The local spectra of regular line graphs

The local spectrum of a graph G = (V, E), constituted by the standard eigenvalues of G and their local multiplicities, plays a similar role as the global spectrum when the graph is “seen” from a given vertex. Thus, for each vertex i ∈ V , the i-local multiplicities of all the eigenvalues add up to 1; whereas the multiplicity of each eigenvalue λ of G is the sum, extended to all vertices, of its local multiplicities. In this work, using the interpretation of an eigenvector as a charge distribution on the vertices, we compute the local spectrum of the line graph LG in terms of the local spectrum of the regular graph G it derives from. Furthermore, some applications of this result are derived as, for instance, some results about the number of circuits of LG

The hierarchical product of graphs

A new operation on graphs is introduced and some of its properties are studied. We call it hierarchical product, because of the strong (connectedness) hierarchy of the vertices in the resulting graphs. In fact, the obtained graphs turn out to be subgraphs of the cartesian product of the corresponding factors. Some well-known properties of the cartesian product, such as a reduced mean distance and diameter, simple routing algorithms and some optimal communication protocols are inherited by the hierarchical product. We also address the study of some algebraic properties of the hierarchical product of two or more graphs. In particular, the spectrum of the binary hypertree $T_m$ (which is the hierarchical product of several copies of the complete graph on two vertices) is fully characterized; turning out to be an interesting example of graph with all its eigenvalues distinct. Finally, some natural generalizations of the hierarchic product are proposed

Estudi i disseny de grans xarxes d'interconnexió: modularitat i comunicació

Normalment les grans xarxes d'interconnexió o de comunicacions estan dissenyades utilitzant tècniques de la teoria de grafs. Aquest treball presenta algunes contribucions a aquest tema. Concretament, presentem dues noves operacions: el "producte Jeràrquic" de grafs i el "producte Manhattan" de digrafs. El primer és una generalització del producte cartesià de grafs i ens permet construir algunes famílies amb un alt grau de jerarquia, com l'arbre binomial, que és una estructura de dades molt utilitzada en algorísmica. El segon dóna lloc a les conegudes Manhattan Street Networks, les quals han estat extensament estudiades i utilitzades per modelar algunes classes de xarxes òptiques. En el nostre treball, definim formalment i analitzem el cas multidimensional d'aquestes xarxes. Estudiem algunes propietats dels grafs o digrafs obtinguts mitjançant les dues operacions esmentades, especialment: els paràmetres estructurals (les propietats de l'operació, els subdigrafs induïts, la distribució de graus i l'estructura de digraf línia), els paràmetres mètrics (el diàmetre, el radi i la distància mitjana), la simetria (els grups d'automorfismes i els digrafs de Cayley), l'estructura de cicles (els cicles hamiltonians i la descomposició en cicles hamiltonians arc-disjunts) i les propietats espectrals (els valors i vectors propis). En el darrer cas, hem trobat, per exemple, que la família dels arbres binomials tenen tots els seus valors propis diferents, "omplint" tota la recta real. A més a més, mostrem la relació del seu conjunt de vectors propis amb els polinomis de Txebishev de segona espècie. També hem estudiat alguns protocols de comunicació, com els enrutaments locals i els algorismes de difusió. Finalment, presentem alguns models deterministes (com les xarxes Sierpinski i d'altres), els quals presenten algunes propietats pròpies de les xarxes complexes reals (com, per exemple, Internet).Large interconnection or communication networks are usually designed and studied by using techniques from graph theory. This work presents some contributions to this subject. With this aim, two new operations are proposed: the "hierarchical product" of graphs and the "Manhattan product" of digraphs. The former can be seen as a generalization of the Cartesian product of graphs and allows us to construct some interesting families with a high degree of hierarchy, such as the well-know binomial tree, which is a data structure very used in the context of computer science. The latter yields, in particular, the known topologies of Manhattan Street Networks, which has been widely studied and used for modelling some classes of light-wave networks. In this thesis, a multidimensional approach is analyzed. Several properties of the graphs or digraphs obtained by both operations are dealt with, but special attention is paid to the study of their structural parameters (operation properties, induced subdigraphs, degree distribution and line digraph structure), metric parameters (diameter, radius and mean distance), symmetry (automorphism groups and Cayley digraphs), cycle structure (Hamilton cycles and arc-disjoint Hamiltonian decomposition) and spectral properties (eigenvalues and eigenvectors). For instance, with respect to the last issue, it is shown that some families of hypertrees have spectra with all different eigenvalues "filling up" all the real line. Moreover, we show the relationship between its eigenvector set and Chebyshev polynomials of the second kind. Also some protocols of communication, such as local routing and broadcasting algorithms, are addressed. Finally, some deterministic models (Sierpinsky networks and others) having similar properties as some real complex networks, such as the Internet, are presented

The local spectra of regular line graphs

The local spectrum of a graph G = (V, E), constituted by the standard eigenvalues of G and their local multiplicities, plays a similar role as the global spectrum when the graph is “seen” from a given vertex. Thus, for each vertex i ∈ V , the i-local multiplicities of all the eigenvalues add up to 1; whereas the multiplicity of each eigenvalue λ of G is the sum, extended to all vertices, of its local multiplicities. In this work, using the interpretation of an eigenvector as a charge distribution on the vertices, we compute the local spectrum of the line graph LG in terms of the local spectrum of the regular graph G it derives from. Furthermore, some applications of this result are derived as, for instance, some results about the number of circuits of LG

The local spectra of regular line graphs

The local spectrum of a graph G = (V, E), constituted by the standard eigenvalues of G and their local multiplicities, plays a similar role as the global spectrum when the graph is “seen” from a given vertex. Thus, for each vertex i ∈ V , the i-local multiplicities of all the eigenvalues add up to 1; whereas the multiplicity of each eigenvalue λ of G is the sum, extended to all vertices, of its local multiplicities. In this work, using the interpretation of an eigenvector as a charge distribution on the vertices, we compute the local spectrum of the line graph LG in terms of the local spectrum of the regular graph G it derives from. Furthermore, some applications of this result are derived as, for instance, some results about the number of circuits of LG