Superradiant laser: First-order phase transition and non-stationary regime

We solve the superradiant laser model in two limiting cases. First the stationary low-pumping regime is considered where a first-order phase transition in the semiclassical solution occurs. This discontinuity is smeared out in the quantum regime. Second, we solve the model in the non-stationary regime where we find a temporally periodic solution. For a certain parameter range well-separated pulses may occur. Received: 19 June 1998 / Accepted: 19 October 1998     

Neural Networks in Which Synaptic Patterns Fluctuate with Time

We study a stochastic neural-network model in which neurons and synapses change with a priori probability p and 1–p, respectively, in the limit p0. This implies neuron activity competing with fast fluctuations of the synaptic connections—in fact, random oscillations around values given by a learning (for example, Hebb's) rule. The consequences for the system performance of a dynamics constantly checking at random the set of memorized patterns is thus studied both analytically and numerically. We describe various nonequilibrium phase transitions whose nature depends on the properties of fluctuations. We find, in particular, that under rather general conditions locally stable mixture states do not occur, and pattern recognition and retrieval processes are substantially improved for some classes of synaptic fluctuations.     

Adaptive fuzzy neural network control on the acoustic field in a duct

Base on the principle of the superposition of waves, active noise control is achieved by adaptively tuning a secondary source which produces an anti-noise of equal amplitude and opposite phase with primary source. This paper presents the study on the acoustic attenuation in a duct by using the combination of fuzzy neural network with error back propagation algorithm to control secondary source. The most important advantage of fuzzy inference system is that the structured knowledge is represented in the form of fuzzy IF-THEN rules. But it lacks the ability to accommodate the change of external environments. Combining neural network with fuzzy system can help in this tuning process by adapting fuzzy sets and creating fuzzy rules. The performance of attenuation and control error can be measured by the microphone placed in the downstream of duct. The results of this study, show that the acoustic attenuation by 40 dB for pure-tone noise and nearly 30 dB for dual-tones noise are obtained.     

Domain wall delocalization,dynamics and fluctuations in an exclusion process with two internal states

We investigate the delocalization transition appearing in an exclusion process with two internal states, respectively on two parallel lanes. At the transition, delocalized domain walls form in the density profiles of both internal states, in agreement with a mean-field approach. Remarkably, the topology of the system’s phase diagram allows for the delocalization of a (localized) domain wall when approaching the transition. We quantify the domain wall’s delocalization close to the transition by analytic results obtained within the framework of the domain wall picture. Power law dependences of the domain wall width on the distance to the delocalization transition as well as on the system size are uncovered, they agree with numerical results.     

Synchronization in a Mutualism Ecosystem Induced by Noise Correlation

Understanding the cause of the synchronization of population evolution is an important issue for ecological improvement. Here we present a Lotka-Volterra-type model driven by two correlated environmental noises and show, via theoretical analysis and direct simulation, that noise correlation can induce a synchronization of the mutualists. The time series of mutual species exhibit a chaotic-like fluctuation, which is independent of the noise correlation, however, the chaotic fluctuation of mutual species ratio decreases with the noise correlation. A quantitative parameter defined for characterizing chaotic fluctuation provides a good approach to measure when the complete synchronization happens.     

热噪声对约瑟夫森结I-V特性及微波感应台阶的影响研究

采用数值仿真的方法研究了热噪声对约瑟夫森结I-V特性及微波感应台阶的影响。研究表明,热噪声导致约瑟夫森结的I-V特性曲线呈现"圆拱化",也使得微波感应台阶高度减小。得出了取不同约瑟夫森结临界电流和结电阻时,热噪声对台阶的影响规律     

Noise spectra of microcavity-emitting field in the linear regime

Our work presents a theoretical study on the behavior of the fluctuation statistics of the field emitted from a semiconductor microcavity containing a quantum well. We derive an analytical expression of the noise spectra in non-resonant pumping. Dynamical behaviors of the noise spectra depending on the thermal bath and the detuning between exciton and cavity frequencies are discussed.     

Enhancing optomechanical force sensing via precooling and quantum noise cancellation

We theoretically investigate optomechanical force sensing via precooling and quantum noise cancellation in two coupled cavity optomechanical systems.We show that force sensing based on the reduction of noise can be used to dramatically enhance the force sensing and that the precooling process can eifectively improve the quantum noise cancellation.Specifically,we examine the effect of optomechanical cooling and noise reduction on the spectral density of the noise of the force measurement;these processes can significantly enhance the performance of optomechanical force sensing,and setting up the system in the resolved sideband regime can lead to an optimization of the cooling processes in a hybrid system.Such a scheme serves as a promising platform for quantum back-action-evading measurements of the motion and a framework for an optomechanical force sensor.     

Design and analysis of a BLPC vocoder-based adaptive feedback cancellation with probe noise

The band-limited linear predictive coding (BLPC) vocoder-based adaptive feedback cancellation (AFC) removes the high-frequency bias, while the low frequency bias persists between the desired input signal and the loudspeaker signal in the estimate of the feedback path. In this paper, we present a BLPC vocoder-based adaptive feedback canceller with probe noise with an objective of reducing the low-frequency bias in digital hearing-aids. A step-wise mathematical analysis of the proposed feedback canceller is presented employing the recursive least square and normalized least mean square adaptive algorithms. It is observed that the optimal solution of the feedback path is unbiased for an unshaped probe noise, but is biased for a shaped probe signal; the bias term does not consist of correlation between the desired input and the loudspeaker output. The identifiability conditions are analysed and it is shown that a delay, greater than or equal to the length of the adaptive filter, must be introduced in the forward path to achieve an unbiased feedback path estimate. Algorithm analysis and computer simulations presented in this paper justify the reason for selecting the proposed design over the existing BLPC vocoder-based feedback cancellation algorithm.