Research article Special Issues

Uplifting edges in higher-order networks: Spectral centralities for non-uniform hypergraphs

  • Received: 09 September 2024 Revised: 21 October 2024 Accepted: 28 October 2024 Published: 11 November 2024
  • MSC : 05C65, 15A72, 68M10

  • Spectral analysis of networks states that many structural properties of graphs, such as the centrality of their nodes, are given in terms of their adjacency matrices. The natural extension of such spectral analysis to higher-order networks is strongly limited by the fact that a given hypergraph could have several different adjacency hypermatrices, and hence the results obtained so far are mainly restricted to the class of uniform hypergraphs, which leaves many real systems unattended. A new method for analyzing non-linear eigenvector-like centrality measures of non-uniform hypergraphs was presented in this paper that could be useful for studying properties of H-eigenvectors and Z-eigenvectors in the non-uniform case. In order to do so, a new operation——the uplift——was introduced, incorporating auxiliary nodes in the hypergraph to allow for a uniform-like analysis. We later argued why this was a mathematically sound operation, and we furthermore used it to classify a whole family of hypergraphs with unique Perron-like Z-eigenvectors. We supplemented the theoretical analysis with several examples and numerical simulations on synthetic and real datasets: On the latter, we find a clear improvement over the existing methods, specially in cases where there is a huge disparity between the structure at each order, and on the former, we find that regardless of the chosen uniformization scheme, the nodes were similarly ranked.

    Citation: Gonzalo Contreras-Aso, Cristian Pérez-Corral, Miguel Romance. Uplifting edges in higher-order networks: Spectral centralities for non-uniform hypergraphs[J]. AIMS Mathematics, 2024, 9(11): 32045-32075. doi: 10.3934/math.20241539

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  • Spectral analysis of networks states that many structural properties of graphs, such as the centrality of their nodes, are given in terms of their adjacency matrices. The natural extension of such spectral analysis to higher-order networks is strongly limited by the fact that a given hypergraph could have several different adjacency hypermatrices, and hence the results obtained so far are mainly restricted to the class of uniform hypergraphs, which leaves many real systems unattended. A new method for analyzing non-linear eigenvector-like centrality measures of non-uniform hypergraphs was presented in this paper that could be useful for studying properties of H-eigenvectors and Z-eigenvectors in the non-uniform case. In order to do so, a new operation——the uplift——was introduced, incorporating auxiliary nodes in the hypergraph to allow for a uniform-like analysis. We later argued why this was a mathematically sound operation, and we furthermore used it to classify a whole family of hypergraphs with unique Perron-like Z-eigenvectors. We supplemented the theoretical analysis with several examples and numerical simulations on synthetic and real datasets: On the latter, we find a clear improvement over the existing methods, specially in cases where there is a huge disparity between the structure at each order, and on the former, we find that regardless of the chosen uniformization scheme, the nodes were similarly ranked.



    The concept of fuzzy sets along with various operations has been introduced by Zadeh in 1965 [1]. Due to the diverse applications of fuzzy sets ranging from engineering, computer science and social behaviour studies; the researchers have taken a keen interest in the subject in its related fields. Rosenfeld is the pioneer, who initiated fuzzification of algebraic structures [2]. He introduced basic definitions which are common and popular among the researchers. Rosenfeld introduced the notions of fuzzy subgroupoids and fuzzy subgroups and obtained some of their basic properties. Most of the recent works on fuzzy groups follow Rosenfeld's definitions. Anthony and Sherwood further redefined and characterized fuzzy subgroups [3,4]. Bhattacharya and Mukherjee introduced the notion of fuzzy normal subgroups, fuzzy relation and fuzzy cosets. They provided fuzzy generalizations of some remarkable results such as, Lagrange's theorem and Cayley's theorem [5,6,7,8,9]. Many other papers on fuzzy subgroups have also appeared which generalize various concepts of group theory such as conjugate subgroups, normal subgroups, quotient groups and cosets, congruence relations, homomorphism, isomorphism, series in groups and many more [10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25].

    Abel-Grassmann's concept of groupoids (AG-groupoids) is about forty years old and, related to this concept, so far more than hundred research papers have been published and many more either lie on the archives or waiting to see the light. Though it was slowly and gradually explored, yet during the last couple of years, it attracted the attention of many researchers and ample research was carried out in this area.

    In 1972, Kazim and Naseeruddin introduced AG-groupoids [26] and called it "left almost semigroup" or "LA-semigroup". In the literature this structure is also known by various names; right modular groupoid" [27], "left invertive groupoid" [28] or commonly by Abel Grassmann's groupoid (AG-groupoid) suggested by Stevanovic and Protic [29]. AG-groupoids have many applications in the theory of flocks [30], differential geometry, geometry and algebra [31,32,33]. Stevanovic and Protic [29] constructed the notion of n-inflation of the AG-groupoids. They also made such a constructions for AG{*}-groupoids [34]. They also discussed the properties of n-inflations of AG-groupoids, inflation's of the AG-band and semi-lattices.

    An AG-groupoid (or LA-semigroups) is a nonassociative groupoid in general, in which the left invertive law "(ab)c=(cb)a holds for all a,b,c". An AG-groupoid generalizes a commutative semigroup, and lies midway between a groupoid and a commutative semigroup. Even though the structure of AG-groupoid is nonassociative and noncommutative, it still holds many interesting properties which are usually found in commutative and associative algebraic structures. Very recently enumerations of AG-groupoids up to order 6 have been carried out with the help of GAP package for AG-groupoids called "AGGROUPOIDS" [35]. Presently, numerous examples of AG-groupoids are available for study, and various conjectures and conclusions can be drawn from the available data.

    In general, an AG-group is a nonassociative structure. Unlike groups and other structures, commutativity and associativity imply each other in AG-groups and thus AG-groups become abelian group if any one of them is allowed in AG-group. It is a generalization of the abelian group and a special case of quasi-group. The structure of AG-group is very interesting in which one has to play with brackets. The order of an element cannot be defined in AG-groups, i.e. AG-groups cannot be locally associative, otherwise, it becomes an abelian group. However, the order of an element up to 2 can be found and is called involution. Further, achievement was made when AG-groups were enumerated up to order 12 [35]. An AG-groupoid (G,) is called an AG-group or left almost group (LA-group), if there exists a unique left identity eG (i.e. ea=a for all aG), for all aG there exists a1G such that a1a=aa1=e. Dually, a right AG-groupoid (G,) is called a right AG-group or right almost group (RA-group), if there exists a unique right identity eG (i.e. ae=a for all aG), for all aG there exists a1G such that a1a=aa1=e.

    In this paper, fuzzy AG-subgroup [36,37] is further generalized and the notions of fuzzy cosets, conjugate fuzzy AG-subgroups, fuzzy quotient AG-subgroup, fuzzy AG-subgroup of the quotient (factor) AG-subgroup, fuzzy homomorphism of AG-group is introduced. These notions will provide a new direction for the researchers in this area. At the end of the paper, fuzzy version of famous Lagrange's theorem for finite AG-group is also introduced. The results in this paper are taken from the PhD thesis of the first author [38].

