基于DPDV算法的二元光学元件设计

为解决用于高斯分布激光束整形的二元光学元件设计问题 ,在深入研究现有的各种迭代算法 ,如GS算法、模拟退火法、Alopex法等的基础上 ,提出了并行模拟退火算法和DPDV算法 (DifferentParametertoDifferentVariables)。特别是DPDV算法综合了各种算法的优点 ,而避开了其缺点。得到了迄今为止最好的计算结果     

双随机相位加密中相息图的优化设计

采用基于记忆的模拟退火法对双随机相位加密中的相息图进行优化设计，并用该法分别对一 个二元图像和一个灰度图像进行了模拟实验.实验结果表明，在不增大设计冗余度的情况下 ，运用该方法可降低相息图和密钥的相位量化带来的误差，得到与原加密图像质量几乎相同 的解密图像. 关键词： 基于记忆的模拟退火法 双随机相位加密 优化设计     

基于改进遗传与模拟退火融合的RISP软硬件划分

软硬件划分是可重构指令集处理器在软硬件协同设计中的关键问题,通过对比遗传算法和经典模拟退火算法的优缺点,提出改进遗传算法的适应度函数,同时将Tsallis接受准则引入到经典模拟退火当中。其思路是用遗传算法的结果来制约模拟退火算法产生的随机状态,然后由模拟退火的接受准则以及产生的随机状态函数对遗传算法的种群进行更新,从而找到全局近似最优解。实验结果证明,改进算法与单一遗传算法以及经典模拟退火算法相比,其收敛速度和适应度更好,找到全局近似最优解的概率更大。     

粉末衍射谱图分解的模拟退火法

将模拟退火法应用于中子和x射线粉末衍射谱图分解研究中. 该方法有两个主要优点：一是 解谱结果不依赖于峰参数初始值的选取，可以任意给定峰参数初始值而不影响收敛性，因而 能克服传统最小二乘拟合法在拟合多峰严重重叠的复杂谱图时遇到的初始解的选取困难；二 是具有寻找全局最优解的能力，可有效解决谱图分解在数学上的多解性问题，这对于因多峰 重叠而可能存在多个局部最优解的谱图分解很有益处. 详细描述了方法的计算步骤，讨论了 有关参数设置，并通过模拟谱和实际谱例子对模拟退火法与传统最小二乘拟合法进行了比较 ，阐明了前者在处理复杂谱图时的独特优越性. 原则上该方法也可应用到与粉末衍射谱类似 能用峰形函数描述的其他实验谱的拟合研究中. 关键词： 谱图分解 模拟退火法 粉末衍射 分峰     

基于像素法用模拟退火-遗传算法搜索一维宽带隙光子晶体

将一维光子晶体用像素填充法进行二进制编码,把模拟退火、遗传算法、模拟退火-遗传混合算法与传输矩阵法结合,搜索、计算了一维光子晶体结构和能带,找到了全方位相对禁带宽度高达43.53%的四层结构和43.76%的两层结构,并给出了一维四层结构光子晶体的能带图及其4个原胞的反射率和透射率的频谱图;发现一维两层结构光子晶体的全方位禁带宽度对每层厚度的变化不敏感,但随着两种介质折射率差的增加而增大.     

基于改进型模拟退火模型的X荧光光谱寻峰方法的研究

在能量色散X荧光分析技术分析中,对谱信息的处理一直是研究的重点,谱光滑、寻峰、峰面积处理都是重中之重,本工作基于模拟退火算法原理,建立一种新的寻峰模型算法,该算法利用模拟退火寻找全局最优点的收敛特性,以Metropolis准则作为峰谷判断的基础,引入新的判定标准和峰谷数组,同时从谱道址两端同时收敛,以收敛到同一最优解为终止条件。同时,利用该算法与简单比较法、三阶导数法进行对比实验,结果证明该算法在X荧光光谱寻峰中有较强能力,在实际生产中具有一定价值。     

实现全局优化的一种新途径

提出了一种在光学自动设计中寻求全局优化的新方法；随机抽样法，在与国外流行的模拟退火法作比较讨论的基础上，给出了两个设计实例，双单透镜和双高斯照相物镜，证明本方法是切实可行的。     

