arXiv subjects

Ying-Hai Wang

Publications and source records attributed to Ying-Hai Wang.

At least 19 recordsLinked to original sources

arXiv2008

Influence of synaptic interaction on firing synchronization and spike death in excitatory neuronal networks

We investigated the influence of efficacy of synaptic interaction on firing synchronization in excitatory neuronal networks. We found spike death phenomena, namely, the state of neurons transits from limit cycle to fixed point or transient state. The phenomena occur under the perturbation of excitatory synaptic interaction that has a high efficacy. We showed that the decrease of synaptic current results in spike death through depressing the feedback of sodium ionic current. In the networks with spike death property the degree of synchronization is lower and unsensitive to the heterogeneity of neurons. The mechanism of the influence is that the transition of neuron state disrupts the adjustment of the rhythm of neuron oscillation and prevents further increase of firing synchronization.

cond-mat.dis-nn↗

arXiv2008

Simple reaction-diffusion population model on scale-free networks

We study a simple reaction-diffusion population model [proposed by A. Windus and H. J. Jensen, J. Phys. A: Math. Theor. 40, 2287 (2007)] on scale-free networks. In the case of fully random diffusion, the network topology cannot affect the critical death rate, whereas the heterogeneous connectivity can cause smaller steady population density and critical population density. In the case of modified diffusion, we obtain a larger critical death rate and steady population density, at the meanwhile, lower critical population density, which is good for the survival of species. The results were obtained using a mean-field-like framework and were confirmed by computer simulations.

physics.soc-ph↗

arXiv2008

Projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks

We study projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks. We relax some limitations of previous work, where projective-anticipating and projective-lag synchronization can be achieved only on two coupled chaotic systems. In this paper, we can realize projective-anticipating and projective-lag synchronization on complex dynamical networks composed by a large number of interconnected components. At the same time, although previous work studied projective synchronization on complex dynamical networks, the dynamics of the nodes are coupled partially linear chaotic systems. In this paper, the dynamics of the nodes of the complex networks are time-delayed chaotic systems without the limitation of the partial-linearity. Based on the Lyapunov stability theory, we suggest a generic method to achieve the projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random dynamical networks and find both the existence and sufficient stability conditions. The validity of the proposed method is demonstrated and verified by examining specific examples using Ikeda and Mackey-Glass systems on Erdos-Renyi networks.

physics.soc-ph↗

arXiv2008

Promote cooperation by localised small-world communication

The emergence and maintenance of cooperation within sizable groups of unrelated humans offer many challenges for our understanding. We propose that the humans' capacity of communication, such as how many and how far away the fellows can build up mutual communications, may affect the evolution of cooperation. We study this issue by means of the public goods game (PGG) with a two-layered network of contacts. Players obtain payoffs from five-person public goods interactions on a square lattice (the interaction layer). Also, they update strategies after communicating with neighbours in learning layer, where two players build up mutual communication with a power law probability depending on their spatial distance. Our simulation results indicate that the evolution of cooperation is indeed sensitive to how players choose others to communicate with, including the amount as well as the locations. The tendency of localised communication is proved to be a new mechanism to promote cooperation.

physics.soc-ph↗

arXiv2007

Cooperation enhanced by the difference between interaction and learning neighborhoods for evolutionary spatial prisoner's dilemma games

We study an evolutionary prisoner's dilemma game with two layered graphs, where the lower layer is the physical infrastructure on which the interactions are taking place and the upper layer represents the connections for the strategy adoption (learning) mechanism. This system is investigated by means of Monte Carlo simulations and an extended pair-approximation method. We consider the average density of cooperators in the stationary state for a fixed interaction graph, while varying the number of edges in the learning graph. According to the Monte Carlo simulations, the cooperation is modified substantially in a way resembling a coherence-resonance-like behavior when the number of learning edges is increased. This behavior is reproduced by the analytical results.

physics.soc-ph↗

arXiv2007

Effects of inhomogeneous influence of individuals on an order-disorder transition in opinion dynamics

We study the effects of inhomogeneous influence of individuals on collective phenomena. We focus analytically on a typical model of the majority rule, applied to the completely connected agents. Two types of individuals $A$ and $B$ with different influence activity are introduced. The individuals $A$ and $B$ are distributed randomly with concentrations $ν$ and $1-ν$ at the beginning and fixed further on. Our main result is that the location of the order-disorder transition is affected due to the introduction of the inhomogeneous influence. This result highlights the importance of inhomogeneous influence between different types of individuals during the process of opinion updating.

