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Let be an endomorphism of an -dimensional vector space .
Definitions. We define the minimal polynomial, , to be the unique monic polynomial of minimal degree such that
. We say that is a zero polynomial for if is the zero endomorphism.
Note that the minimal polynomial exists by virtue of the Cayley-Hamilton theorem, which provides a zero polynomial for .
Properties. Firstly,
is a vector space of dimension . Therefore the vectors,
, are linearly dependant. So there are coefficients, not all zero such that
. We conclude that a non-trivial zero polynomial for exists. We take to be a zero polynomial for of minimal degree with leading coefficient one.
Lemma: If is a zero polynomial for then
.
Proof. By the division algorithm for polynomials,
 with
 . We note that  is also a zero polynomial for  and by minimality of  , must be just 0. Thus we have shown
 . 
The minimal polynomial has a number of interesting properties:
- The roots are exactly the eigenvalues of the endomorphism
- If the minimal polynomial of
splits into linear factors then is upper-triangular with respect to some basis
- The minimal polynomial of
splits into distinct linear factors (i.e. no repeated roots) if and only if is diagonal with respect to some basis.
It is then a simple corollary of the fundamental theorem of algebra that every endomorphism of a finite dimensional vector space over
may be upper-triangularized.
The minimal polynomial is intimately related to the characteristic polynomial for . For let be the characteristc polynomial. Since
, we have by the above lemma that
. It is also a fact that the eigenvalues of are exactly the roots of . So when split into linear factors the only difference between and is the algebraic multiplicity of the roots.
In general they may not be the same - for example any diagonal matrix with repeated eigenvalues.
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