    In the rest of this paper G denotes an AG-group unless otherwise stated and e denotes the left identity of G.

    Definition 1. [37] Let A be any fuzzy subset of an AG-group G i.e. AFP(G). Then A is called a fuzzy AG-subgroup of G if for all x,y in G:

    (i) μA(xy)μA(x)μA(y),

    (ii) μA(x1)μA(x).

    The set of all fuzzy AG-subgroups of G is denoted by F(G). If AF(G), then

    A={xG| μA(x)=μA(e)}. (2.1)

    Example 1. In the AG-group G of order 4 with the following Cayley's table,

    The fuzzy AG-subgroup A of G is defined by

    A={(0,μA(0)),(1,μA(1)),(2,μA(2)),(3,μA(3))}={(0,t0),(1,t1),(2,t2),(3,t2)},

    where t0>t1>t2; and t0,t1,t2[0,1].

    Example 2. Consider the AG-group G of order 4 with the following Cayley's table,

    The fuzzy AG-subgroup A of G is defined by

    A={(0,μA(0)),(1,μA(1)),(2,μA(2)),(3,μA(3))}={(0,t0),(1,t1),(2,t1),(3,t1)},

    where t0,t1[0,1] and t0>t1.

    Proposition 1. [37] If AF(G), then μA(x1)=μA(x) and μA(e)μA(x) for all xG; where e is the left identity of G.

    Definition 2. Let AF(G) and uG. Then B is called fuzzy conjugate (with respect to u) denoted by, AcBu, if μBu(x)=μA((ux)u1) for all xG or simply by

    μB(x)=μA((ux)u1), for all xA.

    Remark 1. It is noted that a fuzzy conjugate subgroup of a fuzzy subgroup is again a fuzzy subgroup, while the fuzzy conjugate of a fuzzy AG-subgroup may or may not be a fuzzy AG-subgroup.

    Example 3. The fuzzy conjugates of a fuzzy AG-subgroup A are given as follows:

    A={(0,μA(0)),(1,μA(1)),(2,μA(2)),(3,μA(3)),(4,μA(4)),(5,μA(5))}={(0,t0),(1,t2),(2,t1),(3,t2),(4,t1),(5,t2)},

    where t0>t1>t2 and t0,t1,t2[0,1] of an AG-group G of order 6 in the following table:

    are given bellow:

    B0={(0,μB0(0)),(1,μB0(1)),(2,μB0(2)),(3,μB0(3)),(4,μB0(4)),(5,μB0(5))}={(0,μA(0)),(1,μA(5)),(2,μA(4)),(3,μA(3)),(4,μA(2)),(5,μA(1))}={(0,t0),(1,t2),(2,t1),(3,t2),(4,t1),(5,t2)}=A,
    B1={(0,μB1(0)),(1,μB1(1)),(2,μB1(2)),(3,μB1(3)),(4,μB1(4)),(5,μB1(5))}={(0,μA(2)),(1,μA(1)),(2,μA(0)),(3,μA(5)),(4,μA(4)),(5,μA(3))}={(0,t1),(1,t2),(2,t0),(3,t2),(4,t1),(5,t2)},
    B2={(0,μB2(0)),(1,μB2(1)),(2,μB2(2)),(3,μB2(3)),(4,μB2(4)),(5,μB2(5))}={(0,μA(4)),(1,μA(3)),(2,μA(2)),(3,μA(1)),(4,μA(0)),(5,μA(5))}={(0,t1),(1,t2),(2,t1),(3,t2),(4,t0),(5,t2)}.

    Similarly, we can calculate B3=A,B4, and B5. Here, both B1=B4 and B2=B5 are not fuzzy AG-subgroups of G, as

    μB1(22)=μB1(0)=t1μB1(2)μB1(2)=t0,

    and

    μB2(44)=μB2(0)=t1μB2(4)μB1(4)=t0.

    Example 4. The fuzzy conjugates of a fuzzy AG-subgroup C are given by:

    C={(0,μC(0)),(1,μC(1)),(2,μC(2)),(3,μC(3)),(4,μC(4)),(5,μC(5)),(6,μC(6)),(7,μC(7)),(8,μC(8))},C={(0,s3),(1,s4),(2,s4)},

    where s3>s4 and s3,s4[0,1], for any AG-group G of order 9 with the following table:

    are given bellow:

    D0={(0,μD0(0)),(1,μD0(1)),(2,μD0(2))}={(0,μC(0)),(1,μC(2)),(2,μC(1))}={(0,s3),(1,s4),(2,s4)}=C,
    D1={(0,μD1(0)),(1,μD1(1)),(2,μD1(2))}={(0,μC(2)),(1,μC(1)),(2,μC(0))}={(0,s4),(1,s4),(2,s3)},

    and

    D2={(0,μD2(0)),(1,μD2(1)),(2,μD2(2))}={(0,μC(1)),(1,μC(0)),(2,μC(2))}={(0,s4),(1,s3),(2,s4)}.

    Hence, D0,D1 and D2 are the fuzzy conjugates of a fuzzy AG-subgroup C, in which D1 and D2 are not fuzzy AG-subgroups of G as

    μD1(22)=μD1(0)=s4μD1(2)μD1(2)=s3,

    and

    μD2(11)=μD2(0)=s4μD2(1)μD2(1)=s3.

    Definition 3. Let AF(G). Then A is called a fuzzy normal AG-subgroup of G if

    μA((xy)x1)=μA(y)for allx,yG.

    In other words, A is fuzzy normal AG-subgroup of G if A is self fuzzy conjugate. FN(G) denotes the set of all fuzzy normal AG-subgroups of G.

    Example 5. Let G be an AG-group of order 6 as defined in Example 3, and let A be fuzzy AG-subgroup of G, defined by

    A={(0,μA(0)),(1,μA(1)),(2,μA(2)),(3,μA(3)),(4,μA(4)),(5,μA(5))}={(0,t0),(1,t1),(2,t0),(3,t1),(4,t0),(5,t1)},

    where t0>t1 and t0,t1[0,1]. The fuzzy conjugates of a fuzzy AG-subgroup A of G, are given bellow:

    B0={(0,μB0(0)),(1,μB0(1)),(2,μB0(2)),(3,μB0(3)),(4,μB0(4)),(5,μB0(5))}={(0,μA(0)),(1,μA(5)),(2,μA(4)),(3,μA(3)),(4,μA(2)),(5,μA(1))}={(0,t0),(1,t1),(2,t0),(3,t1),(4,t0),(5,t1)}=A,
    B1={(0,μB1(0)),(1,μB1(1)),(2,μB1(2)),(3,μB1(3)),(4,μB1(4)),(5,μB1(5))}={(0,μA(2)),(1,μA(1)),(2,μA(0)),(3,μA(5)),(4,μA(4)),(5,μA(3))}={(0,t0),(1,t1),(2,t0),(3,t1),(4,t0),(5,t1)}=A,
    B2={(0,μB2(0)),(1,μB2(1)),(2,μB2(2)),(3,μB2(3)),(4,μB2(4)),(5,μB2(5))}={(0,μA(4)),(1,μA(3)),(2,μA(2)),(3,μA(1)),(4,μA(0)),(5,μA(5))}={(0,t0),(1,t1),(2,t0),(3,t1),(4,t0),(5,t1)}=A.

