Abstract
In this paper, we study the properties of faces and exposed faces of the cone of copositive matrices (copositive cone), paying special attention to issues related to their geometric structure. Based on the concepts of zero and minimal zero vectors, we obtain several explicit representations of faces of the copositive cone and compare them. Given a face of the cone of copositive matrices, we describe the subspace generated by that face and the minimal exposed face containing it. Summarizing the results obtained in the paper, we systematically show what information can be extracted about the given copositive face in the case of incomplete data. Several examples for illustrating the main findings of the paper and also for justifying the usefulness of the developed approach to the study of the facial structure of the copositive cone are discussed.
1. Introduction
The paper is devoted to the study of the facial structure of the cone of copositive matrices and is motivated by our main task for the future: the investigation of optimality conditions for the problems of copositive programming (CoP) and the search for new dual formulations for them.
Copositive problems attract the attention of researchers because they have many interesting applications (see, for example, [1,2,3], and the references therein). Copositive problems belong to the class of conic optimization problems consisting of minimizing a convex function over the intersection of an affine subspace and a convex cone. Conic optimization leads to simple and ingenious formulations of many optimization problems, since it allows one to explicitly describe many important types of constraints in a way that is natural for many applied problems. CoP is sometimes seen as a generalization of Semidefinite Programming (SDP) and a special case of Semi-infinite Programming (SIP), whose important applications are well-known [4,5]. Note that the cone can be considered as a generalization of the cone of semidefinite matrices, but is more complex and its facial structure is less studied than that of the SDP cone.
For convex conic optimization problems, the study of the facial structure of the corresponding cone is crucial, since the properties of its faces can be used for
- (1)
- creation of regularization algorithms (facial reduction algorithms) and their justification,
- (2)
- development and understanding of duality theory,
- (3)
- obtaining optimality conditions,
which are important issues for any optimization problem. For example, in the papers [6,7,8,9], the facial structure of the cone of semidefinite matrices is used to solve the above problems. Currently, some interesting results have been obtained for special classes of faces of the cone in [10,11,12], but in general this problem has not yet been completely resolved. There are many open problems in studying the facial structure of this cone [3,13]. The structure of the faces of other cones is studied in [14].
In our previous work (see [15] and the references in it), we defined the zero and minimal zero vectors of a given convex subset of the cone . These definitions generalize the concepts of zeros and minimal zeros of copositive matrices, which were used in [11] to study the properties of the minimal and maximal faces of . In [15] we showed how with the help of zeros and minimal zeros one can obtain different representations of the faces of the cone and the corresponding dual cones. We also described the minimal face of containing a given convex subset of this cone, and proved some propositions that can be useful for obtaining equivalent representations of feasible sets of copositive problems and creating new numerical methods based on the regularization approach.
In this paper, we will use some of our previous results to give a deeper understanding of the properties of faces of the cone of copositive matrices. In particular, for a given face of , we will describe the minimal exposed face containing this face, and examine the subspace generated by it. Some special classes of faces of the cone and their properties will also be considered. We will show how one can get as much useful information as possible about the properties of a face of in case of incomplete data about this face.
The paper is structured as follows. Section 1 hosts an introduction. Section 2 contains the basic notations and some preliminary results for representing the faces of the cone of copositive matrices in terms of their zeros, which will be used in the following sections. Several examples illustrating these results are also presented in Section 2. In Section 3, we investigate the structural properties of the faces of the cone and the corresponding subspaces. In particular, for a given face of , we describe the subspace generated by that face and the minimal exposed face containing it. In Section 4, we discuss the faces of , which are defined by singleton sets. Section 5 contains several additional examples that justify the usefulness of the approach developed in the paper to the study of the facial structure of the cone . In Section 6, we present the main conclusions and systematically show what information about the face of the copositive cone can be extracted from some incomplete data about this face, based on the results obtained in the paper.
2. Basic Notation and Preliminary Results
2.1. Cones and Faces: General Definitions
Given a finite-dimensional space , let us recall some general definitions.
