Modelling solar radial velocities and photometric variability with SOAP

Stellar activity remains one of the main limitations in the detection of Earth-like planets using radial velocity (RV) measurements. The Sun, as the only star for which surface features can be spatially resolved, offers a unique testbed for studying the impact of active regions on RV and photometric variability. Using (Spot Oscillation And Planet), we modelled solar RV and photometric variability induced by spots and faculae over long timescales. Our goal is to verify whether present-day, state-of-the-art models of the cross-correlation function correctly reproduce the observed variability. Moreover, we aim to assess how the choice of input data and identification technique influences the agreement between simulated and observed signals. SOAPv4 To simulate solar RV and photometric time series, we first identified active regions in SDO images. This was done using mathematical morphological transforms applied to SDO/HMI and AIA images. Mathematical morphological identification was validated against other state-of-the-art identification methods. Using these inputs, we ran to simulate solar RVs and photometry, and we validated the results with HARPS-N RV observations, as well as with VIRGO/SPM photometric measurements. SOAPv4 The simulations that use mathematical morphological identification achieved the best match with the observed RV time series, yielding residuals with a measured standard deviation of sim0.91 m/s. Other state-of-the-art methods produced higher filling factors and, consequently, larger discrepancies. The photometric simulations reproduced the overall variability trends. We demonstrate that mathematical morphological transforms accurately identify solar active regions. Using these inputs, reproduces the observed solar RV variability with a measured standard deviation of the residuals of sim0.91 m/s. Photometric simulations capture the overall variability trends, confirming that can reliably model the impact of both spots and faculae on solar RVs and photometry. SOAPv4 SOAP

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-02-17
DOI
https://doi.org/10.1051/0004-6361/202557827/pdf
Primary Topic
Solar and Space Plasma Dynamics
Type
article
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article

Modelling solar radial velocities and photometric variability with SOAP

Â. R. G. Santos, N. C. Santos, K. Al Moulla, R. Gafeira et al.
Springer Link (Chiba Institute of Technology)
Solar and Space Plasma Dynamics
article

Modelling solar radial velocities and photometric variability with SOAP

Â. R. G. Santos, N. C. Santos, K. Al Moulla, R. Gafeira, E. Cristo, M. Cretignier, A. Barka, T. Barata
article en

Abstract

Stellar activity remains one of the main limitations in the detection of Earth-like planets using radial velocity (RV) measurements. The Sun, as the only star for which surface features can be spatially resolved, offers a unique testbed for studying the impact of active regions on RV and photometric variability. Using (Spot Oscillation And Planet), we modelled solar RV and photometric variability induced by spots and faculae over long timescales. Our goal is to verify whether present-day, state-of-the-art models of the cross-correlation function correctly reproduce the observed variability. Moreover, we aim to assess how the choice of input data and identification technique influences the agreement between simulated and observed signals. SOAPv4 To simulate solar RV and photometric time series, we first identified active regions in SDO images. This was done using mathematical morphological transforms applied to SDO/HMI and AIA images. Mathematical morphological identification was validated against other state-of-the-art identification methods. Using these inputs, we ran to simulate solar RVs and photometry, and we validated the results with HARPS-N RV observations, as well as with VIRGO/SPM photometric measurements. SOAPv4 The simulations that use mathematical morphological identification achieved the best match with the observed RV time series, yielding residuals with a measured standard deviation of sim0.91 m/s. Other state-of-the-art methods produced higher filling factors and, consequently, larger discrepancies. The photometric simulations reproduced the overall variability trends. We demonstrate that mathematical morphological transforms accurately identify solar active regions. Using these inputs, reproduces the observed solar RV variability with a measured standard deviation of the residuals of sim0.91 m/s. Photometric simulations capture the overall variability trends, confirming that can reliably model the impact of both spots and faculae on solar RVs and photometry. SOAPv4 SOAP

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 49%
Solar and Space Plasma Dynamics
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