JOURNAL ARTICLE
Plasma diagnostics and Alfvén wave heating of solar prominences by multiwavelength observations.
Published In: Publications of the Astronomical Society of Japan, 2023, v. 75, n. 5. P. 913 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Hashimoto, Yuki; Ichimoto, Kiyoshi; Huang, Yuwei 3 of 3
Abstract
This article quantitatively investigates the heating of solar prominences—cool, dense plasma structures suspended in the solar corona—focusing on the role of Alfvén waves as a heating mechanism. Using multi-line spectroscopic observations of four quiescent prominences in Hα (6563 Å), Hβ (4861 Å), and Ca ii IR (8542 Å) obtained with the Domeless Solar Telescope at Hida Observatory, the study derives plasma parameters such as temperature, non-thermal velocity, electron density, geometrical thickness, and filling factor through line profile fitting and non-local thermodynamic equilibrium (non-LTE) modeling. The results show that the energy flux carried by Alfvén waves, assuming a magnetic field strength of 20 G, is sufficient to compensate for the net radiative losses in most central regions of the prominences, suggesting Alfvén wave heating as a viable energy source. However, in outer prominence regions where Alfvén wave energy flux is insufficient, additional heating mechanisms—such as enthalpy flux from mass inflow—may contribute, while thermal conduction appears negligible. The study highlights the importance of simultaneous plasma and magnetic field diagnostics for a comprehensive understanding of prominence heating.
Additional Information
- Source:Publications of the Astronomical Society of Japan. 2023/10, Vol. 75, Issue 5, p913
- Document Type:Article
- Subject Area:Astronomy and Astrophysics
- Publication Date:2023
- ISSN:0004-6264
- DOI:10.1093/pasj/psad049
- Accession Number:172895858
- Copyright Statement:Copyright of Publications of the Astronomical Society of Japan is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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