Statistical Analysis of Stochastic Magnetic Fields

Previous work has introduced scale-split energy density \psi for a given vector field B in order to quantify the field stochasticity S(t). Application to turbulent magnetic fields leads to the prediction that tangling magnetic field by turbulence increases magnetic stochasticity. An increasing stochasticity in turn leads to disalignments of the coarse-grained fields at smaller scales thus they average to weaker fields at larger scales upon coarse-graining. The field's resistance against tanglement by the turbulence may lead at some point to its sudden slippage through the fluid, decreasing the stochasticity and increasing the energy density. Thus the maxima (minima) of magnetic stochasticity are expected to approximately coincide with the minima (maxima) of energy density, occurrence of which corresponds to slippage of the magnetic field through the fluid. Field-fluid slippage, on the other hand, has been already found to be intimately related to magnetic reconnection. In this paper, we test these theoretical predictions numerically using a homogeneous, incompressible magnetohydrodynamic (MHD) simulation. Apart from expected small scale deviations, possibly due to e.g., intermittency and strong field annihilation, the theoretically predicted global relationship between stochasticity and magnetic energy is observed in different sub-volumes of the simulation box. This may indicate ubiquitous local field-fluid slippage and small scale reconnection events in MHD turbulence. We also show that the maximum magnetic stochasticity, i.e., \partial_t S(t)=0 & \partial^2_t S(t)<0, leads to sudden increases in kinetic stochasticity level which may correspond to fluid jets driven by the reconnecting field lines, i.e., reconnection. This suggests a new mathematical approach to the reconnection problem.