Glass transition and random walks on complex energy landscapes

We present a simple mathematical model of glassy dynamics seen as a random walk in a directed, weighted network of minima taken as a representation of the energy landscape. Our approach gives a broader perspective to previous studies focusing on particular examples of energy landscapes obtained by sampling energy minima and saddles of small systems. We point out how the relation between the energies of the minima and their number of neighbors should be studied in connection with the network's global topology, and show how the tools developed in complex network theory can be put to use in this context

On the definition of temperature in dense granular media

In this Letter we report the measurement of a pseudo-temperature for compacting granular media on the basis of the Fluctuation-Dissipation relations in the aging dynamics of a model system. From the violation of the Fluctuation-Dissipation Theorem an effective temperature emerges (a dynamical temperature T_{dyn}) whose ratio with the equilibrium temperature T_d^{eq} depends on the particle density. We compare the results for the Fluctuation-Dissipation Ratio (FDR) T_{dyn}/T_d^{eq} at several densities with the outcomes of Edwards' approach at the corresponding densities. It turns out that the FDR and the so-called Edwards' ratio coincide at several densities (very different ages of the system), opening in this way the door to experimental checks as well as theoretical constructions.Comment: RevTex4 4 pages, 4 eps figure

Modeling the evolution of weighted networks

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement mechanism coupled to the local network growth. That coupling can be generalized in order to include the effect of additional randomness and non-linearities which can be present in real-world networks. The model generates weighted graphs exhibiting the statistical properties observed in several real-world systems. In particular, the model yields a non-trivial time evolution of vertices properties and scale-free behavior with exponents depending on the microscopic parameters characterizing the coupling rules. Very interestingly, the generated graphs spontaneously achieve a complex hierarchical architecture characterized by clustering and connectivity correlations varying as a function of the vertices' degree

Basins of attraction of metastable states of the spherical pp-spin model

We study the basins of attraction of metastable states in the spherical $p$-spin spin glass model, starting the relaxation dynamics at a given distance from a thermalized condition. Weighting the initial condition with the Boltzmann distribution we find a finite size for the basins. On the contrary, a white weighting of the initial condition implies vanishing basins of attraction. We make the corresponding of our results with the ones of a recently constructed effective potential.Comment: LaTeX, 7 pages, 7 eps figure

Dynamical and bursty interactions in social networks

We present a modeling framework for dynamical and bursty contact networks made of agents in social interaction. We consider agents' behavior at short time scales, in which the contact network is formed by disconnected cliques of different sizes. At each time a random agent can make a transition from being isolated to being part of a group, or vice-versa. Different distributions of contact times and inter-contact times between individuals are obtained by considering transition probabilities with memory effects, i.e. the transition probabilities for each agent depend both on its state (isolated or interacting) and on the time elapsed since the last change of state. The model lends itself to analytical and numerical investigations. The modeling framework can be easily extended, and paves the way for systematic investigations of dynamical processes occurring on rapidly evolving dynamical networks, such as the propagation of an information, or spreading of diseases

Mean-field diffusive dynamics on weighted networks

Diffusion is a key element of a large set of phenomena occurring on natural and social systems modeled in terms of complex weighted networks. Here, we introduce a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks. We also propose the concept of annealed weighted networks, in which such equations become exact. We show the validity of our approach addressing the problem of the random walk process, pointing out a strong departure of the behavior observed in quenched real scale-free networks from the mean-field predictions. Additionally, we show how to employ our formalism for more complex dynamics. Our work sheds light on mean-field theory on weighted networks and on its range of validity, and warns about the reliability of mean-field results for complex dynamics.Comment: 8 pages, 3 figure

Metastable configurations of spin models on random graphs

One-flip stable configurations of an Ising-model on a random graph with fluctuating connectivity are examined. In order to perform the quenched average of the number of stable configurations we introduce a global order-parameter function with two arguments. The analytical results are compared with numerical simulations.Comment: 11 pages Revtex, minor changes, to appear in Phys. Rev.

Inter- and Intra-Chain Attractions in Solutions of Flexible Polyelectrolytes at Nonzero Concentration

Constant temperature molecular dynamics simulations were used to study solutions of flexible polyelectrolyte chains at nonzero concentrations with explicit counterions and unscreened coulombic interactions. Counterion condensation, measured via the self-diffusion coefficient of the counterions, is found to increase with polymer concentration, but contrary to the prediction of Manning theory, the renormalized charge fraction on the chains decreases with increasing Bjerrum length without showing any saturation. Scaling analysis of the radius of gyration shows that the chains are extended at low polymer concentrations and small Bjerrum lengths, while at sufficiently large Bjerrum lengths, the chains shrink to produce compact structures with exponents smaller than a gaussian chain, suggesting the presence of attractive intrachain interactions. A careful study of the radial distribution function of the center-of-mass of the polyelectrolyte chains shows clear evidence that effective interchain attractive interactions also exist in solutions of flexible polyelectrolytes, similar to what has been found for rodlike polyelectrolytes. Our results suggest that the broad maximum observed in scattering experiments is due to clustering of chains.Comment: 12 pages, REVTeX, 15 eps figure

Voter models on weighted networks

We study the dynamics of the voter and Moran processes running on top of complex network substrates where each edge has a weight depending on the degree of the nodes it connects. For each elementary dynamical step the first node is chosen at random and the second is selected with probability proportional to the weight of the connecting edge. We present a heterogeneous mean-field approach allowing to identify conservation laws and to calculate exit probabilities along with consensus times. In the specific case when the weight is given by the product of nodes' degree raised to a power theta, we derive a rich phase-diagram, with the consensus time exhibiting various scaling laws depending on theta and on the exponent of the degree distribution gamma. Numerical simulations give very good agreement for small values of |theta|. An additional analytical treatment (heterogeneous pair approximation) improves the agreement with numerics, but the theoretical understanding of the behavior in the limit of large |theta| remains an open challenge.Comment: 21 double-spaced pages, 6 figure

Weighted Scale-free Networks in Euclidean Space Using Local Selection Rule

A spatial scale-free network is introduced and studied whose motivation has been originated in the growing Internet as well as the Airport networks. We argue that in these real-world networks a new node necessarily selects one of its neighbouring local nodes for connection and is not controlled by the preferential attachment as in the Barab\'asi-Albert (BA) model. This observation has been mimicked in our model where the nodes pop-up at randomly located positions in the Euclidean space and are connected to one end of the nearest link. In spite of this crucial difference it is observed that the leading behaviour of our network is like the BA model. Defining link weight as an algebraic power of its Euclidean length, the weight distribution and the non-linear dependence of the nodal strength on the degree are analytically calculated. It is claimed that a power law decay of the link weights with time ensures such a non-linear behavior. Switching off the Euclidean space from the same model yields a much simpler definition of the Barab\'asi-Albert model where numerical effort grows linearly with $N$.Comment: 6 pages, 6 figure