Abstract
The energy of a graph G is the sum of the absolute values of its adjacency matrix. In contrast, the trace norm of a digraph Q, which is the sum of the singular values of the corresponding adjacency matrix, is the oriented version of the energy of a graph. It is worth pointing out that one of the main problems in this theory consists of determining appropriated bounds of these types of energies for significant classes of graphs, digraphs and matrices, provided that, in general, finding out their exact values is a problem of great difficulty. In this paper, the trace norm of a -Brauer configuration is introduced. It is estimated and computed by associating suitable families of graphs and posets to Brauer configuration algebras.
1. Introduction
Brauer configuration algebras (BCAs) were introduced recently by Green and Schroll [1]. These algebras are multiserial symmetric algebras whose theory of representation is based on combinatorial data.
Since its introduction, BCAs have been a tool in the research of different fields of mathematics. Its role in algebra, combinatorics, and cryptography is remarkable. For instance, Malić and Schroll [2] associated a Brauer configuration algebra to some dessins d’enfants used to study Riemann surfaces, Cañadas et al. investigated the structure of the keys related to the Advanced Encryption Standard (AES) by using some so-called polygon-mutations in BCAs. On the other hand, BCAs were a helpful tool for Espinosa et al. to describe the number of perfect matchings in some snake graphs. We point out that Schiffler et al. used perfect matchings of snake graphs to provide a formula for the cluster variables associated with appropriated cluster algebras of surface type. In their doctoral dissertation, Espinosa used the notion of the message of a Brauer configuration to obtain the results [3,4]. According to him, each polygon in a Brauer configuration has associated a word. The concatenation of such words constitutes a message after applying a suitable specialization.
Perhaps, the message associated with a Brauer configuration is one of the most helpful tools to obtain applications of BCAs. In this work, we use Brauer configuration messages, some results of the theory of posets (partially ordered sets) and integer partitions to obtain the trace norm of some -Brauer configurations, which are Brauer configurations whose sets of vertices consist only of 0’s and 1’s.
It is worth pointing out that the research on trace norm has its roots in chemistry within the Hückel molecular orbital theory (HMO) [5]. Afterwards, Gutman [6] founded an independent line of investigation in spectral graph theory based on graph energy, which is the sum , where is the set of eigenvalues of the adjacency matrix of a graph G. The trace norm associated with the adjacency matrix of a digraph or quiver Q denoted is a generalization of the graph energy. It is also called the Schatten 1-norm, Ky Fan n-norm or nuclear norm. If are the singular values of the - adjacency matrix , with then . Relationships between energy graph and trace norm were investigated first by Nikiforov [7].
One of the main problems in graph energy theory is giving the extremal values of the energy of significant classes of graphs. For instance, Gutman [6] proved that if is a tree with n vertices then the following identity holds:
where, () denotes the star (the Dynkin diagram of type ) with n vertices.
Graph energy associated with digraphs was investigated first by Kharaghani–Tayfeh–Rezaie [8], afterwards by Agudelo–Nikiforov [9], who found bounds of extremal values of the trace norm for -matrices. It is worth noticing that if the adjacency matrix of a graph G is normal, then the graph energy equals the trace norm. In particular, if the adjacency matrix of a graph G is symmetric, then .
Contributions
In this paper, we introduce the notion of trace norm of a -Brauer configuration. Bounds and explicit values of these trace norms are given for significant classes of graphs induced by this kind of configuration. In particular, the dimension of the associated algebras and their centers are obtained. These results give a relationship between Brauer configuration algebras and graph energy theories with an open problem in the field of integer partitions proposed by Andrews in 1986. Such a problem asks for sets of integer numbers for which , where denote the number of integer partitions of n into parts within the set X with a being a fixed positive integer [10].
As a consequence of their investigations regarding Andrews’s problem, Cañadas et al. [11,12] introduced and enumerated a particular class of integer compositions (i.e., partitions for which the order of the parts matter) of type , for which the Andrews’s problem holds if . For each n, compositions of type constitute a partially ordered set whose number of two-point antichains is given by the integer sequence encoded in the OEIS (On-Line Encyclopedia of Integer Sequences) A344791 [13]. The following identity (2) gives the nth term of this sequence:
where denotes the kth triangular number, and
This paper uses this sequence to estimate eigenvalues sums of matrices associated with polygons of some -Brauer configurations.
