Understanding Eigenvectors: Solving for Eigenvalues and Corresponding Vectors

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squenshl
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Homework Statement
Let ##\mathbb{R}^3\mapsto \mathbb{R}^3## be given by $$T\begin{pmatrix}
x \\
y \\
z
\end{pmatrix} := \begin{pmatrix}
x+y-2z \\
2x-2z \\
y-x
\end{pmatrix}.$$

1. Give a basis of eigenvectors for ##\text{ker}(T)##.
2. Give a basis of eigenvectors for ##\text{ran}(T)##.
Relevant Equations
None
Okay so I found the eigenvalues to be ##\lambda = 0,-1,2## with corresponding eigenvectors ##v =
\begin{pmatrix}
1 \\
1 \\
1
\end{pmatrix},
\begin{pmatrix}
1 \\
0 \\
1
\end{pmatrix},
\begin{pmatrix}
1 \\
1 \\
0
\end{pmatrix}
##.
Not sure what to do next. Thanks!
 
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squenshl said:
1. Give a basis of eigenvectors for ##\text{ker}(T)##.
2. Give a basis of eigenvectors for ##\text{ran}(T)##.
I don't think it makes sense to talk about a basis of eigenvectors for ##\text{ker}(T)## and ##\text{ran}(T)##.
It's more usual for a problem to ask for a basis for each of these subspaces.
 
Ok so the kernel of ##T## is ##(x,y,z)## such that ##T(x,y,z)=0## & this only occurs when we have ## (1,1,1)## so I guess that is the basis for the kernel right?
 
So the basis for the range of ##T## are the other two eigenvectors.
 
Yes. But ##(1,1,1)## is not the only vector, all multiples are as well sent to zero. If the kernel is one dimensional, then the range is two dimensional. The other two eigenvectors are in the range. Now do they span the range? Or more generally: Are eigenvectors to distinct eigenvalues always linearly independent, and why?
 
Right the basis for the kernel is the span of ##(1,1,1)##. Yes eigenvectors are linearly independent so they do span the range thanks!
 
squenshl said:
Right the basis for the kernel is the span of (1,1,1).
A basis for the kernel is the vector <1, 1, 1>, not the span of this vector. ##\text{Ker} (T)## is the set of all constant multiples of <1, 1, 1>; i.e., the span of <1, 1, 1>.