Bilinear form
Encyclopedia : B : BI : BIL : Bilinear form
In mathematics, a bilinear form on a vector space V over a field F is a mapping V × V → F which is linear in both arguments. That is, B : V × V → F is bilinear if the maps
- [v \mapsto B(v, w)]
- [v \mapsto B(w, v)]
Note that a bilinear form is a special case of a bilinear operator.
When F is the field of complex numbers C one is often more interested in sesquilinear forms. These are similar to bilinear forms but are conjugate linear in one argument instead of linear.
Coordinate representation
Let [C=\,\ldots,e_\}] be a basis for V, assuming the latter is of finite dimension. Define the [n\times n] - matrix A by [(A_)=B(e_,e_)]. A is symmetric exactly due to symmetry of the bilinear form. Then if the [n\times 1] matrix x represents a vector v with respect to this basis, and analogously, y represents w, [B(v,w)] is given by :
[x^ A y]
Suppose C' is another basis for V, with : [\begine'_ & \cdots & e'_\end = \begine_ & \cdots & e_\endS] with S an invertible [n\times n] - matrix. Now the new matrix representation for the symmetric bilinear form is given by :
[A' =S^ A S]
Maps to the dual space
Every bilinear form B on V defines a pair of linear maps from V to its dual space V*. Define [B_1,B_2\colon V \to V^*] by
- [B_1(v)(w) = B(v,w)]
- [B_2(v)(w) = B(w,v)]
- [B_1(v) = B(v,)]
- [B_2(v) = B(,v)]
If either of B1 or B2 is an isomorphism, then both are, and the bilinear form B is said to be nondegenerate.
If V is finite-dimensional then one can identify V with its double dual V**. One can then show that B2 is the transpose of the linear map B1 (if V is infinite-dimensional then B2 is the transpose of B1 restricted to the image of V in V**). Given B one can define the transpose of B to be the bilinear form given by
- [B^*(v,w) = B(w,v).]
- [B(v,w)=0\mbox\Rightarrow v=0.]
- [B(v,w) = A(v)(w)]
Reflexivity and orthogonality
A bilinear form B : V × V → F is said to be reflexive if [\forall v,w\in V : B(v,w)=0\Longleftrightarrow B(w,v)=0].
Reflexivity allows us to define orthogonality : two vectors v and w are said to be orthogonal with respect to the reflexive bilinear form if and only if : [B(v,w)=0\Longleftrightarrow B(w,v)=0]
The radical of a bilinear form is the subset of all vectors orthogonal with every other vector. A vector v, with matrix representation x, is in the radical if and only if : [A x= 0 \Longleftrightarrow x^ A=0] The radical is always a subspace of V. It is trivial if and only if the matrix A is nonsingular, and thus if and only if the bilinear form is nondegenerate.
Suppose W is a subspace. Define : [W^=\]
When the bilinear form is nondegenerate, the map [W\leftarrow W^] is bijective, and the dimension of [W^] is dim(V)-dim(W).
One can prove that B is reflexive if and only if it is :
- symmetric : [B(v,w)=B(w,v)] for all [v,w\in V]
- alternating if [B(v,v)=0] for all [v\in V]
If the characteristic of F is not 2 then the converse is also true (every skew-symmetric form is alternating). If, however, char(F) = 2 then a skew-symmetric form is the same thing as a symmetric form and not all of these are alternating.
A bilinear form is symmetric (resp. skew-symmetric) if and only if its coordinate matrix (relative to any basis) is symmetric (resp. skew-symmetric). A bilinear form is alternating if and only if its coordinate matrix is skew-symmetric and the diagonal entries are all zero (which follows from skew-symmetry when char(F) ≠ 2).
A bilinear form is symmetric if and only if the maps [B_1,B_2\colon V \to V^*] are equal, and skew-symmetric if and only if they are negatives of one another. If char(F) ≠ 2 then one can always decompose a bilinear form into a symmetric and a skew-symmetric part as follows
- [B^ = (B \pm B^*)]
Relation to tensor products
By the universal property of the tensor product, bilinear forms on V are in 1-to-1 correspondence with linear maps V ⊗ V → F. If B is a bilinear form on V the corresponding linear map is given by
- [v\otimes w\mapsto B(v,w).]
- [(V\otimes V)^ \cong V^\otimes V^.]
On normed vector spaces
A bilinear form on a normed vector space is bounded, if there is a constant [C] such that for all [u, v\in V]
- [B(u,v) \le C \|u\| \|v\|.]
- [B(u,u) \ge c \|u\|^2.]
See also
External links
- [Bilinear form] on PlanetMath
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