Auerbach's lemma

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Template:Short description In mathematics, Auerbach's lemma, named after Herman Auerbach, is a theorem in functional analysis which asserts that a certain property of Euclidean spaces holds for general finite-dimensional normed vector spaces.

Statement

Let (V,‖⋅‖) be an n-dimensional normed vector space. Then there exists a basis {e1,…,en} of V such that ‖ei‖=1 and ‖ei‖=1 for i=1,…,n, where {e1,…,en} is a basis of V∗ dual to {e1,…,en}, i.e. ei(ej)=δij.

A basis with this property is called an Auerbach basis.

If V is an inner product space (or even infinite-dimensional Hilbert space) then this result is obvious as one may take for {ei} any orthonormal basis of V (the dual basis is then {(ei|⋅)}).

Geometric formulation

An equivalent statement is the following: any centrally symmetric convex body in 𝐑n has a linear image which contains the unit cross-polytope (the unit ball for the ℓ1n norm) and is contained in the unit cube (the unit ball for the ℓ∞n norm).

Proof

By induction on the dimension n. Pick an arbitrary unit vector en∈V. Because the set of norm-1 points make up a convex symmetric body in V, there exists a hyperplane Pn supporting V at en. This is a consequence of the hyperplane separation theorem, which is a consequence of the Hahn–Banach theorem.

Now, define the dual vector en∈V∗, such that {x∈V:en(x)=1}=Pn. That is, the contour surfaces of en are parallel to Pn.

Then, the subspace ker⁡(en) is a normed space of dimension n−1, and apply induction.

Corollary

The lemma has a corollary with implications to approximation theory.

Let V be an n-dimensional subspace of a normed vector space (X,‖⋅‖). Then there exists a projection P of X onto V such that ‖P‖≤n.

Proof

Let {e1,…,en} be an Auerbach basis of V and {e1,…,en} corresponding dual basis. By the Hahn–Banach theorem each ei extends to fi∈X∗ such that ‖fi‖=1. Now set P(x)=∑fi(x)ei. It is easy to check that P is indeed a projection onto V and that ‖P‖≤n (this follows from the triangle inequality).

See also

References

Template:Functional analysis