Wavefront reconstruction algorithm for wavefront sensing based on binary aberration modes

We propose a new algorithm for wavefront sensing based on binary intensity modulation. The algorithm is based on the fact that a wavefront can be expended with a series of orthogonal and binary functions, the Walsh series. We use a spatial light modulator(SLM) to produce different binary-intensity-modulation patterns which are the simple linear transformation of the Walsh series. The optical fields under different binary-intensity-modulation patterns are detected with a photodiode.The relationships between the incident wavefront modulated with the patterns and their optical fields are built to determinate the coefficients of the Walsh series. More detailed and strict relationship equations are established with the algorithm by adding new modulation patterns according to the properties of the Walsh functions. An exact value can be acquired by solving the equations. Finally, with the help of phase unwrapping and smoothing, the wavefront can be reconstructed. The advantage of the algorithm is providing an analytical solution for the coefficients of the Walsh series to reconstruct the wavefront. The simulation experiments are presented and the effectiveness of the algorithm is demonstrated.     

一种新的分段混沌系统的同步控制

利用状态观测器思想构造驱动和响应系统，实现了一个新近提出的分段线性混沌系统的同步控制，并且推导了两个不同初值的系统实现同步的充分条件.理论分析说明该方法对原系统结构没有特殊要求，无需求解Lyapunov函数，适合应用于分段混沌系统.仿真实验的良好结果验证了该算法的有效性，对于不同初值的分段系统均能实现快速同步.同时该算法适用于一类分段混沌系统的同步控制. 关键词： 分段线性混沌系统 状态观测器 同步控制     

Double image encryption based on iterative fractional Fourier transform

We present an image encryption algorithm to simultaneously encrypt two images into a single one as the amplitudes of fractional Fourier transform with different orders. From the encrypted image we can get two original images independently by fractional Fourier transforms with two different fractional orders. This algorithm can be independent of additional random phases as the encryption/decryption keys. Numerical results are given to analyze the capability of this proposed method. A possible extension to multi-image encryption with a fractional order multiplexing scheme has also been given.     

基于瑞利熵的多无源传感器数据关联算法

针对当前多无源传感器数据关联算法构造关联代价时,未考虑位置估计不确定性所引入的误差,提出一种基于位置估计不确定性的被动传感器数据关联算法。首先通过量测与伪量测概率密度函数之间的瑞利熵构建关联代价函数,以准确描述两个相似的概率密度函数之间差异,然后通过具体实验测试本文算法的有效性和优越性。实验结果表明,相对于当前经典的数据关联算法,本文算法提高了数据关联的正确率和速度,具有更高的实际应用价值。     

算法对混沌体系逃逸率的影响

以Hénon-Heiles体系为例，研究算法对混沌体系运动轨道和逃逸率计算结果的影响.比较了新发现的四阶辛算法和一种非辛的高阶算法得到的结果.发现两种算法给出的轨迹之间的距离随时间增大，增加的速度可以作为体系相空间混沌的度量.通过跟踪大数量的粒子轨迹，提取出了逃逸率随体系能量的变化.发现由两种算法得到的逃逸率相互符合得很好. 关键词： 逃逸率 Hénon-Heiles体系 辛算法     

T(1)--T(2) correlation spectra obtained using a fast two-dimensional Laplace inversion

Spin relaxation is a sensitive probe of molecular structure and dynamics. Correlation of relaxation time constants, such as T(1) and T(2), conceptually similar to the conventional multidimensional spectroscopy, have been difficult to determine primarily due to the absense of an efficient multidimensional Laplace inversion program. We demonstrate the use of a novel computer algorithm for fast two-dimensional inverse Laplace transformation to obtain T(1)--T(2) correlation functions. The algorithm efficiently performs a least-squares fit on two-dimensional data with a nonnegativity constraint. We use a regularization method to find a balance between the residual fitting errors and the known noise amplitude, thus producing a result that is found to be stable in the presence of noise. This algorithm can be extended to include functional forms other than exponential kernels. We demonstrate the performance of the algorithm at different signal-to-noise ratios and with different T(1)--T(2) spectral characteristics using several brine-saturated rock samples.     

