One has
.
Taking the square root of both sides gives the result.
Equality holds precisely when one is a nonnegative multiple of the other. This is a consequence of the analogous assertion of the next problem.
The first assertion is the triangle inequality. I claim that equality holds precisely when one vector is a non-positive multiple of the other.
If
for some real
, then substituting shows that the inequality
is equivalent to
and clearly equality holds if
a is non-positive. Similarly, one has equality if
for some real
.
Conversely, if equality holds, then
,
and so
. By Theorem 1-1 (2), it follows that
and
are linearly dependent. If
for some real
, then substituting
back into the equality shows that
must be non-positive or
must be 0.
The case where
is treated similarly.
If
, then the inequality to be proved is just
which is just the triangle inequality. On the other hand, if
,
then the result follows from the first case by swapping the roles of
and
.
The inequality follows from Theorem 1-1(3):
Geometrically, if
,
, and
are the vertices of a triangle, then the
inequality says that the length of a side is no larger than the sum of the
lengths of the other two sides.
Theorem 1-1(2) implies the inequality of Riemann sums:
Taking the limit as the mesh approaches 0, one gets the desired inequality.
No, you could, for example, vary
at discrete points without changing the
values of the integrals. If
and
are continuous, then the assertion
is true.
In fact, suppose that for each
, there is an
with
.
Then the inequality holds true in an open neighborhood of
since
and
are
continuous. So
since the integrand is always
non-negative and is positive on some subinterval of
. Expanding out
gives
for all
. Since the quadratic has no solutions, it must be that its
discriminant is negative.
Let
,
,
and
for all
in
for
. Then part (a) gives the inequality of Theorem 1-1 (2).
Note, however, that the equality condition does not follow from (a).
If
is inner product preserving, then one has by Theorem 1-1 (4):
Similarly, if
is norm preserving, then the polarization identity together
with the linearity of T give:
.
Let
be norm preserving. Then
implies
, i.e. the kernel
of
is trivial. So T is 1-1. Since
is a 1-1 linear map of a finite
dimensional vector space into itself, it follows that
is also onto. In
particular,
has an inverse. Further, given
, there is a
with
, and so
, since
is
norm preserving. Thus
is norm preserving, and hence also inner
product preserving.
Assume
is norm preserving. By Problem 1-7,
is inner product preserving.
So
.
The assertion is false. For example, if
,
,
,
, and
, then
. Now,
,
but
showing
that T is not angle preserving.
To correct the situation, add the condition that the
be pairwise
orthogonal, i.e.
for all
. Using bilinearity,
this means that:
because
all the cross terms are zero.
Suppose all the
are equal in absolute value. Then one has
because all the
are equal and
cancel out. So, this condition suffices to make
be angle preserving.
Now suppose that
for some
and
and that
. Then
since
.
So, this condition suffices to make
not be angle preserving.
The angle preserving
are precisely those which can be expressed in the
form
where U is angle preserving of the kind in part (b), V is
norm preserving, and the operation is functional composition.
Clearly, any
of this form is angle preserving as the composition of two
angle preserving linear transformations is angle preserving. For the
converse, suppose that
is angle preserving. Let
be
an orthogonal basis of
. Define
to be the linear
transformation such that
for each
.
Since the
are pairwise orthogonal and
is angle preserving, the
are also pairwise orthogonal. In particular,
because the cross terms
all cancel out. This proves that
is norm preserving. Now define
to
be the linear transformation
. Then clearly
and
is angle preserving because it is the composition of two angle preserving
maps. Further,
maps each
to a scalar multiple of itself; so
is a map of the type in part (b). This completes the characterization.
The transformation
is 1-1 by Cramer's Rule because the determinant of
its matrix is 1. Further,
is norm preserving since
by the Pythagorean Theorem. By Problem 8(a), it follows that
is angle
preserving.
If
, then one has
.
Further, since
is norm preserving,
. By the definition
of angle, it follows that
.
Let
be the maximum of the absolute values of the entries in the matrix of
and
. One has
. (Correction: Bound should be square root of n times mN.)
One needs to verify the trivial results that (a)
is a linear
tranformation and (b)
. These
follow from bilinearity; the proofs
are omitted. Together these imply that
is a linear transformation.
Since
for
,
has no non-zero vectors
in its kernel and so is 1-1. Since the dual space has dimension n, it follows
that
is also onto. This proves the last assertion.
By bilinearity of the inner product, one has for perpendicular
and
: