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Bilinear operator

From Academic Kids

In mathematics, a bilinear operator is a generalized "multiplication" which satisfies the distributive law.

Contents

Definition

For a formal definition, given three vector spaces V, W and X over the same base field F, a bilinear operator is a function

B : V × WX

such that for any w in W the map

<math>v \mapsto B(v, w)<math>

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

<math>w \mapsto B(v, w)<math>

is a linear operator from W to X. In other words, if we hold the first entry of the bilinear operator fixed, while letting the second entry vary, the result is a linear operator, and similarly if 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 F, and we have a bilinear form, is particularly useful (see for example scalar product, inner product and quadratic form).

The definition works without any changes if instead of vector spaces we use modules over a commutative ring R. It also can be easily generalized to n-ary functions, where the proper term is multilinear.

For the case of a non-commutative base ring R and a right module MR and a left module RN, we can define a bilinear operator B : M × NT, where T is a commutative group, such that for any n in N, m |-> B(m, n) is a group homomorphism, and for any m in M, n |-> B(m, n) is a group homomorphism, and which also satisfies

B(mr, n) = B(m, rn)

for all m in M, n in N and r in R.

Properties

A first immediate consequence of the definition is that <math>B(x,y)=o<math> whenever x=o or y=o. (This is seen by writing the null vector o as 0o 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 VW into X.

If V,W,X are finite-dimensional, then so is L(V,W;X). For X=K, i.e. bilinear forms, the dimension of this space is dimVdimW (while the space L(VW;K) of linear forms is of dimension dimV+dimW). To see this, chose a basis for V and W; then each bilinear map can be uniquely represented by the matrix <math>B(e_i,f_j)<math>, and vice versa. Now, if X is a space of higher dimension, we obviously have dimL(V,W;X)=dimVdimWdimX.

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 operator V × VR.
  • In general, for a vector space V over a field F, a bilinear form on V is the same as a bilinear operator V × VF.
  • If V is a vector space with dual space V*, then the application operator, b(f, v) = f(v) is a bilinear operator 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 operator V × WF.
  • The cross product in R3 is a bilinear operator R3 × R3R3.
  • Let B : V × WX be a bilinear operator, and L : UW be a linear operator, then (v, u) → B(v, Lu) is a bilinear operator on V × U
  • The null map, defined by <math>B(v,w) = o<math> for all (v,w) in VW is the only map from VW to X which is bilinear and linear at the same time. Indeed, if (v,w)∈VW, then if B is linear, <math>B(v,w)= B(v,o)+B(o,w)=o+o<math> if B is bilinear.

See also

he:תבנית בילינארית

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