It is worth noting that the relationships introduced in this paper between the theory of Brauer configuration algebras and the graph energy theory do not appear in the current literature devoted to these topics.
This paper is distributed as follows; in Section 2, we recall definitions and notation used throughout the document. In particular, we introduce the notion of trace norm of a -Brauer configuration. In Section 3, we give our main results, we compute and estimate the trace norm and graph energy of some families of graphs defined by Brauer configuration algebras. Concluding remarks are given in Section 4. Examples of trace norm values associated with some Brauer configurations are given in Appendix A.
The following diagram (3) shows how the notions of Brauer configuration and trace norm are related to some of the main results presented in this paper.
2. Background and Related Work
In this section, we introduce some definitions and notations to be used throughout the paper. In particular, it is given a brief overview regarding the development of the research of graph energy theory, path algebras, and Brauer configuration algebras.
Henceforth, the symbol will denote the adjoint of a matrix A, and the Frobenius norm of a matrix A. Furthermore, is a field, is the set of positive integers, and denotes the nth triangular number.
2.1. Graph Energy
The notion of graph energy as the sum of the absolute values of an adjacency matrix was introduced in 1978 by Gutman based on a series of lectures held by them in Stift Rein, Austria [6]. As we explained in the introduction, he was motivated by earlier results regarding the Hückel orbital total -electron energy. According to Gutman and Furtula [14], the results were proposed at that time in good hope that the mathematical community would recognize its significance. However, there was no interest in the subject despite Gutman’s efforts, perhaps due to the restrictions imposed on the studied graphs.
The interest in graph energy was renewed at the earliest 2000 when a plethora of results started appearing. Since then, more than one hundred variations of the initial notion have been introduced with applications in different sciences fields. In the same work, Gutman and Furtula claim that an average of two papers per week (more than one hundred in 2017) are written regarding the subject.
Some of the graph energy variations are:
- The Nikiforov energy of a matrix M, which is the sum of the singular values of a matrix.
- The Laplacian energy of a graph G of order n and size m defined as the sum of the absolute values of the eigenvalues of the matrix , where is the identity matrix of order n, and is the Laplacian matrix associated with G whose entries are given by the following identities:where denotes the degree of a vertex v in G.
- The Randić energy, which is the sum of the absolute values of the Randić matrix of a graph G, with
Although the notion of graph energy was introduced only for theoretical purposes, currently, its applications embrace a broad class of sciences. The following Table 1 shows some examples of different works devoted to the applications of graph energy and its variations. The authors refer the reader to [14] for more examples of these types of applications.
Table 1.
Works devoted to the applications of the graph energy theory. In the case of pattern recognition, the applications deal with military purposes.
2.2. Path Algebras
This section recalls some facts regarding quivers, their associated path algebras, and corresponding module categories. It is worth noting that the quiver or pass graph technique is used in representation theory, and it is an important tool to solve many ring problems, as Belov-Kanel et al. report in [24].
A quiver is a quadruple consisting of two sets whose elements are called vertices and whose elements are called arrows, s and t are maps such that if is an arrow, then is called the source of , whereas is called the target of [25]. The adjacency matrix and the spectral radius (where runs over all the eigenvalues of ) of a quiver Q are given by those defined by its underlying graph .
Recall that the adjacency matrix associated with a graph G is defined by the following identities:
A path of length with source a and target b is a sequence where for any . Vertices are paths of length 0 [25,26,27].
If Q is a quiver and is an algebraically closed field, then the path algebra of Q is the -algebra whose underlying -vector space has as basis the set of all paths of length in Q, the natural graph concatenation is the product of two paths [25,26].
An -algebra is said to be basic if it has a complete set of primitive orthogonal idempotents such that for all .
A relation for a quiver Q is a linear combination of paths of length with the same starting points and same endpoints, not all coefficients being zero [25,26].
Let Q be a finite and connected quiver. The two-sided ideal of the path algebra generated by the arrows of Q is called the arrow ideal of and is denoted by , is the ideal of generated as an -vector space, by the set of all paths of length . A two- sided ideal I of the path algebra is said to be admissible if there exists such that .
