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  2. Polynomial root-finding algorithms - Wikipedia

    en.wikipedia.org/wiki/Polynomial_root-finding...

    For finding all the roots, arguably the most reliable method is the Francis QR algorithm computing the eigenvalues of the companion matrix corresponding to the polynomial, implemented as the standard method [1] in MATLAB. The oldest method of finding all roots is to start by finding a single root. When a root r has been found, it can be removed ...

  3. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    Appearance. In numerical analysis, a root-finding algorithm is an algorithm for finding zeros, also called "roots", of continuous functions. A zero of a function f is a number x such that f(x) = 0. As, generally, the zeros of a function cannot be computed exactly nor expressed in closed form, root-finding algorithms provide approximations to ...

  4. Jenkins–Traub algorithm - Wikipedia

    en.wikipedia.org/wiki/Jenkins–Traub_algorithm

    The Jenkins–Traub algorithm calculates all of the roots of a polynomial with complex coefficients. The algorithm starts by checking the polynomial for the occurrence of very large or very small roots. If necessary, the coefficients are rescaled by a rescaling of the variable. In the algorithm, proper roots are found one by one and generally ...

  5. Aberth method - Wikipedia

    en.wikipedia.org/wiki/Aberth_method

    The Aberth method, or Aberth–Ehrlich method or Ehrlich–Aberth method, named after Oliver Aberth [1] and Louis W. Ehrlich, [2] is a root-finding algorithm developed in 1967 for simultaneous approximation of all the roots of a univariate polynomial. This method converges cubically, an improvement over the Durand–Kerner method, another ...

  6. Horner's method - Wikipedia

    en.wikipedia.org/wiki/Horner's_method

    This polynomial is further reduced to = + + which is shown in blue and yields a zero of −5. The final root of the original polynomial may be found by either using the final zero as an initial guess for Newton's method, or by reducing () and solving the linear equation. As can be seen, the expected roots of −8, −5, −3, 2, 3, and 7 were ...

  7. Padé approximant - Wikipedia

    en.wikipedia.org/wiki/Padé_approximant

    Padé approximant. In mathematics, a Padé approximant is the "best" approximation of a function near a specific point by a rational function of given order. Under this technique, the approximant's power series agrees with the power series of the function it is approximating. The technique was developed around 1890 by Henri Padé, but goes back ...

  8. Vieta's formulas - Wikipedia

    en.wikipedia.org/wiki/Vieta's_formulas

    Vieta's formulas relate the polynomial coefficients to signed sums of products of the roots r1, r2, ..., rn as follows: Vieta's formulas can equivalently be written as for k = 1, 2, ..., n (the indices ik are sorted in increasing order to ensure each product of k roots is used exactly once). The left-hand sides of Vieta's formulas are the ...

  9. Bairstow's method - Wikipedia

    en.wikipedia.org/wiki/Bairstow's_method

    Bairstow's approach is to use Newton's methodto adjust the coefficients uand vin the quadraticx2+ux+v{\displaystyle x^{2}+ux+v}until its roots are also roots of the polynomial being solved. The roots of the quadratic may then be determined, and the polynomial may be divided by the quadratic to eliminate those roots.