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EXOPLANETARY DETECTION BY MULTIFRACTAL SPECTRAL ANALYSIS
Stockholm University, Nordic Institute for Theoretical Physics (Nordita). Yale University, USA.
Stockholm University, Nordic Institute for Theoretical Physics (Nordita). Yale University, USA; University of Oxford, UK.
Number of Authors: 32017 (English)In: Astronomical Journal, ISSN 0004-6256, E-ISSN 1538-3881, Vol. 153, no 1, article id 12Article in journal (Refereed) Published
Abstract [en]

Owing to technological advances, the number of exoplanets discovered has risen dramatically in the last few years. However, when trying to observe Earth analogs, it is often difficult to test the veracity of detection. We have developed a new approach to the analysis of exoplanetary spectral observations based on temporal multifractality, which identifies timescales that characterize planetary orbital motion around the host star and those that arise from stellar features such as spots. Without fitting stellar models to spectral data, we show how the planetary signal can be robustly detected from noisy data using noise amplitude as a source of information. For observation of transiting planets, combining this method with simple geometry allows us to relate the timescales obtained to primary and secondary eclipse of the exoplanets. Making use of data obtained with ground-based and space-based observations we have tested our approach on HD 189733b. Moreover, we have investigated the use of this technique in measuring planetary orbital motion via Doppler shift detection. Finally, we have analyzed synthetic spectra obtained using the SOAP 2.0 tool, which simulates a stellar spectrum and the influence of the presence of a planet or a spot on that spectrum over one orbital period. We have demonstrated that, so long as the signal-to-noise-ratio >= 75, our approach reconstructs the planetary orbital period, as well as the rotation period of a spot on the stellar surface.

Place, publisher, year, edition, pages
2017. Vol. 153, no 1, article id 12
Keywords [en]
methods: analytical, methods: data analysis, methods: observational, methods: statistical, planets and satellites: detection, techniques: spectroscopic
National Category
Astronomy, Astrophysics and Cosmology
Identifiers
URN: urn:nbn:se:su:diva-140403DOI: 10.3847/1538-3881/153/1/12ISI: 000391682800001OAI: oai:DiVA.org:su-140403DiVA, id: diva2:1081251
Available from: 2017-03-13 Created: 2017-03-13 Last updated: 2022-02-28Bibliographically approved

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Del Sordo, FabioWettlaufer, John S.

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