Math 2.0

Linear and multilinear algebra; matrix theory Proof

Proof that an orthonormal family is linearly independent

Builds on Inner productOrthonormal familyLinear independence

Proof

We take the inner product of a vanishing combination with each vector of the family.

  1. Let VV be an inner product space over 𝕂=ℝ\mathbb{K} = \R or ℂ\C, with inner product ⟨⋅,⋅⟩\ip{\cdot}{\cdot}. Let (ei)i∈I(e_i)_{i \in I} be an orthonormal family in VV, so ⟨ei,ej⟩=δij\ip{e_i}{e_j} = \delta_{ij} for all i,j∈Ii, j \in I.
  2. By the definition of linear independence of a family, it is enough to show that each finite subfamily is linearly independent.
  3. Let i1,…,iki_1, \dots, i_k be distinct indices in II. Let a1,…,ak∈𝕂a_1, \dots, a_k \in \mathbb{K} with a1ei1+⋯+akeik=0a_1 e_{i_1} + \cdots + a_k e_{i_k} = 0.
  4. Fix mm with 1≤m≤k1 \le m \le k. The inner product of 00 with eime_{i_m} is ⟨0,eim⟩=⟨0⋅0,eim⟩=0⋅⟨0,eim⟩=0\ip{0}{e_{i_m}} = \ip{0 \cdot 0}{e_{i_m}} = 0 \cdot \ip{0}{e_{i_m}} = 0, by linearity in the first argument.
  5. Linearity in the first argument also gives ⟨∑l=1kaleil,eim⟩=∑l=1kal⟨eil,eim⟩\ip{\sum_{l=1}^{k} a_l e_{i_l}}{e_{i_m}} = \sum_{l=1}^{k} a_l \ip{e_{i_l}}{e_{i_m}}.
  6. Since the indices are distinct, ⟨eil,eim⟩=δlm\ip{e_{i_l}}{e_{i_m}} = \delta_{lm}. So the sum in step 5 equals ama_m.
  7. By steps 3, 4 and 5, this sum is also 00. Hence am=0a_m = 0.
  8. This holds for each mm, so the only vanishing combination is the trivial one. Thus (ei)i∈I(e_i)_{i \in I} is linearly independent.

Idea

The inner product with eme_m picks out the coefficient of eme_m in a combination, because all the other vectors are orthogonal to eme_m and eme_m has length one. If the combination is zero, each picked coefficient is zero.

Reading path

To understand this page from the ground up, read these 7 pages in order. The foundations come first.

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Each page uses the pages above it. The colour of the bar on a box shows how strong the evidence is, and the box also gives it as text. The list has the same pages.
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  1. Vector space definition
  2. Inner product definition
  3. Linear combination definition
  4. Orthogonal vectors definition
  5. Linear independence definition
  6. Orthonormal family definition
  7. Proof that an orthonormal family is linearly independent proof

Where this leads

121 pages build on this one.

Further reading

  1. Web https://linear.axler.net/LADR4e.pdf, Corollary 6.25
About this page
TagHP32FXA1ZG
URIm2://HP32FXA1ZG
Kindproof
WritingW0 stub
MSC15A63, 46C05
ProvesAn orthonormal family is linearly independent
UsesInner product, Orthonormal family, Linear independence
Changed4 November 2026

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