Magnetized Flows and Self-Organization
in Laboratory Plasma Experiments
S. Hsu, P-24

This colloquium will start with a short introduction to plasma physics and in particular the magnetohydrodynamic (MHD) description of plasmas. The rest of the talk will motivate and then describe the nonlinear MHD physics of “plasma self-organization,” which is the spontaneous generation of large-scale structure from a sea of homogeneous plasma turbulence and of fundamental importance in understanding many laboratory and astrophysical plasmas. Plasma self-organization is intimately connected to two phenomena with hydrodynamic turbulence counterparts: (1) selective decay rates of ideal MHD conserved quantities in the presence of small but finite dissipation and (2) an inverse spectral cascade from large to small wavenumber of one or more ideal invariant. Selective decay allows the prediction of final plasma equilibrium states by solving a variational problem in which one ideal invariant (e.g., magnetic energy) is minimized while another (e.g., magnetic helicity) is held constant. This particular approach, known as “Taylor relaxation,” has been reasonably successful in describing the equilibria of magnetic fusion plasmas such as the Reversed Field Pinch (RFP) and Spheromak. However, Taylor relaxation is limited in its applicability. For example, it assumes zero plasma pressure and flow. The introduction of non-negligible zero-order plasma flows, which has traditionally been neglected in fusion plasma research, brings in new ideal invariants and thus the potential for new self-organization principles leading to a more general class of equilibria. In general, the theoretical principles behind plasma self-organization are well-developed theoretically and in some cases supported by numerical simulations. However, many of the fundamental assumptions and theoretical findings have yet to be investigated experimentally. The talk will conclude by describing laboratory plasma experiments in P-24 that can advance our understanding of plasma self-organization and nonlinear MHD.