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Counting Curves and Their Projections
 Computational Complexity
, 1996
"... . Some deterministic and probabilistic methods are presented for counting and estimating the number of points on curves over finite fields, and on their projections. The classical question of estimating the size of the image of a univariate polynomial is a special case. For curves given by spars ..."
Abstract

Cited by 10 (1 self)
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. Some deterministic and probabilistic methods are presented for counting and estimating the number of points on curves over finite fields, and on their projections. The classical question of estimating the size of the image of a univariate polynomial is a special case. For curves given by sparse polynomials, the counting problem is #Pcomplete via probabilistic parsimonious Turing reductions. 1. Introduction One of the most celebrated results in algebraic geometry is Weil's theorem on the number of points on algebraic curves over a finite field. In this paper, we address some computational problems related to this question. Our main results are: ffi A "computational Weil estimate" for projections of curves and images of polynomials, in Section 3. ffi #Pcompleteness of the exact counting problem for sparse curves, in Section 4. We consider a finite field F q with q elements, an algebraic closure K of F q , a polynomial f 2 F q [x; y] of degree n , the plane curve C = ff = 0...
Detecting lacunary perfect powers and computing their roots
, 2009
"... We consider the problem of determining whether a lacunary (also called a sparse or supersparse) polynomial f is a perfect power, that is, f = h r for some other polynomial h and r ∈ N, and of finding h and r should they exist. We show how to determine if f is a perfect power in time polynomial in t ..."
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Cited by 3 (0 self)
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We consider the problem of determining whether a lacunary (also called a sparse or supersparse) polynomial f is a perfect power, that is, f = h r for some other polynomial h and r ∈ N, and of finding h and r should they exist. We show how to determine if f is a perfect power in time polynomial in the number of nonzero terms of f, and in terms of log deg f, i.e., polynomial in the size of the lacunary representation. The algorithm works over Fq[x] (for large characteristic) and over Z[x], where the cost is also polynomial in log ‖f‖∞. We also give a Monte Carlo algorithm to find h if it exists, for which our proposed algorithm requires polynomial time in the output size, i.e., the sparsity and height of h. Conjectures of Erdös and Schinzel, and recent work of Zannier, suggest that h must be sparse. Subject to a slightly stronger conjectures we give an extremely efficient algorithm to find h via a form of sparse Newton iteration. We demonstrate the efficiency of these algorithms with an implementation using the C++ library NTL. 1.