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  2. Bézout's theorem - Wikipedia

    en.wikipedia.org/wiki/Bézout's_theorem

    Intuitively, the multiplicity of a common zero of several polynomials is the number of zeros into which the common zero can split when the coefficients are slightly changed. For example, a tangent to a curve is a line that cuts the curve at a point that splits in several points if the line is slightly moved.

  3. Zero of a function - Wikipedia

    en.wikipedia.org/wiki/Zero_of_a_function

    The fundamental theorem of algebra shows that any non-zero polynomial has a number of roots at most equal to its degree, and that the number of roots and the degree are equal when one considers the complex roots (or more generally, the roots in an algebraically closed extension) counted with their multiplicities. [3]

  4. Descartes' rule of signs - Wikipedia

    en.wikipedia.org/wiki/Descartes'_rule_of_signs

    Let () be the number of strictly positive roots (counting multiplicity). With these, we can formally state Descartes' rule as follows: Theorem — The number of strictly positive roots (counting multiplicity) of f {\displaystyle f} is equal to the number of sign changes in the coefficients of f {\displaystyle f} , minus a nonnegative even number.

  5. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    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

  6. Geometrical properties of polynomial roots - Wikipedia

    en.wikipedia.org/wiki/Geometrical_properties_of...

    If the coefficients a i of a random polynomial are independently and identically distributed with a mean of zero, most complex roots are on the unit circle or close to it. In particular, the real roots are mostly located near ±1, and, moreover, their expected number is, for a large degree, less than the natural logarithm of the degree.

  7. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    The method will usually converge, provided this initial guess is close enough to the unknown zero, and that f ′ (x 0) ≠ 0. Furthermore, for a zero of multiplicity 1, the convergence is at least quadratic (see Rate of convergence) in a neighbourhood of the zero, which intuitively means that the number of correct digits roughly doubles in ...

  8. Intersection number - Wikipedia

    en.wikipedia.org/wiki/Intersection_number

    The intersection number arises in the study of fixed points, which can be cleverly defined as intersections of function graphs with a diagonals. Calculating the intersection numbers at the fixed points counts the fixed points with multiplicity, and leads to the Lefschetz fixed-point theorem in quantitative form.

  9. Component (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Component_(graph_theory)

    In algebraic graph theory it equals the multiplicity of 0 as an eigenvalue of the Laplacian matrix of a finite graph. [14] It is also the index of the first nonzero coefficient of the chromatic polynomial of the graph, and the chromatic polynomial of the whole graph can be obtained as the product of the polynomials of its components. [15]