Individuals are always limited by some inelastic resources, such as time and energy, which restrict them to dedicate to social interaction and limit their contact capacity. Contact capacity plays an important role in dynamics of social contagions, which so far has eluded theoretical analysis. In this paper, we first propose a non-Markovian model to understand the effects of contact capacity on social contagions, in which each individual can only contact and transmit the information to a finite number of neighbors. We then develop a heterogeneous edge-based compartmental theory for this model, and a remarkable agreement with simulations is obtained. Through theory and simulations, we find that enlarging the contact capacity makes the network more fragile to behavior spreading. Interestingly, we find that both the continuous and discontinuous dependence of the final adoption size on the information transmission probability can arise. And there is a crossover phenomenon between the two types of dependence. More specifically, the crossover phenomenon can be induced by enlarging the contact capacity only when the degree exponent is above a critical degree exponent, while the the final behavior adoption size always grows continuously for any contact capacity when degree exponent is below the critical degree exponent.
In this paper, we consider the dynamic power control for delay-aware D2D communications. The stochastic optimization problem is formulated as an infinite horizon average cost Markov decision process. To deal with the curse of dimensionality, we utilize the interference filtering property of the CSMA-like MAC protocol and derive a closed-form approximate priority function and the associated error bound using perturbation analysis. Based on the closed-form approximate priority function, we propose a low-complexity power control algorithm solving the per-stage optimization problem. The proposed solution is further shown to be asymptotically optimal for a sufficiently large carrier sensing distance. Finally, the proposed power control scheme is compared with various baselines through simulations, and it is shown that significant performance gain can be achieved.
The naturally weak spin-orbit coupling in Graphene can be largely enhanced by adatom deposition (e.g. Weeks et al. Phys. Rev. X 1, 021001 (2011)). However, the dynamics of the adatoms also induces a coupling between phonons and the electron spin. Using group theory and a tight-binding model, we systematically investigate the coupling between the low-energy in-plane phonons and the electron spin in single-layer graphene uniformly decorated with heavy adatoms. Our results provide the foundation for future investigations of spin transport and superconductivity in this system. In order to quantify the effect of the coupling to the lattice on the electronic spin dynamics, we compute the spin-flip rate of electrons and holes. We show that the latter exhibits a strong dependence on the quasi-particle energy and system temperature.
In cloud radio access networks (C-RANs), the baseband units and radio units of base stations are separated, which requires high-capacity fronthaul links connecting both parts. In this paper, we consider the delay-aware fronthaul allocation problem for C-RANs. The stochastic optimization problem is formulated as an infinite horizon average cost Markov decision process. To deal with the curse of dimensionality, we derive a closed-form approximate priority function and the associated error bound using perturbation analysis. Based on the closed-form approximate priority function, we propose a low-complexity delay-aware fronthaul allocation algorithm solving the per-stage optimization problem. The proposed solution is further shown to be asymptotically optimal for sufficiently small cross link path gains. Finally, the proposed fronthaul allocation algorithm is compared with various baselines through simulations, and it is shown that significant performance gain can be achieved.
Epidemic threshold is one of the most important features of the epidemic dynamics. Through a lot of numerical simulations in classic Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Susceptible (SIS) models on various types of networks, we study the simulated identification of epidemic thresholds on finite-size networks. We confirm that the susceptibility measure goes awry for the SIR model due to the bimodal distribution of outbreak sizes near the critical point, while the simulated thresholds of the SIS and SIR models can be accurately determined by analyzing the peak of the epidemic variability. We further verify the accuracy of theoretical predictions derived by the heterogeneous mean-field theory (HMF) and the quenched mean-field theory (QMF), by comparing them with the simulated threshold of the SIR model obtained from the variability measure. The results show that the HMF prediction agrees very well with the simulated threshold, except the case that the networks are disassortive, in which the QMF prediction is more close to the simulated threshold.
