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Fast, algebraic multivariate multipoint evaluation in small characteristic and applications
Vishwas Bhargava (Rutgers, The State University of New Jersey), Sumanta Ghosh (California Institute of Technology), Mrinal Kumar (Indian Institute of Technology Bombay), Chandra Kanta Mohapatra (Indian Institute of Technology Bombay)
Abstract: Multipoint evaluation is the computational task of evaluating a polynomial given as a list of coefficients at a given set of inputs. Besides being a natural and fundamental question in computer algebra on its own, fast algorithms for this problem are also closely related to fast algorithms for other natural algebraic questions like polynomial factorization and modular composition. And while nearly linear time algorithms have been known for the univariate instance of multipoint evaluation for close to five decades due to a work of Borodin and Moenck, fast algorithms for the multivariate version have been much harder to come by. In a significant improvement to the state of art for this problem, Umans and Kedlaya & Umans gave nearly linear time algorithms for this problem over field of small characteristic and over all finite fields respectively, provided that the number of variables n is at most do(1) where the degree of the input polynomial in every variable is less than d. They also stated the question of designing fast algorithms for the large variable case (i.e. n ∉ do(1)) as an open problem.