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2013 IEEE 54th Annual Symposium on Foundations of Computer Science (2008)
Oct. 25, 2008 to Oct. 28, 2008
ISSN: 0272-5428
ISBN: 978-0-7695-3436-7
pp: 146-155
We give an algorithm for modular composition of degree n univariate polynomials over a finite field F_q requiring n^{1 + o(1)}log^{1 + o(1)}q bit operations; this had earlier been achieved in characteristic n^{o(1)} by Umans (2008). As an application, we obtain a randomized algorithm for factoring degree n polynomials over F_q requiring (n^{1.5 + o(1)} + n^{1 + o(1)}log q)log^{1 + o(1)}q bit operations, improving upon the methods of von zur Gathen & Shoup (1992) and Kaltofen & Shoup (1998). Our results also imply algorithms for irreducibility testing and computing minimal polynomials whose running times are best-possible, up to lower order terms.As in Umans (2008), we reduce modular composition to certain instances of multipoint evaluation of multivariate polynomials. We then give an algorithm that solves this problem optimally (up to lower order terms), in arbitrary characteristic. The main idea is to lift to characteristic 0, apply a small number of rounds of multimodular reduction, and finish with a small number of multidimensional FFTs. The final evaluations are then reconstructed using the Chinese Remainder Theorem. As a bonus, we obtain a very efficient data structure supporting polynomial evaluation queries, which is of independent interest.Our algorithm uses techniques which are commonly employed in practice, so it may be competitive for real problem sizes. This contrasts with previous asymptotically fast methods relying on fast matrix multiplication.
modular composition, multipoint evaluation, polynomial factorization, multimodular reduction
Kiran S. Kedlaya, Christopher Umans, "Fast Modular Composition in any Characteristic", 2013 IEEE 54th Annual Symposium on Foundations of Computer Science, vol. 00, no. , pp. 146-155, 2008, doi:10.1109/FOCS.2008.13
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