A set is convex if for any and any , it holds
Given a set denoted by its convex hull, i.e., the minimal (by inclusion) convex set, containing this set, and by its span, i.e., the smallest linear subspace containing . A set is a cone if for any and any , it holds
A nonempty convex subset F of a convex closed set is called face of C if from the condition with and , it follows that . The standard notation is used to denote that F is a face of the set C. We say that a face F, , is proper if and write in this case
A face F of a closed convex set is called exposed if it can be represented as intersection of C with a supporting hyperplane, i.e., there exist and such that for all it holds: and iff Every exposed face should also be a face. Given a face F of a set C, the minimal (by inclusion) exposed face containing F will be called here the minimal exposed face for that face.
Given a cone , its dual cone is given by
Here, and in what follows, the notation means that the item on the left-hand side is being defined to be what is on the right-hand side. Similarly, the notation means that the item on the right-hand side is being defined to be what is on the left-hand side.
2.2. The Cone of Copositive Matrices and Its Faces
In this paper, we are dealing with special classes of cones of matrices, in particular, with the cones of copositive and completely positive matrices.
Given an integer , consider the vector space with the standard orthogonal basis . This is denoted by ; the set of all p-vectors with non-negative components is denoted by —the space of real symmetric matrices.The space is considered here as a vector space with the trace inner product
Let denote the cone of symmetric copositive matrices:
Consider a compact subset of in the form of the simplex
with . It is evident that the cone can be equivalently described as follows:
The dual cone to is the cone of completely positive matrices, defined as
The cones of copositive and completely positive matrices are known to be proper cones, which means that they are closed, convex, pointed, and fully dimensional. The rest of this section is devoted to two alternative representations of the faces of these cones that will be used in this paper. Some of these results were obtained recently in [15]; others are new and have not been published before.
Given a vector with , consider support of , defined as
For a set and a point , the distance between them is denoted by :
Consider a finite set of vectors in the above simplex T,
This is denoted by
If the set I in (2) is empty, we consider that and
The following results were obtained in [15].
Lemma 1
Lemma 2
(Proposition 2 in [15]). Any face of the cone can be presented as follows:
where
with some vector set V given in (2) and some set
whose elements are the sets satisfying the conditions .
In what follows, we assume that any face of is given in the form (5).
The pair of sets will be called here the pair of defining sets for the face It is evident that if , then If then and hence This case is more interesting for research.
Remark 1.
The subspace defined in (6) can be equivalently described as follows:
Let . According to the approach proposed in [15], we define the set of vectors satisfying the following conditions:
The set is empty if , and is the union of a finite number of convex bounded polyhedra otherwise.
Consider the set
composed of all vertices of the set where J is the set of indices of vertices of the set .
In [15], the set was called the set of zeros of the cone and it was shown that this definition is equivalent to the concept of immobile indices of the constraints of certain related conic optimization problems (see, e.g., [16,17]). It was also shown that the set of vertices of coincides with the set of minimal zeros of the matrix set . See [15] for the definition of minimal zeros of
The following lemma is based on the results of [15].
Lemma 3.
Remark 2.
From the above considerations, it follows that, in general, for a given , there may be several pairs of defining sets (see Example 1 below). It is worth mentioning that, at the same time, there are faces of , which have a unique pair of defining sets. We consider a set of such faces in Section 4.
To illustrate the concepts introduced above, consider the following example.
Example 1.
Let , and Set , where and consider the face of defined in (5). It is simple to check this is correct:
and Hence, for this face , the set of minimal zeros (i.e., the set of all vertices of ) is as follows:
and the corresponding set defined in (11) and (10) consists of two sets
Note that, as it follows from Lemmas 2 and 3, in this example we have , but and
For the sets V and given in (2) and (7), consider the corresponding face defined in (5). As above, let be the set of the minimal zeros of . Define the set
Proposition 1.
Proof.
By construction, . Then
Let us show that Suppose the contrary: there exists such that Consequently, there exists such that , . Then for some , it holds:
By construction, we have and by the definition of the set (see (4)), we have with defined in (3). This implies that
According to Lemma 3, there exists a matrix such that inequalities (14) hold true. Let us show that
Indeed, suppose the contrary: there exists such that Then it follows from (14) that and therefore . However, this contradicts (18). Thus, the inequalities (19) are proved.
