27 research outputs found

    The Breadth-one DD-invariant Polynomial Subspace

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    We demonstrate the equivalence of two classes of DD-invariant polynomial subspaces introduced in [8] and [9], i.e., these two classes of subspaces are different representations of the breadth-one DD-invariant subspace. Moreover, we solve the discrete approximation problem in ideal interpolation for the breadth-one DD-invariant subspace. Namely, we find the points, such that the limiting space of the evaluation functionals at these points is the functional space induced by the given DD-invariant subspace, as the evaluation points all coalesce at one point

    Certifying isolated singular points and their multiplicity structure

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    This paper presents two new constructions related to singular solutions of polynomial systems. The first is a new deflation method for an isolated singular root. This construc-tion uses a single linear differential form defined from the Jacobian matrix of the input, and defines the deflated system by applying this differential form to the original system. The advantages of this new deflation is that it does not introduce new variables and the increase in the number of equations is linear instead of the quadratic increase of previous methods. The second construction gives the coefficients of the so-called inverse system or dual basis, which defines the multiplicity structure at the singular root. We present a system of equations in the original variables plus a relatively small number of new vari-ables. We show that the roots of this new system include the original singular root but now with multiplicity one, and the new variables uniquely determine the multiplicity structure. Both constructions are "exact", meaning that they permit one to treat all conjugate roots simultaneously and can be used in certification procedures for singular roots and their multiplicity structure with respect to an exact rational polynomial system

    On isolation of singular zeros of multivariate analytic systems

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    We give a separation bound for an isolated multiple root xx of a square multivariate analytic system ff satisfying that an operator deduced by adding Df(x)Df(x) and a projection of D2f(x)D^2f(x) in a direction of the kernel of Df(x)Df(x) is invertible. We prove that the deflation process applied on ff and this kind of roots terminates after only one iteration. When xx is only given approximately, we give a numerical criterion for isolating a cluster of zeros of ff near xx. We also propose a lower bound of the number of roots in the cluster.Comment: 17 page

    Numerical Algorithms for Dual Bases of Positive-Dimensional Ideals

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    An ideal of a local polynomial ring can be described by calculating a standard basis with respect to a local monomial ordering. However standard basis algorithms are not numerically stable. Instead we can describe the ideal numerically by finding the space of dual functionals that annihilate it, reducing the problem to one of linear algebra. There are several known algorithms for finding the truncated dual up to any specified degree, which is useful for describing zero-dimensional ideals. We present a stopping criterion for positive-dimensional cases based on homogenization that guarantees all generators of the initial monomial ideal are found. This has applications for calculating Hilbert functions.Comment: 19 pages, 4 figure

    Clustering Complex Zeros of Triangular Systems of Polynomials

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    This paper gives the first algorithm for finding a set of natural ϵ\epsilon-clusters of complex zeros of a triangular system of polynomials within a given polybox in Cn\mathbb{C}^n, for any given ϵ>0\epsilon>0. Our algorithm is based on a recent near-optimal algorithm of Becker et al (2016) for clustering the complex roots of a univariate polynomial where the coefficients are represented by number oracles. Our algorithm is numeric, certified and based on subdivision. We implemented it and compared it with two well-known homotopy solvers on various triangular systems. Our solver always gives correct answers, is often faster than the homotopy solver that often gives correct answers, and sometimes faster than the one that gives sometimes correct results.Comment: Research report V6: description of the main algorithm update
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