Stellar magnetic field database and extrapolation method
Abstract
Context . During the past two decades, thousands of stellar magnetic fields have been measured using the Zeeman-Doppler imaging method. No unified database gathers all measurements in a homogeneous way. Aims . The magnetic field of a star is a key ingredient of its plasma interactions with companions, either other stars or exoplanets, and of its radio and X-ray emissions. The dipolar component of a stellar magnetic field, in particular, allows us to estimate the magnetic (Poynting) flux that is carried away by the stellar wind, which sweeps across exoplanets or their magnetospheres and is thought to drive electron acceleration and radio emissions. We built a database of known stellar magnetic fields, of which we inferred the dipolar field component, and we present the methods that we developed to estimate a stellar magnetic field when no measurement is available. Methods . We compiled published Zeeman-Doppler measurements of stellar magnetic fields into a database, and we show how the dipolar component can be extracted from various measurements. We included several other stellar parameters in the database (mass, radius, rotation period, effective temperature, age, and V-band magnitude). Then, we built and compared two extrapolation methods for inferring stellar magnetic fields from the other stellar parameters: a K-nearest neighbors method, and a neural network trained on the database. Results . We present a database of over 2600 stars with an estimate of their dipolar magnetic field, and we introduce methods for predicting this parameter for other stars for which it is not measured to much better than an order of magnitude.
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BibTeX
@article{duchene2026stellar,
title = {{Stellar magnetic field database and extrapolation method}},
author = {Noémie Duchêne and Julien N Girard and Philippe Zarka},
journal = {Astronomy \& Astrophysics - A\&A},
year = {2026},
month = may,
doi = {10.1051/0004-6361/202659108},
url = {https://insu.hal.science/insu-05751654v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Stellar magnetic field database and extrapolation method
AU - Noémie Duchêne
AU - Julien N Girard
AU - Philippe Zarka
PY - 2026
DA - 2026/05/28
JO - Astronomy & Astrophysics - A&A
DO - 10.1051/0004-6361/202659108
UR - https://insu.hal.science/insu-05751654v1
AB - Context . During the past two decades, thousands of stellar magnetic fields have been measured using the Zeeman-Doppler imaging method. No unified database gathers all measurements in a homogeneous way. Aims . The magnetic field of a star is a key ingredient of its plasma interactions with companions, either other stars or exoplanets, and of its radio and X-ray emissions. The dipolar component of a stellar magnetic field, in particular, allows us to estimate the magnetic (Poynting) flux that is carried away by the stellar wind, which sweeps across exoplanets or their magnetospheres and is thought to drive electron acceleration and radio emissions. We built a database of known stellar magnetic fields, of which we inferred the dipolar field component, and we present the methods that we developed to estimate a stellar magnetic field when no measurement is available. Methods . We compiled published Zeeman-Doppler measurements of stellar magnetic fields into a database, and we show how the dipolar component can be extracted from various measurements. We included several other stellar parameters in the database (mass, radius, rotation period, effective temperature, age, and V-band magnitude). Then, we built and compared two extrapolation methods for inferring stellar magnetic fields from the other stellar parameters: a K-nearest neighbors method, and a neural network trained on the database. Results . We present a database of over 2600 stars with an estimate of their dipolar magnetic field, and we introduce methods for predicting this parameter for other stars for which it is not measured to much better than an order of magnitude.
SN - 0004-6361
SN - 1432-0746
ER -