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  2. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    Solving an equation f(x) = g(x) is the same as finding the roots of the function h(x) = f(x) – g(x). Thus root-finding algorithms can be used to solve any equation of continuous functions. However, most root-finding algorithms do not guarantee that they will find all roots of a function, and if such an algorithm does not find any root, that ...

  3. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    Although the convergence of x n + 1 − x n in this case is not very rapid, it can be proved from the iteration formula. This example highlights the possibility that a stopping criterion for Newton's method based only on the smallness of x n + 1 − x n and f(x n) might falsely identify a root.

  4. Householder's method - Wikipedia

    en.wikipedia.org/wiki/Householder's_method

    Suppose f is analytic in a neighborhood of a and f(a) = 0.Then f has a Taylor series at a and its constant term is zero. Because this constant term is zero, the function f(x) / (x − a) will have a Taylor series at a and, when f ′ (a) ≠ 0, its constant term will not be zero.

  5. Polynomial root-finding - Wikipedia

    en.wikipedia.org/wiki/Polynomial_root-finding

    The class of methods is based on converting the problem of finding polynomial roots to the problem of finding eigenvalues of the companion matrix of the polynomial, [1] in principle, can use any eigenvalue algorithm to find the roots of the polynomial. However, for efficiency reasons one prefers methods that employ the structure of the matrix ...

  6. Inverse quadratic interpolation - Wikipedia

    en.wikipedia.org/wiki/Inverse_quadratic...

    The asymptotic behaviour is very good: generally, the iterates x n converge fast to the root once they get close. However, performance is often quite poor if the initial values are not close to the actual root. For instance, if by any chance two of the function values f n−2, f n−1 and f n coincide, the algorithm fails completely. Thus ...

  7. Broyden's method - Wikipedia

    en.wikipedia.org/wiki/Broyden's_method

    Newton's method for solving f(x) = 0 uses the Jacobian matrix, J, at every iteration. However, computing this Jacobian can be a difficult and expensive operation; for large problems such as those involving solving the Kohn–Sham equations in quantum mechanics the number of variables can be in the hundreds of thousands.

  8. Bairstow's method - Wikipedia

    en.wikipedia.org/wiki/Bairstow's_method

    Bairstow's approach is to use Newton's method to adjust the coefficients u and v in the quadratic + + 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.

  9. Methods of computing square roots - Wikipedia

    en.wikipedia.org/wiki/Methods_of_computing...

    In other words, multiply the remainder by 100 and add the two digits. This will be the current value c. Find p, y and x, as follows: Let p be the part of the root found so far, ignoring any decimal point. (For the first step, p = 0.) Determine the greatest digit x such that (+).

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