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May 9, 20260 citations

Stellar magnetic field database and extrapolation method

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NDNoémie DuchêneJGJulien N. GirardPZPhilippe Zarka

Key Points

  • The aim is to create a comprehensive database of stellar magnetic fields and develop methods for estimating magnetic fields in unmeasured stars.
  • Compiled over 2600 Zeeman-Doppler measurements into a cohesive database.
  • Developed two extrapolation methods: K-nearest neighbors and a neural network trained on the database.
  • Inferred dipolar magnetic field components and included additional stellar parameters.
  • Presented a database of over 2600 stars with inferred dipolar magnetic fields.
  • Extrapolation methods predict stellar magnetic fields to within better than an order of magnitude for unmeasured stars.
  • Demonstrated the ability to estimate magnetic flux and its implications on stellar and exoplanet interactions.

Abstract

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. 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. 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. 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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Cite This Study

Duchêne et al. (2026) studied this question.

synapsesocial.com/papers/69fed0e2b9154b0b82877f3chttps://doi.org/10.1051/0004-6361/202659108/pdf
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