These devices are of interest for obtaining energy from the fusion of isotopes of hydrogen heated to a few hundred million degrees centigrade. A second application is to plasmas of astrophysical interest, in particular the plasma of the solar corona. At present my graduate students are working on the development of a df Monte Carlo code to carry out plasma transport calculations that were previously impossible and on the evolution of a magnetic field that is embedded in a chaotic plasma flow, which obeys an equation of advection-diffusion type. The electrically charged particles that form the plasmas of primary interest in astrophysics and in laboratory experiments move a distance between collisions that is far larger than the scale of the plasma. For example, the radii of a toroidal laboratory plasma are roughly a meter but the thermal velocity may carry a particle tens of kilometers before the trajectory is significantly affected by collisions.
Particles go around the torus thousands of times between collisions.
Calculations of plasma transport coefficients, such as diffusion across the magnetic field and the plasma resistivity, must include both the effects of collisions and the particle trajectories. Monte Carlo codes calculate transport coefficients by following the trajectories of a large number of particles. The effects of collisions are simulated using the random number generator in a Monte Carlo operator. My graduate student Maciek Sasinowski has recently developed a Monte Carlo code that directly determines the deviation from the Maxwellian distribution, which requires that far fewer particles be followed than a standard Monte Carlo code which determines the full distribution function. Most natural flows are chaotic which means infinitesimally separated points in the fluid move apart exponentially.