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Random polynomials and expected complexity of bisection methods for real solving

Published: 25 July 2010 Publication History

Abstract

Our probabilistic analysis sheds light to the following questions: Why do random polynomials seem to have few, and well separated real roots, on the average? Why do exact algorithms for real root isolation may perform comparatively well or even better than numerical ones?
We exploit results by Kac, and by Edelman and Kostlan in order to estimate the real root separation of degree d polynomials with i.i.d. coefficients that follow two zero-mean normal distributions: for SO(2) polynomials, the i-th coefficient has variance (d/i), whereas for Weyl polynomials its variance is 1/i!. By applying results from statistical physics, we obtain the expected (bit) complexity of STURM solver, ÕB(rd2τ), where r is the number of real roots and τ the maximum coefficient bitsize. Our bounds are two orders of magnitude tighter than the record worst case ones. We also derive an output-sensitive bound in the worst case.
The second part of the paper shows that the expected number of real roots of a degree d polynomial in the Bernstein basis is √2d ± O(1), when the coefficients are i.i.d. variables with moderate standard deviation. Our paper concludes with experimental results which corroborate our analysis.

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      cover image ACM Other conferences
      ISSAC '10: Proceedings of the 2010 International Symposium on Symbolic and Algebraic Computation
      July 2010
      366 pages
      ISBN:9781450301503
      DOI:10.1145/1837934
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      Published: 25 July 2010

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      Author Tags

      1. Bernstein polynomial
      2. expected complexity
      3. random polynomial
      4. real-root isolation
      5. separation bound

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