Math 2.0

statement theorem

Diagonalisation of a quadratic form

Statement

Let FF be a field of characteristic not 22, and let VV be a vector space over FF of finite dimension nn. Let QQ be a quadratic form on VV. Then VV has a basis (e1,…,en)(e_1, \dots, e_n) and there are a1,…,an∈Fa_1, \dots, a_n \in F such that, for all x1,…,xn∈Fx_1, \dots, x_n \in F, Q(x1e1+⋯+xnen)=a1x12+a2x22+⋯+anxn2.Q(x_1 e_1 + \cdots + x_n e_n) = a_1 x_1^2 + a_2 x_2^2 + \cdots + a_n x_n^2.

Remarks

The basis is orthogonal for the associated symmetric bilinear form, and ai=Q(ei)a_i = Q(e_i). In matrix terms, each symmetric matrix AA over FF has an invertible PP such that PTAPP^T A P is diagonal. The numbers aia_i are not unique; for example, each aia_i can be multiplied by a nonzero square. Over R\R, the orthogonal diagonalisation of the principal axis theorem is a special case.

Explanations

L1 human

Every quadratic form becomes a sum of squares with coefficients after a good change of variables. For example, x2+2xy=(x+y)2−y2x^2 + 2xy = (x + y)^2 - y^2. With u=x+yu = x + y and v=yv = y, the form becomes u2−v2u^2 - v^2.

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  1. Vector space definition
  2. Bilinear form definition
  3. Orthogonal family for a bilinear form definition
  4. Quadratic form definition
  5. Diagonalisation of a quadratic form statement

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Sources

  1. Web https://en.wikipedia.org/wiki/Quadratic_form, Equivalence of forms