    Similarly, we can calculate B3=B4=B5=A. Hence A is fuzzy normal AG-subgroup of G, as A is self conjugate.

    Lemma 1. Let AF(G). Then μA(xy)=μA(yx), for all x,yG.

    Proof. Suppose that AF(G). Then

    μA(xy)=μA((ex)y)=μA((yx)e))(by left invertive law)μA(yx)μA(e)=μA(yx)(by Proposition 1).

    Similarly, we can show that μA(yx)μA(xy), for all x,yG. Consequently, μA(xy)μA(yx)μA(xy), for all x,yG. Hence μA(yx)=μA(xy).

    In the following, a fuzzy coset of fuzzy AG-subgroups and binary operation on fuzzy coset is defined. Various examples of a fuzzy coset of fuzzy AG-subgroups are also constructed, and some of the properties of fuzzy coset of fuzzy AG-subgroups are investigated.

    Definition 4. Let AF(H) where H is an AG-subgroup of G, i.e., HG and xG, then the set Ax defined by

    Ax={(h,μA(hx1)),hH},

    is called fuzzy coset of H in G with respect to the fuzzy AG-subgroup A of H.

    It should be noted that, if AF(G), then by Lemma 1, μA(xy)=μA(yx) for all x,yG. This implies that, each fuzzy left and fuzzy right coset of AG-subgroups always coincide with each other. Therefore, instead of fuzzy left (fuzzy right) coset the term fuzzy coset of AG-subgroup H in G is used.

    Example 6. Consider the AG-group G of order 4 as in Example 2. Let H={0,2} be an AG-subgroup (abelian group) of G:

    A fuzzy subset A of H defined by

    A={(0,μA(0)),(2,μA(2))}={(0,t0),(2,t1)},

    where t0,t1[0,1] and t0>t1, is a fuzzy AG-subgroup of H in G.

    All the disjoint fuzzy coset of H in G with respect to fuzzy AG-subgroup A of H are obtained as follow:

    A0={(0,μA(001)),(2,μA(201))}={(0,μA(0)),(2,μA(2))}A0={(0,t0),(2,t1)}=A,
    A1={(0,μA(011)),(2,μA(211))}={(0,μA(1)),(2,μA(3))}A1=,
    A2={(0,μA(021)),(2,μA(221))}={(0,μA(2)),(2,μA(0))}A2={(0,t1),(2,t0)},
    A3={(0,μA(031)),(2,μA(231))}={(0,μA(3)),(2,μA(1))}A3=.

    Hence A and A2 are the two nonempty disjoint fuzzy cosets of H in G with respect to fuzzy AG-subgroup A of H.

    Example 7. Consider the AG-group G of order 6 as in Example 3. Let H={0,2,4} be an AG-subgroup of G of order 3.

    A fuzzy AG-subgroup A of H in G is given by:

    A={(0,μA(0)),(2,μA(2)),(4,μA(4))}={(0,t0),(2,t1),(4,t1)},

    where t0>t1, and t0,t1[0,1].

    All the disjoint fuzzy cosets of H in G with respect to A of H are obtained as follow:

    A0={(0,μA(001)),(2,μA(201)),(4,μA(401))}={(0,μA(0)),(2,μA(4)),(4,μA(2))}A0={(0,t0),(2,t1),(4,t1)}=A,
    A1={(0,μA(011)),(2,μA(211)),(4,μA(411))}={(0,μA(1)),(2,μA(5)),(4,μA(3))}A1=,
    A2={(0,μA(021)),(2,μA(221)),(4,μA(421))}={(0,μA(2)),(2,μA(0)),(4,μA(4))}A2={(0,t1),(2,t0),(4,t1)},
    A3={(0,μA(031)),(2,μA(231)),(4,μA(431))}={(0,μA(3)),(2,μA(1)),(4,μA(5))}A3=,
    A4={(0,μA(041)),(2,μA(241)),(4,μA(441))}={(0,μA(4)),(2,μA(2)),(4,μA(0))}A4={(0,t1),(2,t1),(4,t0)},
    A5={(0,μA(051)),(2,μA(251)),(4,μA(451))}={(0,μA(5)),(2,μA(3)),(4,μA(1))}A5=.

    Hence A,A2 and A4 are three nonempty disjoint fuzzy cosets of H in G with respect to fuzzy AG-subgroup A of H.

    Example 8. Consider the AG-group G of order 9 as in Example 4. Let

    H1={0,1,2},H2={0,3,7},H3={0,4,6}

    and

    H4={0,5,8}

    be any four nonabelian AG-subgroups of G.

    Here A,B,C and D are fuzzy AG-subgroups of H1,H2,H3 and H4 respectively defined by:

    A={(0,μA(0)),(1,μA(1)),(2,μA(2))}={(0,0.5),(1,0.3),(2,0.3)},
    B={(0,μA(0)),(3,μA(3)),(7,μA(7))}={(0,0.4),(3,0.2),(7,0.2)},
    C={(0,μA(0)),(4,μA(4)),(6,μA(6))}={(0,0.6),(4,0.4),(6,0.4)},

    and

    D={(0,μA(0)),(5,μA(5)),(8,μA(8))}={(0,0.9),(5,0.7),(8,0.7)}.

    Then the following disjoint fuzzy cosets of H1 in G with respect to A are obtained,

    A0={(0,μA(001)),(1,μA(101)),(2,μA(201))}={(0,μA(0)),(2,μA(2)),(4,μA(1))}A0={(0,0.5),(2,0.3),(4,0.3)}=A,
    A1={(0,μA(011)),(1,μA(111)),(2,μA(211))}={(0,μA(1)),(2,μA(0)),(4,μA(2))}A1={(0,0.3),(2,0.5),(4,0.3)},
    A2={(0,μA(021)),(1,μA(121)),(2,μA(221))}={(0,μA(2)),(2,μA(1)),(4,μA(0))}A2={(0,0.0),(2,0.3),(4,0.5)},

    and for all x(GH)

    Ax={(0,μA(0x1)),(1,μA(2x1)),(2,μA(4x1))}Ax=.

    Hence A,A1 and A2 are the three nonempty disjoint fuzzy cosets of H1 in G with respect to fuzzy AG-subgroup A of H1.

    Similarly, all the disjoint fuzzy cosets of B,C and D of H2,H3 and H4 in G respectively can be calculated in the same way.

