3,359 research outputs found

    An Elimination Method for Solving Bivariate Polynomial Systems: Eliminating the Usual Drawbacks

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    We present an exact and complete algorithm to isolate the real solutions of a zero-dimensional bivariate polynomial system. The proposed algorithm constitutes an elimination method which improves upon existing approaches in a number of points. First, the amount of purely symbolic operations is significantly reduced, that is, only resultant computation and square-free factorization is still needed. Second, our algorithm neither assumes generic position of the input system nor demands for any change of the coordinate system. The latter is due to a novel inclusion predicate to certify that a certain region is isolating for a solution. Our implementation exploits graphics hardware to expedite the resultant computation. Furthermore, we integrate a number of filtering techniques to improve the overall performance. Efficiency of the proposed method is proven by a comparison of our implementation with two state-of-the-art implementations, that is, LPG and Maple's isolate. For a series of challenging benchmark instances, experiments show that our implementation outperforms both contestants.Comment: 16 pages with appendix, 1 figure, submitted to ALENEX 201

    Improved algorithm for computing separating linear forms for bivariate systems

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    We address the problem of computing a linear separating form of a system of two bivariate polynomials with integer coefficients, that is a linear combination of the variables that takes different values when evaluated at the distinct solutions of the system. The computation of such linear forms is at the core of most algorithms that solve algebraic systems by computing rational parameterizations of the solutions and this is the bottleneck of these algorithms in terms of worst-case bit complexity. We present for this problem a new algorithm of worst-case bit complexity \sOB(d^7+d^6\tau) where dd and Ï„\tau denote respectively the maximum degree and bitsize of the input (and where \sO refers to the complexity where polylogarithmic factors are omitted and OBO_B refers to the bit complexity). This algorithm simplifies and decreases by a factor dd the worst-case bit complexity presented for this problem by Bouzidi et al. \cite{bouzidiJSC2014a}. This algorithm also yields, for this problem, a probabilistic Las-Vegas algorithm of expected bit complexity \sOB(d^5+d^4\tau).Comment: ISSAC - 39th International Symposium on Symbolic and Algebraic Computation (2014

    On the Complexity of Computing with Planar Algebraic Curves

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    In this paper, we give improved bounds for the computational complexity of computing with planar algebraic curves. More specifically, for arbitrary coprime polynomials ff, g∈Z[x,y]g \in \mathbb{Z}[x,y] and an arbitrary polynomial h∈Z[x,y]h \in \mathbb{Z}[x,y], each of total degree less than nn and with integer coefficients of absolute value less than 2τ2^\tau, we show that each of the following problems can be solved in a deterministic way with a number of bit operations bounded by O~(n6+n5τ)\tilde{O}(n^6+n^5\tau), where we ignore polylogarithmic factors in nn and τ\tau: (1) The computation of isolating regions in C2\mathbb{C}^2 for all complex solutions of the system f=g=0f = g = 0, (2) the computation of a separating form for the solutions of f=g=0f = g = 0, (3) the computation of the sign of hh at all real valued solutions of f=g=0f = g = 0, and (4) the computation of the topology of the planar algebraic curve C\mathcal{C} defined as the real valued vanishing set of the polynomial ff. Our bound improves upon the best currently known bounds for the first three problems by a factor of n2n^2 or more and closes the gap to the state-of-the-art randomized complexity for the last problem.Comment: 41 pages, 1 figur
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