If I is an admissible ideal of , the pair is said to be a bound quiver. The quotient algebra is said to be a bound quiver algebra.
Gabriel [28] proved that any basic algebra is isomorphic to a bound quiver algebra. He also showed the finiteness criterion for these algebras. Taking into account that one of the main problems in the theory of representation of algebras consists of giving a complete description of the indecomposable modules and irreducible morphisms of the category of finitely generated modules of a given algebra .
According to the number of indecomposable modules an algebra can be of finite, tame or wild representation type. We recall that if is a category of finitely generated modules over an -algebra (in this case, is an algebraically closed field). Then a one-parameter family in is a set of modules of the form:
where is a -bimodule, which is finitely generated and free over [29].
Category is said to be of tame representation type or tame type, if , and for every n, the indecomposable modules form a one-parameter family with maybe finitely many exceptions equivalently in each dimension d, all but a finite number of indecomposable -modules of dimension d belong to a finite number of one-parameter families. On the other hand, is of wild representation type or wild type if it contains n-parameter families of indecomposable modules for arbitrarily large n [29].
It is worth noting that Drozd in 1977 and Crawley-Boevey in 1988 proved the following result known as the trichotomy theorem.
Theorem 1
([30,31], Corollary C). Let Λ be a finite-dimensional algebra over an algebraically closed field. Then Λ-mod has either tame type or wild type, and not both.
The following result proved by Smith establishes a relationship between the theory of representation of algebras and the spectra graph theory.
Theorem 2
([32]). Let G be a finite simple graph with the spectral radius (index) . Then if and only if each connected component of G is one of the extended Dynkin diagram , , , , . Moreover, if and only if each connected component of G is one of Dynkin diagrams , , , , .
Remark 1.
Note that if Q is a connected quiver without oriented cycles, then Theorem 2 allows concluding that Q is of finite type (tame type) if and only if (). Otherwise, Q is of wild type. A quiver Q has one of these three properties means that the corresponding path algebra also does.
2.3. {0,1}-Brauer Configuration Algebras
In this section, we discuss some results regarding -Brauer configuration algebras, we refer the reader to [1] for a more detailed study of general Brauer configuration algebras.
-Brauer configuration algebras are bound quiver algebras induced by a Brauer configuration with the following characteristics:
- is said to be the set of vertices.
- is a collection of multisets consisting of vertices called polygons.
- The word defined by the polygon has the form;where , is the number of times that the vertex 0 occurs in the polygon , is the number of times that the vertex 1 appears in the same polygon with .
- is a map , such that . is said to be the multiplicity function associated with .
- Successor sequences and associated with the vertices are defined by an orientation , which is an ordering on the polygons of the form:Successor sequences is a way of recording how vertices appear in the polygons.
The construction of the quiver (or simply Q, if no confusion arises) goes as follows:
- Add a circular relation , to each successor sequence and . , is said to be a special cycle associated with i.
- Define as the set of vertices of Q.
- Each cover in a special cycle defines an arrow .
Note that there are different special cycles associated with a vertex in a polygon .
Figure 1 shows the Brauer quiver induced by a -Brauer configuration .
Figure 1.
Brauer quiver induced by a -Brauer configuration. Symbols , , mean that the corresponding vertex has associated different loops.
The valency of a vertex is given by the identity:
is the number of arrows in the i-cycles. A vertex is said to be truncated if , otherwise i is non-truncated. Vertices 0 and 1 are non-truncated in a -Brauer configuration algebra.
The Brauer configuration algebra (or ) defined by the quiver Q is the path algebra bounded by the admissible ideal (or I) generated by the following set of relations:
- If a polygon contains vertices and are special cycles then .
- If a is the first arrow of a special cycle then .
- , , for all possible values of and s.
- , for all possible values of i.
- , , for all possible values of i and j.
- , for all possible values of i and j.
- , , for all possible values of i and j.
If there exists a word-transformation T such that , for instance, if with a suitable {0,1}-word, then the cumulative message) of is defined in such a way that and the reduced message is defined by the concatenation word:
If can be written as a matrix, then denotes the spectral radius of the Brauer configuration and the trace norm of the Brauer configuration is defined as:
where are the singular values of , i.e., the square roots of the eigenvalues of .
