The nearest-neighbour lookup x → G (see Eq. 11) can be implemented efficiently as a KD-tree . An example of the resulting off-graph gradient paths is shown in Fig. (bottom). In Fig. , it is clear that this technique corrects the grid bias for a DFT grid so that it agrees with the (also corrected) uniform result. The uniform grid shows significantly less grid bias in Fig. due to the inclusion of diagonal moves by the Delaunay triangulation (the DFT grid also has such diagonal moves, but they are less helpful as a significant radial bias remains). These diagonal moves were not present in previous uniform-gridbased approaches , which therefore exhibited significantly larger grid bias than the present method. We note that the methods developed by Rodríguez et. al. are inherently off-grid and so do not suffer from grid-bias, at the cost of requiring it to be possible to evaluate f and ∇f freely. In contrast, Eq. 21 requires no evaluations of f beyond those given as input (Eq. 1), at the expense of a KD-tree lookup.