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Friedberg, et al.  Linear Algebra, 2nd Edition

My question pertains to Exercise 24. My thinking was that if $T$ is diagonalizable with a particular eigenbasis, say: $$\{ \, x_1, x_2 \ldots x_n \ldots \, \}$$ Then, any nontrivial subspace is spanned by some subset of the eigenbasis. So, I don't see why the condition of $T$-invariance is needed. Can you kindly explain?

The proof using the hint given is as follows:

Suppose that $W$ is a nontrivial $T$-invariant subspace of $V$. Any $w \in W$ can be written as $w = a_1x_1 + a_2x_2 \ldots + a_nx_n$. If we group together the eigenvectors corresponding to the same eigenvalue, we have: $$w = y_1 + y_2 \ldots + y_m$$ The spanning set of $\{ \, y_1, y_2 \ldots y_m \, \}$ is finite dimensional and $T$-invariant, so the result from Exercise 23 applies; $w$ is a linear combination of eigenvectors of $T$. This proves that $W$ is spanned by eigenvectors of $T$, and from the spanning set we can pick out a basis for $T|_W$.

Andy Tam
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    You need $T$-invariance because without it, $T$ doesn't restrict to a linear operator. To say that $T$ is a linear operator on a space $W$ means that $T$ takes inputs from $W$ and produces outputs that are again in $W$ (i.e., $T:W \longrightarrow W$.) If the codomain of a linear transformation doesn't agree with it's domain, then it doesn't make sense to talk about diagonlizability. – PeterJL Aug 30 '16 at 04:40
  • There are various proofs at https://math.stackexchange.com/questions/956424 – Bart Michels Jun 03 '18 at 16:12
  • The "canonical duplicate" of this question, with great answers, is https://math.stackexchange.com/q/62338/96384. – Torsten Schoeneberg Sep 15 '21 at 17:17

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