A multilinear map of two variables is a bilinear map. More generally, a multilinear map of k variables is called a k-linear map. If the codomain of a multilinear map is the field of scalars, it is called a multilinear form. Multilinear maps and multilinear forms are fundamental objects of study in multilinear algebra.
If all variables belong to the same space, one can consider symmetric, antisymmetric and alternating k-linear maps. The latter coincide if the underlying ring (or field) has a characteristic different from two, else the former two coincide.
- Any bilinear map is a multilinear map. For example, any inner product on a vector space is a multilinear map, as is the cross product of vectors in .
- The determinant of a matrix is an antisymmetric multilinear function of the columns (or rows) of a square matrix.
- If is a Ck function, then the th derivative of at each point in its domain can be viewed as a symmetric -linear function .
- The tensor-to-vector projection in multilinear subspace learning is a multilinear map as well.
be a multilinear map between finite-dimensional vector spaces, where has dimension , and has dimension . If we choose a basis for each and a basis for (using bold for vectors), then we can define a collection of scalars by
Then the scalars completely determine the multilinear function . In particular, if
for , then
Relation to tensor products
There is a natural one-to-one correspondence between multilinear maps
and linear maps
where denotes the tensor product of . The relation between the functions and is given by the formula
Multilinear functions on n×n matrices
One can consider multilinear functions, on an n×n matrix over a commutative ring K with identity, as a function of the rows (or equivalently the columns) of the matrix. Let A be such a matrix and , 1 ≤ i ≤ n be the rows of A. Then the multilinear function D can be written as
If we let represent the jth row of the identity matrix we can express each row as the sum
Using the multilinearity of D we rewrite D(A) as
Continuing this substitution for each we get, for 1 ≤ i ≤ n
- where, since in our case
- as a series of nested summations.
Therefore, D(A) is uniquely determined by how operates on .
In the case of 2×2 matrices we get
Where and . If we restrict D to be an alternating function then and . Letting we get the determinant function on 2×2 matrices:
A multilinear map has a value of zero whenever one of its arguments is zero.
- Algebraic form
- Multilinear form
- Homogeneous polynomial
- Homogeneous function
- Multilinear projection
- Multilinear subspace learning
- Lang. Algebra. Springer; 3rd edition (January 8, 2002)