推广模拟退火方法及其应用

本文介绍了推广模拟退火方法的基本思想及其统计基础。我们通过一系列标准函数测试了推广模拟退火方法的性能。作为该方法的应用 ,我们研究了Thomson问题和Ni团簇结构。最后 ,探讨了推广模拟退火方法的效率随体系复杂性的变化。     

应用于光束均匀化整形的SAGAGD算法

 分析了模拟退火算法、基因算法、梯度下降法的主要步骤和应用中的优劣，将这三种方法加以综合运用于纯位相元件的优化设计以实现光束均匀化，结果表明，该算法对于设计位相光学元件是十分有效的。     

智能算法在晶体色散方程参量反演中的比较研究

为了研究智能优化算法在不同晶体材料色散方程参数反演中的迭代搜索性能问题,根据已测石英和方解石晶体的实验数据,分别采用遗传算法、模拟退火算法和遗传模拟退火算法应用于晶体色散方程的参数反演中,获得了晶体修正的塞耳迈耶尔方程的参量,同时比较了三种算法在迭代搜索性能、算法稳定性、计算时间和差方和等之间的差异,结果表明,三种算法在晶体色散方程参数反演时都可以得到满意的结果,但是,由于遗传模拟退火算法同时具备遗传算法的快速全局搜索性能和模拟退火算法的极强局部搜索性能,使得在晶体色散方程参数反演中的优化效果更优.因此在建立其它材料色散方程时建议采用遗传模拟退火算法,而且这一结果对研究混合智能算法的迭代搜索性能也是有帮助的.     

Subchannel and power optimization for sum rate maximization in downlink multicarrier NOMA networks

In a multicarrier NOMA system, the subchannel allocation (SA) and power allocation (PA) are intricately linked and essential for improving system throughput. Also, for the successful execution of successive interference cancellations (SIC) at the receiver, a minimum power gap is required among users. As a result, this research comes up with optimization of the SA and PA to maximize the sum rate of the NOMA system while sticking to the minimum power gap constraint in addition to minimum user rate, maximum number of users in a subchannel and power budget constraints for downlink transmission in multicarrier NOMA networks. To ensure that the formulated problem can be solved in polynomial time, we propose solving it in two stages; SA followed by PA. To obtain SA, we investigate four algorithms: Greedy, WSA, WCA, and WCF. For PA, we propose a low-complexity algorithm. We compare the performance of the proposed method with benchmark method that does not consider the minimum power gap constraint. We conclude that employing WCF algorithm with the PA algorithm gives the best sum rate performance.     

Optimization of a total internal reflection lens by using a hybrid Taguchi-simulated annealing algorithm

In this paper, we propose a new method for optimization of a total internal reflection (TIR) lens by using a hybrid Taguchi-simulated annealing algorithm. The conventional simulated annealing (SA) algorithm is a method for solving global optimization problems and has also been used in non-imaging systems in recent years. However, the success of SA depends heavily on the annealing schedule and initial parameter setting. In this study, we successfully incorporated the Taguchi method into the SA algorithm. The new hybrid Taguchi-simulated annealing algorithm provides more precise search results and has lower initial parameter dependence.     

Design of phase plates for shaping partially coherent beams by simulated annealing

Taking the Gaussian Schell-model beam as a typical example of partially coherent beams, this paper applies the simulated annealing （SA） algorithm to the design of phase plates for shaping partially coherent beams. A flow diagram is presented to illustrate the procedure of phase optimization by the SA algorithm. Numerical examples demonstrate the advantages of the SA algorithm in shaping partially coherent beams. An uniform flat-topped beam profile with maximum reconstruction error RE 〈 1.74% is achieved. A further extension of the approach is discussed.     

Fitting PAC spectra with a hybrid algorithm

A hybrid algorithm (HA) that blends features of genetic algorithms (GA) and simulated annealing (SA) was implemented for simultaneous fits of perturbed angular correlation (PAC) spectra. The main characteristic of the HA is the incorporation of a selection criterion based on SA into the basic structure of GA. The results obtained with the HA compare favorably with fits performed with conventional methods.     