The following Proposition 1 and Theorem 3 prove that the dimension and the center of a Brauer configuration algebra can easily be computed from its Brauer configuration [1,33].
Proposition 1
([1], Proposition 3.13). Let Λ be a Brauer configuration algebra associated with the Brauer configuration Γ and let be a full set of equivalence class representatives of special cycles. Assume that for , is a special -cycle where is a non-truncated vertex in Γ. Then
where denotes the number of vertices of Q, denotes the number of arrows in the -cycle and .
Theorem 3
([33], Theorem 4.9). Let Γ be a reduced and connected Brauer configuration and let Q be its induced quiver and let Λ be the induced Brauer configuration algebra such that then the dimension of the center of Λ denoted is given by the formula:
where .
In this case, denotes the radical of a module M, is the intersection of all the maximal submodules of M.
The following are properties of -Brauer configuration algebras based on Proposition 1 and Theorem 3.
Corollary 1.
Let Λ be a Brauer configuration algebra induced by a {0,1}-Brauer configuration with . Then the following statements hold:
- 1.
- Λ is reduced and connected.
- 2.
- , where denotes the jth triangular number.
- 3.
- .
2.4. Posets
A partially ordered set (or poset) is an ordered pair where is a not empty set, and ≤ is a partial order over the elements of , i.e., ≤ is reflexive, antisymmetric, and transitive. Henceforth, if no confusion arises we will write instead of to denote a partially ordered set.
For each , if or , we say that x and y are comparable points, whereas if and , we say that x and y are incomparable points (the subset is a two-point antichain), this situation is denoted by . An ordered set is called a chain (or a totally ordered set or a linearly ordered set) if and only if for all we have or (i.e., x and y are comparable points).
A relation in a poset is said to be a covering, if for any such that it holds that or [34].
3. Applications
In this section, we give applications of -Brauer configuration algebras in graph energy. We start by defining some suitable - Brauer configuration algebras, dimensions of these algebras and corresponding centers are given as well. We also compute and estimate eigenvalues and trace norm of their reduced messages .
- For fixed, let us consider the {0,1}-Brauer configuration , such that:The orientation is defined in such a way that in successor sequences associated with vertices 0 and 1, it holds that , for .Polygons can be seen as -matrices over or as -matrices over the vector space of polynomials of degree . Its construction goes as follows:
- (a)
- For any i, , is a symmetric matrix,
- (b)
- ,
- (c)

- (d)
- Blocks , with are defined as follows:
- Over , , , ,
- Over , ,
Corollary 2.If is the Brauer configuration algebra induced by the {0,1}-Brauer configuration then the following statements hold:whereProof.For fixed, consider the following set:is endowed with a partial order ⊴, which defines the following coverings:defines a matrix whose entries are given by the following identities:Now we are interested in estimating the eigenvalues of . Since the polygons can be seen as square symmetric matrices described in the previous proof as . We will assume that for each n, the real eigenvalues of a matrix are indexed in the following decreasing order:The next result, which derives two inequalities for the eigenvalues of Hermitian matrices, was proved by Bollobás and Nikiforov [35].Theorem 4([35], Theorem 2). Suppose that and let be a Hermitian matrix of size n. For every partition we haveandThe following result on the eigenvalues of can be obtained by applying Theorem 4 to the matrix associated with the polygon .Corollary 3.For and . Let be the matrix associated with the polygon . For partition where . We haveand - For fixed, let be a {0,1}-Brauer configuration such that:The orientation is defined in such a way that in successor sequences associated with vertices 0 and 1, it holds that .Polygons can be seen as -matrices over using the Kronecker product, denoted by ⊗, as follows:Corollary 4.For , if is the Brauer configuration algebra induced by the {0,1}-Brauer configuration then the following statements hold:where and are the nth term of the OEIS sequences and , respectively.Proof.Given , let . For , define if . In this case the poset consists of all subsets of ordered by inclusion.We associate to each finite poset of size n the following -matrix:Under appropriate labeling of poset points , the matrix can be viewed using the Kronecker product as follows:matrices can be seen as pavements, cells with 1’s are colored black and those with 0’s are colored white. Figure 2 shows examples of these types of matrices.