For the above matrices and denote where . From (19) it follows that there exists such that
According to Lemma 1, from the relations above, it follows . Hence, taking into account the fact that, by construction, it holds
we conclude that It is simple to observe that
However, on the other hand, from the relations it follows that The resulting contradiction proves the proposition. □
Let us compare the equivalent representations (10) and (17) of the sets Note that the set is polyhedral, but the set is not (in general). Therefore, to construct the set for any it is enough to solve several Linear Programming (LP) problems. Hence the representation (17) is more constructive than (10) and in the following we assume that the sets are defined by rules (17).
2.3. Exposed Faces of
At the beginning of this section (see Section 2.1), we presented the definition of exposed faces of a cone. Applying the results from [18] (see page 51), we can say that a face is an exposed face of if and only if there exists a matrix such that
The following proposition provides additional information about the structure of exposed faces of .
Proposition 2.
Proof.
As mentioned above, any exposed face can be presented in the form (20) with some . Being completely positive, the matrix A admits the following representation:
It is evident that the conditions and imply Hence the vectors solve the optimization problem
From the optimality conditions for the vectors in the problem above, it follows that Thus, we showed the implication
for any and any A in the form (22).
On the other hand, it is obvious that the conditions imply and then Hence, we have shown that
The next lemma presents one known result that will be constructively proved here by representation (5).
Lemma 4.
For any , there exists anexposedface of such that is anexposedface of .
Proof.
According to Lemma 2, any face of the cone admits the representation (see (5)), where V and are some sets defined in (2) and (7). Using these sets, let us form matrices
It is evident that and
Consider the cone
By construction, is an exposed face of and it easy to see that for any matrix , it holds
These relations imply that
Hence, we have shown that
Now, consider the cone By construction, is an exposed face of the cone (which, in turn, is an exposed face of ) and The lemma is proved. □
From the proof of Lemma 4 it follows that the face representation (5) allows one to explicitly describe an exposed face mentioned in the lemma’s formulation.
3. On the Structural Properties of the Faces of the Cone
3.1. Subspaces Generated by Faces of
Consider the face defined in (5) in the form , where the subspace and the sets V, are given in (6), (2), (7), respectively.
In the previous section, it was shown that the face admits the alternative representation (12) via the subspace described in (13) using the set of the minimal zeros of and the set defined in (11), (17). The following statements establish the relationship between the subspaces , , and .
Lemma 5.
The inclusion holds true.
Proof.
For a fixed , consider . Since , we have
for some . Then
Then and consequently, . The lemma is proved. □
The following example illustrates that, in general,
Example 2.
For , denote Then
The face is exposed, since .
It is easy to check that ,
and with Hence
Thus, we have
Theorem 1.
Proof.
By definition, where From Lemma 3, it follows that
Let us show that . Consider any . It follows from Lemma 3 that there exists satisfying relations (14). Consider a matrix for a sufficiently large . Then for , it holds
It follows from the relations above and Lemma 1 that Hence
This implies that The theorem is proved. □
Corollary 1.
In the notations of Theorem 1, we can state that
To illustrate this corollary, let us again consider Example 2. It easy to see that in this example we have
For a set V in the form (2), construct the matrix and consider the exposed face This face admits the following representations:
where the set is defined in (21), the set is the set of minimal zeros of , and the set is given by (11) and (17).
For the subspaces and the inclusions
hold true. Hence, the representation is the best (in terms of the dimension of the subspace used for the representation).
3.2. On the Construction of the Minimal Exposed Face Containing a Given Face
In this subsection, given a face of the cone , we will consider its minimal exposed face and show how it can be constructed using only the information about the corresponding sets and After that, we will describe the minimal exposed face containing a given convex subset of .
Suppose that for some face (possibly unknown), the corresponding set of minimal zeros in the form (9), and the set defined in (11), (17) are known. Thus, we consider that the finite data sets
are given.
First of all, let us note that using the known sets (28), one can explicitly present the face by the rule (12).
Having data (28), let us partition the index set J into subsets where , such that
(a)
(b) for any it holds
(c) if then we have
Note that the conditions (b) and (c) are equivalent to the following conditions, respectively:
(b1)
(c1) if then for all and all
Proposition 3.
