Noise-Induced Transition in a Voltage-Controlled Oscillator Neuron Model

In the presence of Gaussian white noise, we study the properties of voltage-controlled oscillator neuron model and discuss the effects of the additive and multiplicative noise. It is found that the additive noise can accelerate and counterwork the firing of neuron, which depends on the value of central frequency of neuron itself, while multiplicative noise can induce the continuous change or mutation of membrane potential.     

Neural mechanism for binaural pitch perception via ghost stochastic resonance

We present a physiologically plausible binaural mechanism for the perception of the pitch of complex sounds via ghost stochastic resonance. In this scheme, two neurons are driven by noise and a different periodic signal each (with frequencies f(1)=kf(0) and f(2)=(k+1)f(0), where k>1), and their outputs (plus noise) are applied synaptically to a third neuron. Our numerical results, using the Morris-Lecar neuron model with chemical synapses explicitly considered, show that intermediate noise levels enhance the response of the third neuron at frequencies close to f(0), as in the cases previously described of ghost resonance. For the case of an inharmonic combination of inputs (f(1)=kf(0)+Deltaf and f(2)=(k+1)f(0)+Deltaf) noise is also seen to enhance the rates of most probable spiking for the third neuron at a frequency f(r)=f(0)+[Deltaf(k+12)]. In addition, we show that similar resonances can be observed as a function of the synaptic time constant. The suggested ghost-resonance-based stochastic mechanism can thus arise either at the peripheral level or at a higher level of neural processing in the perception of pitch.     

Linear relaxation times of stochastic processes driven by non-Gaussian noises

The linear relaxation time (LRT) associated with steady-state correlation functions is studied for Langevin equations with non-Gaussian noises: dichotomous Markov noise and Poissonian white shot noise. Exact results for arbitrary models are obtained and compared with results for Gaussian noises. Some general features of LRTs are discussed. The concept of dynamic effective diffusion is introduced and the existence of an optimal effective Fokker-Planck approximation is discussed. Explicit examples for prototype models are presented and briefly compared with the analogs for Gaussian noises.     

Divergence at low bias and down-mixing of the current noise in a diffusive superconductor-normal-metal-superconductor junction

We present current noise measurements in a long diffusive superconductor-normal-metal-superconductor junction in the low voltage regime, in which transport can be partially described in terms of coherent multiple Andreev reflections. We show that, when decreasing voltage, the current noise exhibits a strong divergence together with a broad peak. We ascribe this peak to the mixing between the ac-Josephson current and the noise of the junction itself. We show that the junction noise corresponds to the thermal noise of a nonlinear resistor 4k B T/R with R=V/I(V) and no adjustable parameters.     

Response of Hodgkin–Huxley stochastic bursting neuron to single-pulse stimulus

We investigate Hodgkin–Huxley neuron model with external Gaussian noise in the range of parameters where it exhibits bistability of silent and firing states, and noise-induced bursts occur. We study the response of the system to brief single pulse of current. When noise amplitude increases, the delay time between the stimulus and the first spike decreases substantially even for subthreshold stimulus. The mean number of spikes in a post-stimulus burst has a maximum in a certain range of noise amplitudes. Therefore, we found that Hodgkin–Huxley neuron in the stochastic bursting regime has more improved sensitivity to single-pulse stimulus than in the silent one.     

高功率半导体激光器结温与1/f噪声的关系研究

高功率半导体激光器的结温上升, 不仅影响它的输出功率、斜坡效率、阈值电流和寿命, 而且还会产生光谱展宽和波长偏移. 因此, 热管理成为抽运激光器研发中的一个主要问题. 本文首先建立了噪声功率谱与结温变化的物理模型, 根据压缩感知理论, 将测量得到含有高斯白噪声和1/f噪声的混叠复合噪声信号稀疏化后, 进行基追踪算法去噪, 通过改变算法的迭代次数及测量矩阵大小, 获得1/f噪声电压功率谱与结温变化关系曲线, 避免了直接测量结温的复杂性.通过数值估计结果, 可以较好地指导高功率半导体激光器的热管理工作. 关键词： f噪声')" href="#">1/f噪声 结温度 热阻 高功率半导体激光器     

Spiral Waves and Multiple Spatial Coherence Resonances Induced by Colored Noise in Neuronal Network

Gaussian colored noise induced spatial patterns and spatial coherence resonances in a square lattice neuronal network composed of Morris-Lecar neurons are studied.Each neuron is at resting state near a saddle-node bifurcation on invariant circle,coupled to its nearest neighbors by electronic coupling.Spiral waves with different structures and disordered spatial structures can be alternately induced within a large range of noise intensity.By calculating spatial structure function and signal-to-noise ratio(SNR),it is found that SNR values are higher when the spiral structures are simple and are lower when the spatial patterns are complex or disordered,respectively.SNR manifest multiple local maximal peaks,indicating that the colored noise can induce multiple spatial coherence resonances.The maximal SNR values decrease as the correlation time of the noise increases.These results not only provide an example of multiple resonances,but also show that Gaussian colored noise play constructive roles in neuronal network.     

