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Yong Chen

Publications and source records attributed to Yong Chen.

At least 397 records · Page 22Linked to original sources
arXiv2010

A Heuristic Algorithm for optimizing Page Selection Instructions

Page switching is a technique that increases the memory in microcontrollers without extending the address buses. This technique is widely used in the design of 8-bit MCUs. In this paper, we present an algorithm to reduce the overhead of page switching. To pursue small code size, we place the emphasis on the allocation of functions into suitable pages with a heuristic algorithm, thereby the cost-effective placement of page selection instructions. Our experimental results showed the optimization achieved a reduction in code size of 13.2 percent.

cs.PL↗
arXiv2009

Four-state rock-paper-scissors games on constrained Newman-Watts networks

We study the cyclic dominance of three species in two-dimensional constrained Newman-Watts networks with a four-state variant of the rock-paper-scissors game. By limiting the maximal connection distance $R_{max}$ in Newman-Watts networks with the long-rang connection probability $p$, we depict more realistically the stochastic interactions among species within ecosystems. When we fix mobility and vary the value of $p$ or $R_{max}$, the Monte Carlo simulations show that the spiral waves grow in size, and the system becomes unstable and biodiversity is lost with increasing $p$ or $R_{max}$. These results are similar to recent results of Reichenbach \textit{et al.} [Nature (London) \textbf{448}, 1046 (2007)], in which they increase the mobility only without including long-range interactions. We compared extinctions with or without long-range connections and computed spatial correlation functions and correlation length. We conclude that long-range connections could improve the mobility of species, drastically changing their crossover to extinction and making the system more unstable.

q-bio.PE↗
arXiv2009

Stability and chaotic behavior of Bose-Einstein condensates in optical lattices with two- and three-body interactions

The stability and chaotic behaviors of Bose-Einstein condensates with two- and three-atom interactions in optical lattices are discussed with analytical and numerical methods. It is found that the steady-state relative population appears tuning-fork bifurcation when the system parameters are changed to certain critical values. In particular, the existence of three-body interaction not only transforms the bifurcation point of the system but also affects greatly on the macroscopic quantum self-trapping behaviors of the system associated with the critically stable steady-state solution. In addition, we also investigated the influence of the initial conditions, three-body interaction and the energy bias on the macroscopic quantum self-trapping. Finally, by applying the periodic modulation on the energy bias, we find that the relative population oscillation exhibits a process from order to chaos, via a series of period-doubling bifurcations.

cond-mat.quant-gas↗
arXiv2009

Topological aspect of disclinations in two-dimensional melting

By using topological current theory, we study the inner topological structure of disclinations during the melting of two-dimensional systems. From two-dimensional elasticity theory, it is found topological currents for topological defects in homogeneous equation. The evolution of disclinations is studied, and the branch conditions for generating, annihilating, crossing, splitting, and merging of disclinations are given.

cond-mat.soft↗
arXiv2009

Coevolution of game and network structure: The temptation increases the cooperator density

Most papers about the evolutionary game on graph assume the statistic network structure. However, social interaction could change the relationship of people. And the changing social structure will affect the people's strategy too. We build a coevolutionary model of prisoner's dilemma game and network structure to study the dynamic interaction in the real world. Based on the asynchronous update rule and Monte Carlo simulation, we find that, when players prefer to rewire their links to the richer, the cooperation density will increase. The reason of it has been analyzed.

physics.soc-ph↗
arXiv2009

Stochastic Resonance in Time-delayed Bistable Systems Driven by Weak Periodic Signal

We study theoretically a bistable systems with time-delayed feedback driven by weak periodic force. The effective potential function and the steady-state probability density are derived. The delay time and the strength of its feedback can change the shapes of the potential wells. In the adiabatic approximation, the signal-to-noise ratio (SNR) of the system with a weak periodic force is obtained. The time-delayed feedback modulates the magnitude of SNR by changing the shape of the potential and the effective strength of signal. The maximum of SNR decreases with increasing the feedback intensity $ε$. When $ε$ is negative (or positive), the time delay can suppress (or promote) the stochastic resonance phenomenon.

