Proof of the diagonalisation of a quadratic form by an orthogonal basis
Builds on Quadratic formSymmetric bilinear form associated with a quadratic formSymmetric bilinear formBilinear formOrthogonal family for a bilinear formLinear mapKernel of a linear mapRank–nullity theoremDimensionBasisLinear independenceLinearly independent set of the right size is a basis
Proof
We reduce the statement to the existence of an orthogonal basis, which we prove by induction on .
- Let be the symmetric bilinear form associated with . It is defined since in .
- By the definition of a quadratic form, is a bilinear form. The formula is unchanged when and are swapped, so is symmetric.
- For , the rule gives . So .
- Suppose is a basis that is orthogonal for . Let .
- By steps 3 and 4 and bilinearity, . So it suffices to find a -orthogonal basis.
- We prove by induction on : every symmetric bilinear form on an -dimensional space over has an orthogonal basis. For , every basis is orthogonal, since there are no two distinct indices.
- Let , and assume the claim in dimension . Let be a symmetric bilinear form on with .
- Suppose first that for all . Expanding by bilinearity and symmetry, .
- So , and for all . Then every basis of is orthogonal.
- Otherwise choose with . The map is a linear map from to .
- Since , the image of is all of , which has dimension . Let be the kernel of .
- By the rank–nullity theorem, .
- The restriction of to is a symmetric bilinear form on . By the induction hypothesis, has a basis that is orthogonal for .
- The family is linearly independent. Indeed, let . Applying gives , since for .
- So . Then , and since is a basis of .
- By the definition of dimension and the basis criterion, the independent vectors form a basis of .
- For , by step 13. For , , and by symmetry.
- So is an orthogonal basis, which completes the induction.
- Apply step 6 to the form of step 1. By step 5, with .
Idea
In an orthogonal basis the cross terms disappear, so it is enough to build such a basis. Pick a vector with and pass to the hyperplane of vectors orthogonal to it. Induction finishes the job, and if no such exists the form is zero.
Reading path
To understand this page from the ground up, read these 72 pages in order. The foundations come first. The path takes the proofs Proof of the Steinitz exchange lemma by induction, Proof that every linearly independent set extends to a basis, by Zorn's lemma, Proof of Zorn's lemma, Proof that n independent or n spanning vectors in an n-dimensional space form a basis, Proof that a subspace of a finite-dimensional space has smaller or equal dimension, Proof of the rank–nullity theorem by extending a basis of the kernel.
- Basis concept
- Dimension concept
- Element definition
- Image of a linear map concept
- Kernel of a linear map concept
- Linear independence concept
- Linear map concept
- Linear subspace concept
- Nullity concept
- Proof of Zorn's lemma proof
- Proposition concept
- Rank of a linear map concept
- Spanning set concept
- Vector space definition
- Set definition
- Disjunction definition
- Implication definition
- Predicate definition
- Bilinear form definition
- Linear combination definition
- Linear map definition
- Linear subspace definition
- Family of sets definition
- Ordered pair definition
- Union definition
- Existential quantifier definition
- Universal quantifier definition
- Orthogonal family for a bilinear form definition
- Symmetric bilinear form definition
- Linear independence definition
- Image of a linear map definition
- Kernel of a linear map definition
- Linear span definition
- Quadratic form definition
- Cartesian product definition
- Union of a family of sets definition
- Subset definition
- Uniqueness quantifier definition
- Polar form of a quadratic form definition
- Spanning set definition
- Binary relation definition
- Finite-dimensional vector space definition
- Basis definition
- Symmetric bilinear form associated with a quadratic form definition
- Proof of the Steinitz exchange lemma by induction proof
- Antisymmetric relation definition
- Reflexive relation definition
- Transitive relation definition
- Dimension definition
- Function definition
- Dimension theorem for vector spaces statement
- Steinitz exchange lemma statement
- Preorder definition
- Choice function definition
- Proof that a subspace of a finite-dimensional space has smaller or equal dimension proof
- Rank of a linear map definition
- Proof that n independent or n spanning vectors in an n-dimensional space form a basis proof
- Nullity definition
- Partial order definition
- Axiom of choice statement
- Dimension of a subspace statement
- Linearly independent set of the right size is a basis statement
- Maximal element definition
- Total order definition
- Upper bound definition
- Chain definition
- Zorn's lemma statement
- Proof that every linearly independent set extends to a basis, by Zorn's lemma proof
- Every linearly independent set extends to a basis statement
- Proof of the rank–nullity theorem by extending a basis of the kernel proof
- Rank–nullity theorem statement
- Proof of the diagonalisation of a quadratic form by an orthogonal basis proof
Where this leads
3 pages build on this one.
Further reading
About this page
| Tag | PP93XQZ6WR |
|---|---|
| URI | m2://PP93XQZ6WR |
| Kind | proof |
| Writing | W0 stub |
| MSC | 11E04, 15A63 |
| Proves | Diagonalisation of a quadratic form |
| Uses | Quadratic form, Symmetric bilinear form associated with a quadratic form, Symmetric bilinear form, Bilinear form, Orthogonal family for a bilinear form, Linear map, Kernel of a linear map, Rank–nullity theorem, Dimension, Basis, Linear independence, Linearly independent set of the right size is a basis |
| Changed | 4 November 2026 |
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