Spin-current shot noise as a probe of interactions in mesoscopic systems

It is shown that the spin-resolved current shot noise can probe attractive or repulsive interactions in mesoscopic systems. This is illustrated in two physical situations: (i) a normal-superconducting junction where the spin-current noise is found to be zero, and (ii) a single-electron transistor where the spin-current noise is found to be Poissonian. Repulsive interactions may also lead to weak attractive correlations (bunching of opposite spins) in conditions far from equilibrium. Spin-current shot noise can also be used to measure the spin relaxation time T1, and a setup is proposed in a quantum dot geometry.     

Optimal precision of parameter estimation in images with local sub-Poissonian quantum fluctuations

Non-classical quantum effects allow light with local sub-Poissonian fluctuations below shot noise to be produced. We show that using such light can improve the estimation precision of a parameter in an image beyond the standard Poissonian limit. This benefit is theoretically investigated by means of a phenomenological model of local sub-Poissonian noise which assumes the independence of the fluctuations in each pixel. In particular, a bound on the best precision expectable independently of the exact unbiased estimation protocol used, which is given by the Cramer-Rao bound, is determined from this model. The numerical simulations presented in the special case of the estimation of a displacement of an image perturbed with local sub-Poissonian noise show that a standard estimator can overcome the classical Poissonian limit by reaching this limit precision only beyond a certain value of the photon flux which we characterize. We eventually present some numerical results that demonstrate the generality of the model proposed, of the optimality bounds and of the estimator performance.     

受驱动的关联发射激光:双模亚泊松光

如果在关联发射的基础之上再引入原子相干，这样的系统可产生明亮的双模亚泊松光。运用Ｓｃｕｌｙ－Ｌａｍｂ理论计算ＭａｎｄｅｌＱ因子，一方面，当相对相位和相对振幅的量子噪声被抑制到真空噪声水平时，平均模呈现亚泊松光子分布；或者当平均相位和平均振幅的量子噪声被抑制到真空噪声水平时，相对模呈现亚泊松光子分布，ＭａｎｄｅｌＱ因子的最佳值均可达到－０．５。在上述两种情况下，每个关联发射激光（ＣＥＬ）模呈现亚泊松光子分布，ＭａｎｄｅｌＱ因子的最佳值均可达到－０．２５。     

Transport for System with Three-Value Poissonian Noise

The transport of the overdamped Brownian particles in a spatially periodic potential subject to the three-value Poissonian noise in the stationary state is considered. We show that for the spatially periodic potential, no matter whether it is asymmetric, or is symmetric, flux can be induced. But the mechanism is different. The former is the common action of broken reflection symmetry and transition among three-value Poissonian noise in a cyclic way; the latter is single behavior of transition among three-value Poissonian noise in a cyclic way.     

Channel block-optimized spiking activity of Hodgkin-Huxley neurons on random networks

In this paper, we numerically study the effect of channel block on the spiking temporal coherence and spatial synchronization on Hodgkin-Huxley (HH) neuron networks. It is found that under sodium CB the spike coherence is badly reduced, and the synchronization can, depending on the network randomness (the fraction of random shortcuts), be either enhanced or reduced, while, under potassium CB, the spike coherence can be enhanced but the synchronization is reduced. Interestingly, for certain networks of relatively large randomness, the neuron firings can achieve the best temporal coherence at an optimal potassium CB. These results show that under certain conditions channel blocking can increase and optimize the spike coherence and the synchronization on the complex HH neuron networks, whereby the neurons would exhibit a better and the best sub-threshold signal encoding.     

