PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 9, 20260 citations

Forward modeling solar spectra onto Doppler images of λ And

View Full Paper
ÖAÖ. AdebaliAPA.G.M. Pietrow

Key Points

  • This research aims to explore the relationship between surface temperature information and chromospheric emissions in the RS,CVn-type binary λ And.
  • Utilized Doppler images of λ And to reverse surface temperature information.
  • Injected toy model solar spectra into a full-disk temperature map to model radial velocities and chromospheric emissions.
  • Analyzed three photospheric and four chromospheric emission lines for activity modulation comparison.
  • Chromospheric emissions follow trends similar to observations of λ And, indicating magnetic activity controls variation.
  • Differences in emission amplitudes suggest distinct chromospheric heating mechanisms between λ And and the Sun.
  • Used toy models effectively reproduce spectral behavior, providing insight into active giants' heating mechanisms.

Abstract

Due to their high chromospheric activity and photometric variability, RS,CVn-type binaries are ideal laboratories for studying stellar surface structures and the corresponding stellar activity relations. However, the atmospheric nature of their primary evolved components (luminosity classes III–IV) are more complex than those of main-sequence stars. Additionally, detailed models are still lacking for the sub(giant) systems. Therefore, comparative techniques represent the most effective approach for probing the connection between chromospheric emission and surface structures. Using the Doppler images of łama, we investigated whether surface temperature information can be reversed to create its activity parameters by feeding a toy model solar spectra based on surface images. At the same time, we examined whether spot contributions alone are sufficient to explain the observed activity modulation of the RS,CVn star łama,while quantifying the differences with the actual observations of this star obtained simultaneously with the Doppler images we used. Due to a lack of publicly available starspot models for its stellar type, we adopted the observed solar spectra as the only available approximation of łama's spots. These spectra were injected into a sequence of a full-disk temperature map derived from Doppler imaging that represents a full stellar rotation. These disks were then forward modeled into disk-integrated spectra with the Numerical Empirical Sun-as-a-star Integrator (NESSI). This experiment was performed on three photospheric lines (Fe i 6173 Å, Fe i 6301 Å, and K i 7699 Å) and four chromospheric lines (̋alpha, ̧ahk, and Ca ii 8542 Å). Finally, we used these spectra to calculate the radial velocities and chromospheric emissions diagnostics, which in turn were compared to the original photospheric and chromospheric characteristics of the star. Despite the very different stellar structures and atmospheric stratification between łama,and the Sun, we show that the chromospheric emissions produced by our toy model largely follow the same trend as the original observations of łama. This indicates that the modulation of the chromospheric activity is dominated by magnetic activity associated with the active regions with dark spots. In addition, the differences in the emission amplitudes quantify the different chromospheric heating mechanisms for these two very different types of stars. Using this approach, we show that even with simplified assumptions the spectral behavior of łama,can be qualitatively reproduced. Toy models such as the one presented in this work make an additional dimension available by providing a relation between the surface structures and chromospheric emissions. Such models also help in developing a further understanding of the heating mechanisms of these active giants through comparative techniques, where in this case the spot activity seemingly modulates the chromospheric signal and can explain the bulk of its variations over a rotation.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Adebali et al. (2026) studied this question.

synapsesocial.com/papers/69fed17eb9154b0b82878e32https://doi.org/10.1051/0004-6361/202659430/pdf
Ask AI
Helpful
Bookmark
Share
View Full Paper