Fast in-place algorithms for polynomial operations: division, evaluation, interpolation

Pascal Giorgi, Bruno Grenet, Daniel S. Roche
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引用次数: 8

Abstract

We consider space-saving versions of several important operations on univariate polynomials, namely power series inversion and division, division with remainder, multi-point evaluation, and interpolation. Now-classical results show that such problems can be solved in (nearly) the same asymptotic time as fast polynomial multiplication. However, these reductions, even when applied to an in-place variant of fast polynomial multiplication, yield algorithms which require at least a linear amount of extra space for intermediate results. We demonstrate new in-place algorithms for the aforementioned polynomial computations which require only constant extra space and achieve the same asymptotic running time as their out-of-place counterparts. We also provide a precise complexity analysis so that all constants are made explicit, parameterized by the space usage of the underlying multiplication algorithms.
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多项式运算的快速就地算法:除法,求值,插值
我们考虑了单变量多项式的几个重要运算的节省空间的版本,即幂级数反演和除法,带余数的除法,多点求值和插值。现在的经典结果表明,这类问题可以在(几乎)与快速多项式乘法相同的渐近时间内得到解决。然而,这些缩减,即使应用于快速多项式乘法的原地变体,也会产生至少需要线性的额外空间来存储中间结果的算法。我们为上述多项式计算展示了新的就地算法,它只需要恒定的额外空间,并实现与非就地计算相同的渐近运行时间。我们还提供了精确的复杂性分析,以便所有常数都是显式的,并通过底层乘法算法的空间使用来参数化。
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