    It is important to note that if G is a group and H is any subgroup of G, then (Ha)(Hb)Hab, unless H is normal in G. There is no such condition in AG-groups because of the medial law, i.e. if Ha and Hb belongs to G/H, where G is an AG-group and H is an AG-subgroup of G, then

    (Ha)(Hb)=H(ab),

    without having any extra condition on H [39]. Therefore, using this idea, a fuzzy quotient AG-subgroup or a fuzzy factor AG-subgroup can be defined in the following result.

    Theorem 1. Let HG and AF(H). Show that the set G/A={Ax:xG} forms an AG-group under the binary operation defined by AxAy=A(xy)forallx,yG.

    Proof. First we show that the binary operation is well defined. Let x,y,x,yG such that Ax=Ax and Ay=Ay.

    We show that AxAy=AxAy, i.e. A(xy)=A(xy). By definition of fuzzy cosets A of H we get,

    A(xy)={(h,μA(h(xy)1)):hH}={(h,μA(h(x1y1))):hH},(by Lemma 1-(ix)[34])

    and

    A(xy)={(h,μA(h(xy)1)):hH}={(h,μA(h(x1y1)):hH}.(by Lemma 1-(ix)[34])

    Now, for all x,yG,

    μA(h(x1y1))=μA(e(h(x1y1)))=μA(((xy)1(xy))(h(x1y1)))=μA(((x1y1)(xy))(h(x1y1)))=μA(h(((x1y1)(xy))(x1y1)))(by Lemma 1-(iii)[34])=μA(h(((x1y1)(xy))(x1y1)))(by the left invertive law)=μA(((x1y1)(xy))(h(x1y1)))(by Lemma 1-(iii)[34])μA((x1y1)(xy))μA(h(x1y1)).

    Therefore,

    μA(h(x1y1))μA((x1y1)(xy))μA(h(x1y1)). (3.1)

    Now, we show that μA((x1y1)(xy))=μA(e) in Eq (3.1). Since, Ax=Ax using definition of fuzzy cosets, for all hH we obtain

    μA(hx1)=μA(hx1). (3.2)

    Similarly, since Ay=Ay, again using the definition of fuzzy cosets, for all hH we obtain

    μA(hy1)=μA(hy1). (3.3)

    Now, we have

    μA((x1y1)(xy))=μA(((xy)y1)x1),(by the left invertive law)

    substituting h by ((xy)y1) in Eq (3.2) we get,

    μA((x1y1)(xy))=μA(((xy)y1)x1)=μA(x((yy1)x1)) (by Lemma 1-(xiii)[34])=μA((yy1)(xx1)) (by Lemma 1-(iii) [34])=μA((yy1)e)=μA(y1y)=μA(yy1) (by Lemma (1))=μA(yy1)(substituting hby y in Eq (3.3))=μA(e).

    Therefore, Eq (3.1) implies that μA(h(x1y1))μA(h(x1y1)).

    Similarly, one can prove that μA(h(x1y1))μA(h(x1y1)). Consequently, we have

    μA(h(x1y1))=μA(h(x1y1))μA(h(xy)1)=μA(h(xy)1) (by Lemma 1-(ix)[34])A(xy)=A(xy).

    Hence, the binary operation of cosets is well-defined.

    Now we show that G/A forms an AG-group under the binary operation "".

    Groupoid: G/A is a groupoid as the binary operation "" is closed in G/A.

    AG-groupoid: G/A satisfies the left invertive law under the binary operation "". Since for all x,y,zG,

    (AxAy)Az=AxyAz=A((xy)z)=A((zy)x)(by the left invertive law)=AzyAx=(AzAy)Ax.

    Hence, G/A is an AG-groupoid.

    Nonassociative: Again for all x,y,zG,

    (AxAy)Az=AxyAz=A((xy)z)A(x(yz))=Ax(AyAz).

    Therefore, (AxAy)AzAx(AyAz) in general. Hence, G/A is a nonassociative AG-groupoid.

    Existence of Left Identity: For all xG,

    (AAx)=AeAx=A(ex)=Ax,

    but

    (AxA)=AxAe=A(xe)Ax,(in general)

    This implies that A is the left identity of G/A.

    Existence of Inverses: For all xG,

    AxAx1=A(xx1)=Ae=A,

    and

    Ax1Ax=A(x1x)=Ae=A.

    Thus Ax1 is the inverse of Ax for all xG. Hence, G/A is an AG-group.

    Remark 2. An AG-group G/A, defined in Theorem 1, is called fuzzy quotient AG-subgroup or fuzzy factor AG-subgroup.

    Definition 5. Let G be a finite AG-group and HG, if AF(H), then G/A is an AG-group by Theorem 1. The number of distinct cosets of H in G with respect to AF(H) in G/A (called the index of H in G with respect to A) written as [G:A].

    Example 9. Consider the AG-group G of order 4 as in Example 1. Let H={0,1} be any AG-subgroup of G.

    A fuzzy AG-subgroup A of H in G is defined by:

    A={(0,μA(0)),(1,μA(1))}={(0,0.8),(1,0.4)}.

    The distinct fuzzy cosets of H in G with respect to A in G are A and A1. Therefore, G/A={A,A1} is an AG-group under the binary operation between two cosets defined by

    AxAy=A(xy)for all x,yG.

    Here [G:A]=2.

    Example 10. Consider the AG-group G of order 6 as in Example 3. Let H={0,2,4} be an AG-subgroup of G of order 3.

    A fuzzy AG-subgroup A of H in G is given by:

    A={(0,μA(0)),(2,μA(2)),(4,μA(4))}={(0,t0),(2,t1),(4,t1)},

    where t0>t1, and t0,t1[0,1].

    All the distinct fuzzy cosets of H in G with respect to A of H are A,A2 and A4. Therefore, G/A={A,A2,A4} is an AG-group under the binary operation between two cosets defined by

    AxAy=A(xy)forallx,yG.

    G/A satisfies the left invertive law; for all x,y,zG,

    (AxAy)Az=AxyAz=A((xy)z)=A((zy)x)=AzyAx=(AzAy)Ax.

    G/A is nonassociative; because

    (A2A2)A4=A(22)A4=A(04)=A4,

    and

    A2(A2A4)=A2A(24)=A2A2=A(22)=A0=A.

    This implies that

    (A2A2)A4A2(A2A4).

    A is the left identity of G/A, but not the right one, because AAx=A0Ax=A(0x)=Ax, for all xG, but A2A=A(20)=A4.

    Each fuzzy coset in G/A is the inverse of itself, since all the properties of AG-group are satisfied. Hence G/A is an AG-group as shown in Theorem 1. Here [G:A]=3.

    In the following fuzzy AG-subgroup of the quotient AG-group is defined.

    Theorem 2. Let AF(G) and H be any AG-subgroup of G. If B is any fuzzy subset of G/H, defined by

    B={(Hx,μB(Hx)):Hx(G/H)}={(Hx,(μA(z))):zHxand Hx(G/H)},

    then BF(G/H).