Figure 2. Matrices for and 4.is the matrix associated with the polygon , thus can be computed in the following fashion:Therefore and thus the result holds. □Now we are interested in computing the trace norm of the {0,1}-Brauer configuration . For this, we recall the following theorem about the singular values of the Kronecker product:Theorem 5([36], Theorem 4.2.15). Let and have singular value decompositions and and let and . Then . The nonzero singular values of are the positive numbers (including multiplicities).The following Lemma 1 is helpful to prove Theorem 6.Lemma 1.Let be a given matrix. If then the singular values of B are and for , where is the golden ratio.Proof.Note that . The singular values for are and , then by Theorem 5 the result holds. □Theorem 6.For each , if is the matrix associated with the polygon thenProof.By induction on n. For , . Let us suppose that and let us see that the result is fulfilled for , i.e.,Since , then for the Lemma 1 the singular values of arefor . Thus,□Corollary 5.Proof.By Theorem 6, we have:which is a convergent geometric series with and , therefore:□ - For fixed, let be a {0,1}-Brauer configuration such that:For , the word associated with the polygon has the form , , , .The orientation is defined in such a way that for successor sequences associated with vertices 0 and 1, it holds that .Polygons can be seen as -matrices over . Each row is defined by coefficients of a polynomial with the form , .
Theorem 7.
For , if is the Brauer configuration algebra induced by the {0,1}-Brauer configuration , , and , with for then the following statements hold:
- 1.
- ,
- 2.
- ,
- 3.
- .
Proof.
The Formulas (1) and (2). for the dimension of the algebra and its center are consequences of the definition of a Brauer configuration and Corollary 1.
Let us prove identity 3. Firstly, we note that the characteristic polynomials associated with matrices can be obtained recursively. They obey the following general rules according to the size of the corresponding matrices.
and are characteristic polynomials of the following matrices , and , respectively:
For any , is the characteristic polynomial of .
We note that for , , where
Then . Thus, is a Cauchy subsequence of the sequence , converging to . □
Corollary 6. 
For any , an n-vertex quiver with underlying graph of the form:

is of wild type.
Proof.
Since , then the result holds as a consequence of Theorem 2, Remark 1, and Theorem 7. □
The following results [37] regarding some relationship between graph operations and energy graph allow finding upper and lower bounds for .
Theorem 8
(Theorema 4.18 [37]). Let G, H, and be graphs as specified above. Then
Equality is attained if and only if either u is an isolated vertex of G or v is an isolated vertex of H or both.
Corollary 7
(Corollary 4.6 [37]). If is a cut edge of a simple graph G, then .
As a consequence of these results, we obtain the following Corollary 8.
Corollary 8.
For .
Proof.
The inequality at right hand holds as a consequence of Theorem 8 taking into account that is the coalescence [37] between the cycle and , and that:
and
To prove the left hand inequality, we remove edges and in , obtaining in this fashion a connected tree. Since among all trees of order n, attains the minimal energy. The result holds as a consequence of Corollary 7. □
4. Concluding Remarks
-Brauer configuration algebras give rise to the so-called trace norm of a Brauer configuration. Such Brauer configurations are a source of a great variety of graphs and posets via its reduced message. The structure of the adjacency matrices associated with these graphs allows estimating the corresponding trace norm or graph energy values. In line with the main problem in the graph energy theory, we give explicit formulas for the trace norm of some -matrices associated with these families of graphs and posets. On the other hand, bounds for the energy of some families of graphs can be obtained via graph coalescence. It is worth pointing out that some of these graphs underlying quivers of wild type.
An interesting task for the future will be to find the trace norms of a wide variety of Brauer configuration algebras.
Author Contributions
Investigation, N.A.M., A.M.C., P.F.F.E. and I.D.M.G.; writing—review and editing, N.A.M., A.M.C., P.F.F.E. and I.D.M.G. All authors have read and agreed to the published version of the manuscript.
Funding
MinCiencias-Colombia and Seminar Alexander Zavadskij on Representation of Algebras and their Applications, Universidad Nacional de Colombia.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
N. Agudelo and A.M. Cañadas thanks to MinCiencias and Universidad Nacional de Colombia, sede Bogotá (Convocatoria 848- Programa de estancias Postdoctorales 2019) for their support.
