[Math] How to prove inverse of a linear operator is diagonalizable using concept of eigenspaces

diagonalizationeigenvalues-eigenvectorslinear algebra

Let T be an invertible linear operator on a finite dimensional vector space V.

Given for any eigenvalue $\alpha$ of T, $\alpha$^(-1) is an eigenvalue of T^(-1). I first proved that the eigenspace of T corresponding to eigenvalue $\alpha$ is the same as the eigenspace of T^(-1) corresponding to $\alpha$^(-1).
Now I need to prove that if T is diagonalizable, then T^(-1) is also diagonalizable.

I feel that given that T is invertible and diagonalizable it has a basis $\beta$ consisting of distinct eigenvectors of T. This is where I am stuck. Would I be right in saying that T^(-1) will also have the same basis $\beta$? And hence prove it is diagonalizable?
I only know that the eigenspaces are same for both the operators.

Best Answer

Your proof is basically correct. Since $0$ is not an eigenvector of $T$ (if this is not obvious to you, you should think about proving it), every eigenvector of $T$ is also an eigenvector of $T^{-1}$. There exists by hypothesis a basis consisting of eigenvectors for $T$, and that basis is also a basis of eigenvectors for$~T^{-1}$.

It depends on how diagonalisable was defined for you. For me it is defined as admitting a basis consisting of eigenvectors. You could also define it by saying that the sum of all eigenspaces is the whole space. Then again, since the eigenspaces of $T$ and of $T^{-1}$ are in fact the same, it is obvious that $T$ diagonalisable implies $T^{-1}$ is. This is not really different, but at least the concept of eigenspaces is mentioned.

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