    Proof. By definition of coset in AG-groups, for all x,yG, HxHy=H(xy) by medial law. Therefore, for all x,yG, we get

    μB(HxHy)=μB(H(xy))={(μA(z)):zH(xy)}={(μA(uv)):z=uvH(xy)=HxHyuHx,vHy}{(μA(u)μA(v)):uHx,vHy}={((μA(u)):uHx)}{((μA(v)):vHy)}=μB(Hx)μB(Hy).

    This implies that for all x,yG,

    μB(HxHy)μB(Hx)μB(Hy),

    and

    μB(Hx)1=μB(Hx1)={(μA(z)):zHx1}={(μA(w1)):w1Hx1}{(μA(w)):wHx}=μB(Hx).

    This implies that for all xG,

    μB(Hx)1μB(Hx).

    Hence BF(G/H).

    Remark 3. The fuzzy AG-subgroup defined in Theorem 2, is called the Fuzzy AG-subgroup of the Quotient (or Factor) AG-subgroup.

    Example 11. Let G be the AG-group of order 9 as defined in Example 4. Let H={0,1,2} be an AG-subgroup of G. The distinct cosets of H in G are H={0,1,2}, H3={3,4,5} and H6={6,7,8}. Therefore, G/H={H,H3,H6} is an AG-group defined in the following Cayley's table:

    Consider a fuzzy AG-subgroup A of G defined by

    A={(0,μA(0)),(1,μA(1)),(2,μA(2)),(3,μA(3)),(4,μA(4)),(5,μA(5)),(6,μA(6)),(7,μA(7)),(8,μA(8))}={(0,t0),(1,t1),(2,t1),(3,t2),(4,t2),(5,t2),(6,t2),(7,t2),(8,t2)},

    where t0>t1>t2 and t0,t1,t2[0,1].

    Let BFP(G/H) be defined by

    B={(Hx,μB(Hx)):Hx(G/H)}.

    Then the membership μB(Hx) of Hx(G/H) for all xG is given by:

    μB(H)={μA(0),μA(1),μA(2)}={t0,t1,t1}=t0.
    μB(H3)={μA(3),μA(4),μA(5)}={t2,t2,t2}=t2.
    μB(H6)={μA(6),μA(7),μA(8)}={t2,t2,t2}=t2.

    Therefore, B={(H,t0),(H3,t2),(H6,t2)}. It can be easily verified that BF(G/H).

    Example 12. Consider the AG-group G of order 6 as defined in Example 3. Let H={0,2,4} be an AG-subgroup of G. The distinct cosets of H in G are H={0,2,4} and H3={1,3,5}. Therefore, G/H={H,H1} is an AG-group.

    Define a fuzzy AG-subgroup A of G by:

    A={(0,μA(0)),(1,μA(1)),(2,μA(2)),(3,μA(3)),(4,μA(4)),(5,μA(5))}={(0,t0),(1,t2),(2,t1),(3,t2),(4,t1),(5,t2)},

    where t0>t1>t2 and t0,t1,t2[0,1].

    Let BFP(G/H) defined by

    B={(Hx,μB(Hx)):Hx(G/H)}.

    Then the membership μB(Hx) where Hx(G/H) for all xG are given by:

    μB(H)={μA(0),μA(2),μA(4)}={t0,t1,t1}=t0.
    μB(H1)={μA(1),μA(3),μA(5)}={t2,t2,t2}=t2.

    Therefore, B={(H,t0),(H1,t2)}. It can be easily verified that BF(G/H).

    Theorem 3. If H is an AG-subgroup of an AG-group G and AF(H), then Ax=AyA(x)=A(y), for all x,yG.

    Proof. Let Ax=Ay, for all x,yG. This implies that

    μA(hx1)=μA(hy1)for allhH, (4.1)

    putting h=y in Eq (4.1), we get

    μA(yx1)=μA(e)yx1A(by Definition (2.1))(yx1)xA(x)(xx1)yA(x)(by the left invertive law)yA(x).

    Therefore, A(y)A(x).

    Again putting h=x in Eq (4.1), we get

    μA(xx1)=μA(xy1)μA(xy1)=μA(e)xy1A(by Definition 2.1)
    (xy1)yA(y)(yy1)xA(y)(by the left invertive law)xA(y).

    This implies that A(x)A(y). Thus A(y)A(x)A(y). Hence, A(x)=A(y).

    Conversely, let

    A(x)=A(y)A(x)A(y1)=A(y)A(y1)A(xy1)=A(yy1)A(xy1)=A(e)=Axy1A.

    Now for any x,yG, and hH, it follows that

    μA(hx1)=μA(h((y1y)x1))=μA(h((x1y)y1))(by the left invertive law)=μA((x1y)(hy1))(by Lemma 1-(iii)[34])μA(x1y)μA(hy1)(AF(H))=μA((xy1)1)μA(hy1)(by Lemma 1-(ix)[34])=μA(xy1)μA(hy1)(AF(H))=μA(e)μA(hy1)(by Definition 2.1, as xy1A)=μA(hy1).(by Proposition 1)

    This implies that μA(hx1)μA(hy1).

    Similar, we can show that μA(hy1)μA(hx1).

    Consequently, μA(hx1)=μA(hy1). This implies that Ax=Ay (by definition of cosets).

    Theorem 4. If HG and AFN(H) such that Ax=Ay. Then μA(x)=μA(y), for all x,yG.

    Proof. Let x,yG such that

    Ax=AyA(x)=A(y)(by Theorem 3)A(x)A(y1)=A(y)A(y1)A(xy1)=A(yy1)A(xy1)=A(e)=Axy1A.

    Therefore,

    μA(y)=μA(y1)=μA((x1y1)(x1)1)(μAFN(H))=μA((x1y1)x)=μA((xy1)x1)(by the left invertive law)μA(xy1)μA(x1)=μA(e)μA(x)(by Definition 2.1, as xy1A)=μA(x)(by Proposition 1)μA(y)μA(x).

    Similarly, we can show that μA(x)μA(y). This implies that μA(x)μA(y)μA(x). Hence, μA(x)=μA(y).

    Proposition 2. If HG and AFN(H). Then (Ax)(xh)=(Ax)(hx)=μA(h) for any xG and hH.

    Proof. Using definition of fuzzy cosets of H in G with respect to AF(H), for any xG and hH,

    (Ax)(xh)=μA((xh)x1)=μA(h).(asAFN(H))

    Also

    (Ax)(hx)=μA((hx)x1)=μA((x1x)h)(by the left invertive law)=μA(eh)=μA(h).

    Hence (Ax)(xh)=(Ax)(hx)=μA(h), for all xG and hH.

    Definition 6. (Extension Principle) Let X and Y be any two non-empty sets, and f is a function from X into Y. Let AFP(X) and BFP(Y), define the fuzzy subsets f(A)FP(Y) and f1(B)FP(X), for all yY, by

    (f(A))(y)={{μA(x):xX,f(x)=y}if f1(y),0otherwise

    and for all xX,

    (f1(B))(x)=μB(f(x)),

    here f(A) is called the image of μ under f and f1(B) is called the pre-image (or the inverse image) of B under f.