Conflicts of Interest
The authors declare no conflict of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| (Dimension of a Brauer configuration algebra) | |
| (Dimension of the center of a Brauer configuration algebra) | |
| (Vertices in a Brauer configuration ) | |
| (Message of a Brauer configuration ) | |
| (Reduced message of a Brauer configuration ) | |
| (Number of occurrences of a vertex in a polygon V) | |
| (Ordered sequence of polygons) | |
| (Valency of a vertex ) | |
| (Word associated with a polygon of a Brauer configuration) | |
| (Frobenius norm of matrix M) | |
| (Trace norm of matrix M) | |
| ⊗ | (Kronecker product) |
| (Golden ratio) | |
| (Eigenvalues of matrix M) | |
| (Spectral radius of a graph G) | |
| (Singular values of matrix M) | |
| (The jth triangular number) | |
| (Matrix associated with the polygon ) |
Appendix A
References
- Green, E.L.; Schroll, S. Brauer configuration algebras: A generalization of Brauer graph algebras. Bull. Sci. Math. 2017, 121, 539–572. [Google Scholar] [CrossRef]
- Malić, G.; Schroll, S. Dessins d’enfants and Brauer configuration algebras. In Galois Covers, Grothendieck-Teichmüller Theory and Dessins d’Enfants, Proceedings of the LMS Midlands Regional Meeting & International Workshop, Leicester, UK, 4–7 June 2018; Springer: Cham, Switzerland, 2020; pp. 205–225. [Google Scholar]
- Cañadas, A.M.; Gaviria, I.D.M.; Vega, J.D.C. Relationships between the Chicken McNugget Problem, Mutations of Brauer Configuration Algebras and the Advanced Encryption Standard. Mathematics 2021, 9, 1937. [Google Scholar] [CrossRef]
- Espinosa, P.F.F. Categorification of Some Integer Sequences and Its Applications. Ph.D. Thesis, Universidad Nacional de Colombia, Bogotá, Colombia, 2021. [Google Scholar]
- Coulson, C.A.; O’Leary, B.; Mallion, R.B. Hückel Theory for Organic Chemists; Academic Press: London, UK, 1978. [Google Scholar]
- Gutman, I. The energy of a graph. Ber. Math. Statist. Sekt. Forschungszentrum Graz. 1978, 103, 1–22. [Google Scholar]
- Nikiforov, V. The energy of graphs and matrices. J. Math. Anal. Appl. 2007, 326, 1472–1475. [Google Scholar] [CrossRef]
- Kharaghany, H.; Tayfeh-Rezaie, B. On the energy of (0,1)-matrices. Linear Algebra Appl. 2008, 429, 2046–2051. [Google Scholar] [CrossRef]
- Nikiforov, V.; Agudelo, N. On the minimum trace norm/energy of (0,1)-matrices. Linear Algebra Appl. 2017, 526, 42–59. [Google Scholar] [CrossRef]
- Andrews, G.E. Unsolved problems; further problems on partitions. Am. Math. Mon. 1987, 94, 437–439. [Google Scholar] [CrossRef]
- Cañadas, A.M.; Gaviria, I.D.M.; Giraldo, H. Representation of equipped posets to generate Delannoy numbers. Far East J. Math. Sci. 2017, 8, 1677–1695. [Google Scholar]
- Gaviria, I.D.M. The Auslander-Reiten Quiver of Equipped Posets of Finite Growth Representation Type, Some Functorial Descriptions and Its Applications. Ph.D. Thesis, Universidad Nacional de Colombia, Bogotá, Colombia, 2020. [Google Scholar]
- Sloane, N.J.A. OEIS. Available online: https://oeis.org/search?q=A344791 (accessed on 30 June 2021).
