Since the emergence of surface variants with ambient indices, such as the shift tensor and
the components of
the unit normal, we have been faced with the need to expand the definition of the surface covariant
derivative to
such objects. This is an important step in pursuing a complete analytical framework in which
differential operators can be applied to all types of available objects. It is also an important
step in enabling us to work with the components of vectors rather than vectors themselves.
In our quest for such a generalization of the surface covariant derivative, we can be guided by two
closely related landmark relationships: the equation
which serves as the definition of
the curvature tensor ,
and Weingarten's equation
Since
are the components of
and are
the components of , we should expect that the component forms of these
equations read
and
where is the
proper generalization of the surface covariant derivative. We will indeed arrive at the above
equations, but a fair amount of groundwork needs to be laid down first.
5.1The surface covariant derivative for variants with ambient indices
Our ultimate goal is to give a definition of the surface covariant derivative
for variants with arbitrary collections of surface and ambient indices. However, rather than
postulate the definition and subsequently present its properties, we will show how one can arrive
at the definition on their own.
To this end, let us start with a variant that
features a single ambient index, and attempt to discover the proper form for
by assuming that
has two desirable properties: one, that it satisfies the product rule and, two, that it is
metrinilic with respect to the ambient basis . After
all, these are the two properties that are needed in order to transfer analysis from a Euclidean
space to the component space. Indeed, when the covariant derivative is applied to the combination
, it is
by the product rule that it splits into two, i.e.
and it is by the metrinilic property
that the second term vanishes, i.e.
Thus, it is by combination of these
two properties that the covariant basis
cleanly "separates" from the rest of the terms and thus facilitates conversion to component form.
For a more concrete example, consider the conversion from
By the combination of the product
rule and the metrinilic property, we have
and therefore
Thus,
follows by equating the components
of matching vectors. Similarly, with the help of the product rule and the metrinilic property, we
can transition from
Thus, requiring these two properties
is essential for preserving our analytical framework.
It turns out that requiring the product rule and the metrinilic property essentially determined the
surface covariant derivative. Indeed, for a first-order surface variant ,
consider the vector field
Apply the prospective covariant
derivative to
both sides of this identity. Since is a variant of order zero, its covariant derivative must
coincide with its partial derivative, i.e.
As for the contraction , we
have
By the presumed product rule and
metrinilic property for ,
and the well-established product rule for ,
we find
In order to evaluate the derivative ,
represent the function as a composition of the ambient function
and the equation of the surface , i.e.
Then, by the chain rule, we have
Recall that
Thus,
Picking up where we left off,
now becomes
Since , we
find
Finally, matching up the components,
we arrive at the final identity
It is left as an exercise to show
that for a variant
with a subscript, the corresponding expression is
Importantly, note the similarity
between these relationships and the ambient covariant derivative identities
We would like to reiterate that the above analysis was explorative in nature. We merely identified
the properties that we wished the surface covariant derivative to have and, on the basis of those
properties, derived the identity that must
satisfy. We will move forward by using our present experience to postulate a definition of the
surface covariant derivative, for which we will then prove that the desired properties actually
hold.
5.2The surface covariant derivative in full generality
Let us now build on our experience with the ambient covariant derivative and the explorations in
the previous Section to give the following definition for the surface covariant derivative
for a variant
with a representative collection of ambient indices:
But why stop here? Recall that we
already have a definition for the surface covariant derivative for variants with surface indices,
i.e.
Thus, we can roll the two
definitions into one that applies to variants with arbitrary combinations of ambient and surface
indices. For a variant
with a fully representative collection of indices, the definition reads
As usual, this equation is
interpreted as a four-part recipe for each type of index. Many of its applications rely on its
properties rather than the literal definition itself. For example, as we demonstrated
above, this is the case for the two objects of present interest, the shift tensor and
the components of
the unit normal. On the other hand, when the above definition is used in the literal sense,
it is usually being applied to variants with a small number of indices.
The flagship property of the surface covariant derivative is that it produces tensor outputs for
tensor inputs. More specifically, it produces tensors with one surface covariant order greater than
the input. This property, known as the tensor property, is the cornerstone of the surface covariant
derivative because it guarantees that its use produces geometrically meaningful objects in all
combinations of coordinate systems. The demonstration of this property can be carried out according
to the approach we used in Chapter TBD of Introduction to Tensor Calculus for the ambient
covariant derivative .