A method for removing etalon oscillations from THz time-domain spectra

We present a simple algorithm for removing or reducing spurious oscillations in the THz spectra which result from secondary reflection peaks in samples or optical elements. The algorithm utilizes the fact that a THz time-domain trace containing secondary peaks can be represented as a convolution of the primary peak and two or more delta functions. The algorithm is applicable for samples which are sufficiently thick that the reflection peak does not overlap with the primary peak, and that do not have strong absorption or dispersion.     

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.     

Optimal downlink power allocation in cellular networks

In this paper, we introduce a novel approach for power allocation in cellular networks. In our model, we use sigmoidal-like utility functions to represent different users’ modulation schemes. Each utility function is a representation of the probability of successfully transmitted packets per unit of power consumed by a user, when using a certain modulation scheme. We consider power allocation with utility proportional fairness policy, where the fairness among users is in utility percentage i.e. percentage of successfully transmitted packets of the corresponding modulation scheme. We formulate our power allocation optimization problem as a product of utilities of all users and prove that it is convex and therefore the optimal solution is tractable. We present a distributed algorithm to allocate base station powers optimally with priority given to users running lower modulation schemes while ensuring non-zero power allocation to users running higher modulation schemes. Our algorithm prevents fluctuation in the power allocation process and is capable of traffic and modulation dependent pricing policy. This can be used to flatten traffic and decrease the service price for users. We also compare our results with a benchmark algorithm and show that our algorithm performs better in allocating powers fairly to all users without dropping any user in order to maximize performance.     

Optical image encryption based on two beams’ interference

We proposed a method for optical image encryption on the basis of interference theory. An optical image can be produced by the interference of two beams passed two different masks. One of the masks can only modulate the phase of the beam and another can only modulate the amplitude of the beam. The encryption method is quite simple and does not need iterative algorithm. The results of simulation coincide with our method and demonstrate the feasibility of this method.     

Numerical propagation of partially coherent laser beams through optical systems

The propagation of partially coherent beams through optical systems is computed numerically in one transverse dimension. The optical system is divided into different elementary segments, through which the propagation of light can be calculated by appropriate operators, working on the coherence function or the Wigner distribution function respectively. For the necessary changes between these two functions describing the partially coherent beams, the use of the remarkable z-transform seems to be an advantage. With this algorithm the grid and the resolution in the spatial frequency domain can be arbitrarily chosen in contrast to the usual Fourier transform, the influence of phase aberrations on the focusability of Gauss-Schell model beams is discussed as an application example of the numerical model. With the help of this tool, practical beam guiding systems can be simulated for use with multimode laser radiation.     

Exponential speedup of quantum newton optimization algorithm for general polynomials

Quantum optimization algorithms can outperform their classical counterpart and are key in modern technology. The second-order optimization algorithm(the Newton algorithm) is a critical optimization method, speeding up the convergence by employing the second-order derivative of loss functions in addition to their first derivative. Here, we propose a new quantum second-order optimization algorithm for general polynomials with a computational complexity of O(poly(log d)). We use this algorithm to solve the nonlinear equation and learning parameter problems in factorization machines. Numerical simulations show that our new algorithm is faster than its classical counterpart and the first-order quantum gradient descent algorithm. While existing quantum Newton optimization algorithms apply only to homogeneous polynomials, our new algorithm can be used in the case of general polynomials, which are more widely present in real applications.     