Suppose that for a face , the sets (28) are known. Let be the partition of the set J such that the conditions(a)–(c)are satisfied. Then the set can be presented in the form
where
Proof.
For consider By construction, the vector admits a representation
For any , taking into account condition b1), let us calculate
Then by definition, and we have shown the inclusion
Now let us show that Consider . By construction,
If there exists such that , then and, consequently, . Suppose that on the contrary, it holds
Denoted by It is evident that and
Let be such that
Denoted by
If , then and hence, . However, this contradicts (33). Therefore,
Consider any Suppose that Then wherefrom, taking into account that by construction , we get the inequality contradicting (34). Hence, we have shown that there exist and such that
Let . The condition implies the conditions and . The condition is equivalent to the following one: wherefrom, taking into account that , we obtain Thus, we have shown that
In a similar way, we can show that
Hence, due to the condition (c) (see also (c1)), for and
, there exists such that
As per the properties of minimal zeroes, it follows that
Remark 3.
Note that it follows from Proposition 3 that the set can be explicitly described using only the available data (28) (the set of minimal zeros of and the set ).
Using the partition of the set J satisfying the conditions (a)–(c), let us define the following index sets:
Proposition 4.
Proof.
Suppose the contrary: for some and , it holds This implies the existence of an index such that Consequently, there exists such that The latter condition implies that there exists a matrix such that Furthermore, note that the inclusion implies Since and , then by construction, we have for all Hence
The obtained contradiction proves inclusions (39).
Let be the partition of the set J introduced above. Denoted by
For any by construction, we have
Let us prove the following Lemma.
Lemma 6.
Consider any Recall that the vectors are defined in (40). It follows from these definitions that
where
Notice that, by construction (see (41)),
Suppose that . Then, for all and all , we have
and hence,
By construction, and it follows from (42) that .
Suppose that . Hence, for any we have These equalities and (37) imply the equalities Then, by definition,
Now let Taking into account (37), we conclude that Consequently, The lemma is proved.
Note that it follows from Proposition 2 that the cone is an exposed face of and therefore, from the lemma above it follows that the cone is an exposed face of as well.
Theorem 2.
Proof.
Note that it follows from (38) that . By construction, , where is an exposed face. Then is an exposed face of containing the face
To prove that is the minimal exposed face, suppose the contrary: there exists another exposed face , such that and a matrix , such that
As is an exposed face, for some vectors it holds
Since then there exists such that By assumption, . Then and, consequently for some , where the set is defined in (30). Hence with some These relations together with (43) imply
where
From the assumption , it follows (where the sets , are defined in (42)) and hence,
Taking into account the latter inclusion and relations (46), we get
This result contradicts the inequality , which proves the theorem. □
Using Theorem 2 and following the proof of Lemma 4, one can easily prove the following statement.
Corollary 2.
Any face of the cone is an exposed face of its minimal exposed face.
Note that for any face and the corresponding minimal exposed face
Theorem 3.
A face is exposed if and only if , where
Proof.
Let us show that the faces and of admit representations
where is the set of all minimal zeros of these faces, and the set is defined in (4).
Let be a face of with the corresponding set of minimal zeros . Let the set be defined in (11). Then, according to Lemma 3 (see (12)), the face can be presented in the form
Now consider the cone
Since then it is evident that
Let us show that Consider any It is evident that the conditions imply that and due to Lemma 1 we conclude that . This implies that Thus, we have proved that the cone can be presented as
Similarly, it can be shown that the cone defined in (44) can be presented in the form (48) with defined in (47). Thus, representations (48) are justified.
As before, based on (14) and (18), it is simple to show that there exists such that Note that the set is closed and bounded; therefore, for some sufficiently small , it holds
Note that, from (38), it follows . Suppose that . Then there exists such that From the conditions , , , and inequalities (49), it follows that for a sufficiently small , we have
Taking into account (48), we conclude that and . Therefore . As is the minimal exposed face containing , it is obvious that is not exposed.
Now, suppose that . Then it follows from (48) that and hence is an exposed face. The theorem is proved. □
Theorem 3 reduces the answer to the question of whether a given face is exposed to checking the condition , which can be done by solving a unique LP problem when the data (28) is assumed to be known.
Remark 4.
