1. Introduction
Differentiability has almost always been considered in mathematical analysis only for functions
with an open domain
(see [
1,
2,
3]). In the paper [
4], the authors made a natural generalization of differentiability by defining it at some non-inner points of the functional domain, which include not only the boundary points of the domain but also all points where the notion of differentiability is meaningful (points admitting neighborhood ray, i.e., points that allow a segment line beginning in them and belonging to the domain). They were motivated by some problems and shortcomings encountered in some applications of the traditional approach to differentiability. In the literature, there are some other generalizations and approaches to differentiability (derivability) such as the fractional derivative [
5] or the derivative at the endpoints of a segment [
6]. However, the generalization given in [
4] allows applications in all areas where standard differentiability can be applied. Since some unexpected phenomena may appear in this generalized approach to differentiability in special cases (such as the non-uniqueness of the differential in some special cases, a function discontinuity at a point where a function is differentiable), the results published in [
4] are also interesting from a purely mathematical point of view. Therefore, it is natural and challenging to extend the well-known concept of differentiability with this extended and generalized approach. In this paper, we present some new results from this research, the first results of which have been published in [
4].
The focus of this work is the mapping
,
, which associates with each point
a unique differential (a linear operator)
, where
denotes the vector space of all linear operators
. To ensure the correctness of this mapping, some conditions are imposed on the set
X. To ensure the existence of the differential of the function
f at each point
, we assume that each point admits an nbd ray into
X and that the function
f is differentiable on
X. To ensure the uniqueness of the differential of the function
f at each point, we assume that its linearization space at each point
is equal to
. A reminder of all these notions, already introduced in [
4], is given in the preliminaries section. The main goal of this paper is to establish the notion of continuous differentiability, i.e., continuity of the mapping
. However, the continuity of
can be regarded as reasonable only if we endow the vector space
of linear operators with a topological structure. In order to do that, we first introduce the operator norm to obtain
as normed vector space. In addition to continuously differentiable functions, we consider functions of the class
This notion is somewhat stronger than continuous differentiability, and it avoids possible pathologies such as the discontinuity of continuously differentiable functions. In the last section, we present a characterization of continuous differentiability. We also establish a sufficient condition for the differentiability of function at a point. It is widely known that the continuity of partial derivatives at interior points of the function domain implies the differentiability of the functions at these points. However, here, we provide a more general and stronger result with a broader possible application. We have proved that the continuity of the derivatives at some not necessarily interior points of the functional domain in the direction of
n linear independent vectors implies (continuous) differentiability.
2. Preliminaries
In this section, we give an overview of the main concepts, notations, and statements needed for the generalized approach to differentiability that we will use in this paper. Since the reader can find all of these with much more details, examples, and explanations in [
4], we will list them here only briefly to complete this work. We say that a point
admits a neighborhood ray (or simply admits an nbd ray) in
X if there exists
such that the line segment
is contained in
X. For a given
, if there exists
such that
, then we say that the point
admits a neighborhood ray in
X in the direction of
V. The set
is said to be the set of linear contributions at
in
X, and its linear hull
is called the linearization space at
with respect to
X. In addition,
is also called the linearization space of the function
f at the point
whenever the function
is given.
The function
is said to be differentiable at the point
admitting an nbd ray in
X if
for some linear operator
. If such a linear operator exists, we call it the differential of the function
f at the point
. Every linear operator
that coincides with
A on the subspace
is the differential of the function
f at
. Therefore, the differential of a function at a point need not be unique, but they all agree on
. However, if
, then it is unique and is denoted by
.
Let and be a point admitting an nbd ray in X. A neighborhood U of the point in X is said to be a raylike neighborhood of the point in X provided holds for every . If there exists at least one raylike nbd in X of the point we say that the point admits a raylike nbd in X. If is differentiable at admitting a raylike nbd in X, then it is also continuous at . Differentiability does not imply continuity in general.
