection efficiency (SDE) up to a factor ̃2.5× for low S/R light curves. For simulated transits, the transit detection rate improves by a factor ̃2 - 5× in the low-S/R regime compared to TFA. TFAW signal approximation performs up to a factor ̃2× better than bin averaging for planetary transits. The standard deviations of simulated and real TFAW light curves are ̃40% better compared to TFA. TFAW yields better MCMC posterior distributions and returns lower uncertainties, less biased transit parameters and narrower (by approximately ten times) credibility intervals for simulated transits. TFAW is also able to improve the characterization of multiperiodic signals. We present a newly-discovered variable star from TFRM.
publishDate 2018
dc.date.none.fl_str_mv 2018
2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/208020
url https://hdl.handle.net/2445/208020
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1051/0004-6361/201730671
Astronomy & Astrophysics, 2018, vol. 619, num.A86, p. 1-13
https://doi.org/10.1051/0004-6361/201730671
dc.rights.none.fl_str_mv (c) The European Southern Observatory (ESO), 2018
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) The European Southern Observatory (ESO), 2018
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 13 p.
application/pdf
dc.publisher.none.fl_str_mv EDP Sciences
publisher.none.fl_str_mv EDP Sciences
dc.source.none.fl_str_mv Articles publicats en revistes (Física Quàntica i Astrofísica)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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