  We prove and apply an optimal low-rank approximation of the Cauchy kernel
over separated real domains. A skeleton decomposition is the minimum over
real-valued functions of the maximum relative pointwise error. We present an
algorithm to optimize its parameters, demonstrate suboptimal but effective
heuristic approximations, and identify numerically stable forms.
