简谐噪声激励下FitzHugh-Nagumo神经元的动力学行为

研究了简谐噪声激励下的FitzHugh-Nagumo神经元模型, 其放电形式、相干共振等动力学行为均受噪声阻尼参数和频率参数的影响.选择不同的参数所得到的神经元的放电形式不同.神经元存在共振特性,对某一频率的噪声有更强的响应,在此频率参数下的峰序列更有序,出现相干共振系数的极小值.噪声的阻尼参数越大,不同的频率成分越多,神经元的响应也变得杂乱,进而导致神经元与噪声的同步变弱,峰序列相干共振系数也相应增大.     

简谐噪声激励下FitzHugh-Nagumo神经元的动力学行为

研究了简谐噪声激励下的FitzHugh-Nagumo神经元模型, 其放电形式、相干共振等动力学行为均受噪声阻尼参数和频率参数的影响.选择不同的参数所得到的神经元的放电形式不同.神经元存在共振特性,对某一频率的噪声有更强的响应,在此频率参数下的峰序列更有序,出现相干共振系数的极小值.噪声的阻尼参数越大,不同的频率成分越多,神经元的响应也变得杂乱,进而导致神经元与噪声的同步变弱,峰序列相干共振系数也相应增大. 关键词： 简谐噪声 FitzHugh-Nagumo神经元 相干共振 峰峰间隔     

Double coherence resonance of the FitzHugh Nagumo neuron driven by harmonic velocity noise

The effect of noise frequency on the FitzHugh–Nagumo neuron is investigated by the use of the harmonic velocity noise, which has a direct frequency parameter and no zero frequency part of the power spectrum. It is shown that the neuron has the resonance characteristic strongly responding to the noise with a certain frequency at fixed power, and there is double coherence resonance related to the frequency and the intensity. If the harmonic velocity noise lacks low frequency ingredients, there is no synchronization between the frequency of the neuron and that of the noise. Thus the low frequency part of the noise plays an important role in creating the synchronization.     

Soluble models for dynamics driven by a super-diffusive noise

We explicitly discuss scalar Langevin type of equations where the deterministic part is linear, but where the integrated noise source is a non-linear diffusion process exhibiting superdiffusive behavior. We calculate transient and stationary probabilities and study the possibility of noise induced transitions from a unimodal to a bimodal probability shape. Illustrations from finance and dynamical systems are given.     

Stochastic resonance of a periodically driven neuron under non-Gaussian noise

We investigate the first-passage-time statistics of the integrate-fire neuron model driven by a sub-threshold harmonic signal superposed with a non-Gaussian noise. Here, we considered the noise as the result of a random multiplicative process displaced from the origin by an additive term. Such a mechanism generates a power-law distributed noise whose characteristic decay exponent can be finely tuned. We performed numerical simulations to analyze the influence of the noise non-Gaussian character on the stochastic resonance condition. We found that when the noise deviates from Gaussian statistics, the resonance condition occurs at weaker noise intensities, achieving a minimum at a finite value of the distribution function decay exponent. We discuss the possible relevance of this feature to the efficiency of the firing dynamics of biological neurons, as the present result indicates that neurons would require a lower noise level to detect a sub-threshold signal when its statistics departs from Gaussian.     

Double coherence resonance in neuron models driven by discrete correlated noise

We study the influence of correlations among discrete stochastic excitatory or inhibitory inputs on the response of the FitzHugh-Nagumo neuron model. For any level of correlation, the emitted signal exhibits at some finite noise intensity a maximal degree of regularity, i.e., a coherence resonance. Furthermore, for either inhibitory or excitatory correlated stimuli, a double coherence resonance is observable. Double coherence resonance refers to a (absolute) maximum coherence in the output occurring for an optimal combination of noise variance and correlation. All of these effects can be explained by taking advantage of the discrete nature of the correlated inputs.     

Geometric phase of a qubit driven by a phase noise laser under non-Markovian dynamics

Robustness of the geometric phase (GP) with respect to the environmental effects is a basic condition for an effective quantum computation. Here, we study quantitatively the GP of a two-level atom system driven by a phase noise laser under non-Markovian dynamics in terms of different parameters involved in the whole system. We find that with the change of the damping coupling, the GP is very sensitive to its properties exhibiting long collapse and revival phenomena, which play a significant role in enhancing the stabilization and control of the system dynamics. Moreover, we show that the GP can be considered as a tool for testing and characterizing the nature of the qubit–environment coupling. Due to the significance of how a system is quantum correlated with its environment in the construction of a scalable quantum computer, the entanglement dynamics between the qubit with its environment under external classical noise is evaluated and investigated during the time evolution.     

Stratonovich model driven by dichotomous noise: analytical results

Stationary and dynamic properties of the Stratonovich model driven by a dichotomous Markovian process (DMP) are investigated analytically. The stationary probability densityp _st and its moments are calculated exactly and the shape ofp _st is discussed in the whole parameter region. The location of the maxima ofp _st shows a behaviour similar to order parameters in continuous phase transitions. The time dependence of moments and the probability density is studied investigating (i) a series expansion of the formal solution for a given realization of the driving process, and (ii) the analytic behaviour of the Laplace transform of the probability density. As a function of physical parameters, qualitative changes of the long time behaviour may occur. Method (i) is generalized to determine the dynamics of moments for a superposition of independent DMP's (pregaussian noise).     

