Math 2.0

Number theory Proof

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 nn.

  1. Let B(u,v)=12(Q(u+v)−Q(u)−Q(v))B(u, v) = \frac12 \bigl( Q(u + v) - Q(u) - Q(v) \bigr) be the symmetric bilinear form associated with QQ. It is defined since 2≠02 \ne 0 in FF.
  2. By the definition of a quadratic form, BB is a bilinear form. The formula is unchanged when uu and vv are swapped, so BB is symmetric.
  3. For v∈Vv \in V, the rule Q(av)=a2Q(v)Q(av) = a^2 Q(v) gives Q(2v)=4Q(v)Q(2v) = 4 Q(v). So B(v,v)=12(4Q(v)−2Q(v))=Q(v)B(v, v) = \frac12 \bigl( 4 Q(v) - 2 Q(v) \bigr) = Q(v).
  4. Suppose (e1,…,en)(e_1, \dots, e_n) is a basis that is orthogonal for BB. Let ai=Q(ei)a_i = Q(e_i).
  5. By steps 3 and 4 and bilinearity, Q(∑ixiei)=∑i,jxixjB(ei,ej)=∑iaixi2Q(\sum_i x_i e_i) = \sum_{i,j} x_i x_j B(e_i, e_j) = \sum_i a_i x_i^2. So it suffices to find a BB-orthogonal basis.
  6. We prove by induction on nn: every symmetric bilinear form on an nn-dimensional space over FF has an orthogonal basis. For n≤1n \le 1, every basis is orthogonal, since there are no two distinct indices.
  7. Let n≥2n \ge 2, and assume the claim in dimension n−1n - 1. Let BB be a symmetric bilinear form on VV with dim⁡V=n\dim V = n.
  8. Suppose first that B(v,v)=0B(v, v) = 0 for all vv. Expanding by bilinearity and symmetry, B(u+v,u+v)=B(u,u)+2B(u,v)+B(v,v)B(u + v, u + v) = B(u, u) + 2 B(u, v) + B(v, v).
  9. So 2B(u,v)=02 B(u, v) = 0, and B(u,v)=0B(u, v) = 0 for all u,vu, v. Then every basis of VV is orthogonal.
  10. Otherwise choose e1∈Ve_1 \in V with c=B(e1,e1)≠0c = B(e_1, e_1) \ne 0. The map f(v)=B(e1,v)f(v) = B(e_1, v) is a linear map from VV to FF.
  11. Since f(e1)=c≠0f(e_1) = c \ne 0, the image of ff is all of FF, which has dimension 11. Let WW be the kernel of ff.
  12. By the rank–nullity theorem, dim⁡W=n−1\dim W = n - 1.
  13. The restriction of BB to W×WW \times W is a symmetric bilinear form on WW. By the induction hypothesis, WW has a basis e2,…,ene_2, \dots, e_n that is orthogonal for BB.
  14. The family e1,…,ene_1, \dots, e_n is linearly independent. Indeed, let c1e1+⋯+cnen=0c_1 e_1 + \cdots + c_n e_n = 0. Applying ff gives c1c=0c_1 c = 0, since f(ei)=0f(e_i) = 0 for i≥2i \ge 2.
  15. So c1=0c_1 = 0. Then c2e2+⋯+cnen=0c_2 e_2 + \cdots + c_n e_n = 0, and c2=⋯=cn=0c_2 = \cdots = c_n = 0 since e2,…,ene_2, \dots, e_n is a basis of WW.
  16. By the definition of dimension and the basis criterion, the nn independent vectors e1,…,ene_1, \dots, e_n form a basis of VV.
  17. For 2≤i≠j2 \le i \ne j, B(ei,ej)=0B(e_i, e_j) = 0 by step 13. For j≥2j \ge 2, B(e1,ej)=f(ej)=0B(e_1, e_j) = f(e_j) = 0, and B(ej,e1)=0B(e_j, e_1) = 0 by symmetry.
  18. So e1,…,ene_1, \dots, e_n is an orthogonal basis, which completes the induction.
  19. Apply step 6 to the form BB of step 1. By step 5, Q(x1e1+⋯+xnen)=a1x12+⋯+anxn2Q(x_1 e_1 + \cdots + x_n e_n) = a_1 x_1^2 + \cdots + a_n x_n^2 with ai=Q(ei)a_i = Q(e_i).

Idea

In an orthogonal basis the cross terms xixjx_i x_j disappear, so it is enough to build such a basis. Pick a vector e1e_1 with Q(e1)≠0Q(e_1) \ne 0 and pass to the hyperplane of vectors orthogonal to it. Induction finishes the job, and if no such e1e_1 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.

  1. Basis concept
  2. Dimension concept
  3. Element definition
  4. Image of a linear map concept
  5. Kernel of a linear map concept
  6. Linear independence concept
  7. Linear map concept
  8. Linear subspace concept
  9. Nullity concept
  10. Proof of Zorn's lemma proof
  11. Proposition concept
  12. Rank of a linear map concept
  13. Spanning set concept
  14. Vector space definition
  15. Set definition
  16. Disjunction definition
  17. Implication definition
  18. Predicate definition
  19. Bilinear form definition
  20. Linear combination definition
  21. Linear map definition
  22. Linear subspace definition
  23. Family of sets definition
  24. Ordered pair definition
  25. Union definition
  26. Existential quantifier definition
  27. Universal quantifier definition
  28. Orthogonal family for a bilinear form definition
  29. Symmetric bilinear form definition
  30. Linear independence definition
  31. Image of a linear map definition
  32. Kernel of a linear map definition
  33. Linear span definition
  34. Quadratic form definition
  35. Cartesian product definition
  36. Union of a family of sets definition
  37. Subset definition
  38. Uniqueness quantifier definition
  39. Polar form of a quadratic form definition
  40. Spanning set definition
  41. Binary relation definition
  42. Finite-dimensional vector space definition
  43. Basis definition
  44. Symmetric bilinear form associated with a quadratic form definition
  45. Proof of the Steinitz exchange lemma by induction proof
  46. Antisymmetric relation definition
  47. Reflexive relation definition
  48. Transitive relation definition
  49. Dimension definition
  50. Function definition
  51. Dimension theorem for vector spaces statement
  52. Steinitz exchange lemma statement
  53. Preorder definition
  54. Choice function definition
  55. Proof that a subspace of a finite-dimensional space has smaller or equal dimension proof
  56. Rank of a linear map definition
  57. Proof that n independent or n spanning vectors in an n-dimensional space form a basis proof
  58. Nullity definition
  59. Partial order definition
  60. Axiom of choice statement
  61. Dimension of a subspace statement
  62. Linearly independent set of the right size is a basis statement
  63. Maximal element definition
  64. Total order definition
  65. Upper bound definition
  66. Chain definition
  67. Zorn's lemma statement
  68. Proof that every linearly independent set extends to a basis, by Zorn's lemma proof
  69. Every linearly independent set extends to a basis statement
  70. Proof of the rank–nullity theorem by extending a basis of the kernel proof
  71. Rank–nullity theorem statement
  72. Proof of the diagonalisation of a quadratic form by an orthogonal basis proof

Where this leads

3 pages build on this one.

Further reading

  1. Web https://kconrad.math.uconn.edu/blurbs/linmultialg/bilinearform.pdf, Theorem 4.7
About this page
TagPP93XQZ6WR
URIm2://PP93XQZ6WR
Kindproof
WritingW0 stub
MSC11E04, 15A63
ProvesDiagonalisation of a quadratic form
UsesQuadratic 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
Changed4 November 2026

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