Since every point of an open set in admits a raylike nbd in it, all phenomena and pathologies listed before are not possible for functions defined on an open domain.
Let
,
be a point admitting an nbd ray in
X in the direction of the vector
. The set
is said to be the set of linear contributions at
in the direction of
V into
X. If the limit
exists, we call it the derivative at
of the function
in the direction of
V and denote it by
. The derivative at
in the direction of the
i-th basis vector of the standard ordered basis for
(
) is called the i-th partial derivative of
f at
and is denoted by
Let be a point admitting an nbd ray in X in the direction of . If is differentiable at , then f has a derivative at in the direction of V and the value of each differential of the function f at at V is equal to . Especially, if then .
A function
,
is differentiable at a point
if and only if all its coordinate functions
,
(
denotes the projection map) are differentiable at
. If
admits an nbd ray in
X in the direction of
then the linear operator
in the pair of standard bases is represented by the well-known Jacobi matrix determined by the numbers
,
. If
admits an nbd ray in
X in the direction of
n linearly independent vectors
, then
is represented by the following matrix
in the pair of ordered bases
and
.
We end this section with two theorems (Theorem 6 and Theorem 9 in [
4]), which we will hereinafter use.
Theorem 1. Let , , , and . Let be a point admitting a raylike nbd in X, and let be the point admitting a raylike nbd in Y. If f is differentiable at and g is differentiable at , then the composition is differentiable at and is its differential at the point , where and are differentials at the points and of the functions f and g, respectively.
Theorem 2. Let , and be a point admitting an nbd ray in The function f is differentiable at if and only if is differentiable at for every . A linear operator is the differential of the function f at if and only if is the differential of the function at for .
3. Vector Space
In this section, we study the space of all linear operators . As we will show, this space can be organized in the structure of a normed vector space. Since a differential of a function at a point is a linear operator, obtaining a topological structure (induced by the norm) on is the necessary step so that the continuity of the mapping , can be regarded as reasonable for a function , which is differentiable at every point of its domain and whose linearization space is at every .
The well-known fact in linear algebra (see, e.g., [
7,
8,
9]) is that the sets
and
(set of all real
matrices) are vector spaces. We recall that every linear operator on every basis
of
is uniquely determined by its action. If for a linear operator
holds
where
is a basis of
, then
A can be represented as a linear combination
of the linear operators
, defined as follows
Therefore, the set
constitutes a basis of the vector space
. The set
consisting of all matrices having all 0 values except the value 1 at the position
constitutes a basis of vector space
. Indeed, for any matrix
it holds
For every linear operator
, let us denote by
its matrix representation in the ordered pair of bases
and
. This defines a mapping
of vector spaces which bijectively maps the basis
to the basis
Consequently,
is an isomorphism of vector spaces ([
7]).
Furthermore, a function which associates with the vector
of a canonical basis
of
the matrix
, for all
induces a unique isomorphism
that maps the matrix
to the vector
We will now introduce a norm on the space
. One way to do this is quite simple and natural. It is suffices to inherit the Euclidean norm
given on
by this formula
. Since
and
are isomorphisms, it is trivial to check that this indeed defines a norm. However, a standard norm on the space
, usually studied in functional analysis (see [
10,
11,
12]), is called the operator norm and is defined as follows:
Properties of the operator norm can be found in [
10,
11,
12,
13], but for the sake of completeness of this paper, we bring the following proposition omitting its proof (see Proposition 3, Chapter 6. in [
13].)
Proposition 1. For every pair of linear operators and , it holds
Theorem 3. A composition of linear operators is a continuous function.
Proof. Let
g denote linear operators composition
,
. Let
be an arbitrary point of its domain and let
. Notice that for every
, the following equality holds
By Proposition 1 and triangle inequality, it follows
Let
and let
be any point such that
where
d denotes a standard product metric. It follows
and
and consequently
which proves that the function
g is continuous at the point
. □
It is widely known that all norms given on a finite-dimensional real vector space are equivalent, i.e., all induced topologies are the same (see Theorem 1.21. in [
11,
14]).