用于半导体激光器光束整形的衍射光学元件的设计研究

采用模拟退火法（ＳＡ）和输入 输出法（Ｉ-Ｏ）相结合的算法（ＳＡＩＯ）设计了８台阶的衍射光学元件，将椭圆高斯分布的激光束变换到均匀圆光束，转换到圆均匀区的能量效率达到了９１.９％．计算结果表明，用ＳＡＩＯ设计得到的输出波形边缘陡直，在平顶区的起伏和光滑程度比单独使用ＳＡ或Ｉ-Ｏ有明显改善 关键词：     

Trade-off between diffraction efficiency and uniformity for design of binary diffractive laser beam shaper

The trade-off between diffraction efficiency and uniformity is studied when a binary phase-only diffractive optical element (DOE) is designed for transforming a Gaussian beam to an expanded squared uniform intensity distribution. The simulated annealing (SA) algorithm and Fresnel diffraction theory are applied in our design. Two types of cost functions are utilized in the SA algorithm, and the cases of different incident Gaussian diameters and bright-area sizes of the target patterns are studied. The mechanisms of reducing nonuniformity by the two cost functions are essentially different, and the mechanism combining nonuniformity and the intensity difference between the reconstructed and target patterns has better results. Satisfactory performance can be obtained under the trade-off between them.     

Numerical and experimental study on coherent beam combining of fibre amplifiers using simulated annealing algorithm

We present the numerical and experimental study on the coherent beam combining of fibre amplifiers by means of simulated annealing (SA) algorithm. The feasibility is validated by the Monte Carlo simulation of correcting static phase distortion using SA algorithm. The performance of SA algorithm under time-varying phase noise is numerically studied by dynamic simulation. It is revealed that the influence of phase noise on the performance of SA algorithm gets stronger with an increase in amplitude or frequency of phase noise; and the laser array that contains more lasers will be more affected from phase noise. The performance of SA algorithm for coherent beam combining is also compared with a widely used stochastic optimization algorithm, i.e., the stochastic parallel gradient descent (SPGD) algorithm. In a proof-of-concept experiment we demonstrate the coherent beam combining of two 1083~nm fibre amplifiers with a total output power of 12~W and 93% combining efficiency. The contrast of the far-field coherently combined beam profiles is calculated to be as high as 95%.     

DESIGNING A DIFFRACTIVE OPTICAL ELEMENT FOR CONTROLLING THE BEAM PROFILE IN A THREE-DIMENSIONAL SPACE USING THE SIMULATED ANNEALING ALGORITHM

We have designed a spatially quantized diffractive optical element (DOE) for controlling the beam profile in a three-dimensional space with the help of the simulated annealing (SA) algorithm. In this paper, we investigate the annealing schedule and the neighbourhood which are the deterministic parameters of the process that warrant the quality of the SA algorithm. The algorithm is employed to solve the discrete stochastic optimization problem of the design of a DOE. The objective function which constrains the optimization is also studied. The computed results demonstrate that the procedure of the algorithm converges stably to an optimal solution close to the global optimum with an acceptable computing time. The results meet the design requirement well and are applicable.     

Comparison of several stochastic parallel optimization algorithms for adaptive optics system without a wavefront sensor

Optimizing the system performance metric directly is an important method for correcting wavefront aberrations in an adaptive optics (AO) system where wavefront sensing methods are unavailable or ineffective. An appropriate “Deformable Mirror” control algorithm is the key to successful wavefront correction. Based on several stochastic parallel optimization control algorithms, an adaptive optics system with a 61-element Deformable Mirror (DM) is simulated. Genetic Algorithm (GA), Stochastic Parallel Gradient Descent (SPGD), Simulated Annealing (SA) and Algorithm Of Pattern Extraction (Alopex) are compared in convergence speed and correction capability. The results show that all these algorithms have the ability to correct for atmospheric turbulence. Compared with least squares fitting, they almost obtain the best correction achievable for the 61-element DM. SA is the fastest and GA is the slowest in these algorithms. The number of perturbation by GA is almost 20 times larger than that of SA, 15 times larger than SPGD and 9 times larger than Alopex.