- Gutman, I.; Furtula, B. Graph energies and their applications. Bulletin 2019, 44, 29–45. [Google Scholar]
- Dhanalakshmi, A.; Rao, K.S.; Sivakumar, K. Characterization of α-cyclodextrin using adjacency and distance matrix. Indian J. Sci. 2015, 12, 78–83. [Google Scholar]
- Giuliani, A.; Filippi, S.; Bertolaso, M. Why network approach can promote a new way of thinking in biology. Front. Genet. 2014, 5, 83. [Google Scholar] [CrossRef]
- Yuge, K. Graph representation for configuration properties of crystalline solids. J. Phys. Soc. Jpn. 2017, 86, 024802. [Google Scholar] [CrossRef]
- Van Mieghem, P.; Van de Bovenkamp, R. Accuracy criterion for the mean-field approximation in susceptible-infected-susceptible epidemics on networks. Phys. Rev. E 2015, 91, 032812. [Google Scholar]
- Angadi, S.A.; Hatture, S.M. Face recognition through symbolic modelling of face graphs and texture. Int. J. Pattern Rec. Artif. Intell. 2019, 33, 1956008. [Google Scholar] [CrossRef]
- Bai, Y.; Dong, L.; Hunag, X.; Yang, W.; Liao, M. Hierarchical segmentation of polarimetric SAR image via non-parametric graph entropy. In Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada, 13–18 July 2014. [Google Scholar]
- Akram, M.; Naz, S. Energy of pythagorean fuzzy graphs with applications. Mathematics 2018, 6, 136. [Google Scholar] [CrossRef]
- Pugliese, A.; Nilchiani, R. Complexity analysis of fractionated spacecraft architectures. Am. Inst. Aeronaut. Astronaut. Space Forum 2017, 33, 2721275. [Google Scholar]
- Bolaños, M.E.; Aviyente, S. Quantifying the functional importance of neural assemblies in the brain using Laplacian Hückel graph energy. In Proceedings of the 2011 IEEE International Conference on Acoustics, Speech and Signal Processing, Prague, Czech Republic, 22–27 May 2011; pp. 753–756. [Google Scholar]
- Belov-Kanel, A.; Rowen, L.H.; Vishne, U. Full quivers of representations of algebras. Trans. Am. Math. Soc. 2021, 364, 5525–5569. [Google Scholar] [CrossRef]
- Assem, I.; Skowronski, A.; Simson, D. Elements of the Representation Theory of Associative Algebras; Cambridge University Press: Cambridge, UK, 2006. [Google Scholar]
- Auslander, M.; Reiten, I.; Smalo, S.O. Representation Theory of Artin Algebras; Cambridge University Press: Cambridge, UK, 1995. [Google Scholar]
- Simson, D. Linear Representations of Partially Ordered Sets and Vector Space Categories; Gordon and Breach: London, UK, 1992. [Google Scholar]
- Gabriel, P. Unzerlegbare Darstellungen I. Manuscripta Math. 1972, 6, 71–103. [Google Scholar] [CrossRef]
- Crabbe, A.; Leuschke, G. Wild hypersurfaces. J. Pure Appl. Algebra 2011, 215, 2884–2891. [Google Scholar] [CrossRef][Green Version]
- Drozd, J. On tame and wild matrix problems. In Matrix Problems, Kiev.; Istitute of Mathematics of SA of Ukr. SSR: Kyiv, Ukraine, 1977; pp. 104–114. (In Russian) [Google Scholar]
- Crawley-Boevey, W. On tame algebras and bocses. Proc. Lond. Math. Soc. 1988, 56, 451–483. [Google Scholar] [CrossRef]
- Smith, J.H. Some properties of the spectrum of a graph. In Combinatorial Structures and Their Applications; Guy, R., Hanani, H., Sauer, N., Schönheim, J., Eds.; Gordon and Breach: New York, NY, USA, 1970; pp. 403–406. [Google Scholar]
- Sierra, A. The dimension of the center of a Brauer configuration algebra. J. Algebra 2018, 510, 289–318. [Google Scholar] [CrossRef]
- Davey, B.A.; Priestley, H.A. Introduction to Lattices and Order, 2nd ed.; Cambridge University Press: Cambridge, UK, 2002. [Google Scholar]
- Bollobás, B.; Nikiforov, V. Graphs and Hermitian matrices: Eigenvalue interlacing. Discret. Math. 2004, 289, 119–127. [Google Scholar] [CrossRef][Green Version]
- Horn, R.; Johnson, C. Topics in Matrix Analysis; Cambridge University Press: Cambridge, UK, 1991. [Google Scholar]
- Li, X.; Shi, Y.; Gutman, I. Graph Energy; Springer: New York, NY, USA, 2012. [Google Scholar]
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