arXiv subjects

Hanshuang Chen

Publications and source records attributed to Hanshuang Chen.

46 records · Page 3Linked to original sources

arXiv2013

How does degree heterogeneity affect nucleation of Ising model on complex networks?

We investigate the nucleation of Ising model on complex networks and focus on the role played by the heterogeneity of degree distribution on nucleation rate. Using Monte Carlo simulation combined with forward flux sampling, we find that for a weak external field the nucleation rate decreases monotonically as degree heterogeneity increases. Interestingly, for a relatively strong external field the nucleation rate exhibits a nonmonotonic dependence on degree heterogeneity, in which there exists a maximal nucleation rate at an intermediate level of degree heterogeneity. Furthermore, we develop a heterogeneous mean-field theory for evaluating the free-energy barrier of nucleation. The theoretical estimations are qualitatively consistent with the simulation results. Our study suggests that degree heterogeneity plays a nontrivial role in the dynamics of phase transition in networked Ising systems.

cond-mat.stat-mech↗

arXiv2013

Mobility and density induced amplitude death in metapopulation networks of coupled oscillators

We investigate the effects of mobility and density on the amplitude death of coupled oscillators in metapopulation networks, wherein each node represents a subpopulation with any number of mobile individuals. We perform stochastic simulations of the dynamical reaction-diffusion processes associated with the Landau-Stuart oscillators in scale-free networks. Interestingly, we find that, with increasing the mobility rate or density, the system may undergo phase transitions from incoherent state to amplitude death, and then to frequency synchronization. Especially, there exists an extent of intermediate mobility rate and density leading to global oscillator death. In addition, we show this nontrivial phenomenon is robust to different network topologies. Our findings may invoke further efforts and attentions to explore the underlying mechanism of collective behaviors in metapopulation coupled systems.

nlin.AO↗

arXiv2012

An efficient strategy to suppress epidemic explosion in heterogeneous metapopulation networks

We propose an efficient strategy to suppress epidemic explosion in heterogeneous metapopulation networks, wherein each node represents a subpopulation with any number of individuals and is assigned a curing rate that is proportional to $k^α$ with $k$ the node degree and $α$ an adjustable parameter. We have performed stochastic simulations of the dynamical reaction-diffusion processes associated with the susceptible-infected-susceptible model in scale-free networks. We found that the epidemic threshold reaches a maximum when the exponent $α$ is tuned to be $α_{opt}\simeq 1.3$. This nontrivial phenomenon is robust to the change of the network size and the average degree. In addition, we have carried out a mean field analysis to further validate our scheme, which also demonstrates that epidemic explosion follows different routes for $α$ larger or less than $α_{opt}$. Our work suggests that in order to effectively suppress epidemic spreading on heterogeneous complex networks, subpopulations with higher degrees should be allocated more resources than just being linearly dependent on the degree $k$.

physics.soc-ph↗

arXiv2012

Noise-induced vortex reversal of self-propelled particles

We report an interesting phenomenon of noise-induced vortex reversal in a two-dimensional system of self-propelled particles (SPP) with soft-core interactions. With the aid of forward flux sampling, we analyze the configurations along the reversal pathway and thus identify the mechanism of vortex reversal. We find that statistically the reversal exhibits a hierarchical process: those particles at the periphery first change their motion directions, and then more inner layers of particles reverse later on. Furthermore, we calculate the dependence of the average reversal rate on noise intensity $D$ and the number $N$ of SPP. We find that the rate decreases exponentially with the reciprocal of $D$. Interestingly, the rate varies nonmonotonically with $N$ and a minimal rate exists for an intermediate value of $N$.

cond-mat.stat-mech↗

arXiv2012

Nucleation pathways on complex networks

Identifying nucleation pathway is important for understanding the kinetics of first-order phase transitions in natural systems. In the present work, we study nucleation pathway of the Ising model in homogeneous and heterogeneous networks using the forward flux sampling method, and find that the nucleation processes represent distinct features along pathways for different network topologies. For homogeneous networks, there always exists a dominant nucleating cluster to which relatively small clusters are attached gradually to form the critical nucleus. For heterogeneous ones, many small isolated nucleating clusters emerge at the early stage of the nucleation process, until suddenly they form the critical nucleus through a sharp merging process. By analyzing the properties of the nucleating clusters along the pathway, we show that the main reason behind the different routes is the heterogeneous character of the underlying networks.

