October 6, 2021 Poster Open Access

Santos, Angela R. G.; Mathur, Savita; García, Rafael A.; Cunha, Margarida S.; Avelino, Pedro P.; Broomhall, Anne-Marie; Egeland, Ricky; Breton, Sylvain N.

MARC21 XML Export

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    <subfield code="a">Part of the results, particularly on the ACF for artificial date, are published and can be found here: https://ui.adsabs.harvard.edu/abs/2021MNRAS.508..267S/abstract

The rotation and average S_ph catalog can be found here:
https://ui.adsabs.harvard.edu/abs/2019ApJS..244...21S/abstract
https://ui.adsabs.harvard.edu/abs/2021ApJS..255...17S/abstract

The machine learning algorithm for rotation, ROOSTER, is described here:
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    <subfield code="u">CEA, Université Paris-Saclay</subfield>
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    <subfield code="a">García, Rafael A.</subfield>
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    <subfield code="a">Avelino, Pedro P.</subfield>
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    <subfield code="u">Department of Physics, University of Warwick</subfield>
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    <subfield code="u">Department of Physics, University of Warwick</subfield>
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    <subfield code="a">&lt;p&gt;Rotational modulation due to dark spots co-rotating with the stellar surface allows us to constrain rotation and magnetic properties of solar-like stars. The long-term observations collected by &lt;em&gt;Kepler&lt;/em&gt; (and those that will be collected by PLATO) are preferred for a better characterization of magnetic activity. In this work, we investigate the temporal variability of the photometric magnetic activity proxy S&lt;sub&gt;ph&lt;/sub&gt;, as well as the characteristic timescale of active-regions in solar-like stars.&lt;/p&gt;</subfield>
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