Non mean-field behavior of the contact process on scale-free networks

We present an analysis of the classical contact process on scale-free networks. A mean-field study, both for finite and infinite network sizes, yields an absorbing-state phase transition at a finite critical value of the control parameter, characterized by a set of exponents depending on the network structure. Since finite size effects are large and the infinite network limit cannot be reached in practice, a numerical study of the transition requires the application of finite size scaling theory. Contrary to other critical phenomena studied previously, the contact process in scale-free networks exhibits a non-trivial critical behavior that cannot be quantitatively accounted for by mean-field theory.Comment: 5 pages, 4 figures, published versio

Optimization of Network Robustness to Waves of Targeted and Random Attack

We study the robustness of complex networks to multiple waves of simultaneous (i) targeted attacks in which the highest degree nodes are removed and (ii) random attacks (or failures) in which fractions $p_t$ and $p_r$ respectively of the nodes are removed until the network collapses. We find that the network design which optimizes network robustness has a bimodal degree distribution, with a fraction $r$ of the nodes having degree k_2= (\kav - 1 +r)/r and the remainder of the nodes having degree $k_1=1$, where \kav is the average degree of all the nodes. We find that the optimal value of $r$ is of the order of $p_t/p_r$ for $p_t/p_r\ll 1$

Mechanical properties of wood-derived silicon carbide aluminum-alloy composites as a function of temperature

The mechanical behavior [i.e., stiffness, strength, and toughness (K_(IC))] of SiC Al–Si–Mg metal–ceramic composites (50:50 by volume) was studied at temperatures ranging from 25 to 500 °C. The SiC phase was derived from wood precursors, which resulted in an interconnected anisotropic ceramic that constrained the pressure melt-infiltrated aluminum alloy. The composites were made using SiC derived from two woods (sapele and beech) and were studied in three orthogonal orientations. The mechanical properties and corresponding deformation micromechanisms were different in the longitudinal (LO) and transverse directions, but the influence of the precursor wood was small. The LO behavior was controlled by the rigid SiC preform and the load transfer from the metal to the ceramic. Moduli in this orientation were lower than the Halpin–Tsai predictions due to the nonlinear and nonparallel nature of the Al-filled pores. The LO K_(IC) agreed with the Ashby model for the K_(IC) contribution of ductile inclusions in a brittle ceramic

Heterogeneous pair approximation for voter models on networks

For models whose evolution takes place on a network it is often necessary to augment the mean-field approach by considering explicitly the degree dependence of average quantities (heterogeneous mean-field). Here we introduce the degree dependence in the pair approximation (heterogeneous pair approximation) for analyzing voter models on uncorrelated networks. This approach gives an essentially exact description of the dynamics, correcting some inaccurate results of previous approaches. The heterogeneous pair approximation introduced here can be applied in full generality to many other processes on complex networks.Comment: 6 pages, 6 figures, published versio

Extremal dynamics on complex networks: Analytic solutions

The Bak-Sneppen model displaying punctuated equilibria in biological evolution is studied on random complex networks. By using the rate equation and the random walk approaches, we obtain the analytic solution of the fitness threshold $x_c$ to be 1/(_f+1), where _f=/ (=) in the quenched (annealed) updating case, where is the n-th moment of the degree distribution. Thus, the threshold is zero (finite) for the degree exponent \gamma 3) for the quenched case in the thermodynamic limit. The theoretical value x_c fits well to the numerical simulation data in the annealed case only. Avalanche size, defined as the duration of successive mutations below the threshold, exhibits a critical behavior as its distribution follows a power law, P_a(s) ~ s^{-3/2}.Comment: 6 pages, 2 figure

Surface phase transitions in one-dimensional channels arranged in a triangular cross-sectional structure: Theory and Monte Carlo simulations

