Question

Prove that if A is a square matrix of size n \times n, then A_k \rightarrow 0 as k \rightarrow \infty if and only if \mid \lambda_i \mid < 1 \ \forall i

Solution

Norm is a value that indicates the magnitude of a matrix. If the positive power of a matrix results in a smaller matrix, it means that the magnitude of the resultant matrix has decreased after the exponentiation. Thus,

(1)   \begin{equation*}     \left\ A_k \rightarrow 0 \ as \ k \rightarrow \infty \Rightarrow \lVert A_k \rVert < \lVert A \rVert \end{equation*}

Let \lambda be the spectral radius (\rho(A)) of A. Then, spectral radius \rho(A_k) will be \lambda_k.

Let \lVert . \rVert be a consistent norm (induced norms are consistent). Then according to spectral radius formula:

(2)   \begin{equation*}     \left\ \rho(A) \le {\lVert A_k \rVert}^{1/k} \end{equation*}

(3)   \begin{equation*}     \left\ \Rightarrow \lVert \lambda_k \rVert \le \lVert A_k \rVert  \end{equation*}

Similarly,

(4)   \begin{equation*}     \left\ \lVert \lambda \rVert \le \lVert A \rVert \end{equation*}

Applying (1) in (3),

(5)   \begin{equation*}     \left\ \lVert \lambda_k \rVert < \lVert A \rVert \end{equation*}

Apply (4) in (5),

    \begin{align*}     \left \lVert \lambda_k \rVert < \lVert \lambda \rVert \end{align*}

    \begin{align*}     \left \Rightarrow \lVert \lambda_k - 1 \rVert < \lVert 1 \rVert \end{align*}

Since \lambda is the spectral radius, all other eigenvalues of A can only have values less than \lambda. Thus, \mid \lambda_i \mid < 1 \ \forall i.

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