On the Criticality of Adaptive Boolean Network Robots

Systems poised at a dynamical critical regime, between order and disorder, have been shown capable of exhibiting complex dynamics that balance robustness to external perturbations and rich repertoires of responses to inputs. This property has been exploited in artificial network classifiers, and preliminary results have also been attained in the context of robots controlled by Boolean networks. In this work, we investigate the role of dynamical criticality in robots undergoing online adaptation, i.e., robots that adapt some of their internal parameters to improve a performance metric over time during their activity. We study the behavior of robots controlled by random Boolean networks, which are either adapted in their coupling with robot sensors and actuators or in their structure or both. We observe that robots controlled by critical random Boolean networks have higher average and maximum performance than that of robots controlled by ordered and disordered nets. Notably, in general, adaptation by change of couplings produces robots with slightly higher performance than those adapted by changing their structure. Moreover, we observe that when adapted in their structure, ordered networks tend to move to the critical dynamical regime. These results provide further support to the conjecture that critical regimes favor adaptation and indicate the advantage of calibrating robot control systems at dynamical critical states.     

A Kind of Neural Network Model Displaying Self-Organized Criticality

Based on the LISSOM model and the OFC earthquake model, we introduce a selforganized neural network model, in which the distribution of the avalanche sizes (unstable neurons) shows power-law behavior. In addition, we analyze the influence of various factors of the model on the power-law behavior of the avalanche size distribution.     

Effects of Inhibitory Signal on Criticality in Excitatory-Inhibitory Networks

We study the criticality in excitatory-inhibitory networks consisting of excitable elements. We investigate the effects of the inhibitory strength using both numerical simulations and theoretical analysis. We show that the inhibitory strength cannot affect the critical point. The dynamic range is decreased as the inhibitory strength increases.To simulate of decreasing the efficacy of excitation and inhibition which was studied in experiments, we remove excitatory or inhibitory nodes, delete excitatory or inhibitory links, and weaken excitatory or inhibitory coupling strength in critical excitatory-inhibitory network. Decreasing the excitation, the change of the dynamic range is most dramatic as the same as previous experimental results. However, decreasing inhibition has no effect on the criticality in excitatory-inhibitory network.     

The Dynamical Structure Function of the One‐Component Plasma Revisited

We present high precision Molecular Dynamics simulations for the dynamical structure function, S (k, ω), of the classical Coulomb One Component Plasma (OCP), for a wide range of the coupling parameter Γ (from 0.05 to 10 000). We follow the positive‐to‐negative transition of the slope of the ω (k) dispersion curve at small wave numbers caused by the onset of correlations with increasing coupling. The high signal‐to‐noise ratio of the data over several orders of magnitude allows examination of a wide dynamical range of S (k, ω), including extreme values of ω and k, and the identification of waves at higher harmonics of the plasma frequency. Sum rules are found to be accurately satisfied. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Instantaneously Dynamical Response and Correlation Functions in Independent-Oscillator Model

For the independent-oscillator model (IOM), the explicit expressions of the instantaneously dynamical response functions (Χ₁ + Υ,t₁), X(t₁ + Υ,t₁)) and correlation functions (φ(t₁ + Υ,t₁)+Φ(t₁ + Υ,t₁)) for both the system and environment are derived. It is shown that for external perturbation the environment of IOM is dynamically stable and the system is oscillatory. Although the external perturbation exists, there is still strongly temporal correlation for the system, for the environment, however, the temporal correlation quickly decays with the second time variable Υ and is almost independent of the first time variable t₁, nevertheless is significantly affected by dissipation. It is shown that the environment behaves as a heat bath from the dynamical point of view.     

自能函数和夸克的动力学质量(英文)

研究夸克的质量是QCD研究中的一个非常重要问题。因为, 夸克质量是标准模型的基本输入参数, 准确地确定这些参数无论对于唯象的应用还是对于理论的应用都是极其重要的。基于参数化的完全穿衣服的夸克传播子, 研究了自能函数和夸克的动力学质量。理论预言了夸克质量和自能函数, 其结果与文献中的经验值相符合, 也与Dyson Schwinger方程解一致。反过来这也说明了参数化的夸克传播子是成功和可靠的。Study of mass of quark is one of the most important issues in the investigation of QCD. Because masses of quarks are fundamental QCD input parameters of standard Model, and an accurate determination of these parameters is extremely important for both phenomenological and theoretical applications. Based on the parameterized fully dressed quark propagator proposed by us, the theoretical predictions of the masses of quarks are predicted in this short note. The effective quark mass is defined by the scalar self energy function Bf(p2) and vector self energy function Af(p2). The results of our calculations are in agreement with the empirical values used widely in literature and also show that the parameterized form of quark propagator is an applicable and reliable approximation.     

Dynamical Change of Quantum Fisher Information of Cavity-Reservoir Systems

We study the quantum Fisher information(QFI) dynamics of the phase parameter in the enlarged cavityreservoir systems at zero temperature under two situations of large N limit and non-Markovian environment,respectively.We find an important relation that the total quantities of QFI of the cavity and reservoir are equal to unit during the dynamical evolution.The lost QFI of the cavity transfers to its corresponding reservoir with the same quantities simultaneously.Moreover,we also find that the detuning parameter and non-Markovian effect are two significant factors to affect the preservation of QFI.     

Effects of Interactive Function Forms in a Self-Organized Critical Model Based on Neural Networks

Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we introduce a kind of coupled map lattice system to investigate scale-invariance behavior in the activity of model neural populations. We let the parameter β, which together with α represents the interactive strength between neurons, have different function forms, and we find the function forms and their parameters are very important to our model‘s avalanche dynamical behaviors, especially to the emergence of different avalanche behaviors in different areas of our system.     