Corollary 1. All norms given on the space induce the same topology structure.
Corollary 2. Let and be bases of spaces and respectively. The mapping between the topological space whose topology is induced by the operator norm and the Euclidean space whose topology is induced by the Euclidean norm is a homeomorphism.
Proof. If we take on the space
the norm
defined by the Formula (
1), then the mapping
is the isometry between metric spaces
and
whose metrics are induced by the norms
and
, respectively. Consequently,
is a homeomorphism between induced topological spaces
and
(induced metrics define topologies on them). By Corollary 1, topological space
endowed with the topology induced by the metric
coincides with the topological space
endowed with the topology induced by the metric
Therefore, by taking the latest topological space, the mappings and remain continuous, which proves the statement. □
Corollary 3. For every , the function which maps every linear operator in its coordinate function , ( is the projection mapping) is continuous.
Proof. The function
can be viewed as:
The statement now follows from Theorem 3. □
Corollary 4. Let X be a topological space. A function is continuous if and only if is continuous, for every .
Proof. Notice that the continuity of the function is equivalent to the continuity of the function f, , which is equivalent to the continuity of the function . Since and are homeomorphisms (Corollary 2), it follows that is continuous. The necessity is the consequence of the previous corollary. □
Corollary 5. Let X be a topological space. If the functions are continuous, then the function is continuous, for every
4. Continuously Differentiable Functions
The main goal of this section is to explore the nature of the mapping for a differentiable function where is the set in which each point admits an nbd ray in it and , for every . The mapping associates with each point the unique differential belonging to . Since is endowed with a topological structure induced by the operator norm and X already has a topological structure inherited from the Euclidean space , it makes sense to consider the continuity of . If is a continuous mapping, then it means that f is a continuously differentiable function. However, for such a function, some undesirable phenomena might occur (see Example 2). To avoid pathologies (such as the discontinuity of continuously differentiable functions), we will strengthen the condition of continuous differentiability to obtain the notion of class functions. These functions are considered the most beautiful in this context.
Definition 1. Let , be a function and let every point admit an nbd ray in X such that . The function f is said to be continuously differentiable provided it is differentiable on X and the mapping is continuous. If in addition every point admits a raylike nbd in X, then we say that f is of the class . The set of all functions of the class is denoted by or simply in the case .
Example 1. Since the differential of the linear operator f at each point is equal to the same linear operator, the mapping from the previous definition is constant and thus continuous. Therefore, every linear operator is a function of class . For the same reason, every constant function on the set X is continuously differentiable as in the previous definition.
Since every point P of an open set admits a raylike nbd in it and the linearization space at P with respect to X is equal to , it holds:
Corollary 6. Let be an open set. A function is continuously differentiable if and only if it is a function of the class .
The notion of continuous differentiability coincides with the notion of “being of class ” for functions with an open domain. In this case, the two terms are synonymous, which can be found in almost all university textbooks dealing with the traditional approach to differentiability. However, for functions with a non-open domain, these terms differ, as we can see in the following example.
Example 2. Let , , be points of Let us denote by a compact set from bounded by lengths , and , . Let be a compact set from bounded by lengths , , and . Let . Let us define the function where and . The function f is differentiable and the differential is unique at every point in its domain since the linearization space of the function f at every point is equal to . Since for every , the function is continuous, so f is continuously differentiable. However, all the points are the points of discontinuity of the function , thus it is not of class . If we transform the function f to be continuous by setting for each , it would still not be of class because points of length do not admit a raylike nbd in X.
Proposition 2. Let and be the sets for which each point admits a raylike nbd in X, i.e., in Y, and let , for every and , for every . If the function is of class , then the restriction is a function of class
Proof. The statement follows from the continuity of the function
as a restriction of the continuous function
and the equality
for every
(Proposition 3 in [
4]). □
In the context of continuous differentiability on the dual space , we can use either the operator norm or the induced norm after identifying the linear operator A with a vector where and is any pair of ordered space bases and , respectively (Corollary 1).
