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A scalar quantity is invariant under all possible rotational transformations.
The individual components of a vector are not scalars because they change under
transformation. Can we form a scalar out of some combination of the components
of one, or more, vectors? Suppose that we were to define the
``ampersand'' product,
 |
(16) |
for general vectors
and
. Is
invariant under transformation, as must be the case if it is a scalar number?
Let us consider an example. Suppose that
and
. It is easily seen that
. Let
us now rotate the basis through
about the
-axis. In the new
basis,
and
, giving
. Clearly,
is not invariant under rotational transformation, so
the above definition is a bad one.
Consider, now,
the dot product or scalar product,
 |
(17) |
Let us rotate the basis though
degrees about the
-axis. According to
Eqs. (10)-(12), in the new basis
takes the form
Thus,
is invariant under rotation about the
-axis. It can easily
be shown that it is also invariant under rotation about the
- and
-axes.
Clearly,
is a true scalar, so the above definition is
a good one. Incidentally,
is the only
simple combination of
the components of two vectors which transforms like a scalar. It is easily
shown that the dot product is commutative and distributive:
The associative property is meaningless for the dot product, because we cannot
have
, since
is scalar.
We have shown that the dot product
is coordinate independent.
But what is the physical significance of this? Consider the special case
where
. Clearly,
 |
(20) |
if
is the position vector of
relative to the origin
.
So, the invariance of
is equivalent to the invariance
of the length, or magnitude, of vector
under transformation. The length of
vector
is usually denoted
(``the modulus of
'') or sometimes
just
, so
 |
(21) |
Figure 5:
A vector triangle.
 |
Let us now investigate the general case. The length squared of
in Fig. 5 is
 |
(22) |
However, according to the ``cosine rule'' of trigonometry,
 |
(23) |
where
denotes the length of side
. It follows that
 |
(24) |
Clearly, the invariance of
under transformation is equivalent
to the invariance of the angle subtended between the two vectors. Note that
if
then either
,
, or the vectors
and
are mutually perpendicular. The angle
subtended between two vectors
can easily be obtained from the dot product: i.e.,
 |
(25) |
Note that
, etc., where
is
the angle subtended between vector
and the
-axis.
The work
performed by a constant force
which moves an object through a displacement
is the product of the magnitude of
times the displacement in the direction
of
. So, if the angle subtended between
and
is
then
 |
(26) |
Next: The Vector Product
Up: Vectors
Previous: Vector Area
Richard Fitzpatrick
2007-07-14