cond-mat.stat-mech↗

arXiv2011

Coarse-grained Monte Carlo simulations of the phase transition of Potts model on weighted networks

Developing effective coarse grained (CG) approach is a promising way for studying dynamics on large size networks. In the present work, we have proposed a strength-based CG (\sCG) method to study critical phenomena of the Potts model on weighted complex networks. By merging nodes with close strength together, the original network is reduced to a CG-network with much smaller size, on which the CG-Hamiltonian can be well-defined. In particular, we make error analysis and show that our strength-based CG approach satisfies the condition of statistical consistency, which demands that the equilibrium probability distribution of the CG-model matches that of the microscopic counterpart. Extensive numerical simulations are performed on scale-free networks, without or with strength-correlation, showing that this \sCG approach works very well in reproducing the phase diagrams, fluctuations, and finite size effects of the microscopic model, while the \dCG approach proposed in our recent work [Phys. Rev. E 82, 011107(2010)] does not.

cond-mat.stat-mech↗

arXiv2011

Optimal modularity for nucleation in network-organized Ising model

We study nucleation dynamics of Ising model in a topology that consists of two coupled random networks, thereby mimicking the modular structure observed in real-world networks. By introducing a variant of a recently developed forward flux sampling method, we efficiently calculate the rate and elucidate the pathway for nucleation process. It is found that as the network modularity becomes worse the nucleation undergoes a transition from two-step to one-step process. Interestingly, the nucleation rate shows a nonmonotonic dependency on the modularity, in which a maximal nucleation rate occurs at a moderate level of modularity. A simple mean field analysis is proposed to qualitatively illustrate the simulation results.

cond-mat.stat-mech↗

arXiv2010

Nucleation in scale-free networks

We have studied nucleation dynamics of the Ising model in scale-free networks with degree distribution $P(k)\sim k^{-γ}$ by using forward flux sampling method, focusing on how the network topology would influence the nucleation rate and pathway. For homogeneous nucleation, the new phase clusters grow from those nodes with smaller degree, while the cluster sizes follow a power-law distribution. Interestingly, we find that the nucleation rate $R_{Hom}$ decays exponentially with the network size $N$, and accordingly the critical nucleus size increases linearly with $N$, implying that homogeneous nucleation is not relevant in the thermodynamic limit. These observations are robust to the change of $γ$ and also present in random networks. In addition, we have also studied the dynamics of heterogeneous nucleation, wherein $w$ impurities are initially added, either to randomly selected nodes or to targeted ones with largest degrees. We find that targeted impurities can enhance the nucleation rate $R_{Het}$ much more sharply than random ones. Moreover, $\ln (R_{Het}/R_{Hom})$ scales as $w^{γ-2/γ-1}$ and $w$ for targeted and random impurities, respectively. A simple mean field analysis is also present to qualitatively illustrate above simulation results.

cond-mat.stat-mech↗

arXiv2010

Statistically consistent coarse-grained simulations for critical phenomena in complex networks

We propose a degree-based coarse graining approach that not just accelerates the evaluation of dynamics on complex networks, but also satisfies the consistency conditions for both equilibrium statistical distributions and nonequilibrium dynamical flows. For the Ising model and susceptible-infected-susceptible epidemic model, we introduce these required conditions explicitly and further prove that they are satisfied by our coarse-grained network construction within the annealed network approximation. Finally, we numerically show that the phase transitions and fluctuations on the coarse-grained network are all in good agreements with those on the original one.

cond-mat.stat-mech↗

arXiv2009

Resonant response of forced complex networks: the role of topological disorder

We investigate the effect of topological disorder on a system of forced threshold elements, where each element is arranged on top of complex heterogeneous networks. Numerical results indicate that the response of the system to a weak signal can be amplified at an intermediate level of topological disorder, thus indicating the occurrence of topological-disorder-induced resonance. Using mean field method, we obtain an analytical understanding of the resonant phenomenon by deriving the effective potential of the system. Our findings might provide further insight into the role of network topology in signal amplification in biological networks.

cond-mat.dis-nn↗