our model function is underdetermined–it has only three components, but $3N-2$ parameters for $N$ terms. Thus the trust-region algorithm was unviable, and we used a Levenberg-Marquardt algorithm instead. This algorithm is a local optimizer, meaning that in order to converge to a set of optimal fit parameters, the initial fit parameters fed into the algorithm must be in the catchment basin of a reasonable local minimum. This places a large significance on the initial guess for the fit parameters. For instance, if one were to try and fit to the canted solenoid field using an arbitrary initial guess of $C_i = k_{xi} = k_{yi} = b_y = 1$ for all $i$, then the optimizer would not converge. Looking at the field data, it is difficult to determine what a suitable initial guess might be. We got around this by splitting the optimization into parts. We first fit the model to just one component of the magnetic field, then used this fit as the initial guess for the fit of the entire field. In the case of both LGB’s, by ignoring the $B_y$ and $B_z$ components we were able to adequately fit to the $B_x$ component of the field with the 