Physics projects for Y3 and Y4 students

Project description

Multi-spacecraft data analysis of plasma turbulence

(supervisor: Xing Li)

Nature of project: data analysis, data analysis

Available to students on full-time physics degree schemes only.

Project description and methodology

Like its counterpart in neutral fluid/gas, turbulence in plasmas is non-linear in nature. Our knowledge of space plasma turbulence is often limited by measurement constraint since quite often measurements are only available from a single satellite. Cluster mission (with four satellites) has opened new opportunities for the study of plasma turbulence. The k-filtering technique is a multi-spacecraft data analysis tool that we can use to learn the three dimensional information of the turbulence power in the wave number space. The method uses simultaneous measurements of several satellites and adopts a plane wave (Fourier analysis) approach. It is possible at each sampling frequency, a number of local maximum of wave power in the 3D wave number space can be determined. Note, the limit (aliasing effect, due to the periodic property of sine/cosine functions) of such technique has to be dealt with.

A successful project will develop beyond the above in one/some of the following directions:
General understanding of plasma waves at scales of ion gyration in a plasma.

Or critical review of plasma turbulence theory.

When considering where to take your project, please bear in mind the time available. It is preferable to do fewer things well than to try many and not get conclusive results on any of them. However, sometimes it is useful to have a couple of strands of investigation in parallel to work on in case delays occur.

Additional scope or challenge if taken as a Year-4 project: Plasma turbulence at ion kinetic scales. Knowledge of plasma waves when kinetic effects are important.

Please speak to Xing Li (xxl) if you consider doing this project.

Initial literature for students:

  1. Pincon, J. L., & Lefeuvre, F. 1991, JGR, 96, 1789
  2. Pincon, J.-L., & Motschmann, U. 1998, ISSIR, 1, 65
  3. Sahraoui, F., Belmont, G., Goldstein, M. L., & Rezeau, L. 2010a, JGR, 115, A04206

Novelty, degree of difficulty and amount of assistance required

The project can be conceptually challenging. Supervisor will supply the IDL codes used in data analysis.

Project milestones and deliverables (including timescale)

milestoneto be completed by
Learn IDL, read documentation of Cluster instruments (HIA, FGM)end of October
initial data handling using IDLChristmas
Analyse data from 2004end of February
Analysis of wave vector space spectral anisotropyEaster