Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 30 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 18 tok/s Pro
GPT-5 High 12 tok/s Pro
GPT-4o 91 tok/s Pro
Kimi K2 184 tok/s Pro
GPT OSS 120B 462 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

New Progress in Classic Area: Polynomial Root-squaring and Root-finding (2206.01727v2)

Published 30 May 2022 in math.NA and cs.NA

Abstract: The DLG root-squaring iterations, due to Dandelin 1826 and rediscovered by Lobachevsky 1834 and Graeffe 1837, have been the main approach to root-finding for a univariate polynomial p(x) in the 19th century and beyond, but not so nowadays because these iterations are prone to severe numerical stability problems. Trying to avoid these problems we have found simple but novel reduction of the iterations applied for Newton's inverse ratio -p'(x)/p(x) to approximation of the power sums of the zeros of p(x) and its reverse polynomial. The resulting polynomial root-finders can be devised and performed independently of DLG iterations, based on Newton's identities or Cauchy integrals. In the former case the computation involve a set of leading or tailing coefficients of an input polynomial. In the latter case we must scale the variable and increase the arithmetic computational cost to ensure numerical stability. Nevertheless the cost is still manageable, at least for fast root-refinement, and the algorithms can be applied to a black box polynomial p(x)--given by a black box for the evaluation of the ratio p'(x)/p(x) rather than by its coefficients. This enables important computational benefits, including efficient recursive as well as concurrent approximation of a set of zeros of p(x) or even all of its zeros, acceleration where an input polynomial can be evaluated fast, and extension to approximation of the eigenvalues of a matrix or a polynomial matrix, being efficient if the matrix can be inverted fast, e.g., is data sparse. We also recall our recent fast algorithms for approximation of the root radii, that is, the distances to the roots from the origin or any complex value to the zeros of p(x), and apply it for fast black box initialization of polynomial root-finding by means of functional iterations, e.g., Newton's, Ehrlich's, and Weierstrass's.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.

Authors (1)