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Improving transit characterisation with Gaussian process modelling of stellar variability

Barros, S. C. C. and Demangeon, O. and Diaz, R. F. and Cabrera Perez, Juan and Santos, N. C. and Faria, J. and Pereira, F. (2020) Improving transit characterisation with Gaussian process modelling of stellar variability. Astronomy & Astrophysics, 634, p. 75. EDP Sciences. DOI: 10.1051/0004-6361/201936086 ISSN 0004-6361

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Official URL: https://www.aanda.org/articles/aa/abs/2020/02/aa36086-19/aa36086-19.html

Abstract

Context. New photometric space missions to detect and characterise transiting exoplanets are focusing on bright stars to obtain high cadence, high signal-to-noise light curves. Since these missions will be sensitive to stellar oscillations and granulation even for dwarf stars, they will be limited by stellar variability. Therefore, it is crucial and timely to develop robust methods to account for and correct for stellar variability. Aims: We tested the performance of Gaussian process (GP) regression on the characterisation of transiting planets, and in particular to determine how many components of variability are necessary to describe high cadence, high signal-to-noise light curves expected from CHEOPS and PLATO. To achieve this, we selected a sample of bright stars observed in the asteroseismology field of CoRoT at high cadence (32 s) and high signal-to-noise ratio (S/N). Methods: We used GPs to model stellar variability including different combinations of stellar oscillations, granulation, and rotational modulation models. We preformed model comparison to find the best activity model fit to our data. We compared the best multi-component model with the usual one-component model used for transit retrieval and with a non-GP model. Results: We found that the best GP stellar variability model contains four to five variability components: one stellar oscillation component, two to four granulation components, and/or one rotational modulation component, which is consistent with results from asteroseismology. However, this high number of components is in contrast with the one-component GP model (1GP) commonly used in the literature for transit characterisation. Therefore, we compared the performance of the best multi-component GP model with the 1GP model in the derivation of transit parameters of simulated transits. We found that for Jupiter- and Neptune-size planets the best multi-component GP model is slightly better than the 1GP model, and much better than the non-GP model that gives biased results. For Earth-size planets, the 1GP model fails to retrieve the transit because it is a poor description of stellar activity. The non-GP model gives some biased results and the best multi-component GP is capable of retrieving the correct transit model parameters. Conclusions: We conclude that when characterising transiting exoplanets with high S/Ns and high cadence light curves, we need models that couple the description of stellar variability with the transits analysis, like GPs. Moreover, for Earth-like exoplanets a better description of stellar variability (achieved using multi-component models) improves the planetary characterisation. Our results are particularly important for the analysis of TESS, CHEOPS, and PLATO light curves.

Item URL in elib:https://elib.dlr.de/134191/
Document Type:Article
Title:Improving transit characterisation with Gaussian process modelling of stellar variability
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Barros, S. C. C.Instituto de Astrofisica e Ciencias do Espaco, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762 Porto, PortugalUNSPECIFIED
Demangeon, O.instituto de astrofísica e ciências do espaço, universidade de porto, caup, rua das estrelas, 4150-762 porto, portugalUNSPECIFIED
Diaz, R. F.Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Buenos Aires, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Astronomia y Fisica del Espacio (IAFE), Buenos Aires, ArgentinaUNSPECIFIED
Cabrera Perez, JuanJuan.Cabrera (at) dlr.dehttps://orcid.org/0000-0001-6653-5487
Santos, N. C.Instituto de Astrofisica e Ciencias do Espaco, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762 Porto, Portugal; Departamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Rua Campo Alegre, 4169-007 Porto, PortugalUNSPECIFIED
Faria, J.Instituto de Astrofísica e Ciências do Espaço, Universidade de Porto, CAUP, Rua das Estrelas, 4150-762 Porto, PortugalUNSPECIFIED
Pereira, F.Instituto de Astrofisica e Ciencias do Espaco, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762 Porto, PortugalUNSPECIFIED
Date:2020
Journal or Publication Title:Astronomy & Astrophysics
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:634
DOI :10.1051/0004-6361/201936086
Page Range:p. 75
Publisher:EDP Sciences
ISSN:0004-6361
Status:Published
Keywords:planets and satellites: fundamental parameters; planets and satellites: composition; methods: data analysis; techniques: photometric; stars: activity; Astrophysics - Earth and Planetary Astrophysics; Astrophysics - Instrumentation and Methods for Astrophysics; Astrophysics - Solar and Stellar Astrophysics
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Science and Exploration
DLR - Research area:Raumfahrt
DLR - Program:R EW - Erforschung des Weltraums
DLR - Research theme (Project):R - Project PLATO
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Planetary Research > Extrasolar Planets and Atmospheres
Deposited By: Cabrera Perez, Juan
Deposited On:27 Feb 2020 11:44
Last Modified:19 May 2020 13:36

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