A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w1 and w0 occur with probabilities p and 1-p, respectively. The fraction of infected nodes rho(p) shows a non-monotonic behavior, with rho drops with p for small p and increases for large p. For small to moderate w1/w0 ratios, rho(p) exhibits a minimum that signifies an optimal suppression. For large w1/w0 ratios, the suppression leads to an absorbing phase consisting only of healthy nodes within a range p_L =< p =< p_R, and an active phase with mixed infected and healthy nodes for p < p_L and p>p_R. A mean field theory that ignores spatial correlation is shown to give qualitative agreement and capture all the key features. A physical picture that emphasizes the intricate interplay between infections via w0 links and within clusters formed by nodes carrying the w1 links is presented. The absorbing state at large w1/w0 ratios results when the clusters are big enough to disrupt the spread via w0 links and yet small enough to avoid an epidemic within the clusters. A theory that uses the possible local environments of a node as variables is formulated. The theory gives results in good agreement with simulation results, thereby showing the necessity of including longer spatial correlations.
Recently, the impacts of spatiotemporal heterogeneities of human activities on spreading dynamics have attracted extensive attention. In this paper, to study heterogeneous response times on information spreading, we focus on the susceptible-infected spreading dynamics with adjustable power-law response time distribution based on uncorrelated scale-free networks. We find that the stronger the heterogeneity of response times is, the faster the information spreading is in the early and middle stages. Following a given heterogeneity, the procedure of reducing the correlation between the response times and degrees of individuals can also accelerate the spreading dynamics in the early and middle stages. However, the dynamics in the late stage is slightly more complicated, and there is an optimal value of the full prevalence time changing with the heterogeneity of response times and the response time-degree correlation, respectively. The optimal phenomena results from the efficient allocation of heterogeneous response times.
A precise measurement of the atmospheric mass-squared splitting |Delta m^2_{mumu}| is crucial to establish the three-flavor paradigm and to constrain the neutrino mass models. In addition, a precise value of |Delta m^2_{mumu}| will significantly enhance the hierarchy reach of future medium-baseline reactor experiments like JUNO and RENO-50. In this work, we explore the precision in |Delta m^2_{mumu}| that will be available after the full runs of T2K and NOvA. We find that the combined data will be able to improve the precision in |Delta m^2_{mumu}| to sub-percent level for maximal 2-3 mixing. Depending on the true value of sin^2theta_{23} in the currently-allowed 3 sigma range, the precision in |Delta m^2_{mumu}| will vary from 0.87% to 1.24%. We further demonstrate that this is a robust measurement as it remains almost unaffected by the present uncertainties in theta_{13}, delta_{CP}, the choice of mass hierarchy, and the systematic errors.
We consider generation of dark matter mass via radiative electroweak symmetry breaking in an extension of the conformal Standard Model containing a singlet scalar field with a Higgs portal interaction. Generating the mass from a sequential process of radiative electroweak symmetry breaking followed by a conventional Higgs mechanism can account for less than 35% of the cosmological dark matter abundance for dark matter mass $M_s>80 GeV$. However in a dynamical approach where both Higgs and scalar singlet masses are generated via radiative electroweak symmetry breaking we obtain much higher levels of dark matter abundance. At one-loop level we find abundances of 10%--100% with $106 GeV<M_s<120 GeV$. However, when the higher-order effects needed for consistency with a $125 GeV$ Higgs mass are estimated, the abundance becomes 10%--80% for $80 GeV<M_s<96 GeV$, representing a significant decrease in the dark matter mass. The dynamical approach also predicts a small scalar-singlet self-coupling, providing a natural explanation for the astrophysical observations that place upper bounds on dark matter self-interaction. The predictions in all three approaches are within the $M_s>80 GeV$ detection region of the next generation XENON experiment.
We report new detections of thermal emission from the transiting hot Jupiter WASP-43b in the H and Ks-bands as observed at secondary eclipses. The observations were made with the WIRCam instrument on the CFHT. We obtained a secondary eclipse depth of 0.103$_{-0.017}^{+0.017}%$ and 0.194$_{-0.029}^{+0.029}%$ in the H and Ks-bands, respectively. The Ks band depth is consistent with previous measurement in the narrow band centered at 2.09um by Gillon et al. (2012). Our eclipse depths in both bands are consistent with a blackbody spectrum with a temperature of ~1850 K, slightly higher than the dayside equilibrium temperature without day-night energy redistribution. Based on theoretical models of the dayside atmosphere of WASP-43b, our data constrain the day-night energy redistribution in the planet to be $lesssim 15-25$%, depending on the metal content in the atmosphere. Combined with energy balance arguments our data suggest that a strong temperature inversion is unlikely in the dayside atmosphere of WASP-43b. However, a weak inversion cannot be strictly ruled out at the current time. Future observations are required to place detailed constraints on the chemical composition of the atmosphere.
