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Let $V\neq\{0\}$ be a finite-dimensional vector space over a field $F$ and let $\alpha \in \text{End}(V)$.

Suppose that $\lambda$ is an eigenvalue of $\alpha$ with multiplicity $r$ as a root of the minimal polynomial of $\alpha$.

I want to show that $r$ is the least positive integer s.t. $\ker(\alpha-\lambda\iota)^r=\ker(\alpha-\lambda\iota)^R$ for all $R\geq r$.

I have been able to show that $r=\dim V$ satisfies this property but I can't seem to get this sharper result. Any pointers/hints would be very gratefully received!

Many thanks.

1 Answers1

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Lemma: $\ker(\beta^{n})\subseteq \ker(\beta^{n+1})$. I will take this for granted, unless you want a proof.

Now, write the minimal polynomial of $\alpha$ as $$ p(t) = (t - \lambda)^rq(t) $$ where $(t - \lambda) \not \mid q(t)$. Now, since $p(\alpha) = 0$, we have $(\alpha - \lambda I)^r q(\alpha) = 0$, which is to say that $q(\alpha)V \subset \ker(\alpha - \lambda I)^r$.

One direction:

Now, suppose there were an $r'<r$ with $\ker(a -\lambda I)^{r'} = \ker(a - \lambda I)^r$. It would follow that $q(\alpha)V \subset \ker(\alpha - \lambda I)^{r'}$, which would imply that $$ (\alpha - \lambda I)^{r'} q(\alpha) = 0 $$ which contradicts our definition of a minimal polynomial.

The other direction:

Now, suppose that there were some $R > r$ with $\ker(A - \lambda I)^r \neq \ker(A - \lambda I)^R$. By our lemma, we deduce that $\ker(A - \lambda I)^r \subsetneq \ker(A - \lambda I)^R$. So, there is a vector $v$ such that $(A - \lambda I)^{r'}v = w \neq 0$, but $(A - \lambda I)^{r'+1} v = (A - \lambda I)w= 0$ for some $r' \geq r$.

However, we know that $q(\alpha)(\alpha - \lambda I)^r = 0$, which means that $$ q(\alpha) w = p(\alpha)v = 0v = 0 $$ That is, $w \in \ker(q(\alpha))$. We also have $w \in \ker(A - \lambda I)$.

That is, $\alpha w = \lambda w$, and $q(\alpha)w = q(\lambda) w = 0$. Thus, we conclude that $q(\lambda) = 0$, which is a contradiction of our definition of $q(t)$.

The conclusion follows.


Note that if we may use Jordan canonical form here, this amounts to a proof by computation.

Ben Grossmann
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