Please contact me if you are interested in PhD research in any of these areas.
On a dark, dark night, in a dark, dark place, look up at the Milky Way. Hopefully you might see something like this:
What is immediately striking is that, for a galaxy containing 100 billion stars, much of the Milky Way is obscured by dark, dusty blotches. These dark "molecular clouds" are the stellar nurseries of our galaxy, the birthplace of new stars. Here are two of our nearest star forming regions up close:
|Rho Ophiuchus molecular cloud, one of the closest star forming regions to us, at a distance of ~140 parsecs (450 light-years).||Hubble Space Telescope mosaic of the Orion Nebula, our most spectacular nearby star forming region (~350 parsecs/1000 light-years away)||Baby stars in the heart of the Orion Nebula, complete with planet-forming discs silhouetted against the nebula.|
The problem for us as humans is that star formation is a relatively long process, taking of order 1-10 million years, simply because it involves gathering material over huge distances by the gentle but steady pull of gravity. Thus when we observe the molecular clouds of the Milky Way, all we get is a momentary snapshot of what is really a highly dynamic process. We therefore use computer simulations to speed up the process to a few months inside a supercomputer, by solving the equations which govern the basic physical processes, i.e. gravity, gas dynamics and, through my research, the effects of magnetic fields. The results go something like this:
In our calculations we have found that magnetic fields can substantially change the picture of star cluster formation — they strongly reduce the rate at which stars form by stopping the gas from collapsing under its own gravity, producing star formation that is less vigourous, in turn leading to fewer low mass objects known as "brown dwarfs" (failed stars). This brought the predicted number of stars as a function of mass from the calculations into better agreement with the observed mass distribution of young stars. Predicting the mass distribution of stars (i.e., how stars get their mass) is a key aim of our work since it is very important for galaxy formation models.
Magnetic fields can also produce some of the most spectacular phenomena in astrophysics, such as the launch of jets from newborn stars:
In some recent work with Matthew Bate (Exeter, UK) and PhD student Terry Tricco (Monash), we were able to reproduce this phenomena, capturing the magnetic launching of jets during a short (10,000-year) stall phase (known as the "first core") during the collapse of gas under gravity to form a protostar:
Previously it was not thought that collimated (needle-like) jets could be launched during this phase, but in November 2011 there was a spectacular detection (by Mike Dunham and colleagues) of a candidate first-core jet, with properties matching those predicted from the simulations. These observations and theoretical predictions are currently being followed up with the new ALMA telescope high in the mountains of Chile.
With colleagues Christoph Federrath (Monash) and Chris Brunt (Exeter, UK) we have been investigating various aspects of the turbulence that is observed in molecular clouds. While turbulence in ordinary fluids like water is only partially understood, the motions observed in star-forming clouds are much faster than the speed of sound, i.e. highly supersonic, with Mach numbers ranging from around 5 up to 20, making the properties quite different to turbulence in water. Understanding turbulence in this regime can help us predict the process of star formation, as well as being of more fundamental importance. Below is an example of a calculation from a recent comparison between different simulation codes, showing gas driven to supersonic speeds in a box with periodic boundary conditions:
Of particular relevance to star formation is how turbulence distributes the gas as a function of density — i.e., the probability of a given parcel of gas being at a particular density, measured by the "Probability Density Function" or PDF. In particular the PDF in supersonic turbulence shows a characteristic "log-normal" shape (see right panel, below) that is very similar to the mass distribution of young stars, suggesting a link between the two.
One of the more fundamental aspects that we have investigated is how the distribution of gas as a function of density changes with the Mach number of the turbulence. Knowing this relationship means that we can make theoretical predictions for the mass distribution of stars and the star formation rate that can be compared against observational measurements.
With colleagues Giuseppe Lodato (Milan, Italy) and Chris Nixon (Boulder, Colorado, USA) I have a long-term project to understand the dynamics of accretion discs — the swirling of gas that form when material tries to land on a star or black hole, observed around many different kinds of objects including young stars, white dwarfs, neutron stars, black holes and supermassive black holes — essentially whereever there is gas falling onto a gravitating object. In particular we are trying to understand what happens when the disc is warped, tilted, buckled, bent or broken, and how these disturbances travel in the disc:
In some recent work we looked at warps driven in a misaligned accretion disc by a spinning black hole. The results were completely unexpected, that the black hole can "tear up" the disc, rapidly accelerating it's ability to feed itself:
What enables all of the research above is the development of ever improving algorithms for solving the equations of astrophysical gas dynamics on a computer. Although the least "glamourous" part of my research in terms of public appeal, it is what drives our ability to perform ever more realistic simulations of astrophysical phenomena. A brief scan of my list of publications shows the kind of highly technical nature of the work that underpins our applications to astrophysics.
The method we use and develop, Smoothed Particle Hydrodynamics, uses moving particles to represent the fluid, instead of the standard approach which uses a grid. This has advantages for many problems, not only in astrophysics but also for simulation of water and other fluids or gases on Earth.