Monte Carlo simulations and finite-size scaling analysis have been carried out to study the critical behavior in a submonolayer lattice-gas of interacting monomers adsorbed on one-dimensional channels arranged in a triangular cross-sectional structure. The model mimics a nanoporous environment, where each nanotube or unit cell is represented by a one-dimensional array. Two kinds of lateral interaction energies have been considered: $1)$ $w_L$, interaction energy between nearest-neighbor particles adsorbed along a single channel and $2)$ $w_T$, interaction energy between particles adsorbed across nearest-neighbor channels. For $w_L/w_T=0$ and $w_T > 0$, successive planes are uncorrelated, the system is equivalent to the triangular lattice and the well-known $(\sqrt{3} \times \sqrt{3})$ $[(\sqrt{3} \times \sqrt{3})^*]$ ordered phase is found at low temperatures and a coverage, $\theta$, of 1/3 $[2/3]$. In the more general case ($w_L/w_T \neq 0$ and $w_T > 0$), a competition between interactions along a single channel and a transverse coupling between sites in neighboring channels allows to evolve to a three-dimensional adsorbed layer. Consequently, the $(\sqrt{3} \times \sqrt{3})$ and $(\sqrt{3} \times \sqrt{3})^*$ structures "propagate" along the channels and new ordered phases appear in the adlayer. The Monte Carlo technique was combined with the recently reported Free Energy Minimization Criterion Approach (FEMCA), to predict the critical temperatures of the order-disorder transformation. The excellent qualitative agreement between simulated data and FEMCA results allow us to interpret the physical meaning of the mechanisms underlying the observed transitions.Comment: 24 pages, 6 figure

Constraining the cosmic radiation density due to lepton number with Big Bang Nucleosynthesis

The cosmic energy density in the form of radiation before and during Big Bang Nucleosynthesis (BBN) is typically parameterized in terms of the effective number of neutrinos N_eff. This quantity, in case of no extra degrees of freedom, depends upon the chemical potential and the temperature characterizing the three active neutrino distributions, as well as by their possible non-thermal features. In the present analysis we determine the upper bounds that BBN places on N_eff from primordial neutrino--antineutrino asymmetries, with a careful treatment of the dynamics of neutrino oscillations. We consider quite a wide range for the total lepton number in the neutrino sector, eta_nu= eta_{nu_e}+eta_{nu_mu}+eta_{nu_tau} and the initial electron neutrino asymmetry eta_{nu_e}^in, solving the corresponding kinetic equations which rule the dynamics of neutrino (antineutrino) distributions in phase space due to collisions, pair processes and flavor oscillations. New bounds on both the total lepton number in the neutrino sector and the nu_e -bar{nu}_e asymmetry at the onset of BBN are obtained fully exploiting the time evolution of neutrino distributions, as well as the most recent determinations of primordial 2H/H density ratio and 4He mass fraction. Note that taking the baryon fraction as measured by WMAP, the 2H/H abundance plays a relevant role in constraining the allowed regions in the eta_nu -eta_{nu_e}^in plane. These bounds fix the maximum contribution of neutrinos with primordial asymmetries to N_eff as a function of the mixing parameter theta_13, and point out the upper bound N_eff < 3.4. Comparing these results with the forthcoming measurement of N_eff by the Planck satellite will likely provide insight on the nature of the radiation content of the universe.Comment: 17 pages, 9 figures, version to be published in JCA

A New Analysis Method for Simulations Using Node Categorizations

Most research concerning the influence of network structure on phenomena taking place on the network focus on relationships between global statistics of the network structure and characteristic properties of those phenomena, even though local structure has a significant effect on the dynamics of some phenomena. In the present paper, we propose a new analysis method for phenomena on networks based on a categorization of nodes. First, local statistics such as the average path length and the clustering coefficient for a node are calculated and assigned to the respective node. Then, the nodes are categorized using the self-organizing map (SOM) algorithm. Characteristic properties of the phenomena of interest are visualized for each category of nodes. The validity of our method is demonstrated using the results of two simulation models. The proposed method is useful as a research tool to understand the behavior of networks, in particular, for the large-scale networks that existing visualization techniques cannot work well.Comment: 9 pages, 8 figures. This paper will be published in Social Network Analysis and Mining(www.springerlink.com