Note that, given a face one can show that the respective minimal zeros and the sets can be uniquely constructed using only the set of all zeros of this face. Hence the minimal exposed face containing can be constructed on the basis of the set of all zeros of .
There may exist several different faces having the same sets of all their zeros: . Hence all these faces have the same minimal exposed face.
Let us illustrate this with the following example.
Example 3.
For , consider the sets
For each face , denote by the corresponding set of zeros, by the set of minimal zeros, and by , the sets defined in (17), (37), respectively. Here we have
For the faces , are not exposed since , and the face is exposed by construction (see Proposition 2). Here the sets and are defined by (47) for
Note that the faces , are different, but have the same set of zeros. Hence for any , the minimal exposed face containing should be the same. In fact, in our case, for we have
3.3. The Minimal and the Minimal Exposed Faces Containing a Given Set
Based on the results obtained in Section 3.2 and in [15], it is easy to describe the minimal exposed face containing a given closed convex subset of .
Let Q be a convex subset of . Consider the corresponding set of zeros
that is either empty or the union of a finite number of convex bounded polyhedra.
Let be the set of all vertices of the set
It was shown in [15] that the minimal face of containing Q can be presented in the form , where
Applying Theorem 2, we conclude that the minimal exposed face containing the set Q has the form
where the sets are defined by the rules (37) with the sets and replaced by and
4. Faces of Defined by Singleton Sets
In this section, we consider a special class of faces of namely, faces defined by the sets V and , where V is a singleton. Since V is a singleton, then by construction, the set is a singleton as well and we can assume that these sets have the form
Note that the class of faces defined by singleton sets is interesting in terms of studying the facial structure of the cone since all maximal faces of belong to it.
Recall that by definition, a face of is the maximal face if and there does not exist a face such that and
The next lemma is proved in [11].
Lemma 7.
A face is maximal if and only if there exists such that
The main result of this section is the proof of the following lemma.
Lemma 8.
Consider a face with the defining sets V and satisfying (50). Then
(i) and
(ii)the pair is unique, i.e., there is no other pair such that
(iii)
Proof.
(i) Let us show that and Without loss of generality, we can suppose that
and present in the form , where with and
Let be an orthogonal basis in Denoted by
Consider any vector . Since the representation holds, it is easy to check that
Consider a matrix where I is the identity matrix and is a matrix with positive elements.
By construction, and and
Then , and
(ii) Using the latter equalities, it is easy to show that the face has a unique defining pair , i.e., there no other sets and such that
(iii) Finally, let us prove that the dimension of the face with is equal to Taking into account Corollary 1, it is enough to show that
Let us prove that the matrices
are linearly independent. Suppose the contrary, i.e., there exist such that
Note that the above-proven lemma generalizes the related result from [11], where it was shown that a maximal face of has dimension
For a given , set and consider faces
with the defining sets and such that and for all .
It follows from Lemma 8 that all faces in (54) are different; for any the face has a unique pair of defining sets and , and its dimension is .
Set . From Theorem 2, one can conclude that is the minimal exposed face of containing all other faces which are all not exposed. Note that if , then and the set of faces defined in (54) consists of a unique exposed face .
5. Examples
In this section, we present a few more examples that justify the advantages of the approach developed here to the study of the facial structure of the cone and illustrate some of the properties of the faces of .
Let us start with an example illustrating the usefulness of the set of minimal zeros of a face of the cone and the corresponding set , introduced in this paper. In particular, this example shows that these sets make it possible to explicitly describe the cone dual to this face without using the closure operator.
As above, for some sets V and in the form (2) and (7), we will consider face of the cone defined in (5), the corresponding set of its minimal zeros, and the set of the sets defined by rules (17).
Consider the dual to cone . It was shown in [15] that
where
Here, denotes the closure of a set .
It was shown in [15] that and, in general,
Now, let us illustrate that in general and, therefore, , which means that we cannot omit the use of the closure operator in that equalities in (55) that concern the sets and (constructed using the defining sets V and ), while in the equality in (55) regarding the set (constructed using the sets and ), no closure operator is needed. This gives us an explicit description of the dual cone .
Example 4.
