# Zero of a function

In mathematics, a **zero**, also sometimes called a **root**, of a real-, complex- or generally vector-valued function *f* is a member *x* of the domain of *f* such that *f*(*x*) **vanishes** at *x*; that is,

In other words, a "zero" of a function is an input value that produces an output of zero (0).^{[1]}

A **root** of a polynomial is a zero of the associated polynomial 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. For example, the polynomial *f* of degree two, defined by

has the two roots 2 and 3, since

If the function maps real numbers to real numbers, its zeroes are the *x*-coordinates of the points where its graph meets the *x*-axis. An alternative name for such a point (*x*,0) in this context is an ** x-intercept**.

## Polynomial roots

{{#invoke:main|main}} Every real polynomial of odd degree has an odd number of real roots (counting multiplicities); likewise, a real polynomial of even degree must have an even number of real roots. Consequently, real odd polynomials must have at least one real root (because one is the smallest odd whole number), whereas even polynomials may have none. This principle can be proven by reference to the intermediate value theorem: since polynomial functions are continuous, the function value must cross zero in the process of changing from negative to positive or vice-versa.

### Fundamental theorem of algebra

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The fundamental theorem of algebra states that every polynomial of degree *n* has *n* complex roots, counted with their multiplicities. The non-real roots of polynomials with real coefficients come in conjugate pairs.^{[1]} Vieta's formulas relate the coefficients of a polynomial to sums and products of its roots.

## Computing roots

{{#invoke:main|main}} {{#invoke:main|main}} Computing roots of certain functions, especially polynomial functions, frequently requires the use of specialised or approximation techniques (for example, Newton's method).

## Zero set

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In topology and other areas of mathematics, the **zero set** of a real-valued function *f* : *X* → **R** (or more generally, a function taking values in some additive group) is the subset of *X* (the inverse image of {0}).

Zero sets are important in many areas of mathematics. One area of particular importance is algebraic geometry, where the first definition of an algebraic variety is through zero-sets. For instance, for each set *S* of polynomials in *k*[*x*_{1}, ..., *x*_{n}], one defines the zero-locus *Z*(*S*) to be the set of points in **A**^{n} on which the functions in *S* simultaneously vanish, that is to say

- Then a subset
*V*of**A**^{n}is called an**affine algebraic set**if*V*=*Z*(*S*) for some*S*. These affine algebraic sets are the fundamental building blocks of algebraic geometry.

## See also

- Zero (complex analysis)
- Pole (complex analysis)
- Fundamental theorem of algebra
- Newton's method
- Sendov's conjecture
- Marden's theorem
- Vanish at infinity

## References

- ↑
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