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Within is a list of simulations done since the beginning of the project. It has been partitioned such that simulations done with the original version of radiometer are in the bottom section, while simulations done with more up-to-date versions of radiometer are nearer to the top. Structure is as follows:

  • Date: Author, Title: pdf
    • Short description of contents within


  • 7/16/16: Levi Walls, Preliminary Love Wave Recoveries: pdf
    • Example showing the radiometer code for simulated Love wave recoveries works as it should
  • 9/21/15: Levi Walls, Comparison of Rayleigh Wave Recoveries at Differing Observation Lengths: pdf
    • Looking at real data and using “realistic” parameters; still get junk results despite having long observation time.
  • 9/16/15: Levi Walls, Comparison of Rayleigh Wave Recoveries at Homestake: pdf
    • Looking at real data with perceivably realistic parameter values–did not yield any good skymaps
  • 9/14/15: Levi Walls, Rayleigh Recoveries with Realistic Parameters: pdf
    • Looking at real data using what was thought to be realistic parameters. “Junk” recoveries; i.e. no distinct signal was recovered—especially at low values of ϵ. Increasing ϵseems not to have a great effect on the signal recovery; however, the power diminishes slightly.
  • 9/4/15: Levi Walls, Effects of Varying α and є in Rayleigh Wave Recovery: pdf
    • As α is varied, there is more variation in the recovered power signals than when є is varied. Frequently, there will be a strong signal recovered; then, a weaker signal (of the same shape) will be recovered 180° from the original.


  • 3/1/2015: Noah Bittermann, Rayleigh Wave Diagnostics: pdf
    • Looking at the effects of varying horizontal/vertical component of Rayleigh waves
  • 8/21/14: Noah Bittermann, S-waves 2.0: pdf
    • Describes geometry of S-wave propagation; correctly recover injection position, shows strong dependence on scale of the array (or equivalently on the frequency of the wave), as well as on the array configuration. Changing polarization can change the shape of the recovered blob, but the blob is typically well centered.
  • 8/21/14: Noah Bittermann, Frequency and Time Average Tests: pdf
    • found that averaging over recoveries at different frequencies improves the recovered position (have to check if this is dominated by the lowest frequencies), while averaging over longer periods of time yields the same checker board patterns.
groups/homestake/simulations/home.txt · Last modified: 2016/07/21 11:24 by walls