Effects of Interactive Function Forms in a Self-Organized Critical Model Based on Neural Networks

Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we introduce a kind of coupled map lattice system to investigate scale-invariance behavior in the activity of model neural populations. We let the parameter β, which together with α represents the interactive strength between neurons, have different function forms, and we find the function forms and their parameters are very important to our model‘‘s avalanche dynamical behaviors, especially to the emergence of different avalanche behaviors in different areas of our system.     

Effects of Interactive Function Forms and Refractoryperiod in a Self-Organized Critical Model Based on Neural Networks

Based on the standard self-organizing map neural network model and an integrate-and-tire mechanism, we investigate the effect of the nonlinear interactive function on the self-organized criticality in our model. Based on these we also investigate the effect of the refractoryperiod on the self-organized criticality of the system.     

Effects of Interactive Function Forms and Refractoryperiod in a Self-Organized Critical Model Based on Neural Networks

Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we investigate the effect of the nonlinear interactive function on the self-organized criticality in our model. Based on the sewe also investigate the effect of the refractoryperiod on the self-organized criticality of the system.     

Coherent Transport and Dynamical Entropy for Fermionic Systems

This paper consists of two parts. First we set up a general scheme of local traps in a homogeneous deterministic quantum system. The current of particles caught by the trap is linked to the dynamical behaviour of the trap states. In this way, transport properties in a homogeneous system are related to spectral properties of a coherent dynamics. Next we apply the scheme to a system of Fermions in the one-particle approximation. We obtain in particular lower bounds for the dynamical entropy in terms of the current induced by the trap.     

Effects of Vertex Activity and Self-organized Criticality Behavior on a Weighted Evolving Network

Effects of vertex activity have been analyzed on a weighted evolving network. The network is characterized by the probability distribution of vertex strength, each edge weight and evolution of the strength of vertices with different vertex activities. The model exhibits self-organized criticality behavior. The probability distribution of avalanche size for different network sizes is also shown. In addition, there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities.     

Effects of Vertex Activity and Self-organized Criticality Behavior on a Weighted Evolving Network

Effects of vertex activity have been analyzed on a weighted evolving network. The network is characterized by the probability distribution of vertex strength, each edge weight and evolution of the strength of vertices with different vertex activities. The model exhibits self-organized criticality behavior. The probability distribution of avalanche size for different network sizes is also shown. In addition, there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities.     

Effects of Aging and Self-organized Criticality in a Pulse-Coupled Integrate-and-Fire Neuron Model Based on Small World Networks

Effects of aging and self-organized criticality in a pulse-coupled integrate-and-fire neuron model based on small world networks have been studied. We give the degree distribution of aging network, average shortest path length, the diameter of our network, and the clustering coefficient, and find that our neuron model displays the power-law behavior, and with the number of added links increasing, the effects of aging become smaller and smaller. This shows that if the brain works at the self-organized criticality state, it can relieve some effects caused by aging.     

Modeling Topology and Nonlinear Dynamical Behavior of the Weighted Scale-Free Networks

An improved weighted scale-free network, which has two evolution mechanisms： topological growth and strength dynamics, has been introduced. The topology structure of the model will be explored in details in this work. The evolution driven mechanism of Olami-Feder Christensen （OFC） model is added to our model to study the self-organlzed criticality and the dynamical behavior. We also.consider attack mechanism and the study of the model with attack is also investigated in this paper. We tlnd there are differences between the model with attack and without attack.     

连续混沌调频信号的动力学设计与分析

提出了基于连续混沌时间尺度变换的连续混沌调频信号动力学设计理论,并以Colpitts电路为例给出了具体的实现模型.通过吸引子重构和Lyapunov指数分析,阐述了连续混沌调频信号的动力学特性.结果显示连续混沌调频信号的最大Lyapunov指数与混沌信号的最大Lyapunov指数相同;连续混沌调频信号的动力学设计实现方式简单且系统参数易于控制,同时信号形式与数学意义上的连续混沌调频信号保持一致.     

Modeling Topology and Nonlinear Dynamical Behavior of the Weighted Scale-Free Networks

An improved weighted scale-free network, which has two evolution mechanisms: topological growth and strength dynamics, has been introduced. The topology structure of the model will be explored in details in this work. The evolution driven mechanism of Olami-Feder-Christensen (OFC) model is added to our model to study the self-organized criticality and the dynamical behavior. We also consider attack mechanism and the study of the model with attack is also investigated in this paper. We find there are differences between the model with attack and without attack.     

Synchronization and Bifurcation of General Complex Dynamical Networks

In the present paper, synchronization and bifurcation of general complex dynamical networks are investigated. We mainly focus on networks with a somewhat general coupling matrix, i.e., the sum of each row equals a nonzero constant u. We derive a result that the networks can reach a new synchronous state, which is not the asymptotic limit set determined by the node equation. At the synchronous state, the networks appear bifurcation if we regard the constant u as a bifurcation parameter. Numerical examples are given to illustrate our derived conclusions.     

Dynamical correlation functions of the quadratic coupling spin-Boson model

The spin-boson model with quadratic coupling is studied using the bosonic numerical renormalization group method.We focus on the dynamical auto-correlation functions C_O(ω), with the operator taken as σ_x, σ_z, and X, respectively. In the weak-coupling regime α α_c, these functions show power law ω-dependence in the small frequency limit, with the powers 1 + 2s, 1 + 2s, and s, respectively. At the critical point α = α_c of the boson-unstable quantum phase transition, the critical exponents y_O of these correlation functions are obtained as yσ_x= yσ_z= 1-2s and yX=-s, respectively. Here s is the bath index and X is the boson displacement operator. Close to the spin flip point, the high frequency peak of Cσ_x(ω) is broadened significantly and the line shape changes qualitatively, showing enhanced dephasing at the spin flip point.