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Solar Physics

, 294:151 | Cite as

A Time–Distance Helioseismology Method for Quasi-Linear Geometries

  • Shea A. Hess WebberEmail author
  • W. Dean Pesnell
Article

Abstract

Helioseismology is the study of the solar interior, through which we extract flow and wave-speed information from Doppler velocity observations at the surface. Local helioseismology involves the study of small regions on the solar disk and is used to create a detailed picture of the interior in that particular region. Perturbations in the flow and wave-speed results indicate, e.g. magnetic-flux or temperature variations. There are multiple methods used in local-helioseismic research, but all current local-helioseismic techniques assume a point-source perturbation. For this study, we develop a new time–distance (TD) helioseismic methodology that can exploit the quasi-linear geometry of an elongated feature, allowing us to i) improve the signal-to-noise ratio of the TD results, and ii) greatly decrease the number of calculations required and therefore the computing time of the TD analysis. Ultimately, the new method will allow us to investigate solar features with magnetic-field configurations previously unexplored. We validate our new technique using a simple \(f\)-mode wave simulation, comparing results of point-source and linear perturbations. Results indicate that local-helioseismic analysis is dependent on the geometry of the system and can be improved by taking the magnetic-field configuration into account.

Keywords

Helioseismology 

Notes

Acknowledgments

This research was conducted mainly at George Mason University and NASA’s Goddard Space Flight Center with the support of NASA’s SDO mission, with collaborations at Stanford University and Max Planck Institute for Solar System Research. The project is now being continued through NASA contract NAS5-02139 (HMI) at Stanford University. All SDO/AIA and HMI data are archived and made available by the Joint Science Operations Center (JSOC: jsoc.stanford.edu/). The authors would like to thank T. Duvall, R. Cameron, and A. Birch for their theoretical guidance and implementation help on this project. The authors would also like to thank B. Hindman and L. Gizon for permitting the use of their figures in this article (Figures 1 and 6).

Disclosure of Potential Conflicts of Interest

The authors declare that they have no conflicts of interest.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Stanford UniversityStanfordUSA
  2. 2.NASA GSFCGreenbeltUSA

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