Extending the FIP bias sample to magnetically active stars

Challenging the FIP bias paradigm

¹ Konkoly Observatory, Research Centre for Astronomy and Earth Sciences (ELKH), Budapest, Hungary
e-mail: seli.balint@csfk.org
² Eötvös University, Department of Astronomy, Pf. 32, 1518 Budapest, Hungary
³ Space Science Division, Code 7684, Naval Research Laboratory, Washington DC 20375, USA
⁴ University College London, Mullard Space Science Laboratory, Holmbury St. Mary, Dorking, Surrey, RH5 6NT, UK
⁵ LESIA, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, Univ. Paris Diderot, Sorbonne Paris Cité, 5 place Jules Janssen, 92195 Meudon, France

Received: 7 June 2021
Accepted: 28 November 2021

Abstract

Context. The different elemental abundances of the photosphere and the corona are striking features of not only the Sun, but of other stars as well. This phenomenon is known as the first ionisation potential (FIP) effect, and its strength can be characterized by the FIP bias, the logarithmic abundance difference between low- and high-FIP elements in the corona, compared to the photosphere. The FIP bias was shown to depend on the surface temperature of the star.

Aims. We aim to extend the T_eff−FIP bias relationship to a larger stellar sample and analyse the effect of other astrophysical parameters on the relation (e.g. surface gravity, age, activity indicators).

Methods. We compiled FIP bias and other parameters for 59 stars for which coronal composition is available, now including evolved stars. Using principal component analysis and linear discriminant analysis, we searched for correlations with other astrophysical parameters within the sample that may influence the stellar FIP bias.

Results. Adding stars to the T_eff−FIP bias diagram unveiled new features in its structure. In addition to the previously known relationship, there appears to be a second branch: a parallel sequence about 0.5 dex above it. While the T_eff remains the main determinant of the FIP bias, other parameters such as stellar activity indicators also have influence. We find three clusters in the FIP bias determinant parameter space. One distinct group is formed by the evolved stars. Two groups contain main sequence stars in continuation separated roughly by the sign change of the FIP-bias value.

Conclusions. The new branch of the T_eff−FIP bias diagram contains stars with higher activity level, in terms of X-ray flux and rotational velocity. The Rossby number also seems to be important, indicating possible dependence on the type of dynamo operating in these stars influencing their FIP bias. The two main-sequence clusters run from the earliest spectral types of A-F with shallow convection zones through G-K-early-M stars with gradually deeper convection zones, and they end with the fully convective M dwarf stars, depicting the change of the dynamo type with the internal differences of the main sequence stars in connection with the FIP-bias values.