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Codomain

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Image of a function(f) from X(left) to Y(right). The smaller oval inside Y is the image of f. Y is the Codomain of f.

In mathematics, the codomain, or target set, of a function is the set Y into which all of the output of the function is constrained to fall. It is the set Y in the notation fX → Y.

The codomain (or target) is part of the modern definition of a function f as a triple (XYF), with F a subset of the Cartesian product X × Y. The set of all elements of the form f(x), where x ranges over the elements of the domain X, is called the image of f. In general, the image of a function is a subset of its codomain but not necessarily the same set; a function that is not surjective has elements y in its codomain for which the equation f(x) = y does not have a solution.

An older definition of functions which does not include a codomain is also widely used.[1] For example in set theory it is desirable to permit the domain of a function to be a proper class X, in which case there is formally no such thing as a triple (XYF). With such a definition functions do not have a codomain, although some authors still use it informally after introducing a function in the form fX → Y.[2][3][4][5][6]

Examples

For a function

defined by

, or equivalently

The codomain of is , but f does not map to any negative number. Thus the image of f is the set ,i.e., the interval [0,∞).

An alternative function is defined thus:

While and map a given x to the same number, they are not, in the modern view, the same function because they have different codomains. A third function h can be defined to demonstrate why:

The domain of h must be defined to be :

.

The compositions are defined

,
.

On inspection, is not useful. It is true, unless defined otherwise, that the image of is not known; it is only known that it is a subset of . For this reason, it is possible that h, when composed on f, might receive an argument for which no output is defined – negative numbers are not elements of the domain of h, which is the square root function.

Function composition therefore is a useful notation only when the codomain of the function on the right side of a composition (not its image, which is a consequence of the function and could be unknown at the level of the composition) is the same as the domain of the function on the left side.

The codomain affects whether a function is a surjection, in that the function is surjective if and only if its codomain equals its image. In the example, is a surjection while is not. The codomain does not affect whether a function is an injection.

A second example of the difference between codomain and image is demonstrated by the linear transformations between two vector spaces – in particular, all the linear transformations from R2 to itself, which can be represented by the 2x2 matrices with real coefficients. Each matrix represents a map with the domain R2 and codomain R2. However, the image is uncertain. Some transformations may have image equal to the whole codomain (in this case the matrices with rank 2) but many do not, instead mapping into some smaller subspace (the matrices with rank 1 or 0). Take for example the matrix T given by

which represents a linear transformation that maps the point (x, y) to (x, x). The point (2, 3) is not in the image of T, but is still in the codomain since linear transformations from R2 to R2 are of explicit relevance. Just like all 2x2 matrices, T represents a member of that set. Examining the differences between the image and codomain can often be useful for discovering properties of the function in question. For example, it can be concluded that T does not have full rank since its image is smaller than the whole codomain.

Notes

References

  • Eccles, Peter J. (1997), An Introduction to Mathematical Reasoning: Numbers, Sets, and Functions, Cambridge University Press, ISBN 978-0521597180
  • Forster, Thomas (2003), Logic, Induction and Sets, Cambridge University Press, ISBN 9780521533614
  • Mac Lane, Saunders (1998), Categories for the working mathematician (2nd ed.), Springer, ISBN 978-0387984032
  • Scott, Dana S.; Jech, Thomas J. (1967), Axiomatic set theory, Symposium in Pure Mathematics, American Mathematical Society, ISBN 978-0821802458
  • Sharma, A.K. (2004), Introduction To Set Theory, Discovery Publishing House, ISBN 978-8171418770
  • Stewart, Ian; Tall, David Orme (1977), The foundations of mathematics, Oxford University Press, ISBN 978-0198531654