Effective long-time phase dynamics of limit-cycle oscillators driven by weak colored noise

An effective white-noise Langevin equation is derived that describes long-time phase dynamics of a limit-cycle oscillator driven by weak stationary colored noise. Effective drift and diffusion coefficients are given in terms of the phase sensitivity of the oscillator and the correlation function of the noise, and are explicitly calculated for oscillators with sinusoidal phase sensitivity functions driven by two typical colored Gaussian processes. The results are verified by numerical simulations using several types of stochastic or chaotic noise. The drift and diffusion coefficients of oscillators driven by chaotic noise exhibit anomalous dependence on the oscillator frequency, reflecting the peculiar power spectrum of the chaotic noise.     

简谐速度噪声与简谐噪声环境中谐振子的动力学共振

通过求解简谐势场中的广义量子朗之万方程，得到平均能量的精确表达式.由于简谐速度噪声与简谐噪声功率谱的不同特点，两种内部噪声驱动的谐振子在简谐外力的作用下具有不同的共振特征.这些特征可用来检验两种噪声.     

采用双脉冲驱动产生高次谐波阿秒脉冲

提出了采用双脉冲机理来产生阿秒脉冲的方法.研究发现采用双脉冲不仅可以产生单个的阿秒脉冲，从而突破目前产生阿秒脉冲的驱动源（几个飞秒的超短激光脉冲）的能量限制，而且在相同的峰值强度下，双脉冲能够产生强度更高的阿秒脉冲. 关键词： 阿秒脉冲 双脉冲机理 高次谐波     

Stratonovich model driven by dichotomous noise: Mean first passage time

The mean first passage time to reach a noise-induced state starting from a local minimum of the stationary probability density is calculated analytically exploiting a novel type of boundary conditions. The result is checked by digital simulation for typical values of the parameters.     

A microscopic model for noise induced transport: Heat-bath nonlinearly driven by external white noise

This work explores the observation that, even in the absence of a net externally applied bias, a symmetric homogeneous system coupled linearly to two heat baths is capable of producing unidirectional motion simply by nonlinearly driving one of the heat baths by an external Gaussian white noise. This is quite contrary to the traditional observation that, in order to obtain a net drift current, a state-dependent dissipation, which is a consequence of nonlinear system-bath coupling, is ubiquitous.     

Spontaneous emission properties of a driven five-level atom embedded in photonic crystals

The spontaneous emission spectra of a five-level double tripod-type atom embedded in photonic crystals (PCs) are investigated by means of two external fields driving different atomic transitions. We find that due to the quantum interference effects caused by two driving fields, the spontaneous emission spectra exhibit different features from the case of only one driving field. The influences of the parameters of two external driving fields, photonic band-gap (PBG), as well as the atomic initial states on the spectra are analyzed in detail. It is shown that some interesting phenomena such as spectral-line enhancement, spectral-line suppression, spectral-line narrowing, the appearance of dark lines, and multi-peak structures can be observed in the spectra by appropriately modulating the available system parameters. These investigations may find applications in high-precision spectroscopy.     

Characteristics and synchronization of time-delay systems driven by a common noise

We investigate the characteristics of time-delay systems in the presence of Gaussian noise. We show that the delay time embedded in the time series of time-delay system with constant delay cannot be estimated in the presence noise for appropriate values of noise intensity thereby forbidding any possibility of phase space reconstruction. We also demonstrate the existence of complete synchronization between two independent identical time-delay systems driven by a common noise without explicitly establishing any external coupling between them.     

Studies of phase return map and symbolic dynamics in a periodically driven Hodgkin–Huxley neuron

How neuronal spike trains encode external information is a hot topic in neurodynamics studies.In this paper,we investigate the dynamical states of the Hodgkin–Huxley neuron under periodic forcing.Depending on the parameters of the stimulus,the neuron exhibits periodic,quasiperiodic and chaotic spike trains.In order to analyze these spike trains quantitatively,we use the phase return map to describe the dynamical behavior on a one-dimensional(1D)map.According to the monotonicity or discontinuous point of the 1D map,the spike trains are transformed into symbolic sequences by implementing a coarse-grained algorithm—symbolic dynamics.Based on the ordering rules of symbolic dynamics,the parameters of the external stimulus can be measured in high resolution with finite length symbolic sequences.A reasonable explanation for why the nervous system can discriminate or cognize the small change of the external signals in a short time is also presented.     

Temperature-dependent stochastic dynamics of the Huber-Braun neuron model

The response of a four-dimensional mammalian cold receptor model to different implementations of noise is studied across a wide temperature range. It is observed that for noisy activation kinetics, the parameter range decomposes into two regions in which the system reacts qualitatively completely different to small perturbations through noise, and these regions are separated by a homoclinic bifurcation. Noise implemented as an additional current yields a substantially different system response at low temperature values, while the response at high temperatures is comparable to activation-kinetic noise. We elucidate how this phenomenon can be understood in terms of state space dynamics and gives quantitative results on the statistics of interspike interval distributions across the relevant parameter range.     

Information entropy of a dynamical system driven by quasimonochromatic noise

This paper shows the Fokker-Planck equation of a dynamical system driven by quasimonochromatic noise. Based on the Fokker-Planck equation and the definition of Shannon's information entropy, the exact time dependence of entropy flux and entropy production for the system is calculated. The relationship between the properties of quasimonochromatic noise and dissipative parameter and their effects on entropy flux and entropy production are discussed.