Orthogonal basis

In mathematics, particularly linear algebra, an orthogonal basis for an inner product space $V$ is a basis for $V$ whose vectors are mutually orthogonal. If the vectors of an orthogonal basis are normalized, the resulting basis is an orthonormal basis.

As coordinates

Any orthogonal basis can be used to define a system of orthogonal coordinates $V.$ Orthogonal (not necessarily orthonormal) bases are important due to their appearance from curvilinear orthogonal coordinates in Euclidean spaces, as well as in Riemannian and pseudo-Riemannian manifolds.

In functional analysis

In functional analysis, an orthogonal basis is any basis obtained from an orthonormal basis (or Hilbert basis) using multiplication by nonzero scalars.

Extensions

Symmetric bilinear form

The concept of an orthogonal (but not of an orthonormal) basis is applicable to a vector space $V$ (over any field) equipped with a symmetric bilinear form $\langle \cdot ,\cdot \rangle ,$ where orthogonality of two vectors $v$ and $w$ means $\langle v,w\rangle =0.$ For an orthogonal basis $\left\{e_{k}\right\}:$ $\langle e_{j},e_{k}\rangle ={\begin{cases}q(e_{k})&j=k\\0&j\neq k,\end{cases}}$ where $q$ is a quadratic form associated with $\langle \cdot ,\cdot \rangle :$ $q(v)=\langle v,v\rangle$ (in an inner product space $q(v)=\|v\|^{2}.$ ).

Hence for an orthogonal basis $\left\{e_{k}\right\},$ $\langle v,w\rangle =\sum _{k}q(e_{k})v^{k}w^{k},$ where $v_{k}$ and $w_{k}$ are components of $v$ and $w$ in the basis.

Quadratic form

The concept of orthogonality may be extended to a vector space (over any field) equipped with a quadratic form $q(v)$ . Starting from the observation that, when the characteristic of the underlying field is not 2, the associated symmetric bilinear form $\langle v,w\rangle ={\tfrac {1}{2}}(q(v+w)-q(v)-q(w))$ allows vectors $v$ and $w$ to be defined as being orthogonal with respect to $q$ when $q(v+w)-q(v)-q(w)=0.$ This definition extends to include characteristic 2.^{[citation needed]}

References

Lang, Serge (2004), Algebra, Graduate Texts in Mathematics, vol. 211 (Corrected fourth printing, revised third ed.), New York: Springer-Verlag, pp. 572–585, ISBN 978-0-387-95385-4
Milnor, J.; Husemoller, D. (1973). Symmetric Bilinear Forms. Ergebnisse der Mathematik und ihrer Grenzgebiete. Vol. 73. Springer-Verlag. p. 6. ISBN 3-540-06009-X. Zbl 0292.10016.

External links

Weisstein, Eric W. "Orthogonal Basis". MathWorld.

v t e Linear algebra
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Basic concepts	Scalar Vector Vector space Scalar multiplication Vector projection Linear span Linear map Linear projection Linear independence Linear combination Multilinear map Basis Change of basis Row and column vectors Row and column spaces Kernel Eigenvalues and eigenvectors Transpose Linear equations
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Bilinear	Orthogonality Dot product Hadamard product Inner product space Outer product Kronecker product Gram–Schmidt process
Multilinear algebra	Determinant Cross product Triple product Seven-dimensional cross product Geometric algebra Exterior algebra Bivector Multivector Tensor Outermorphism
Vector space constructions	Dual Direct sum Function space Quotient Subspace Tensor product
Numerical	Floating-point Numerical stability Basic Linear Algebra Subprograms Sparse matrix Comparison of linear algebra libraries
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v t e Hilbert spaces
Basic concepts	Adjoint Inner product and L-semi-inner product Hilbert space and Prehilbert space Orthogonal complement Orthonormal basis
Main results	Bessel's inequality Cauchy–Schwarz inequality Riesz representation
Other results	Hilbert projection theorem Parseval's identity Polarization identity (Parallelogram law)
Maps	Compact operator on Hilbert space Densely defined Hermitian form Hilbert–Schmidt Normal Self-adjoint Sesquilinear form Trace class Unitary
Examples	Cⁿ(K) with K compact & n<∞ Segal–Bargmann F