Write , with . The minimal polynomial means and . Choose with . For each , set . ThenThus . Also because applying to zero still gives zero. Therefore the kernel dimensions of powers of a nilpotent map increase strictly until the nilpotency index:The same reasoning covers , when the nilpotent linear map is zero on a nonzero vector space.
Put , including . The restriction of to has kernel , so the rank-nullity theorem givesLikewise has kernel and hence image dimension . But , which impliesComparing dimensions yields the required concavity of the kernel dimensions of powers of a nilpotent map:
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