  This paper presents a heuristic derivation of a geometric minimum action
method that can be used to determine most-probable transition paths in
noise-driven dynamical systems. Particular attention is focused on systems that
violate detailed balance, and the role of the stochastic vorticity tensor is
emphasized. The general method is explored through a detailed study of a
two-dimensional quadratic shear flow which exhibits bifurcating most-probable
transition pathways.
