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Cayley–Hamilton theorem

Statement

Every square matrix AA satisfies its own characteristic polynomial: if p(λ)=det⁡(λI−A)p(\lambda)=\det(\lambda I - A), then p(A)=0p(A) = 0 (the zero matrix).

Why is it true?

The characteristic polynomial p(λ)p(\lambda) is built exactly so that p(λ)=0p(\lambda)=0 whenever λ\lambda is an eigenvalue of AA. Plugging the matrix AA itself in for λ\lambda looks like a huge leap, but it works because AA acts on each eigenvector the same way the scalar eigenvalue does, and (in the diagonalizable case) the eigenvectors span the whole space — so p(A)p(A) kills every direction, meaning p(A)p(A) is the zero matrix.

Proof sketch

For diagonalizable A=PDP−1A=PDP^{-1} with D=diag(λ1,…,λn)D=\mathrm{diag}(\lambda_1,\dots,\lambda_n), p(A)=Pp(D)P−1p(A)=Pp(D)P^{-1} and p(D)=diag(p(λ1),…,p(λn))=0p(D)=\mathrm{diag}(p(\lambda_1),\dots,p(\lambda_n))=0 since each λi\lambda_i is a root of pp. The general (non-diagonalizable) case follows by a density/continuity argument, or directly via the adjugate identity adj(λI−A)(λI−A)=p(λ)I\mathrm{adj}(\lambda I-A)(\lambda I - A)=p(\lambda)I treated as a polynomial identity in matrices.

Stated by

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Step-by-step proofs

No step-by-step proof yet for this theorem.

References

  1. Roger A. Horn, Charles R. Johnson (2012). Matrix Analysis · DOI:10.1017/CBO9781139020411