Diagonal translation operators form the core of the dynamic multilevel fast multipole algorithm (MLFMA). An application of the MLFMA requires knowledge of these operators over a large number of samples. In fact, the cost of a naive evaluation is O(N3/2), where N is the number of unknowns. More importantly, in a distributed memory computer, if the operators are precomputed and replicated in every processor, the memory requirements scale as O(Np), where p is the number of processors. In this paper, we construct fast polynomial representations of the diagonal operators which require storage, and which can be computed in O(N log(1/ϵ)) time, where ϵ is the desired precision. We report some numerical results demonstrating the performance of the new representations.
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Velamparambil et al. (2001) studied this question.
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