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  Efficiently Computing Real Roots of Sparse Polynomials

Jindal, G., & Sagraloff, M. (2017). Efficiently Computing Real Roots of Sparse Polynomials. Retrieved from http://arxiv.org/abs/1704.06979.

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 Creators:
Jindal, Gorav1, Author           
Sagraloff, Michael1, Author           
Affiliations:
1Algorithms and Complexity, MPI for Informatics, Max Planck Society, ou_24019              

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Free keywords: Computer Science, Symbolic Computation, cs.SC
 Abstract: We propose an efficient algorithm to compute the real roots of a sparse polynomial $f\in\mathbb{R}[x]$ having $k$ non-zero real-valued coefficients. It is assumed that arbitrarily good approximations of the non-zero coefficients are given by means of a coefficient oracle. For a given positive integer $L$, our algorithm returns disjoint disks $\Delta_{1},\ldots,\Delta_{s}\subset\mathbb{C}$, with $s<2k$, centered at the real axis and of radius less than $2^{-L}$ together with positive integers $\mu_{1},\ldots,\mu_{s}$ such that each disk $\Delta_{i}$ contains exactly $\mu_{i}$ roots of $f$ counted with multiplicity. In addition, it is ensured that each real root of $f$ is contained in one of the disks. If $f$ has only simple real roots, our algorithm can also be used to isolate all real roots. The bit complexity of our algorithm is polynomial in $k$ and $\log n$, and near-linear in $L$ and $\tau$, where $2^{-\tau}$ and $2^{\tau}$ constitute lower and upper bounds on the absolute values of the non-zero coefficients of $f$, and $n$ is the degree of $f$. For root isolation, the bit complexity is polynomial in $k$ and $\log n$, and near-linear in $\tau$ and $\log\sigma^{-1}$, where $\sigma$ denotes the separation of the real roots.

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Language(s): eng - English
 Dates: 2017-04-232017
 Publication Status: Published online
 Pages: 9 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 1704.06979
URI: http://arxiv.org/abs/1704.06979
BibTex Citekey: DBLP:journals/corr/JindalS17
 Degree: -

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