cond-mat.stat-mech↗
arXiv2008

Graphene Segregated on Ni surfaces and Transferred to Insulators

We report an approach to synthesize high quality graphene by surface segregation and substrate transfer. Graphene was segregated from Ni surface under the ambient pressure by dissolving carbon in Ni at high temperatures followed by cooling down with various rates. Different cooling rates led to different segregation behaviors, strongly affecting the thickness and quality of the graphene films. Electron microscopy and Raman spectroscopy indicated that the graphene films synthesized with medium cooling rates have high quality crystalline structure and well-controlled thicknesses. The graphene films were transferred to insulating substrates by wet etching and found to maintain their high quality.

cond-mat.mtrl-sci↗
arXiv2008

Detection of subthreshold pulses in neurons with channel noise

Neurons are subject to various kinds of noise. In addition to synaptic noise, the stochastic opening and closing of ion channels represents an intrinsic source of noise that affects the signal processing properties of the neuron. In this paper, we studied the response of a stochastic Hodgkin-Huxley neuron to transient input subthreshold pulses. It was found that the average response time decreases but variance increases as the amplitude of channel noise increases. In the case of single pulse detection, we show that channel noise enables one neuron to detect the subthreshold signals and an optimal membrane area (or channel noise intensity) exists for a single neuron to achieve optimal performance. However, the detection ability of a single neuron is limited by large errors. Here, we test a simple neuronal network that can enhance the pulse detecting abilities of neurons and find dozens of neurons can perfectly detect subthreshold pulses. The phenomenon of intrinsic stochastic resonance is also found both at the level of single neurons and at the level of networks. At the network level, the detection ability of networks can be optimized for the number of neurons comprising the network.

q-bio.NC↗
arXiv2008

Effect of memory on the prisoner's dilemma game in a square lattice

We have studied the effect of memory on evolution of the prisoner's dilemma game using square lattice networks. Based on extensive simulations, we found that the density of cooperators was enhanced by an increasing memory effect for most parameters. However, we also observed that the density of cooperators decreased with an increased memory effect in the case of a large memory and moderate temptation. It is interesting to note that memory makes cooperators immune from temptation. The strength of protection reaches its maximal value only for the moderate memory effect.

physics.soc-ph↗
arXiv2008

Topological defects in two-dimensional crystals

By using topological current theory, we study the inner topological structure of the topological defects in two-dimensional (2D) crystal. We find that there are two elementary point defects topological current in two-dimensional crystal, one for dislocations and the other for disclinations. The topological quantization and evolution of topological defects in two-dimensional crystals are discussed. Finally, We compare our theory with Brownian-dynamics simulations in 2D Yukawa systems.

cond-mat.stat-mech↗
arXiv2008

Coexistence of hexatic and isotropic phases in two-dimensional Yukawa systems

We have performed Brownian dynamics simulations on melting of two-dimensional colloidal crystal in which particles interact with Yukawa potential. The pair correlation function and bond-orientational correlation function was calculated in the Yukawa system. An algebraic decay of the bond orientational correlation function was observed. By ruling out the coexistence region, only a unstable hexatic phase was found in the Yukawa systems. But our work shows that the melting of the Yukawa systems is a two-stage melting not consist with the KTHNY theory and the isotropic liquid and the hexatic phase coexistence region was found. Also we have studied point defects in two-dimensional Yukawa systems.

cond-mat.soft↗
arXiv2008

Topological dynamics and dynamical scaling behavior of vortices in a two-dimensional XY model