Generalizing that approach to the surface covariant derivative is left as an important technical
exercise for the reader.
We will now describe all of the remaining key properties of the surface covariant derivative. We
will begin with the chain rule -- a new property that
does not share with its predecessors. The rest of the properties will be familiar from studying the
ambient covariant derivative as well as the limited version of the surface covariant derivative
introduced in Chapter 2.
5.3The chain rule
The surface covariant derivative
applies to surface variants, such as the components of
the unit normal or the shift tensor .
However, the surface variant may well be the surface restriction of a variant defined in the
broader ambient space. For example,
can be applied to the position vector , the ambient covariant basis , or
any other ambient variant. Of course, such variants are also subject to the ambient covariant
derivative and
the role of the chain rule is to relate the two derivatives.
Naturally, ambient variants can have only ambient indices. While the chain rule holds for variants
with arbitrary ambient indicial signatures, we will demonstrate it by a variant
with a representative collection of indices. The chain rule reads
In other words, the surface
covariant derivative is the "orthogonal projection" of the ambient covariant derivative.
The proof of the chain rule requires a straightforward application of the definition of the surface
covariant derivative. Suppose that denotes the dependence of on
the ambient coordinates, while denotes the dependence of its surface
restriction on the surface coordinates. The two functions are related by the equation
where are the equations of the surface.
By definition, we have
The partial derivative
can be obtained by differentiating the identity
with respect to
which yields
Since ,
we have
and, therefore,
Upon factoring out ,
we find
Since the quantity in parentheses is
precisely ,
we have arrived at the identity
which is indeed the relationship we
set out to show.
Note the interesting correspondence between the chain rule and the directional derivative formula
or
This formula states that is the orthogonal projection of onto the ray . Similarly, we can think of as
a "directional derivative" of
along the tangent plane. Correspondingly, is
the orthogonal projection of
onto the tangent plane.
One immediate consequence of the chain rule is the metrinilic property of the surface covariant
derivative with respect to the ambient metrics. Indeed, in order to evaluate , note
that
and, since
we conclude that
Naturally, the same conclusion can
be reached for all other surface metrics. In summary, we have
We will now enumerate all of the remaining properties of the surface covariant derivative starting
with the complete description of the metrinilic property.
5.4The essential properties of the surface covariant derivative
5.4.1The metrinilic property
At the end of the previous Section, we demonstrated the metrinilic property of the surface
covariant derivative with respect to the ambient metrics. Note, however, that the full-fledged
version of the derivative introduced in this Chapter coincides with its predecessor described in
Chapter 2 for objects with surface indices.
Therefore, much like its predecessor, the full-fledged derivative is metrinilic with respect to the
surface metrics, i.e.
Recall, however, that, crucially,
is
not metrinilic with respect to the surface covariant basis , which
is one important aspect in which surfaces differ from Euclidean spaces.
5.4.2The product rule
The surface covariant derivative satisfies the product rule, also known as the Leibniz
rule. For example,
The product rule can be demonstrated
in the same way as the corresponding property for the ambient covariant derivative which was
described in Chapter TBD of Introduction to Tensor Calculus. It is left as an exercise for
the reader.
5.4.3Index juggling "across" the surface covariant derivative
The combination of the metrinilic property and the product rule implies that indices can be juggled
freely "across" the surface covariant derivative. The corresponding property for the ambient
derivative was discussed in Chapter TBD of Introduction to Tensor Calculus.
For ambient indices, we have
while
implies
Similarly, for surface indices, we
have
while
implies
In summary, we are able to juggle indices freely without any regard for the presence of the surface
covariant derivative. Justifying this statement is left as an exercise for the reader.
5.4.4Commutativity with contraction
The surface covariant derivative
commutes with contraction of both surface and ambient indices. The corresponding property for the
ambient derivative was discussed in Section TBD of Introduction to Tensor Calculus.
Consider the expressions
and
Each of these expressions can be
interpreted in two different ways depending on the order in which the covariant derivative and
contraction are applied. However, regardless of the interpretation, the expressions yield the same
results. The proof of this property as left as an exercise for the reader.
5.4.5The commutative property
The surface covariant derivatives commute when applied to variants with ambient indices, i.e.
