Usage
  • 194 views
  • 264 downloads

Statistical Methods To Study Turbulence In The Magnetized Interstellar Medium

  • Author / Creator
    Kandel, Dinesh
  • It has been well known that turbulent motions are ubiquitous in the interstellar medium. These motions are very important in governing various astrophysical processes like star formation. Both observational and numerical studies are important to understand turbulent motions, and a gap between these two studies exists. To bridge this gap, various statistical techniques have been developed. These techniques so far have assumed isotropy and homogeneity in space. While this assumption is good in the absence of magnetic fields, isotropy is broken in the presence of magnetic field as the direction of magnetic field breaks the symmetry in space. In this thesis, we have developed an extension to current statistical techniques, which use intensity maps, such as velocity channel analysis and velocity centroids, to study turbulence anisotropy, and have discussed how statistical anisotropy of intensity maps can be used to study media magnetization, and separate different fundamental MHD modes: Alfven, fast and slow modes.

  • Subjects / Keywords
  • Graduation date
    Fall 2017
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3HD7P665
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
  • Supervisor / co-supervisor and their department(s)
  • Examining committee members and their departments
    • Pogosyan, Dmitri (Physics)
    • Rosolowsky, Erik (Physics)
    • Sydora, Richard (Physics)
    • Heinke, Craig (Physics)