Identifying activity induced RV periodicities and correlations using central line moments

ABSTRACT The radial velocity (RV) method of exoplanet detection requires mitigation of nuisance signals arising from stellar activity. Using analytic cool and facular spot models, we explore the use of central line moments (CLMs) for recovering and monitoring rotation induced RV variability. Different spot distribution patterns, photosphere-spot contrast ratios, and the presence or absence of the convective blueshift lead to differences in CLM signals between M and G dwarfs. Harmonics of the rotation period are often recovered with the highest power in standard periodogram analyses. By contrast, we show the true stellar rotation may be more reliably recovered with string length minimization. For solar minimum activity levels, recovery of the stellar rotation signal from CLMs is found to require unfeasibly high signal-to-noise observations. The stellar rotation period can be recovered at solar maximum activity levels from CLMs for reasonable cross-correlation function (CCF) signal-to-noise ratios >1000–5000. The CLMs can be used to recover and monitor stellar activity through their mutual correlations and correlations with RV and bisector inverse span. The skewness of a CCF, a measure of asymmetry, is described by the third CLM, $M_3$. Our noise-free simulations indicate the linear RV versus $M_3$ correlation is up to 10 per cent higher than the RV versus bisector inverse span correlation. We find a corresponding ∼5 per cent increase in linear correlation for CARMENES observations of the M star, AU Mic. We also assess the effectiveness of the time derivative of the second CLM, $M_2$, for monitoring stellar activity.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2024-09-12
DOI
https://doi.org/10.1093/mnras/stae2125
Citations
5
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.81

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article

Identifying activity induced RV periodicities and correlations using central line moments

M. Damasso, F. Liebing, S. V. Jeffers, C. A. Haswell et al.
5 citations
Monthly Notices of the Royal Astronomical Society
Computational Drug Discovery Methods
1.81
article

Identifying activity induced RV periodicities and correlations using central line moments

M. Damasso, F. Liebing, S. V. Jeffers, C. A. Haswell, M. Perger, G. Anglada‐Escudé, J. R. Barnes
article en
5 citations

Abstract

ABSTRACT The radial velocity (RV) method of exoplanet detection requires mitigation of nuisance signals arising from stellar activity. Using analytic cool and facular spot models, we explore the use of central line moments (CLMs) for recovering and monitoring rotation induced RV variability. Different spot distribution patterns, photosphere-spot contrast ratios, and the presence or absence of the convective blueshift lead to differences in CLM signals between M and G dwarfs. Harmonics of the rotation period are often recovered with the highest power in standard periodogram analyses. By contrast, we show the true stellar rotation may be more reliably recovered with string length minimization. For solar minimum activity levels, recovery of the stellar rotation signal from CLMs is found to require unfeasibly high signal-to-noise observations. The stellar rotation period can be recovered at solar maximum activity levels from CLMs for reasonable cross-correlation function (CCF) signal-to-noise ratios >1000–5000. The CLMs can be used to recover and monitor stellar activity through their mutual correlations and correlations with RV and bisector inverse span. The skewness of a CCF, a measure of asymmetry, is described by the third CLM, $M_3$. Our noise-free simulations indicate the linear RV versus $M_3$ correlation is up to 10 per cent higher than the RV versus bisector inverse span correlation. We find a corresponding ∼5 per cent increase in linear correlation for CARMENES observations of the M star, AU Mic. We also assess the effectiveness of the time derivative of the second CLM, $M_2$, for monitoring stellar activity.

Monthly Notices of the Royal Astronomical SocietyVol. 534(2)
Institute of Space Sciences (ES), The Open University (GB), Institut d'Estudis Espacials de Catalunya (ES), Osservatorio Astrofisico di Torino (IT), Institute of Space Sciences (ES), Max Planck Institute for Solar System Research (DE)
Ministerio de Ciencia, Innovación y Universidades, Centres de Recerca de Catalunya, Deutsche Forschungsgemeinschaft, Generalitat de Catalunya, Science and Technology Facilities Council, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 13%
Computational Drug Discovery Methods
1.81
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