The Cayley–Hamilton Theorem
Matrices add, subtract, multiply and scale much like numbers (except AB=BA in general), so we can substitute a matrix into a polynomial. For p(x)=x2−3x+2, replacing x by a square matrix A gives
p(A)=A2−3A+2I,
where the constant 2 becomes 2I so it can be added to matrices.
The Cayley–Hamilton theorem makes a striking claim: every square matrix satisfies its own characteristic equation.
The characteristic polynomial
Every n×n matrix A has a characteristic polynomial
p(λ)=det(λI−A),
a degree-n polynomial whose roots are the eigenvalues. For a 2×2 matrix it is λ2−(trA)λ+detA. For A=(1324) this is p(λ)=λ2−5λ−2.
The statement
If p(λ)=λn+cn−1λn−1+⋯+c1λ+c0 is the characteristic polynomial of A, then
p(A)=An+cn−1An−1+⋯+c1A+c0I=0,
the n×n zero matrix.
For the example, A2−5A−2I=(0000).
Why it is surprising, and a quick check
The polynomial is built from det(λI−A), yet feeding A back into it annihilates it — and this holds for any A, invertible or not. You can verify it on the general 2×2 matrix A=(acbd), where p(λ)=λ2−(a+d)λ+(ad−bc): a short computation of A2−(a+d)A+(ad−bc)I gives the zero matrix.
Why it matters
Cayley–Hamilton lets you rewrite any high power Ak (for k≥n) as a combination of I,A,…,An−1, which speeds up computing powers, exponentials and inverses. …