Math 2.0

Linear and multilinear algebra; matrix theory Proof

Proof of the existence of an orthonormal basis by the Gram–Schmidt process

Builds on Inner productNorm induced by an inner productOrthonormal familyOrthonormal basisAn orthonormal family is linearly independentEvery linearly independent set extends to a basisDimension theorem for vector spacesGram–Schmidt processGram–Schmidt vectors are orthogonalLinearly independent set of the right size is a basisLinear span

Proof

We first prove the extension statement. The existence then follows by extending the empty family.

  1. Let VV be an inner product space over ℝ\R or ℂ\C of finite dimension nn, with inner product ⟨⋅,⋅⟩\ip{\cdot}{\cdot} and induced norm ∥⋅∥\norm{\cdot}.
  2. Let (ei)i∈I(e_i)_{i \in I} be an orthonormal family in VV. Its vectors are distinct, since ⟨ei,ej⟩=0≠1=⟨ei,ei⟩\ip{e_i}{e_j} = 0 \ne 1 = \ip{e_i}{e_i} for i≠ji \ne j.
  3. The family is linearly independent. So its set of vectors extends to a basis BB of VV.
  4. All bases of VV have the same cardinality, so BB has nn elements. Hence the family is finite. Write it e1,…,eme_1, \dots, e_m with m≤nm \le n.
  5. List BB as v1,…,vnv_1, \dots, v_n with vi=eiv_i = e_i for i≤mi \le m. Let u1,…,unu_1, \dots, u_n be the vectors of the Gram–Schmidt process applied to v1,…,vnv_1, \dots, v_n.
  6. We show uj=eju_j = e_j for j≤mj \le m, by induction on jj. First, u1=v1=e1u_1 = v_1 = e_1.
  7. Let 2≤j≤m2 \le j \le m and assume ui=eiu_i = e_i for i<ji < j. Then uj=ej−∑i<j⟨ej,ei⟩⟨ei,ei⟩ei=eju_j = e_j - \sum_{i<j} \frac{\ip{e_j}{e_i}}{\ip{e_i}{e_i}} e_i = e_j, because ⟨ej,ei⟩=0\ip{e_j}{e_i} = 0 for i≠ji \ne j.
  8. By the properties of the Gram–Schmidt vectors, u1,…,unu_1, \dots, u_n are nonzero and pairwise orthogonal. Also span⁡(u1,…,un)=span⁡(v1,…,vn)=V\operatorname{span}(u_1, \dots, u_n) = \operatorname{span}(v_1, \dots, v_n) = V.
  9. Set fj=uj/∥uj∥f_j = u_j / \norm{u_j}, which is defined since uj≠0u_j \ne 0. Then ⟨fj,fj⟩=⟨uj,uj⟩/∥uj∥2=1\ip{f_j}{f_j} = \ip{u_j}{u_j} / \norm{u_j}^2 = 1.
  10. For i≠ji \ne j, ⟨fi,fj⟩=⟨ui,uj⟩/(∥ui∥∥uj∥)=0\ip{f_i}{f_j} = \ip{u_i}{u_j} / (\norm{u_i} \norm{u_j}) = 0, since ∥uj∥\norm{u_j} is real. So f1,…,fnf_1, \dots, f_n is an orthonormal family.
  11. For j≤mj \le m, fj=ej/∥ej∥=ejf_j = e_j / \norm{e_j} = e_j, since ∥ej∥=1\norm{e_j} = 1.
  12. The family f1,…,fnf_1, \dots, f_n is linearly independent by step 10 and the same result as in step 3. It has n=dim⁡Vn = \dim V vectors, so it is a basis of VV.
  13. So f1,…,fnf_1, \dots, f_n is an orthonormal basis of VV that extends e1,…,eme_1, \dots, e_m. This proves the second claim.
  14. The empty family is orthonormal, because the condition on pairs is vacuous. Applying step 13 to it gives an orthonormal basis of VV. This proves the first claim.

Idea

Extend the orthonormal family to any basis, then run Gram–Schmidt and normalise. The process leaves the first vectors alone, because they are already orthogonal unit vectors. The output is orthonormal, hence independent, and has the right number of vectors to be a basis.

Reading path

To understand this page from the ground up, read these 59 pages in order. The foundations come first. The path takes the proofs Proof of the Steinitz exchange lemma by induction, Proof that the Gram–Schmidt vectors are orthogonal, Proof that an orthonormal family is linearly independent, 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.

  1. Element definition
  2. Proof of Zorn's lemma proof
  3. Proposition concept
  4. Vector space definition
  5. Set definition
  6. Disjunction definition
  7. Implication definition
  8. Predicate definition
  9. Inner product definition
  10. Linear combination definition
  11. Linear subspace definition
  12. Norm definition
  13. Family of sets definition
  14. Ordered pair definition
  15. Union definition
  16. Existential quantifier definition
  17. Universal quantifier definition
  18. Inner product space definition
  19. Orthogonal vectors definition
  20. Linear independence definition
  21. Linear span definition
  22. Cartesian product definition
  23. Subset definition
  24. Union of a family of sets definition
  25. Uniqueness quantifier definition
  26. Norm induced by an inner product definition
  27. Orthonormal family definition
  28. Spanning set definition
  29. Binary relation definition
  30. Proof that an orthonormal family is linearly independent proof
  31. Finite-dimensional vector space definition
  32. Basis definition
  33. Gram–Schmidt process concept
  34. Proof of the Steinitz exchange lemma by induction proof
  35. Antisymmetric relation definition
  36. Reflexive relation definition
  37. Transitive relation definition
  38. Function definition
  39. Dimension definition
  40. Dimension theorem for vector spaces statement
  41. Orthonormal basis definition
  42. An orthonormal family is linearly independent statement
  43. Proof that the Gram–Schmidt vectors are orthogonal proof
  44. Steinitz exchange lemma statement
  45. Preorder definition
  46. Choice function definition
  47. Gram–Schmidt vectors are orthogonal statement
  48. Proof that n independent or n spanning vectors in an n-dimensional space form a basis proof
  49. Partial order definition
  50. Axiom of choice statement
  51. Linearly independent set of the right size is a basis statement
  52. Maximal element definition
  53. Total order definition
  54. Upper bound definition
  55. Chain definition
  56. Zorn's lemma statement
  57. Proof that every linearly independent set extends to a basis, by Zorn's lemma proof
  58. Every linearly independent set extends to a basis statement
  59. Proof of the existence of an orthonormal basis by the Gram–Schmidt process proof

Where this leads

117 pages build on this one.

Further reading

  1. Web https://linear.axler.net/LADR4e.pdf, Theorems 6.35 and 6.36
About this page
Tag6G6ZHPR66X
URIm2://6G6ZHPR66X
Kindproof
WritingW0 stub
MSC15A63, 46C05
ProvesExistence of an orthonormal basis
UsesInner product, Norm induced by an inner product, Orthonormal family, Orthonormal basis, An orthonormal family is linearly independent, Every linearly independent set extends to a basis, Dimension theorem for vector spaces, Gram–Schmidt process, Gram–Schmidt vectors are orthogonal, Linearly independent set of the right size is a basis, Linear span
Changed4 November 2026

Markdown · JSON · Edit on GitHub

What this page needs for W1

  • an inventory row: the row of the inventory that the node accounts for (0 of 1)

The writing levels say how complete the text of a page is. They do not measure its truth.

What links here

No page links to this page yet.