physics.soc-ph↗

arXiv2007

Effects of inhomogeneous activity of players and noise on cooperation in spatial public goods games

We study the public goods game in the noisy case by considering the players with inhomogeneous activity teaching on a square lattice. It is shown that the introduction of the inhomogeneous activity of teaching of the players can remarkably promote cooperation. By investigating the effects of noise on cooperative behavior in detail, we find that the variation of cooperator density $ρ_C$ with the noise parameter $κ$ displays several different behaviors: $ρ_C$ monotonically increases (decreases) with $κ$; $ρ_C$ firstly increases (decreases) with $κ$ and then it decreases (increases) monotonically after reaching its maximum (minimum) value, which depends on the amount of the multiplication factor $r$, on whether the system is homogeneous or inhomogeneous, and on whether the adopted updating is synchronous or asynchronous. These results imply that the noise plays an important and nontrivial role in the evolution of cooperation.

physics.soc-ph↗

arXiv2007

The public goods game on homogeneous and heterogeneous networks: investment strategy according to the pool size

We propose an extended public goods interaction model to study the evolution of cooperation in heterogeneous population. The investors are arranged on the well known scale-free type network, the Barabási-Albert model. Each investor is supposed to preferentially distribute capital to pools in its portfolio based on the knowledge of pool sizes. The extent that investors prefer larger pools is determined by investment strategy denoted by a tunable parameter $α$, with larger $α$ corresponding to more preference to larger pools. As comparison, we also study this interaction model on square lattice, and find that the heterogeneity contacts favors cooperation. Additionally, the influence of local topology to the game dynamics under different $α$ strategies are discussed. It is found that the system with smaller $α$ strategy can perform comparatively better than the larger $α$ ones.

q-fin.GN↗

arXiv2007

Response of degree-correlated scale-free networks to stimuli

The response of degree-correlated scale-free attractor networks to stimuli is studied. We show that degree-correlated scale-free networks are robust to random stimuli as well as the uncorrelated scale-free networks, while assortative (disassortative) scale-free networks are more (less) sensitive to directed stimuli than uncorrelated networks. We find that the degree-correlation of scale-free networks makes the dynamics of attractor systems different from uncorrelated ones. The dynamics of correlated scale-free attractor networks result in the effects of degree correlation on the response to stimuli.

cond-mat.dis-nn↗

arXiv2007

Memory based Boolean game and self-organized phenomenon on networks

We study a memory-based Boolean game (MBBG) taking place on the regular ring, wherein each agent acts according to its local optimal states of the last M time steps recorded in memory, and the agents in the minority are rewarded. One free parameter p among 0 and 1 is introduced to denote the strength of the agents' willing to make a decision according to its memory. We find that, given proper willing strength p, the MBBG system can spontaneously evolve to a state of better performance than the random game; while for larger p, the herd behavior emerges which reduces the system profit. By analyzing the dependence of the system's dynamics on the memory capacity M, we find that a higher memory capacity favors the emergence of the better performance state, and effectively restrains the herd behavior, therefore increases the system profit. Considering the high cost of long-time memory, the enhancement of memory capacity for restraining the herd behavior is also discussed, and the M=5 is suggested to be one good choice.

physics.soc-ph↗

arXiv2007

Excitable Greenberg-Hastings cellular automaton model on scale-free networks

We study the excitable Greenberg-Hastings cellular automaton model on scale-free networks. We obtained analytical expressions for no external stimulus and the uncoupled case. It is found that the curves, the average activity $F$ versus the external stimulus rate $r$, can be fitted by a Hill function, but not exactly, and there exists a relation $F\propto r^α$ for the low-stimulus response, where Stevens-Hill exponent $α$ ranges from $α= 1$ in the subcritical regime to $α= 0.5$ at criticality. At the critical point, the range reaches the maximal. We also calculate the average activity $F^{k}(r)$ and the dynamic range $Δ^{k}(p)$ for nodes with given connectivity $k$. It is interesting that nodes with larger connectivity have larger optimal range, which could be applied in biological experiments to reveal the network topology.

cond-mat.stat-mech↗

arXiv2007

Evolutionary prisoner's dilemma game with dynamic preferential selection

We study a modified prisoner's dilemma game taking place on two-dimensional disordered square lattices. The players are pure strategists and can either cooperate or defect with their immediate neighbors. In the generations each player update its strategy by following one of the neighboring strategies with a probability dependent on the payoff difference. The neighbor selection obeys a dynamic preferential rule, i.e., the more frequently a neighbor's strategy was adopted by the focal player in the previous rounds, the larger probability it will be chosen to refer to in the subsequent rounds. It is found that cooperation is substantially promoted due to this simple selection mechanism. Corresponding analysis is provided by the investigations of the distribution of players' impact weights, persistence, and as well as correlation function.