    In the following some important results on fuzzy homomorphism from AG-groups G into G are discussed.

    Theorem 5. Let AF(G) and G be an AG-group. Suppose f is a homomorphism of G into G. Show that f(A)F(G).

    Proof. Here we have two cases:

    (1) Let u,vG. Suppose either uf(G) or vf(G) or both u,vf(G). Then

    (f(A))(u)(f(A))(v)=0(f(A))(uv).(byDefinition6)

    Now assume that uf(G). Then u1f(G). Thus

    (f(A))(u)=0=(f(A))(u1).

    Hence f(A)F(G). (2) Now suppose u,vf(G), then there exist x,yG such that u=f(x) and v=f(y). Then (by Definition 6)

    (f(A))(uv)={μA(z):zG,f(z)=uv}{μA(xy):x,yG,f(x)=u,f(y)=v}{μA(x)μA(y):x,yG,f(x)=u,f(y)=v}({μA(x):xG,f(x)=u})({μA(y):yG,f(y)=v})=(f(A))(u)(f(B))(v).

    Also

    (f(A))(u1)={μA(w):wG,f(w)=u1}={μA(w1):wG,f(w1)=u}=(f(A))(u).

    Hence f(A)F(G).

    Theorem 6. Let BF(G) of an AG-group G and f is a homomorphism from G into G. Show that f1(B)F(G).

    Proof. Suppose x,yG. Then (by Definition 6)

    (f1(B))(xy)=μB(f(xy))=μB(f(x)f(y))(f is a homomorphism)μB(f(x))μB(f(y))(BF(G))=(f1(B))(x)(f1(B))(y).

    Further,

    (f1(B))(x1)=μB(f(x1))=μB((f(x))1)(f is a homomorphism)=μB(f(x))(BF(G))=(f1(B))(x).

    Hence f1(B)F(G).

    Theorem 7. Let AFN(G) and G be an AG-group. If f is an epimorphism from G onto G. Then f(A)FN(G).

    Proof. By Theorem 5, f(A)F(G). Now let x,yG. Since f is onto, then f(u)=x for some uG. Thus

    (f(A))((xy)x1)={μA(z):zG,f(z)=(xy)x1}={μA(z):zG,f(z)=(f(u)y)(f(u))1}={μA(z):zG,f(u)f(z)=f(u)((f(u)y)(f(u))1)}(by cancellation law)={μA(uz):zG,f(uz)=(f(u)y)(f(u)(f(u))1)}(by Lemma 1-(iii)[34])={μA(uz):zG,f(uz)=(f(u)y)e}={μA(uz):zG,f(uz)=(ey)f(u)}(by the left invertive law)={μA(uz):zG,f(uz)f(u1)=(yf(u))f(u1)}={μA(uzu1):zG,f(uzu1)=(f(u1)f(u))y}(by the left invertive law)={μA(z):uzu1G,f(z)=y}={μA(z):zG,f(z)=y}=(fA)(y).

    Therefore, it follows that f(A)FN(G).

    Theorem 8. Let BFN(G) and G be an AG-group. If f is a homomorphism from G into G. Then f1(B)FN(G).

    Proof. By Theorem 6, f1(B)F(G). Now let x,yG. Then

    (f1(B))(xyx1)=μB(f(xyx1))=μB(f(xy)f(x1))=μB((f(x)f(y))(f(x))1) (f is a homomorphism)μB(f(y)) (BF(G))=(f1(B))(y).

    Therefore, it follows that f1(B)FN(G).

    Theorem 9. For any HG, if AFN(H). Then the following assertions hold:

    (1) G/AG/A;

    (2) IfBFP(G/A), defined by B(Ax)=μA(x) for all xG, then BFN(G/A).

    Proof. Let HG and AFN(H).

    (1) Both G/A and G/A are AG-groups by Theorem 1. Define a mapping ϕ:G/AG/A by

    ϕ(Ax)=Axfor allxG.

    By Theorem 3, ϕ is an isomorphism, and AxAy=A(xy) and AxAy=A(xy) holds for all x,yG.

    (2) LetBFP(G/A) be defined by

    B(Ax)=μA(x)for allxG. (5.1)

    We show that BFN(G/A). For all x,yG,

    B(AxAy)=B(A(xy))=μA(xy) (by Eq 5.1)μA(x)μA(y) (ANF(H))=B(Ax)B(Ay),(by Eq 5.1)

    and

    B((Ax)1)=B(Ax1)=μA(x1)μA(x)=B(Ax).

    Hence BF(G/A).

    Next we show that BFN(G/A). For x,yG,

    B((AxAy)(Ay)1)=B(A(xy)Ay1)B((AxAy)(Ay)1)=B(A((xy)y1))=μA((xy)y1) (by Eq 5.1)=μA(y) (AFN(H))=B(Ay). (by Eq 5.1)

    Hence BFN(G/A).

    Theorem 10. Let HG and AFN(H). Then BFP(G/A) defined by B(Ax)=μA(x) for all xG is a fuzzy normal AG-subgroup in G/A.

    Proof. Let HG and AFN(H). Let BFP(G/A) defined by B(Ax)=μA(x). We will show that BFN(G/A). First we will show that the mapping μB:G/A[0,1] iswell-defined.

    For any xG we have

    Ax=Ay(Ax)y1=(Ay)y1(y1x)A=(y1y)A (by the left invertive law)(y1x)A=eA=Ay1xA (by the definition of cosets in AG-groups)μA(y1x)=μA(e)(by Definition 2.1)μA(xy1)=μA(e)(asAF(H))μA((xy1)y)=μA(y)μA((yy1)x)=μA(y)(by the left invertive law)μA(x)=μA(y)B(Ax)=B(Ay).(by definition)

    This implies that the mapping μB is well defined.

    Now we show that B is fuzzy AG-subgroup of G/A. Let Ax and Ay be any arbitrary elements in G/A. Then

    B(AxAy)=B(A(xy)) (by the definition of fuzzy cosets)=μA(xy) (by the definition of B)μA(x)μA(y)=B(Ax)B(Ay)(by the definition of B)

    and

    B((Ax)1)=B(Ax1) (by the definition of cosets)=μA(x1)=μA(x)=B(Ax).

    This implies that B is fuzzy AG-subgroup of G/A.

    Next we show that B is a fuzzy normal AG-subgroup of G/A. For any Ax and Ay in G/A,

    B((AxAy)(Ax)1)=B(A(xy)(Ax1))=B(A((xy)x1))=μA((xy)x1)=μA(y) (AFN(H))=B(Ay).

    Hence BFN(G/A).

    Theorem 11. Let HG and AF(G). Define a mapping θ:GG/A as follows:

    θ(x)=Ax, for allxG.

    Then θ is homomorphism with kernel Ax.

    Proof. Since θ(xy)=A(xy)=AxAy=θ(x)θ(y)for allx,yG, θ is homomorphism. Further, kernel of θ consists of all xG for which

    Ax=AeμA(x)=μA(e), (by Theorem 4)xA.

