Math 2.0

Linear and multilinear algebra; matrix theory Definition

Spectrum of a matrix

Builds on Eigenvalue

Definition

Let FF be a field and let AA be an n×nn \times n matrix over FF. The spectrum of AA is the set σ(A)={λ∈F:A−λIn is not invertible}.\sigma(A) = \{\lambda \in F : A - \lambda I_n \text{ is not invertible}\}. It is the set of eigenvalues of AA.

Remarks

The spectrum has at most nn elements, because each eigenvalue is a root of the characteristic polynomial of degree nn. Over ℂ\C, the spectrum of each square matrix is nonempty. The spectrum depends on the field: the real matrix (0−110)\begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix} has empty spectrum over ℝ\R and spectrum {i,−i}\{i, -i\} over ℂ\C. Some authors count the eigenvalues with their multiplicities and call this list the spectrum.

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  1. Vector space definition
  2. Linear map definition
  3. Endomorphism definition
  4. Eigenvalue definition
  5. Spectrum of a matrix definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Spectrum_of_a_matrix, Definition
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