Transport for System with Three-Value Poissonian Noise

The transport of the overdamped Brownian particles in a spatially periodic potential subject to the three value Poissonian noise in the stationary state is considered. We show that for the spatially periodic potential, no matter whether it is asymmetric, or is symmetric, flux can be induced. But the mechanism is different. The former is the common action of broken reflection symmetry and transition among three-value Poissonian noise in a cyclic way; the latter is single behavior of transition among three-value Poissonian noise in a cyclic way.     

Neural circuitry for recognizing interspike interval sequences

Sensory systems present environmental information to central nervous system as sequences of action potentials or spikes. How do animals recognize these sequences carrying information about their world? We present a biologically inspired neural circuit designed to enable spike pattern recognition. This circuit is capable of training itself on a given interspike interval (ISI) sequence and is then able to respond to presentations of the same sequence. The essential ingredients of the recognition circuit are (a) a tunable time delay circuit, (b) a spike selection unit, and (c) a tuning mechanism using spike timing dependent plasticity of inhibitory synapses. We have investigated this circuit using Hodgkin-Huxley neuron models connected by realistic excitatory and inhibitory synapses. It is robust in the presence of noise represented as jitter in the spike times of the ISI sequence.     

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.     

Manipulation of photon statistics of highly degenerate incoherent radiation

Highly degenerate incoherent radiation has a Gaussian density matrix and a large occupation number of modes f. If it is passed through a weakly transmitting barrier, its counting statistics is close to Poissonian. We show that a second identical barrier, in series with the first, drastically modifies the statistics. The variance of the photocount is increased above the mean by a factor f times a numerical coefficient. The photocount distribution reaches a limiting form with a Gaussian body and highly asymmetric tails. These are general consequences of the combination of weak transmission and multiple scattering.     

Effect of excess noise on continuous variable entanglement sudden death and Gaussian quantum discord

A symmetric two-mode Gaussian entangled state is used to investigate the effect of excess noise on entanglement sudden death and Gaussian quantum discord with continuous variables. The results show that the excess noise in the channel can lead to entanglement sudden death of a symmetric two-mode Gaussian entangled state, while Gaussian quantum discord never vanishes. As a practical application, the security of a quantum key distribution （QKD） scheme based on a symmetric two-mode Gaussian entangled state against collective Gaussian attacks is analyzed. The calculation results show that the secret key cannot be distilled when entanglement vanishes and only quantum discord exists in such a QKD scheme.     

基于1/f噪声的NPN晶体管辐照感生电荷的定量分离

本文针对NPN双极性晶体管, 在研究辐照感生的氧化层电荷及界面态对晶体管基极电流和1/f噪声的影响的基础上, 建立辐照感生氧化层电荷及界面态与基极电流和1/f噪声的定量物理模型. 根据所建立的模型, 提出一种新的分离方法, 利用1/f噪声和表面电流求出氧化层电荷密度, 利用所求得氧化层电荷密度和表面电流求出界面态密度. 利用本方法初步实现了辐照感生氧化层电荷及界面态的定量计算.     

The spike timing precision of FitzHugh--Nagumo neuron network coupled by gap junctions

It has been proved recently that the spike timing can play an important role in information transmission, so in this paper we develop a network with N-unit FitzHugh--Nagumo neurons coupled by gap junctions and discuss the dependence of the spike timing precision on synaptic coupling strength, the noise intensity and the size of the neuron ensemble. The calculated results show that the spike timing precision decreases as the noise intensity increases; and the ensemble spike timing precision increases with coupling strength increasing. The electric synapse coupling has a more important effect on the spike timing precision than the chemical synapse coupling.     

Experimental investigation of noise-assisted information transmission and storage via stochastic resonance

We present experimental results on the information transmission and storage via stochastic resonance in circuits designed and built around Schmitt triggers (STs). First, we investigate the performance of a transmission line comprised of five STs and show it to exhibit stochastic resonance. Each ST in the line is fed with white Gaussian noise, and the first ST is driven by a non-return-to-zero pseudo-random bit sequence with sub-threshold amplitude. Parameters such as bit error rate (Q-factor) are measured (calculated) and shown to exhibit a minimum (maximum) for an optimum amount of noise. Interestingly, we find that system performance degrades with the number of STs as if the system were linear and impaired only by additive Gaussian noise. We then propose and build a 1-bit storage device based on two STs in a loop configuration. We demonstrate that such a system is capable of storing one bit of information only in the presence of noise, and that there is a regime where the efficiency of such a device increases with increasing noise.Our results point to the feasibility of building ‘blocks’ that can transmit, store and eventually process information, whose performance is not only robust against noise, but can actually benefit from it.