    Thus Kerθ=A.

    Remark 4. Such a homomorphism exists for every fuzzy AG-subgroup A of H in G and is called natural homomorphism from G onto G/A.

    Definition 7. Let AF(G), and θ be a homomorphism from G into G/A. Then Kerθ={xG:Ax=Ae}={xG:Ax=Ae}.

    In the following, we introduce fuzzy Lagrange's Theorem for AG-groups of finite order.

    Theorem 12. (Fuzzy Lagrange's Theorem for Finite AG-group): Let G be a finite AG-group, H an AG-subgroup of G and AF(H). Then the index of H in G with respect to A divides the order of G.

    Proof. It follows from Theorem 11 that there is a homomorphism θ from G onto G/A, the set of all fuzzy cosets of A, defined in (11). Let H be an AG-subgroup of G defined by H={xG:Ax=Ae}. Let xH, then Ax=AeAx=Ae (by Theorem 3). Therefore H={xG:Ax=Ae}. Now G is a disjoint union of the cosets of an AG-group G with respect to H, i.e.

    G=(H=Hx1)Hx2Hxk, (6.1)

    where x1H and xi(GH), for all 1<ik. Then we show that corresponding to each Hxi;1ik, given in (6.1), there is a fuzzy coset belonging to G/A, and further this correspondence is one-one. To see this, consider any coset Hxi for any hH, ψ(hxi)=A(hxi)=AhAxi=AeAxi=A(exi)=Axi. Thus ψ maps each element of Hxi into the fuzzy cosets Axi.

    Next we show that ψ is well-defined. Consider Hxi=Hxj for each i,jwhere1ikand 1jk. Then

    x1jxiH (cosets in AG-groups)A(x1jxi)=AeA(x1jxi)=Ae (by Theorem 3)A(x1jxi)A(x1i)=AeA(x1i)A((x1jxi)(x1i))=A(e(x1i))A((x1ixi)(x1j))=A(x1i) (by left invertive law)A(x1j)=A(x1i)A(xi)=A(xj)Axi=Axj (by Theorem 3)ψ(Hxi)=ψ(Hxj).

    Thus ψ is well-defined.

    Further, we show that ψ is one-one, for each i,j where 1ik and 1jk. Consider

    ψ(Hxi)=ψ(Hxj)Axi=AxjA(xi)=A(xj) (by Theorem 3)A(x1i)=A(x1j)(cosets in AG-groups)AeA(x1i)=AeA(x1j)A(ex1i)=A(ex1j)A(ex1i)=A((x1ixi)x1j)A(ex1i)=A((x1jxi)x1i)A((x1jxi)x1i)=A(ex1i)A(x1jxi)=AeA(x1jxi)=Ae(x1jxi)HHxi=Hxj. (for each i and j where1ik  and 1jk).

    From the above discussion, it is now clear that the number of distinct cosets of H (index) in G equals the number of fuzzy cosets of A, which is a divisor of the order of G. Hence we conclude that the index of H in G with respect to A also divides the order of G.

    In this paper, a study of fuzzy AG-subgroups of AG-groups is initiated. Fuzzy cosets, quotient AG-subgroups relative to fuzzy AG-subgroups and fuzzy quotient AG-subgroups are defined, various notions and results are provided. Fuzzy Lagrange's theorem for finite AG-groups is stated and proved. The results in this paper are among the very few where non-associative fuzzy algebraic structures have been studied.

    The authors declare that they have no conflict of interest.



