Generic bivariate multi-point evaluation, interpolation and modular composition with precomputation

Vincent Neiger, J. Rosenkilde, Grigory Solomatov
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引用次数: 6

Abstract

Suppose K is a large enough field and P ⊂ K2 is a fixed, generic set of points which is available for precomputation. We introduce a technique called reshaping which allows us to design quasi-linear algorithms for both: computing the evaluations of an input polynomial f ∈ K [x, y] at all points of P and computing an interpolant f ∈ K[x, y] which takes prescribed values on P and satisfies an input y-degree bound. Our genericity assumption is explicit and we prove that it holds for most point sets over a large enough field. If P violates the assumption, our algorithms still work and the performance degrades smoothly according to a distance from being generic. To show that the reshaping technique may have an impact on other related problems, we apply it to modular composition: suppose generic polynomials M ∈ K[x] and A ∈ K[x] are available for precomputation, then given an input f ∈ K[x, y] we show how to compute f (x, A(x)) rem M(x) in quasi-linear time.
通用二元多点评估、插值和预计算模组合
假设K是一个足够大的域,P∧K2是一个固定的、可用于预计算的点的一般集合。我们引入了一种称为重塑的技术,它允许我们设计拟线性算法:计算输入多项式f∈K[x, y]在P的所有点上的评估,以及计算插值函数f∈K[x, y],它在P上取规定的值并满足输入y度界。我们的泛型假设是显式的,并且我们证明了它在足够大的域上对大多数点集成立。如果P违反了假设,我们的算法仍然有效,并且性能会根据与泛型的距离平滑地下降。为了表明重塑技术可能对其他相关问题产生影响,我们将其应用于模组合:假设一般多项式M∈K[x]和A∈K[x]可用于预计算,然后给定输入f∈K[x, y],我们展示如何在拟线性时间内计算f (x, A(x))和M(x)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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