In the case of
for the differentiable function
, a mapping
is defined by the association
i.e., by the function
Note that a function
is a homeomorphism (Corollary 2); thus, the mapping
can be identified with the association
Therefore, it holds
. Consequently, in addition to the notion of continuous differentiability of such functions, we use the notion of continuous derivability of the function
, which denotes a differentiable function whose derivative function
is continuous. Since by Theorem 7 in [
4] the derivability of the function
f is equivalent to differentiability, it follows from Corollary 2 in [
4] that:
Corollary 7. Let be the set on which every point admits an nbd ray. The function is continuously differentiable if and only if it is continuously derivable.
A counterexample in which a real function of a real variable can be continuously differentiable but not belong to class
is given in Example 9 in [
4].
Corollary 8. Let be a set for which every point admits an nbd ray. The function is of class if and only if it is continuously differentiable.
The following example shows that a differentiable function need not necessarily be continuously differentiable.
Example 3. The function , is differentiable but not continuously differentiable. Indeed, f is differentiable at every point of the domain, and its derivative ishowever, has discontinuity at the point because at this point, the left and right limits ( and ) of the function differ.
Theorem 4. Let and be sets whose linearization spaces are and for all and , and every point in X admits an nbd ray neighborhood in X. Let be a function such that . If is the function of class and is a continuously differentiable function, then is a function of class .
Proof. According to the definition of continuous differentiability and functions of class
the functions
f and
g satisfy the conditions of Theorem 1 for each
; thus,
is a differentiable function for every
and
holds. Let us prove that the function
defined by a rule
is continuous. Notice that the function
is a composition of functions
Since the function
is continuous, and according to Theorem 3, the mapping
is continuous, it follows that
is a continuous function. □
5. Characterization Theorems of Continuous Differentiability
We have seen that the differentiability of the function
, at the point
, implies the existence of derivatives in the directions of all vectors in whose direction there exists an nbd ray of
in
X (Corollary 5 in [
4]), while the converse is not true in general (Example 8 in [
4]). However, if along with the existence of the derivatives in the directions of
n linearly independent vectors the continuity of the corresponding derivatives functions on a special set containing the point
is fulfilled, then this implies also the differentiability of the function. It is known that the existence and continuity of the partial derivatives of a function given on an open domain implies the differentiability of this function:
Theorem 5. Let be an open set and let be a mapping such that there exists an i-th partial derivative of f at P, for every and every . If the partial derivatives , are continuous functions at , then f is differentiable at .
This theorem can be found in any university handbook of mathematical analysis (see, e.g., Theorem 9.21 in [
1]). We generalize this result, which is a part of common mathematical knowledge, in two ways. First, we consider functions given on much more general domains than open sets. Second, we establish a relation between the existence and continuity of derivatives in the direction of “admissible” vectors (partial derivatives are only a special case of this).
Let and be the point admitting an nbd ray in X in the direction of the vector , , where are linearly independent vectors and let be the set of linear contributions at in X. If there exist , , , , such that set is in the neighborhood of the point 0 in , then the set is said to be a raylike set in X at in the direction of the linear combinations of vectors . It is easy to see that any point of admits an nbd ray in X in the direction of the vector , , and that the linearization space at any point with respect to X is equal to . In addition, notice that the set is a raylike nbd of in X. Indeed, for every it is because it holds , for every , and consequently .
Example 4. Let . If , are non-collinear vectors and if is a closed triangle with vertices A, , then the (closed) parallelogram with vertices , and is a raylike set in X at A in the direction of the linear combinations of the vectors In fact, the set of linear contributions at A in X coincides with a triangle with vertices 0, and but without a vertex in 0, and the parallelogram with vertices 0, , and is the neighborhood of the origin 0 in . Therefore, the parallelogram is the raylike set in X at A in the direction of the linear combinations of the vectors .
