An alternative to the Euler--Maclaurin formula: Approximating sums by integrals only
This provides a more efficient and parallelizable method for approximating sums, benefiting numerical computation and theoretical studies.
The authors propose an alternative summation formula that approximates sums using only integrals, avoiding high-order derivatives, and demonstrate that it outperforms the Euler-Maclaurin formula in speed and memory, with near-complete parallelizability. In one example, both the EM and Alt implementations compute Hurwitz zeta values faster than Mathematica's built-in function.
The Euler--Maclaurin (EM) summation formula is used in many theoretical studies and numerical calculations. It approximates the sum $\sum_{k=0}^{n-1} f(k)$ of values of a function $f$ by a linear combination of a corresponding integral of $f$ and values of its higher-order derivatives $f^{(j)}$. An alternative (Alt) summation formula is proposed, which approximates the sum by a linear combination of integrals only, without using high-order derivatives of $f$. Explicit and rather easy to use bounds on the remainder are given. Possible extensions to multi-index summation are suggested. Applications to summing possibly divergent series are presented. It is shown that the Alt formula will in most cases outperform, or greatly outperform, the EM formula in terms of the execution time and memory use. One of the advantages of the Alt calculations is that, in contrast with the EM ones, they can be almost completely parallelized. Illustrative examples are given. In one of the examples, where an array of values of the Hurwitz generalized zeta function is computed with high accuracy, it is shown that both our implementation of the EM formula and, especially, the Alt formula perform much faster than the built-in Mathematica command HurwitzZeta[].