Position: Research Fellow (EPSRC)
PHD RESEARCH (2006-2009, CFSA, University of Warwick)
Title: Turbulence and Scaling phenomena in Solar System Plasmas
Abstract: In this thesis we use techniques associated with the statistical properties of large stochastic datasets to probe the scaling properties of solar wind timeseries. In particular, we consider single-point spacecraft measurements of interplanetary vector quantities such as velocity and magnetic field. These techniques are first applied to well-known distributions such as the normal distribution in order to demonstrate the scaling properties associated with different types of timeseries. For example, a normal distribution can be thought of as the steps of a Brownian walk and is a fractal process or in other words there is a power-law relation between stepsize and the length of the walk. This simple behaviour is complicated when intermittency (similar to large jumps in a random walk) and multifractality are introduced. We also show other model distributions exhibiting these effects and the consequences on the statistical analysis results.
These methods are then applied to in situ solar wind observations by monitors such as the ACE and Ulysses spacecraft. ACE occupies a privileged position at the Lagrangian point between the Sun and the Earth, whereas Ulysses was the first spacecraft to explore the Sun's polar regions. We are thus able to show the scaling behaviour of velocity and magnetic field fluctuations for a wide range of different solar wind conditions (such as fast and slow solar wind speeds) and between periods of maximum and minimum solar activity and to examine both ecliptic and polar solar wind behaviour. The large datasets available mean we can probe fluctuations over a wide range of scales from the inertial range to the larger energy containing scales. We find that the polar inertial range (small-scale) behaviour for fast solar wind can be summarised for the magnetic field by a single function, which holds for all components and for different successive solar minima.
We further use ACE measurements to examine the velocity and magnetic field large-scale fluctuations normal and parallel to the local background magnetic field and propose that the parallel velocity component carries the signature of coronal processes convected outwards into the solar wind. The scaling exponents obtained constrain the models for these processes.
Current work focuses on understanding and analysing "real world" datasets of the human brain and finance stock markets from a complex systems perspective. This work is carried out in collaboration with Warwick Business School (WBS) and the Brain Mapping Unit at the University of Cambridge. In particular I use network theory to describe cognitive processes.