MHB Null and non null eigenvalues (Oinker's question at Yahoo Answers)

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The discussion revolves around finding eigenvalues and eigenvectors of a specific matrix D, which are determined to be 5 and -2, with corresponding eigenvectors (1,1) and (3,-4), respectively. It is established that if 0 is an eigenvalue of a matrix B, then B is not invertible, as this leads to a zero determinant. Conversely, if B is non-invertible, it is proven that 0 must be an eigenvalue. Additionally, for an invertible matrix B, if λ is an eigenvalue, then 1/λ is confirmed to be an eigenvalue of B's inverse. This discussion highlights key properties of eigenvalues in relation to matrix invertibility.
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Here is the question:

(a) Find the eigenvalues of the matrix D below. For each eigenvalue, find a corresponding eigenvector.

D =
2 3
4 1(b) Suppose B is an n×n matrix, and λ = 0 is an eigenvalue of B. Prove that B is not invertible.

(c) Suppose B is an n × n non-invertible matrix. Prove that λ = 0 is an eigenvalue of B.

(d) Suppose B is an invertible n × n matrix, and λ is an eigenvalue of B. Prove that 1 is
an eigenvalue of B−1.

Here is a link to the question:

Matrix Question?? a.b.c.d.? - Yahoo! Answers

I have posted a link there to this topic so the OP can find my response.
 
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Hello Oinker,

$(a)\;$ Eigenvalues of $A=\begin{bmatrix}{2}&{3}\\{4}&{1}\end{bmatrix}$: $$\chi_A(\lambda)=\lambda^2-(\mbox{trace }A)\;\lambda+\det A=\lambda^2-3\lambda-10=0\\\Leftrightarrow \lambda=5\mbox{ (simple) }\vee\;\lambda=-2\mbox{ (simple) }$$ Eigenvectors and corresponding basis: $$\ker(A-5I)\equiv\left \{ \begin{matrix} -3x_1+3x_2=0\\4x_1-4x_2=0\end{matrix}\right.,\qquad B_5=\{(1,1)^T\}$$ $$\ker(A+2I)\equiv\left \{ \begin{matrix} 4x_1+3x_2=0\\4x_1+3x_2=0\end{matrix}\right.,\qquad B_{-2}=\{(3,-4)^T\}$$
$(b)\;$ If $\lambda=0$ is eigenvalue of $B$, then $\det (B-0I)=0$ so, $\det B=0$. As a consequence, $B$ is not invertible.

$(c)\;$ If $B$ is not invertible, $0=\det (B)=\det(B-0I)$ which implies that $\lambda=0$ is an eigenvalue of $B$.

$(d)\;$ According to $(b)$ and $(c)$, if $\lambda$ is an eigenvalue of $B$, necessarily $\lambda\neq 0$ and there exists $0\ne x\in K^n$ suach that $Bx=\lambda x$. Then, $$Bx=\lambda x\Rightarrow B^{-1}(Bx)=B^{-1}(\lambda x)\Rightarrow Ix=\lambda (B^{-1}x)\Rightarrow B^{-1}x=\frac{1}{\lambda}x$$ which implies that $1/\lambda$ is an eigenvalue of $B^{-1}$.
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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