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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 zeros.
In various areas of mathematics, the zero set of a function is the set of all its zeros. More precisely, if f : X → R {\displaystyle f:X\to \mathbb {R} } is a real-valued function (or, more generally, a function taking values in some additive group ), its zero set is f − 1 ( 0 ) {\displaystyle f^{-1}(0)} , the inverse image of { 0 ...
It is easy to find situations for which Newton's method oscillates endlessly between two distinct values. For example, for Newton's method as applied to a function f to oscillate between 0 and 1, it is only necessary that the tangent line to f at 0 intersects the x-axis at 1 and that the tangent line to f at 1 intersects the x-axis at 0. [19]
If it is not the case, zero is a root, and the localization of the other roots may be studied by dividing the polynomial by a power of the indeterminate, getting a polynomial with a nonzero constant term. For k = 0 and k = n, Descartes' rule of signs shows that the polynomial has exactly one positive real root.
Solutions of the equation are also called roots or zeros of the polynomial on the left side. The theorem states that each rational solution x = p ⁄ q, written in lowest terms so that p and q are relatively prime, satisfies: p is an integer factor of the constant term a 0, and; q is an integer factor of the leading coefficient a n.
For a fourth degree complex polynomial P (quartic function) with four distinct zeros forming a concave quadrilateral, one of the zeros of P lies within the convex hull of the other three; all three zeros of P' lie in two of the three triangles formed by the interior zero of P and two others zeros of P. [2]
For example, λ may be negative, in which case the eigenvector reverses direction as part of the scaling, or it may be zero or complex. In this shear mapping the red arrow changes direction, but the blue arrow does not. The blue arrow is an eigenvector of this shear mapping because it does not change direction, and since its length is unchanged ...
The zeros of the polynomial = are precisely the n th roots of unity, each with multiplicity 1. The n th cyclotomic polynomial is defined by the fact that its zeros are precisely the primitive n th roots of unity, each with multiplicity 1.