By using topological current theory we study the inner topological structure of vortices a two-dimensional (2D) XY model and find the topological current relating to the order parameter field. A scalar field, $ψ$, is introduced through the topological current theory. By solving the scalar field, the interaction energy of vortices in a 2D XY model is revisited. We study the dynamical evolution of vortices and present the branch conditions for generating, annihilating, crossing, splitting and merging of vortices. During the growth or annihilation of vortices, the dynamical scaling law of relevant length in a 2D XY model, $ξ(t)\propto(t-t^*)^{1/z}$, is obtained in the neighborhood of the limit point, given the dynamic exponent $z=2$. This dynamical scaling behavior is consistent with renormalization group theory, numerical simulations, and experimental results. Furthermore, it is found that during the crossing, splitting and merging of vortices, the dynamical scaling law of relevant length is $ξ(t)\propto(t-t^*)$. However, if vortices are at rest during splitting or merging, the dynamical scaling law of relevant length is a constat.

cond-mat.stat-mech↗
arXiv2008

Solitons in Bose-Einstein Condensates with time-dependent atomic scattering length in an expulsive parabolic and complex potential

We present two families of analytical solutions of the one-dimensional nonlinear Schrödinger equation which describe the dynamics of bright and dark solitons in Bose-Einstein condensates (BECs) with the time-dependent interatomic interaction in an expulsive parabolic and complex potential. We also demonstrate that the lifetime of both a bright soliton and a dark soliton in BECs can be extended by reducing both the ratio of the axial oscillation frequency to radial oscillation frequency and the loss of atoms. It is interested that a train of bright solitons may be excited with a strong enough background. An experimental protocol is further designed for observing this phenomenon.

cond-mat.other↗
arXiv2008

Topology and Dynamics of Attractor Neural Networks: The Role of Loopiness

We derive an exact representation of the topological effect on the dynamics of sequence processing neural networks within signal-to-noise analysis. A new network structure parameter, loopiness coefficient, is introduced to quantitatively study the loop effect on network dynamics. The large loopiness coefficient means the large probability of finding loops in the networks. We develop the recursive equations for the overlap parameters of neural networks in the term of the loopiness. It was found that the large loopiness increases the correlations among the network states at different times, and eventually it reduces the performance of neural networks. The theory is applied to several network topological structures, including fully-connected, densely-connected random, densely-connected regular, and densely-connected small-world, where encouraging results are obtained.

cond-mat.dis-nn↗
arXiv2008

Emergence of synchronization induced by the interplay between two prisoner's dilemma games with volunteering in small-world networks

We studied synchronization between prisoner's dilemma games with voluntary participation in two Newman-Watts small-world networks. It was found that there are three kinds of synchronization: partial phase synchronization, total phase synchronization and complete synchronization, for varied coupling factors. Besides, two games can reach complete synchronization for the large enough coupling factor. We also discussed the effect of coupling factor on the amplitude of oscillation of $cooperator$ density.

physics.soc-ph↗
arXiv2008

Transient dynamics for sequence processing neural networks: effect of degree distributions

We derive a analytic evolution equation for overlap parameters including the effect of degree distribution on the transient dynamics of sequence processing neural networks. In the special case of globally coupled networks, the precisely retrieved critical loading ratio $α_c = N ^{-1/2}$ is obtained, where $N$ is the network size. In the presence of random networks, our theoretical predictions agree quantitatively with the numerical experiments for delta, binomial, and power-law degree distributions.

cond-mat.dis-nn↗
arXiv2007

Transient Dynamics of Sparsely Connected Hopfield Neural Networks with Arbitrary Degree Distributions

Using probabilistic approach, the transient dynamics of sparsely connected Hopfield neural networks is studied for arbitrary degree distributions. A recursive scheme is developed to determine the time evolution of overlap parameters. As illustrative examples, the explicit calculations of dynamics for networks with binomial, power-law, and uniform degree distribution are performed. The results are good agreement with the extensive numerical simulations. It indicates that with the same average degree, there is a gradual improvement of network performance with increasing sharpness of its degree distribution, and the most efficient degree distribution for global storage of patterns is the delta function.

cond-mat.dis-nn↗