基于半导体光放大器的干涉型器件中噪声特性的分析

分析了基于半导体光放大器(SOA)的干涉仪分别处于“开”、“关”两种工作状态时的输出信噪比及噪声指数,发现当干涉仪处于“开”态时输出信噪比有所恶化,并导出了附加噪声因子的表达式。实验结果进一步证明了理论分析的正确性。     

微通道板固定图案噪声及测试研究

叙述微通道板的噪声,着重介绍微通道板固定图案噪声及其简便新颖而又实用的一种测试方法,给出测试结果并进行分析。     

Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI

Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.     

加性噪声对激光一级相变类比的影响

从单模激光场的增益－噪声模型出发,导出了激光场定态强度分布函数,研究了定态分布函数的极值点随加性噪声、乘性噪声和注入信号的变化情况。结果表明,乘性噪声是使激光系统出现一级相变类比的关键因素,注入信号使相变行为减弱,而加性噪声却使得定态分布中极值点的数量和位置出现来回跳跃式变化。     

自适应光学系统对实际大气湍流波前的时域校正效果

引入时域校正因子（系统团环校正波前残余误差与系统开环时的湍流波前扰动误差之比）和系统测量信噪比,分析了自适应光学系统对实际大气湍流扰动的时域校正效果与湍流功率指数、湍流功率谱转折频率、系统测量信噪比、系统时间延迟以及系统闭环带宽的关系,并给出了系统的最佳闭环带宽。此外还分析了弱光61单元自适应学系统的时域校正效果。     

CCD变积累控制技术

在分析微光图像噪声特性的基础上，提出了通过对微光图像信号进行积分，抑制随机噪声的方法，发展了ＣＣＤ可变积累控制技术，研制了ＣＣＤ外围驱动控制和视频制式转换系统，使激光图像信号直接在ＣＣＤ电荷包中进行多帧累加，有效地抑制了随机噪声，提高了低照度与低对比情况下的信噪比和灵敏度，同时避免了后续实时处理电路的高原干扰，图像质量有了明显的改善。     

A branching process model for sand avalanches

An analytically solvable model for sand avalanches of noninteracting grains of sand, based on the Chapman-Kolmogorov equations, is presented. For a single avalanche, distributions of lifetimes, sizes of overflows and avalanches, and correlation functions are calculated. Some of these are exponentials, some are power laws. Spatially homogeneous distributions of avalanches are also studied. Computer simulations of avalanches of interacting grains of sand are compared to the solutions to the Chapman-Kolmogorov equations. We find that within the range of parameters explored in the simulation, the approximation of noninteracting grains of sand is a good one.     

NMR phase noise in bitter magnets

We have studied the temporal instability of a high field resistive Bitter magnet through nuclear magnetic resonance (NMR). This instability leads to transverse spin decoherence in repeated and accumulated NMR experiments as is normally performed during signal averaging. We demonstrate this effect via Hahn echo and Carr--Purcell--Meiboom--Gill (CPMG) transverse relaxation experiments in a 23-T resistive magnet. Quantitative analysis was found to be consistent with separate measurements of the magnetic field frequency fluctuation spectrum, as well as with independent NMR experiments performed in a magnetic field with a controlled instability. Finally, the CPMG sequence with short pulse delays is shown to be successful in recovering the intrinsic spin--spin relaxation even in the presence of magnetic field temporal instability.     

On the Positivity of the Stochastic Heat Equation

We study the positivity preserving properties of the heat equation with a white noise potential and random initial condition. Moreover, we find a generalized Feynman--Kac formula for the solution of the problem using methods from the white noise analysis. The initial condition can anticipate the driving white noise. We show that the solution is positive, when the random initial condition is positive. For the case of a time-dependent white noise potential, we give a special representation of the solution together with regularity results.