The assumption that the ambient
space is Euclidean is essential for this property to hold. When the ambient space is not Euclidean,
this commutative property would not hold. The proof of this property, which is based on deriving
the identity
where is
the (vanishing) ambient Riemann-Christoffel tensor, is left as an exercise.
On the other hand, the surface covariant derivatives do not commute for variants with surfaces
indices. We are already familiar with this property from Chapter 2 where we discussed the fact that
where the surface
Riemann-Christoffel tensor
is given by
Note that Chapter 7 in its entirety is devoted to the study of the
Riemann-Christoffel tensor.
5.5The surface covariant derivatives of and
Having established the product rule and the metrinilic properties of the surface covariant
derivative ,
we have retroactively validated the arguments made at the top of this Chapter by which we converted
the vector identities
and
into their component counterparts
and
Like its vector counterpart, the
latter formula is known as Weingarten's equation. It is left as an exercise to derive this
formula by differentiating the explicit expression for the components , i.e.
Finally, note that contracting both sides of the equation
with gives
an explicit expression for the curvature tensor ,
i.e.
Similarly, contracting both sides of
the equation
with
(and, subsequently, renaming into ) yields another explicit expression
for the curvature tensor, i.e.
When the ambient space is referred
to affine coordinates, the covariant derivative reduces to the partial derivative, i.e.
5.6The normal derivative
Consider a scalar field defined in the ambient space. We can
evaluate the directional derivative of along any direction at any point in
the ambient space. However, at the points on the surface, there is a special direction that we
might be particularly interested in -- the normal direction. The directional derivative in the
normal direction is known as the normal derivative.
Recall from Chapter TBD of Introduction to Tensor Calculus, that the directional derivative
of a field along the ray is given by the formula
where is the
gradient of and is the unit vector pointing in the direction of the ray . Thus, at a point on a surface, the
normal derivative of , denoted by
is given by
which, in component form, reads
With the help of the normal derivative, we can decompose the ambient covariant derivative along the tangent and
normal directions. Recall the projection formula
Contracting both sides of this
formula with , we find
Since
we discover that
Contracting both sides with the
ambient contravariant basis ,
we get the corresponding decomposition for the vector gradient , i.e.
which can also be written in the
invariant form
The above equation relates various first-order derivatives of . We will now derive the beautiful
invariant formula
relating second-order derivatives of . Note that each term in this formula
has a straightforward geometric interpretation: is the
surface Laplacian of , is the ambient Laplacian
of , is the second-order
normal derivative (this
requires proof which is left as an exercise), and, finally, is the product of the
mean curvature and
the normal derivative . In terms of the invariant symbols for
the surface Laplacian and for the ambient Laplacian, the above identity can be
written as
In order to prove this identity, recall that, by the chain rule
and therefore
Applying the product rule on the
right, we find
Since
we have
Applying the chain rule again to the
second term, i.e.
yields
Finally, according to the projection formula
we have
Upon multiplying out the parentheses and absorbing the Kronecker delta, we arrive at the final
result
This completes our discussion of the surface covariant derivative and puts us in a position to
continue our exploration of curvature.
5.6.1Exercises
Exercise 5.1Show that for a first-order variant indexed by a subscript, the prospective surface covariant derivative , subject to the product rule and the metrinilic property, must satisfy the identity
Exercise 5.2Use the techniques employed in Chapter TBD of Introduction to Tensor Calculus to demonstrate the tensor property of the surface covariant derivative.
Exercise 5.3Show that the surface covariant derivative satisfies the product rule. For example,
Exercise 5.4Justify each of the index juggling relationships in Section 5.4.3.
Exercise 5.5Show the contraction property of the surface covariant derivative.
Exercise 5.6Show that
where is the ambient Riemann-Christoffel tensor. Since , we can conclude that
i.e. the surface covariant derivatives commute when applied to .
Exercise 5.7Derive Weingarten's equation
by applying the literal definition of the surface covariant derivative to the explicit expression for the components of the normal
Exercise 5.8Show that when the formula
is used for the calculation of the curvature tensor, the term with the surface Christoffel symbol in can be omitted.
Exercise 5.9Show that the collection of second-order surface covariant derivatives is related to the ambient covariant derivatives by the identity
Exercise 5.10Explain why the equation
represents an invalid application of the chain rule.
Problem 5.1Show that
See Problem TBD (second directional derivative) in Introduction to Tensor Calculus.