We know that ( 1 , 0 , 0 ) , ( 0 , 1 , 0 ) , ( 0 , 0 , 1 ) (1,0,0),(0,1,0),(0,0,1) ( 1 , 0 , 0 ) , ( 0 , 1 , 0 ) , ( 0 , 0 , 1 ) is the standard basis of R 3 R^3 R 3 .
Given T ( z 1 , z 2 , z 3 ) = ( 2 z 2 , 0 , 5 z 3 ) T(z_1,z_2,z_3) = ( 2z_2, 0, 5z_3) T ( z 1 , z 2 , z 3 ) = ( 2 z 2 , 0 , 5 z 3 ) .
Now, T ( 1 , 0 , 0 ) = ( 0 , 0 , 0 ) T(1,0,0) =(0,0,0) T ( 1 , 0 , 0 ) = ( 0 , 0 , 0 ) , T ( 0 , 1 , 0 ) = ( 2 , 0 , 0 ) T(0,1,0) =(2,0,0) T ( 0 , 1 , 0 ) = ( 2 , 0 , 0 ) and T ( 0 , 0 , 1 ) = ( 0 , 0 , 5 ) T(0,0,1)=(0,0,5) T ( 0 , 0 , 1 ) = ( 0 , 0 , 5 ) .
So, Matrix T = [ 0 2 0 0 0 0 0 0 5 ] T = \begin{bmatrix} 0 & 2 &0\\ 0 & 0 & 0 \\ 0 & 0 & 5 \end{bmatrix} T = ⎣ ⎡ 0 0 0 2 0 0 0 0 5 ⎦ ⎤ .
Since, T is upper-triangular Matrix, so eigen-values of T are 0 , 0 , 5 0,0,5 0 , 0 , 5 .
Eigenvector of T with respect to eigen-value 0 :
[ T − 0 I ] X = O ⟹ [ 0 2 0 0 0 0 0 0 5 ] [ x 1 x 2 x 3 ] = [ 0 0 0 ] [T -0I]X = O \implies \begin{bmatrix} 0 & 2 &0\\ 0 & 0 & 0 \\ 0 & 0 & 5 \end{bmatrix} \begin{bmatrix} x_1 \\ x_2 \\ x_3 \end{bmatrix} =
\begin{bmatrix} 0 \\ 0 \\ 0 \end{bmatrix} [ T − 0 I ] X = O ⟹ ⎣ ⎡ 0 0 0 2 0 0 0 0 5 ⎦ ⎤ ⎣ ⎡ x 1 x 2 x 3 ⎦ ⎤ = ⎣ ⎡ 0 0 0 ⎦ ⎤
⟹ x 2 = 0 , x 3 = 0 \implies x_2 = 0, x_3 = 0 ⟹ x 2 = 0 , x 3 = 0 and let x 1 = k x_1 = k x 1 = k
So, eigenvector is [ 1 0 0 ] t [ 1 \ 0 \ 0 ]^t [ 1 0 0 ] t .
Eigenvalue 0 has arithmetic multiplicity 2, but rank of T is 2, so geometric multiplicity corresponding to 0 is = n − ρ ( T ) = 3 − 2 = 1 = n - \rho(T ) = 3- 2 = 1 = n − ρ ( T ) = 3 − 2 = 1 . So, corresponding to eigenvalue 0, only one eigenvector exists and calculated above.
Eigenvector of T with respect to eigen-value 5 :
[ T − 5 I ] X = O ⟹ [ − 5 2 0 0 − 5 0 0 0 0 ] [ x 1 x 2 x 3 ] = [ 0 0 0 ] [T -5I]X = O \implies \begin{bmatrix} -5 & 2 &0\\ 0 & -5 & 0 \\ 0 & 0 & 0\end{bmatrix} \begin{bmatrix} x_1 \\ x_2 \\ x_3 \end{bmatrix} =
\begin{bmatrix} 0 \\ 0 \\ 0 \end{bmatrix} [ T − 5 I ] X = O ⟹ ⎣ ⎡ − 5 0 0 2 − 5 0 0 0 0 ⎦ ⎤ ⎣ ⎡ x 1 x 2 x 3 ⎦ ⎤ = ⎣ ⎡ 0 0 0 ⎦ ⎤
⟹ x 1 = 0 , x 2 = 0 \implies x_1 = 0, x_2 = 0 ⟹ x 1 = 0 , x 2 = 0 and let x 3 = k x_3 = k x 3 = k
So, eigenvector is [ 0 0 1 ] t [ 0 \ 0 \ 1 ]^t [ 0 0 1 ] t .
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