# Bilinear map

In mathematics, a **bilinear map** is a function combining elements of two vector spaces to yield an element of a third vector space, and is linear in each of its arguments. Matrix multiplication is an example.

## Definition

### Vector spaces

Let *V*, *W* and *X* be three vector spaces over the same base field *F*. A bilinear map is a function

*B*:*V*×*W*→*X*

such that for any *w* in *W* the map

*v*↦*B*(*v*,*w*)

is a linear map from *V* to *X*, and for any *v* in *V* the map

*w*↦*B*(*v*,*w*)

is a linear map from *W* to *X*.

In other words, when we hold the first entry of the bilinear map fixed while letting the second entry vary, the result is a linear operator, and similarly for when we hold the second entry fixed.

If *V* = *W* and we have *B*(*v*, *w*) = *B*(*w*, *v*) for all *v*, *w* in *V*, then we say that *B* is *symmetric*.

The case where *X* is the base field *F*, and we have a **bilinear form**, is particularly useful (see for example scalar product, inner product and quadratic form).

### Modules

The definition works without any changes if instead of vector spaces over a field *F*, we use modules over a commutative ring *R*. It generalizes to *n*-ary functions, where the proper term is *multilinear*.

For non-commutative rings *R* and *S*, a left *R*-module *M* and a right *S*-module *N*, a bilinear map is a map *B* : *M* × *N* → *T* with *T* an (*R*, *S*)-bimodule, and for which any *n* in *N*, *m* ↦ *B*(*m*, *n*) is an *R*-module homomorphism, and for any *m* in *M*, *n* ↦ *B*(*m*, *n*) is an *S*-module homomorphism. This satisfies

*B*(*r*⋅*m*,*n*) =*r*⋅*B*(*m*,*n*)*B*(*m*,*n*⋅*s*) =*B*(*m*,*n*) ⋅*s*

for all *m* in *M*, *n* in *N*, *r* in *R* and *s* in *S*, as well as *B* being additive in each argument.

## Properties

A first immediate consequence of the definition is that *B*(*v*, *w*) = 0_{X} whenever *v* = 0_{V} or *w* = 0_{W}. This may be seen by writing the zero vector 0_{X} as 0 ⋅ 0_{X} (and similarly for 0_{W}) and moving the scalar 0 "outside", in front of *B*, by linearity.

The set *L*(*V*, *W*; *X*) of all bilinear maps is a linear subspace of the space (viz. vector space, module) of all maps from *V* × *W* into *X*.

If *V*, *W*, *X* are finite-dimensional, then so is *L*(*V*, *W*; *X*). For *X* = *F*, i.e. bilinear forms, the dimension of this space is dim *V* × dim *W* (while the space *L*(*V* × *W*; *F*) of *linear* forms is of dimension dim *V* + dim *W*). To see this, choose a basis for *V* and *W*; then each bilinear map can be uniquely represented by the matrix *B*(*e*_{i}, *f*_{j}), and vice versa.
Now, if *X* is a space of higher dimension, we obviously have dim *L*(*V*, *W*; *X*) = dim *V* × dim *W* × dim *X*.

## Examples

- Matrix multiplication is a bilinear map M(
*m*,*n*) × M(*n*,*p*) → M(*m*,*p*). - If a vector space
*V*over the real numbers**R**carries an inner product, then the inner product is a bilinear map*V*×*V*→**R**. - In general, for a vector space
*V*over a field*F*, a bilinear form on*V*is the same as a bilinear map*V*×*V*→*F*. - If
*V*is a vector space with dual space*V*^{∗}, then the application operator,*b*(*f*,*v*) =*f*(*v*) is a bilinear map from*V*^{∗}×*V*to the base field. - Let
*V*and*W*be vector spaces over the same base field*F*. If*f*is a member of*V*^{∗}and*g*a member of*W*^{∗}, then*b*(*v*,*w*) =*f*(*v*)*g*(*w*) defines a bilinear map*V*×*W*→*F*. - The cross product in
**R**^{3}is a bilinear map**R**^{3}×**R**^{3}→**R**^{3}. - Let
*B*:*V*×*W*→*X*be a bilinear map, and*L*:*U*→*W*be a linear map, then (*v*,*u*) ↦*B*(*v*,*Lu*) is a bilinear map on*V*×*U*.

## See also

## External links

- Hazewinkel, Michiel, ed. (2001), "Bilinear mapping",
*Encyclopedia of Mathematics*, Springer, ISBN 978-1-55608-010-4