This set is due Monday, April 11. The questions in problem 2 are required from everybody, and graduate students should also work on problem 1. (Of course, it would make me happier if everybody attempts problem 1 as well.)
1. Let be a real finite-dimensional, inner product space. For
, define
,
and
.
a. Prove that is a norm on the vector space
. In particular,
for all
. Also, prove that
for all
b. Prove that for all
. Is
also a norm?
c. Prove that for any there are vectors
of norm 1 with
and
.
d. Suppose now that is such that
. Prove (without appealing to the fundamental theorem of algebra and without using determinants) that
admits an eigenvalue
(real) with eigenvector
as in item c and, in fact,
.
e. Prove that for any , we have
.
f. Suppose that is self-adjoint. Check that so is
and that
. In particular, this gives a proof that squares of self-adjoint operators on real vector spaces admit eigenvalues that does not use the fundamental theorem of algebra. Check that the eigenvalues of
are non-negative.
g. Again, let be self-adjoint. (So we know there is an orthonormal basis for
consisting of eigenvectors of
) Assume also that
is invertible, that there is a unique eigenvalue
of
of largest absolute value, and that this
satisfies
. Let
be an eigenvector of
with eigenvalue
and such that
. Starting with a vector
of norm 1 (arbitrary except for the fact that
is not orthogonal to
), define a sequence
of unit vectors by setting
(and note we are not dividing by 0, so these vectors are well defined). Also, define a sequence of numbers by setting
Prove that there is a sequence with each
equal to 1 or
and such that
and
as .
2. Solve problems 7.1, 7.3, 7.6, 7.7, 7.11, 7.14 from the book.
Note: In problem 1.f, the eigenvalues of are precisely the squares of the eigenvalues of
, but at the moment I do not have a way of showing this directly. As extra-credit, show without appealing to the fundamental theorem of algebra (and without using determinants, of course) that
must have a real eigenvalue.