Given that the optimizations used in this process vary widely in the sets of parameters that they produce, it is useful to characterize the quality of the surrogate models over the parameter space. Specifically, we measure their global accuracy by comparing the generated surrogate models. We also measure the roughness over the surrogate models by running multiple minimizations on the final surrogate models. We performed this analysis for the 𝑁 = 10 optimization runs.