Math 2.0

Linear and multilinear algebra; matrix theory Concept

Definite and indefinite quadratic forms

Summary

Let AA be a symmetric n×nn \times n matrix, and let Q(x)=x𝖳AxQ(x) = x^{\mathsf{T}} A x be its real quadratic form on ℝn\mathbb{R}^n. The form QQ is positive definite if Q(x)>0Q(x) > 0 for all x≠0x \ne 0. It is negative definite if Q(x)<0Q(x) < 0 for all x≠0x \ne 0. It is positive or negative semidefinite if Q(x)≥0Q(x) \ge 0 or Q(x)≤0Q(x) \le 0 for all xx, and indefinite if it takes both positive and negative values.

Remarks

The form QQ is positive definite if and only if all eigenvalues of AA are positive. It is indefinite if and only if AA has a positive and a negative eigenvalue. On ℝ2\mathbb{R}^2, x12+x22x_1^2 + x_2^2 is positive definite, x12x_1^2 is positive semidefinite but not definite, and x12−x22x_1^2 - x_2^2 is indefinite. In the second derivative test, the matrix AA is the Hessian matrix of a function at a critical point.

Where this leads

2 pages build on this one.

Further reading

  1. Web https://en.wikipedia.org/wiki/Definite_quadratic_form, lead section
  2. Web https://en.wikipedia.org/wiki/Definite_quadratic_form, Matrix form
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