707 research outputs found
Spectra of Modular and Small-World Matrices
We compute spectra of symmetric random matrices describing graphs with
general modular structure and arbitrary inter- and intra-module degree
distributions, subject only to the constraint of finite mean connectivities. We
also evaluate spectra of a certain class of small-world matrices generated from
random graphs by introducing short-cuts via additional random connectivity
components. Both adjacency matrices and the associated graph Laplacians are
investigated. For the Laplacians, we find Lifshitz type singular behaviour of
the spectral density in a localised region of small values. In the
case of modular networks, we can identify contributions local densities of
state from individual modules. For small-world networks, we find that the
introduction of short cuts can lead to the creation of satellite bands outside
the central band of extended states, exhibiting only localised states in the
band-gaps. Results for the ensemble in the thermodynamic limit are in excellent
agreement with those obtained via a cavity approach for large finite single
instances, and with direct diagonalisation results.Comment: 18 pages, 5 figure
Design of Easily Synchronizable Oscillator Networks Using the Monte Carlo Optimization Method
Starting with an initial random network of oscillators with a heterogeneous
frequency distribution, its autonomous synchronization ability can be largely
improved by appropriately rewiring the links between the elements. Ensembles of
synchronization-optimized networks with different connectivities are generated
and their statistical properties are studied
Statistical mechanics of budget-constrained auctions
Finding the optimal assignment in budget-constrained auctions is a
combinatorial optimization problem with many important applications, a notable
example being the sale of advertisement space by search engines (in this
context the problem is often referred to as the off-line AdWords problem).
Based on the cavity method of statistical mechanics, we introduce a message
passing algorithm that is capable of solving efficiently random instances of
the problem extracted from a natural distribution, and we derive from its
properties the phase diagram of the problem. As the control parameter (average
value of the budgets) is varied, we find two phase transitions delimiting a
region in which long-range correlations arise.Comment: Minor revisio
Potts q-color field theory and scaling random cluster model
We study structural properties of the q-color Potts field theory which, for
real values of q, describes the scaling limit of the random cluster model. We
show that the number of independent n-point Potts spin correlators coincides
with that of independent n-point cluster connectivities and is given by
generalized Bell numbers. Only a subset of these spin correlators enters the
determination of the Potts magnetic properties for q integer. The structure of
the operator product expansion of the spin fields for generic q is also
identified. For the two-dimensional case, we analyze the duality relation
between spin and kink field correlators, both for the bulk and boundary cases,
obtaining in particular a sum rule for the kink-kink elastic scattering
amplitudes.Comment: 27 pages; 6 figures. Published version, some comments and references
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Combinatorial approach to Modularity
Communities are clusters of nodes with a higher than average density of
internal connections. Their detection is of great relevance to better
understand the structure and hierarchies present in a network. Modularity has
become a standard tool in the area of community detection, providing at the
same time a way to evaluate partitions and, by maximizing it, a method to find
communities. In this work, we study the modularity from a combinatorial point
of view. Our analysis (as the modularity definition) relies on the use of the
configurational model, a technique that given a graph produces a series of
randomized copies keeping the degree sequence invariant. We develop an approach
that enumerates the null model partitions and can be used to calculate the
probability distribution function of the modularity. Our theory allows for a
deep inquiry of several interesting features characterizing modularity such as
its resolution limit and the statistics of the partitions that maximize it.
Additionally, the study of the probability of extremes of the modularity in the
random graph partitions opens the way for a definition of the statistical
significance of network partitions.Comment: 8 pages, 4 figure
Replica bounds for diluted non-Poissonian spin systems
In this paper we extend replica bounds and free energy subadditivity
arguments to diluted spin-glass models on graphs with arbitrary, non-Poissonian
degree distribution. The new difficulties specific of this case are overcome
introducing an interpolation procedure that stresses the relation between
interpolation methods and the cavity method. As a byproduct we obtain
self-averaging identities that generalize the Ghirlanda-Guerra ones to the
multi-overlap case.Comment: Latex file, 15 pages, 2 eps figures; Weak point revised and
corrected; Misprints correcte
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