Research opportunities
Research in solar astrophysics addresses key problems in the physics of solar flares, flare statistics, the modelling of coronal magnetic fields, solar-terrestrial relations, and solar activity in general. Computational and traditional methods are applied to solve critical problems. Techniques include large scale computation, theory/modelling, data analysis, visualization, and a combination of these methods. I work within the School of Physics, but my research overlaps with many different fields, and I would like to invite students from computer science, mathematics and engineering to apply as long as they meet the Honours prerequisites. In particular, I have projects available that are predominantly computational, including large-scale parallel computing, suitable for students with a general science background.

Research projects are available for students at Third Year, Honours and Ph.D. levels. I encourage students to participate in all aspects of research, including identifying a project. The goal is to locate a question that you find interesting. The question may be completely novel or part of a program of ongoing research, provided I think that we can answer it!


A nonlinear force-free magnetic field model for solar active region 10953.
Research in this area will develop skills (computation, numerical analysis, modelling, visualisation, data analysis, statistical techniques) which are highly transferrable and attractive to employers. Candidates will have the opportunity to collaborate with experts at world class institutions with whom I maintain ongoing research partnerships, including Lockheed Martin and Stanford University. My research is published in high-impact peer reviewed journals such as the Astrophysical Journal, the premier US journal in the field. You can achieve research at this level!
Bayesian prediction of solar flares
In 1859 a gigantic solar flare erupted on the Sun, disabling telegraph communications on the Earth (an entertaining account is given in Stuart Clark's book The Sun Kings). Solar flares are magnetic explosions in the solar atmosphere that affect our local "space weather," producing dangerous energetic particle populations and disruptive electrical current systems in our local space environment. The "Carrington flare" of 1859 is believed to have been the largest solar flare of the last 150 years. Such events are a cause for concern: a recent study (Odenwald, Green, and Taylor 2006) suggests that a Carrington event at the next solar maximum could incur US$70 billion in lost revenue. Large solar flares appear to occur at random, but there are many indicators that flares might occur. Can we combine these indicators to make a more accurate forecast? What limits the predictability of flares? This project will apply state-of-the-art techniques from Bayesian inference to these key problems.
Skills learnt: Markov chain Monte Carlo methods, Bayesian inference, prediction methods, numerical methods, data analysis, visualization techniques
References: Wheatland, M.S. 2005, A statistical solar flare forecast method, Space Weather Vol. 3, No. 7, S07003 doi:10.1029/2004SW000131 (past work)

Large solar flares - random or not?
Large solar flares influence our local "space weather," and are capable of damaging satellite electronics, and posing radiation risks to astronauts and crews on polar commercial aircraft flights. Flares -- in particular the largest events -- appear to occur randomly in sunspot regions, although the mean rate of flares varies with the number of sunspots, which follows an 11-year cycle. But how random are these events? It has been claimed that they are "non-Poisson," i.e. exhibit anomalous correlations in occurrence times, compared with a random process. This project will investigate this basic question.
References: Hudson, H.S. 2007, The unpredictability of the most energetic solar events, The Astrophysical Journal Letters 663, L45
Skills learnt: Programming, data analysis, numerical methods, statistics

Feel free to discuss these and other research opportunities with me, in person or via e-mail.

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