physics.soc-ph↗

arXiv2007

Effects of degree distribution in mutual synchronization of neural networks

We study the effects of the degree distribution in mutual synchronization of two-layer neural networks. We carry out three coupling strategies: large-large coupling, random coupling, and small-small coupling. By computer simulations and analytical methods, we find that couplings between nodes with large degree play an important role in the synchronization. For large-large coupling, less couplings are needed for inducing synchronization for both random and scale-free networks. For random coupling, cutting couplings between nodes with large degree is very efficient for preventing neural systems from synchronization, especially when subnetworks are scale-free.

cond-mat.dis-nn↗

arXiv2007

Promotion of cooperation induced by nonlinear attractive effect in spatial Prisoner's Dilemma game

We introduce nonlinear attractive effects into a spatial Prisoner's Dilemma game where the players located on a square lattice can either cooperate with their nearest neighbors or defect. In every generation, each player updates its strategy by firstly choosing one of the neighbors with a probability proportional to $\mathcal{A}^α$ denoting the attractiveness of the neighbor, where $\mathcal{A}$ is the payoff collected by it and $α$ ($\geq$0) is a free parameter characterizing the extent of the nonlinear effect; and then adopting its strategy with a probability dependent on their payoff difference. Using Monte Carlo simulations, we investigate the density $ρ_C$ of cooperators in the stationary state for different values of $α$. It is shown that the introduction of such attractive effect remarkably promotes the emergence and persistence of cooperation over a wide range of the temptation to defect. In particular, for large values of $α$, i.e., strong nonlinear attractive effects, the system exhibits two absorbing states (all cooperators or all defectors) separated by an active state (coexistence of cooperators and defectors) when varying the temptation to defect. In the critical region where $ρ_C$ goes to zero, the extinction behavior is power law-like $ρ_C$ $\sim$ $(b_c-b)^β$, where the exponent $β$ accords approximatively with the critical exponent ($β\approx0.584$) of the two-dimensional directed percolation and depends weakly on the value of $α$.

physics.soc-ph↗

arXiv2006

Walks on weighted networks

We investigate the dynamics of random walks on weighted networks. Assuming that the edge's weight and the node's strength are used as local information by a random walker, we study two kinds of walks, weight-dependent walk and strength-dependent walk. Exact expressions for stationary distribution and average return time are derived and confirmed by computer simulations. We calculate the distribution of average return time and the mean-square displacement for two walks on the BBV networks, and find that a weight-dependent walker can arrive at a new territory more easily than a strength-dependent one.

cond-mat.stat-mech↗

arXiv2006

Walks on Apollonian networks

We carry out comparative studies of random walks on deterministic Apollonian networks (DANs) and random Apollonian networks (RANs). We perform computer simulations for the mean first passage time, the average return time, the mean-square displacement, and the network coverage for unrestricted random walk. The diffusions both on DANs and RANs are proved to be sublinear. The search efficiency for walks with various strategies and the influence of the topology of underlying networks on the dynamics of walks are discussed. Contrary to one's intuition, it is shown that the self-avoiding random walk, which has been verified as an optimal strategy for searching on scale-free and small-world networks, is not the best strategy for the DAN in the thermodynamic limit.

cond-mat.stat-mech↗

arXiv2006

Waveform sample method of excitable sensory neuron

We present a new interpretation for encoding information of the period of input signals into spike-trains in individual sensory neuronal systems. The spike-train could be described as the waveform sample of the input signal which locks sample points to wave crests with randomness. Based on simulations of the Hodgkin-Huxley (HH) neuron responding to periodic inputs, we demonstrate that the random sampling is a proper encoding method in medium frequency region since power spectra of the reconstructed spike-trains are identical to that of neural signals.

q-bio.NC↗

arXiv2005

Epidemic spreading with time delay in complex networks

We present a modified \emph{susceptible-infected-susceptible} (SIS) model on complex networks, small-world and scale-free, to study epidemic spreading with the effect of time delay which is introduced to the infected phase. Considering the topology of the network, both uniform and degree-dependent delays are studied during the contagion process. We find that the existence of time delay will enhance both outbreaks and prevalence of infectious diseases in the network.

physics.soc-ph↗