    [1] S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, D. U. Hwang, Complex networks: Structure and dynamics, Phys. Rep., 424 (2006), 175–308. https://doi.org/10.1016/j.physrep.2005.10.009 doi: 10.1016/j.physrep.2005.10.009
    [2] F. Battiston, G. Cencetti, I. Iacopini, V. Latora, M. Lucas, A. Patania, et al., Networks beyond pairwise interactions: Structure and dynamics, Phys. Rep., 874 (2020), 1–92. https://doi.org/10.1016/j.physrep.2020.05.004 doi: 10.1016/j.physrep.2020.05.004
    [3] S. Boccaletti, P. De Lellis, C. del Genio, K. Alfaro-Bittner, R. Criado, S. Jalan, et al., The structure and dynamics of networks with higher-order interactions, Phys. Rep., 1018 (2023), 1–64. https://doi.org/10.1016/j.physrep.2023.04.002 doi: 10.1016/j.physrep.2023.04.002
    [4] Z. K. Zhang, C. Liu, A hypergraph model of social tagging networks, J. Stat. Mech.-Theory E., 2010. https://doi.org/10.1088/1742-5468/2010/10/P10005
    [5] X. L. Liu, C. Zhao, Eigenvector centrality in simplicial complexes of hypergraphs, Chaos Interdisc. J. Nonlinear Sci., 33 (2023). https://doi.org/10.1063/5.0144871 doi: 10.1063/5.0144871
    [6] L. Page, S. Brin, R. Motwani, T. Winograd, The pagerank citation ranking: Bringing order to the web, In: Proceedings of the 7th International World Wide Web Conference, 1998,161–172.
    [7] A. R. Benson, Three hypergraph eigenvector centralities, SIAM J. Math. Data Sci., 1 (2019), 293–312. https://doi.org/10.1137/18M1203031 doi: 10.1137/18M1203031
    [8] L. Q. Qi, Z. Y. Luo, Tensor analysis: Spectral theory and special tensors, Society for Industrial and Applied Mathematics, Philadelphia, PA, 2017.
    [9] D. A. Bini, B. Meini, F. Poloni, On the solution of a quadratic vector equation arising in markovian binary trees, Numer. Linear Algebr., 18 (2011), 981–991. https://doi.org/10.1002/nla.809 doi: 10.1002/nla.809
    [10] L. Q. Qi, Y. J. Wang, E. X. Wu, D-eigenvalues of diffusion kurtosis tensors, J. Comput. Appl. Math., 221 (2008), 150–157. https://doi.org/10.1016/j.cam.2007.10.012 doi: 10.1016/j.cam.2007.10.012
    [11] S. L. Hu, L. Q. Qi, G. F. Zhang, Computing the geometric measure of entanglement of multipartite pure states by means of non-negative tensors, Phys. Rev. A, 93 (2016). https://doi.org/10.1103/PhysRevA.93.012304 doi: 10.1103/PhysRevA.93.012304
    [12] A. R. Benson, D. Gleich, J. Leskovec, Tensor spectral clustering for partitioning higher-order network structures, In: Proceedings of the 2015 SIAM International Conference on Data Mining, 2015,118–126. https://epubs.siam.org/doi/abs/10.1137/1.9781611974010.14
    [13] M. Ng, L. Qi, G. L. Zhou, Finding the largest eigenvalue of a nonnegative tensor, SIAM J. Matrix Anal. A., 31 (2009), 1090–1099. https://doi.org/10.1137/09074838X doi: 10.1137/09074838X
    [14] S. Vigna, Spectral ranking, Cambridge University Press, 2016,433–445. https://doi.org/10.1017/nws.2016.21
    [15] E. Estrada, The structure of complex networks: Theory and applications, Oxford University Press, New York, 2012.
    [16] C. D. Meyer, Matrix analysis and applied linear algebra, SIAM, 2023.
    [17] K. J. Pearson, T. Zhang, On spectral hypergraph theory of the adjacency tensor, Graph. Combinator., 30 (2014), 1233–1248. https://doi.org/10.1007/s00373-013-1340-x doi: 10.1007/s00373-013-1340-x
    [18] K. C. Chang, K. J. Pearson, T. Zhang, Some variational principles for z-eigenvalues of nonnegative tensors, Linear Algebra Appl., 438 (2013), 4166–4182. https://doi.org/10.1016/j.laa.2013.02.013 doi: 10.1016/j.laa.2013.02.013
    [19] A. R. Benson, D. Gleich, Computing tensor z-eigenvectors with dynamical systems, SIAM J. Matrix Anal. A., 40 (2019), 1311–1324. https://doi.org/10.1137/18M1229584 doi: 10.1137/18M1229584
    [20] S. G. Aksoy, I. Amburg, S. J. Young, Scalable tensor methods for nonuniform hypergraphs, SIAM J. Math. Data Sci., 6 (2024). https://doi.org/10.1137/23M1584472 doi: 10.1137/23M1584472
    [21] K. C. Chang, T. Zhang, On the uniqueness and non-uniqueness of the positive z-eigenvector for transition probability tensors, J. Math. Anal. Appl., 408 (2013), 525–540. https://doi.org/10.1016/j.jmaa.2013.04.019 doi: 10.1016/j.jmaa.2013.04.019
    [22] K. C. Chang, K. J. Pearson, T. Zhang, Perron-Frobenius theorem for nonnegative tensors, Commun. Math. Sci., 6 (2008), 507–520.
    [23] K. Kovalenko, M. Romance, E. Vasilyeva, D. Aleja, R. Criado, D. Musatov, et al., Vector centrality in hypergraphs, Chaos Soliton. Fract., 162 (2022), 112397. https://doi.org/10.1016/j.chaos.2022.112397 doi: 10.1016/j.chaos.2022.112397
    [24] Y. M. Zhen, J. H. Wang, Community detection in general hypergraph via graph embedding, J. Am. Stat. Assoc., 118 (2022), 1620–1629. https://doi.org/10.1080/01621459.2021.2002157 doi: 10.1080/01621459.2021.2002157
    [25] X. Ouvrard, J. M. Le Goff, S. Marchand-Maillet, Adjacency and tensor representation in general hypergraphs part 1: e-adjacency tensor uniformisation using homogeneous polynomials, arXiv preprint, 2018. https://doi.org/10.48550/arXiv.1712.08189
    [26] A. Banerjee, A. Char, B. Mondal, Spectra of general hypergraphs, Linear Algebra Appl., 518 (2017), 14–30. https://doi.org/10.1016/j.laa.2016.12.022 doi: 10.1016/j.laa.2016.12.022
    [27] N. W. Landry, M. Lucas, I. Iacopini, G. Petri, A. Schwarze, A. Patania, et al., XGI: A Python package for higher-order interaction networks, J. Open Source Softw., 8 (2023). https://doi.org/10.21105/joss.05162
    [28] A. R. Benson, R. Abebe, M. T. Schaub, A. Jadbabaie, J. Kleinberg, Simplicial closure and higher-order link prediction, P. Natl. Acad. Sci., 115 (2018), E11221–E11230. https://doi.org/10.1073/pnas.1800683115 doi: 10.1073/pnas.1800683115
    [29] L. Isella, J. Stehlé, A. Barrat, C. Cattuto, J. F. Pinton, W. Van den Broeck, What's in a crowd? analysis of face-to-face behavioral networks, J. Theor. Biol., 271 (2011), 166–180. https://doi.org/10.1016/j.jtbi.2010.11.033 doi: 10.1016/j.jtbi.2010.11.033
    [30] D. R. Hofstadter, Gödel, Escher, Bach: An Eternal Golden Braid, Basic Books Inc., 1979.
    [31] J. Stehlé, N. Voirin, A. Barrat, C. Cattuto, L. Isella, J. F. Pinton, et al., High-resolution measurements of face-to-face contact patterns in a primary school, PloS One, 6 (2011), e23176. https://doi.org/10.1371/journal.pone.0023176 doi: 10.1371/journal.pone.0023176
    [32] R. Mastrandrea, J. Fournet, A. Barrat, Contact patterns in a high school: A comparison between data collected using wearable sensors, contact diaries and friendship surveys, PloS One, 10 (2015), e0136497. https://doi.org/10.1371/journal.pone.0136497 doi: 10.1371/journal.pone.0136497
    [33] C. Cattuto, W. Van den Broeck, A. Barrat, V. Colizza, J. F. Pinton, A. Vespignani, Dynamics of person-to-person interactions from distributed rfid sensor networks, PloS One, 5 (2010), e11596. https://doi.org/10.1371/journal.pone.0011596 doi: 10.1371/journal.pone.0011596
    [34] K. I. Goh, M. E. Cusick, D. Valle, B. Childs, M. Vidal, A. L. Barabási, The human disease network, P. Natl. Acad. Sci., 104 (2007), 8685–8690. https://doi.org/10.1073/pnas.0701361104 doi: 10.1073/pnas.0701361104
    [35] M. Dewar, J. Healy, X. Pérez-Giménez, P. Prałat, J. Proos, B. Reiniger, et al., Subhypergraphs in non-uniform random hypergraphs, arXiv preprint, 2018. https://doi.org/10.48550/arXiv.1703.07686
    [36] T. G. Kolda, J. R. Mayo, An adaptive shifted power method for computing generalized tensor eigenpairs, SIAM J. Matrix Anal. Appl., 35 (2014), 1563–1581. https://doi.org/10.1137/140951758 doi: 10.1137/140951758
    [37] G. Gallo, G. Longo, S. Pallottino, S. Nguyen, Directed hypergraphs and applications, Discrete Appl. Math., 42 (1993), 177–201. https://doi.org/10.1016/0166-218X(93)90045-P doi: 10.1016/0166-218X(93)90045-P
    [38] G. Contreras-Aso, R. Criado, M. Romance, Beyond directed hypergraphs: Heterogeneous hypergraphs and spectral centralities, J. Complex Netw., 12 (2024), cnae037. https://doi.org/10.1093/comnet/cnae037 doi: 10.1093/comnet/cnae037
    [39] J. L. Guo, X. Y. Zhu, Q. Suo, J. Forrest, Non-uniform evolving hypergraphs and weighted evolving hypergraphs, Sci. Rep., 6 (2016), 36648. https://doi.org/10.1038/srep36648 doi: 10.1038/srep36648
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