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Solar flares are magnetic explosions on the Sun, which directly affect the Earth through their influence on our local space weather. The basic process underlying flare energy release is poorly understood, and we are not able to accurately predict the occurrence of flares. Different projects in solar flare physics are available, involving theory, computation, and data analysis.
Masters/PHD
The first recorded sighting of a solar flare was by Richard Carrington in 1859. The flare was followed by remarkable events at the Earth including aurorae being observed in the tropics, the failure of telegraph systems, and erratic compass readings. However, the possibility of a "Sun-Earth connection" was dismissed at the time. Today, space weather is an area of intense research interest. Solar flares and Coronal Mass Ejections or CMEs (flare-associated expulsions of material from the Sun) can produce space weather storms which damage satellite electronics, induce large currents in power grids on the Earth, and pose radiation risks for travellers in space. Flares occur in the solar corona above active regions around sunspots.
Flares involve the sudden release of stored magnetic energy, built up over days prior to a flare. Vector magnetograms provide observational evidence of the stored energy in the form of large electrical currents flowing into the corona, but the role of these currents in the flare process is not well understood. The energy release mechanism must involve magnetic reconnection, a process in which magnetic fields change their connectivity, and this is also inadequately understood, although there has been progress in recent decades in the development of ideas in 3-D reconnection theory. At present we are not able to accurately predict the occurrence of a flare.
This Research Opportunity describes a range of possible projects in solar flare physics, catering to students with interests in theory, computation, and data analysis. Research topics include:
1. Developing 3-D magnetic reconnection models which account for the role of electrical currents in the reconnection process.
2. Constructing computational models of pre-flare and post-flare magnetic field configurations in flare-producing active regions using the Nonlinear Force-Free Field (NLFFF) model, to better understand how flares occur.
3. Developing improved solar flare prediction methods, which incorporate more physics into the prediction.
PhD projects may be tailored to suit the individual needs of prospective students. Excellent facilities are available to support this work, including access to high-performance computing resources and solar data. Students should have a strong background in physics, and for the computational projects, high-level programming skills.
HDR Inherent Requirements
In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:
- Confidential disclosure and registration of a disability that may hinder your performance in your degree;
- Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
- Ability to perform independently and/or with minimal supervision;
- Ability to undertake certain physical tasks (e.g. heavy lifting);
- Ability to undertake observatory, sensory and communication tasks;
- Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);
- Ability to work in confined spaces or at heights;
- Ability to operate heavy machinery (e.g. farming equipment);
- Hold or acquire an Australian driver’s licence;
- Hold a current scuba diving license;
- Hold a current Working with Children Check;
- Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)
You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.
The opportunity ID for this research opportunity is 2202