Year: 2018
Type: article
Abstract: Magnetohydrodynamic turbulence displays velocity anisotropies that reflect the direction of the magnetic field. This anisotropy has led to the development of a number of statistical techniques for studying magnetic fields in the interstellar medium. In this paper, we review and compare three techniques that use radio position–position–velocity data to determine magnetic field strength and morphology: the correlation function anisotropy (CFA), principal component analysis of anisotropies (PCAA), and the more recent velocity gradient technique (VGT). We compare these three techniques and suggest improvements to the CFA and PCAA techniques to increase their accuracy and versatility. In particular, we suggest and successfully implement a much faster way to calculate nonperiodic correlation functions for the CFA. We discuss possible improvements to the current implementation of the PCAA. We show the advantages of the VGT in terms of magnetic field tracing and stress the complementary nature with the other two techniques.
Source: The Astrophysical Journal
Authors: Ka Ho Yuen, Junda Chen, Yue Hu, Ka Wai Ho, A. Lazarian, Victor Lazarian, Bo Yang, Blakesley Burkhart, Caio Correia, Jungyeon Cho, Bruno Canto, J. R. De Medeiros
Institutions: University of Wisconsin–Madison, Tongji University, Chinese University of Hong Kong, Smithsonian Institution, Harvard University, Smithsonian Astrophysical Observatory, Center for Astrophysics Harvard & Smithsonian, Universidade Federal do Rio Grande do Norte, Chungnam National University
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
Funders: National Science Foundation, Smithsonian Institution, National Research Foundation, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, National Research Foundation of Korea, Fundação de Apoio à Pesquisa do Rio Grande do Norte, Universidade Federal do Rio Grande do Norte, Smithsonian Astrophysical Observatory
OpenAlex ID: W2795765369