Let us once again consider Example 1 (see Section 2.2), where , and , with We have shown that the face of has the form (15) and
Consider a vector where , and the matrix
By construction, and it is easy to see that for any . Consequently,
Suppose that . Hence it can be presented in the form
where with
It follows from the latest relations that
The obtained contradiction proves that . Remind that by construction, Hence
Note that one can show that if for a face , the set of zeros consists of isolated elements then all these zeros are the minimal ones. In the next example, we will show that there exists an exposed face of with and , for which the set of zeros consists of isolated elements such that which illustrates that the number of the minimal zeros can be greater than the number of elements in the defining set To construct this face we will use some data from Example 5 in [19].
Example 5.
Set and consider a matrix , where It is shown in [19] that and it has 33 isolated zeros:
where and
Consider an exposed face
By construction,
It follows from the relations above that
Hence, according to Lemma 3, the face admits a representation where subspace is defined in (13).
Based on Theorem 1, we can easily determine the dimension of :
6. Summary of the Results and Conclusions
The main contribution of the paper is to study the properties of faces of the copositive cone . The concepts of zeros and minimal zeros were formulated for the case of an arbitrary face of the cone of copositive matrices and allowed us to obtain various representations of this face, an explicit representation of the subspace generated by it, and to describe the minimal exposed face containing .
Summarizing the results of the paper, let us consider a few possible scenarios for their application, starting with the strongest and most effective one.
Given a face of , the following sets (the data) are related to it:
1. the corresponding set of all zeros of ,
2. the set of minimal zeros of (the set of vertices of the set
3. the set defined in (11),
4. some sets V and such that the cone admits representation (5).
Suppose we do not have complete information about the cone , as only some of the sets from the list above are given. Let us see what information we can easily acquire in the case of incomplete data. The following scenarios are possible here.
- A
- In the case when the finite data sets enumerated in 2. and 3. are given, we can
- (a1)
- explicitly describe the corresponding face of the cone :
- (a2)
- easily construct the set (see Proposition 3);
- (a3)
- explicitly describe (without using the closure operator) the cone that is dual to the face (see (55));
- (a4)
- explicitly describe the minimal exposed face containing the face and check whether the face is exposed (see Theorems 2 and 3);
- (a5)
- determine andwhere
- B
- Suppose that only the set (the first set in the list 1.–4.) is given. In this case, we can only do the following:
- (b1)
- find the set of vertices of the set ;
- (b2)
- construct the sets defined in (37), and hence
- (b3)
- explicitly describe the minimal exposed face containing the face but not the face itself.
- C
- D
- Suppose that additionally to the data given in Scenario C (i.e., the pair of the sets , defining the face by the rule (5)), the set of minimal zeros of is given. In this case one can easily find the sets and hence provide all the constructions described in the items (a1)–(a5) of Scenario A.
Remark 5.
From the above considerations, it follows that the data set is the most useful finite data set for the corresponding face. In some cases, for , the set can be constructed based on the available data V and . From Proposition 1, it follows that having , V and , one can find the set , solving several Linear Programming problems.
In general case, the problem of finding the set is not trivial, but is very important and deserves a separate consideration.
The results of the paper may help to better understand the facial structure of the cone of copositive matrices and this knowledge can be effectively used in the duality theory of copositive optimization. The explicit descriptions of the faces of the copositive cone and their dual cones can be used in constructive regularization procedures based on the face reduction approach.
Author Contributions
Conceptualization, O.K.; methodology, O.K.; formal analysis, O.K. and T.T.; investigation, O.K. and T.T.; writing—original draft preparation, O.K. and T.T.; writing—review and editing, O.K. and T.T. All authors have read and agreed to the published version of the manuscript.
Funding
This research was partially supported by the state research program “Convergence” (Republic Belarus), Task 1.3.01, by Portuguese funds through CIDMA—Center for Research and Development in Mathematics and Applications, and FCT—Portuguese Foundation for Science and Technology, within the project UIDB/04106/2020.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
The authors thank the anonymous reviewers whose important comments and suggestions helped to significantly improve the presentation of this paper.
Conflicts of Interest
The authors declare no conflict of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| LP | Linear Programming |
| CoP | Copositive Programming |
| SIP | Semi-infimite Programming |
| SDP | Semidefinite Programming |
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