§ Cayley hamilton for 2x2 matrices in sage via AG
- I want to 'implement' the zariski based proof for cayley hamilton in SAGE and show that it works by checking the computations scheme-theoretically.
- Let's work through the proof by hand. Take a 2x2 matrix
[a, b; c, d]
. - The charpoly is
|[a-l; b; c; d-l]| = 0
, which is p(l) = (a-l)(d-l) - bc = 0
- This simplified is
p(l) = l^2 - (a + d) l + ad - bc = 0
. - Now, let's plug in
l = [a; b; c; d]
to get the matrix eqn -
[a;b;c;d]^2 - (a + d)[a;b;c;d] + [ad - bc; 0; 0; ad - bc] = 0
. - The square is going to be
[a^2 +]
- Let
X
be the set of (a, b, c, d)
such that the matrices [a;b;c;d]
satisfy their only charpoly. - Consider the subset
U
of the set (a, b, c, d)
such that the matrix [a;b;c;d]
has distinct eigenvalues. - For any matrix with distinct eigenvalues, it is easy to show that they satisfy their charpoly.
- First see that diagonal matrices satisfy their charpoly by direct computation:
[a;0;0;b]
has eigenvalues (a, b)
. Charpoly is l^2 - l(a + b) + ab
. Plugging in the matrix, we get [a^2;0;0;b^2] - [a(a+b);0;0;b(a+b)] + [ab;0;0;ab]
which cancels out to 0
. - Then note that similar matrices have equal charpoly, so start with
|(λI - VAV')| = 0
. rewrite as (VλIV' - VAV') = 0
, which is V(λI - A)V' = 0
, which is the same λI - A = 0
. - Thus, this means that a matrix with distinct eigenvalues, which is similar to a diagonal matrix (by change of basis), has a charpoly that satisfies cayley hamilton.
- Thus, the set of matrices with distinct eigenvalues,
U
is a subset of X
.
- However, it is not sufficient to show that the system of equations has an infinite set of solutions.
- For example,
xy = 0
has infinite solutions (x=0, y=k)
and (x=l, y=0)
, but that does not mean that it is identically zero. - This is in stark contrast to the 1D case, where a polynomial
p(x) = 0
having infinite zeroes means that it must be the zero polynomial. - Thus, we are forced to look deeper into the structure of solution sets of polynomials, and we need to come up with the notion of irreducibility.
- See that the space
K^4
is irreducible, where K
is the field from which we draw coefficients for our matrix.
- Next, we note that
X
is a closed subset of k^4
since it's defined by the zero set of the polynomial equations. - We note that
U
is an open subset of k^4
since it's defined as the non-zero set of the discriminant of the charpoly! (ie, we want non-repeated roots) - Also note that
U
is trivially non-empty, since it has eg. all the diagonal matrices with distinct eigenvalues. - So we have a closed subset
X
of k^4
, with a non-empty open subset U
inside it. - But now, note that the closure of
U
must lie in X
, since X
is a closed set, and the closure U
of the subset of a closed set must lie in X
. - Then see that since the space is irreducible, the closure of
U
(an open) must be the whole space. - This means that all matrices satisfy cayley hamilton!