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  2. Methods of computing square roots - Wikipedia

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

    A method analogous to piece-wise linear approximation but using only arithmetic instead of algebraic equations, uses the multiplication tables in reverse: the square root of a number between 1 and 100 is between 1 and 10, so if we know 25 is a perfect square (5 × 5), and 36 is a perfect square (6 × 6), then the square root of a number greater than or equal to 25 but less than 36, begins with ...

  3. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    Newton's method is a powerful technique—in general the convergence is quadratic: as the method converges on the root, the difference between the root and the approximation is squared (the number of accurate digits roughly doubles) at each step. However, there are some difficulties with the method.

  4. Gauss–Legendre algorithm - Wikipedia

    en.wikipedia.org/wiki/Gauss–Legendre_algorithm

    Gauss–Legendre algorithm. The Gauss–Legendre algorithm is an algorithm to compute the digits of π. It is notable for being rapidly convergent, with only 25 iterations producing 45 million correct digits of π. However, it has some drawbacks (for example, it is computer memory -intensive) and therefore all record-breaking calculations for ...

  5. 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 ...

  6. Horner's method - Wikipedia

    en.wikipedia.org/wiki/Horner's_method

    Alternatively, Horner's method also refers to a method for approximating the roots of polynomials, described by Horner in 1819. It is a variant of the Newton–Raphson method made more efficient for hand calculation by the application of Horner's rule. It was widely used until computers came into general use around 1970.

  7. Fast inverse square root - Wikipedia

    en.wikipedia.org/wiki/Fast_inverse_square_root

    The fast inverse square generates a good approximation with only one division step. The length of the vector is determined by calculating its Euclidean norm: the square root of the sum of squares of the vector components. When each component of the vector is divided by that length, the new vector will be a unit vector pointing in the same direction

  8. Graeffe's method - Wikipedia

    en.wikipedia.org/wiki/Graeffe's_method

    Graeffe's method. In mathematics, Graeffe's method or Dandelin–Lobachesky–Graeffe method is an algorithm for finding all of the roots of a polynomial. It was developed independently by Germinal Pierre Dandelin in 1826 and Lobachevsky in 1834. In 1837 Karl Heinrich Gräffe also discovered the principal idea of the method. [ 1]

  9. Laguerre's method - Wikipedia

    en.wikipedia.org/wiki/Laguerre's_method

    Laguerre's method. In numerical analysis, Laguerre's method is a root-finding algorithm tailored to polynomials. In other words, Laguerre's method can be used to numerically solve the equation p(x) = 0 for a given polynomial p(x). One of the most useful properties of this method is that it is, from extensive empirical study, very close to being ...