Polynomial root-finding
From: Alex Renelt (renelt_at_web.de)
Date: 03/03/05
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Date: Thu, 03 Mar 2005 20:54:47 +0100
Some time ago there was a discussion in this group about the "state of
the art" of certain polynomial root finders.
I'm writing a paper about polynomials and the process of zero finding
(plus implementations in python) for a german math course. I'm
considering the following methods as "sure-fire technics":
-companion matrix approach (QR-Algo. etc.)
To my mind stable, quiet fast, widely used but unsuited for higher
degrees (memory usage) and multiple zeros.
-jenkins-traub method (esp. rpoly)
For sure _one_ of the best methods but I don't like it much because
- for me - it seems to be quiet complicated and I hate deflation.
-laguerre
Also deflation... But my choice for fast initial approximations, e.g. for
-Durand-Kerner or Dochev or Weierstrass or what so ever called method
Wonderful simple. But stable? Some interesting modifications (see
Petkovic for example).
Is it used in any program or library you know?
There are some extensions to speed up the convergence for multiple
zeros. But how to identify them during computation?
-Multroot (Matlab package, ACM Algo 835 I believe)
Needs a polynomial zero finder itself (matlab built in roots function).
Especially made for inexact coefficients and roots of high
multiplicities. I don't understand the method but it works - slowly but
quiet nice.
I'm asking everybody for suggestions about the "state of the art" of the
above mentioned methods (or additional ones).
Thanks a lot,
Alex
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