Theorem 6. Let , and be linearly independent vectors such that admits an nbd ray in X in the direction of the vector , . Let there exist a raylike set W in X at in the direction of the linear combinations of vectors . Let be a mapping for which there exist all derivatives in the direction of the vector at every point in W. If all directional derivatives , , are continuous functions at , then f is differentiable at .
Proof. By Theorem 2, it suffices to prove the statement for the scalar case
. Let
be the set of linear contributions at
in
Then,
is the neighborhood of the point
in
, and there are numbers
,
,
,
,
, such that
Then, for each
, there are numbers
such that
and holds
Let us introduce auxiliary functions
for every
Now, it follows from the previous equality
Note that
is differentiable by the assumption of the theorem, and it holds
for every
. According to Lagrange’s theorem [
15], there are
such that
Since
is an open set in
, by Theorem 1 in [
4], it is enough to prove that it is
Since
, it follows exactly the required if
However, this holds true because of the continuity of the partial derivatives
at point
. Since
is a neighborhood of 0 in
by Theorem 1 in [
4], it follows
Thus, we have shown that the function
f is differentiable at
and that its differential
is given by
for every
□
Proposition 3. Let be an open set, and linearly independent vectors. Then, there exists a raylike set in Ω there at in the direction of the linear combinations of the vectors .
Proof. There exists a ball and it holds where is the set of linear contributions at in . Suffice it to note that for and , a set is a neighborhood of point 0 in , so is a raylike set in at in the direction of the linear combinations of vectors . □
Corollary 9. Let be an open set and linearly independent vectors. Let be a mapping for which there exist derivatives in direction of the vector , for each and all . If all directional derivatives , , are continuous functions at , then f is differentiable at .
Proof. The proof follows from the previous theorem and proposition. □
Let
be a set of
linearly independent vectors, such that every point
admits an nbd ray in
X in the direction of the vectors
,
. Let
be a continuously differentiable function. Then, by Corollary 5 in [
4], there exist derivatives
in the direction of the vectors
,
,
Since
is a homeomorphism, the function
is continuous if and only if
is continuous. However,
is a vector function whose coordinate functions are the directional derivatives:
Thus, if is continuous, then all these derivatives exist, and they are continuous mappings at every point in the domain of the function f. On the other hand, if all directional derivatives , , exist on X and are continuous at every point of the domain, and there exists a raylike set in X at every point (and consequently raylike nbd of it) in the direction of the linear combinations of the vectors then, by the previous theorem, the function f is differentiable, and the function (and then also ) is continuous. So, we have shown that it holds:
Corollary 10. Let be a set and be linearly independent vectors such that there exists a raylike set in X at every point in the direction of the linear combinations of the vectors . A function is of the class if and only if there exist directional derivatives , , for each and all the functions , , are continuous.
Corollary 11. Let be an open set and be linearly independent vectors. Mapping is of the class if and only if there exist directional derivatives , , for every , and all the functions , , are continuous.
Corollary 12. Let be a set, a function, and let every point of the set X admit an nbd ray in X, and let the space of linearization of the function f at every point of its domain be equal to . The function is of the class if and only if is of the class , for every .
Proof. If f is of class , then by Theorem 1, is of class , because according to Example 1, is of the class , for every . If is of the class , for every , then f is a differentiable function by Theorem 2. Notice that by the assumption all the functions , , are continuous. Since it holds , , the statement follows from Corollary 4. □
Corollary 13. Let be a set, each point of the set X admit an nbd ray in X, and the space of linearization at each point of X with respect to X be equal to . Then, the set together with the operations of addition and multiplication of functions with a scalar constitute a vector space.
Proof. The differentiability of a linear combination of differentiable functions follows from Theorem 4 in [
4], and the continuous differentiability of a linear combination of functions of class
follows from Corollary 5 for
. □