Flexible single molecule simulation of reaction–diffusion processes

An algorithm is developed for simulation of the motion and reactions of single molecules at a microscopic level. The molecules diffuse in a solvent and react with each other or a polymer and molecules can dissociate. Such simulations are of interest e.g. in molecular biology. The algorithm is similar to the Green’s function reaction dynamics (GFRD) algorithm by van Zon and ten Wolde where longer time steps can be taken by computing the probability density functions (PDFs) and then sample from the distribution functions. Our computation of the PDFs is much less complicated than GFRD and more flexible. The solution of the partial differential equation for the PDF is split into two steps to simplify the calculations. The sampling is without splitting error in two of the coordinate directions for a pair of molecules and a molecule-polymer interaction and is approximate in the third direction. The PDF is obtained either from an analytical solution or a numerical discretization. The errors due to the operator splitting, the partitioning of the system, and the numerical approximations are analyzed. The method is applied to three different systems involving up to four reactions. Comparisons with other mesoscopic and macroscopic models show excellent agreement.     

A new algorithm for anisotropic solutions

We establish a new algorithm that generates a new solution to the Einstein field equations, with an anisotropic matter distribution, from a seed isotropic solution. The new solution is expressed in terms of integrals of an isotropic gravitational potential; and the integration can be completed exactly for particular isotropic seed metrics. A good feature of our approach is that the anisotropic solutions necessarily have an isotropic limit. We find two examples of anisotropic solutions which generalise the isothermal sphere and the Schwarzschild interior sphere. Both examples are expressed in closed form involving elementary functions only.     

一种求解级联拉曼光纤激光器的方法

 根据适应度函数的具体情况改进了微粒群算法,与基本微粒群算法相比,其复杂函数的寻优能力得到了提高。利用改进的微粒群算法对不同结构的拉曼光纤激光器理论模型对应的适应度函数进行了算法测试,保证适应度函数精度(10^-5)的情况下,计算时间不超过15 s。与Newton-Raphson打靶算法配合时,有效地缩短计算时间、提高打靶算法稳定性和计算精度。最后,利用该算法数值分析了二阶掺磷拉曼光纤激光器输出端反射率、光纤长度和泵浦功率对输出功率的影响。     

Feedback-controlled femtosecond pulse shaping

We describe the experimental implementation of feedback-optimized femtosecond laser pulse shaping. A frequency-domain phase shaper is combined with different pulse characterization methods and appropriate optimization algorithms to compensate for any phase deviation. In particular, bandwidth-limited, amplified laser pulses are achieved by maximizing the second-harmonic generation (SHG) of the shaped laser pulses with the aid of an evolutionary algorithm. Real-time measurement of the absolute phases is achieved with spectral interferometry where the reference pulse is characterized by FROG, the so-called TADPOLE method. Using the complete electric field as feedback, arbitrary laser pulse shapes can be optimally generated in two different ways. First, a local convergence algorithm can be used to apply reliable and accurate spectral chirps. Second, an evolutionary algorithm can be employed to reach specific temporal profiles.     

Functional integrals for the partition functions of dual strings

We show how the partition functions and helicity partition functions of the known dual strings can be obtained from functional integrals. We define these integrals using a cut-off which is essentially equivalent to Ramanujan's definition of divergent sums. This leads to a very compact algorithm.     

A computational algorithm for computing nonlinear auditory frequency selectivity.

Computational algorithms that mimic the response of the basilar membrane must be capable of reproducing a range of complex features that are characteristic of the animal observations. These include complex input output functions that are nonlinear near the site's best frequency, but linear elsewhere. This nonlinearity is critical when using the output of the algorithm as the input to models of inner hair cell function and subsequent auditory-nerve models of low- and high-spontaneous rate fibers. We present an algorithm that uses two processing units operating in parallel: one linear and the other compressively nonlinear. The output from the algorithm is the sum of the outputs of the linear and nonlinear processing units. Input to the algorithm is stapes motion and output represents basilar membrane motion. The algorithm is evaluated against published chinchilla and guinea pig observations of basilar membrane and Reissner's membrane motion made using laser velocimetry. The algorithm simulates both quantitatively and qualitatively, differences in input/output functions among three different sites along the cochlear partition. It also simulates quantitatively and qualitatively a range of phenomena including isovelocity functions, phase response, two-tone suppression, impulse response, and distortion products. The algorithm is potentially suitable for development as a bank of filters, for use in more comprehensive models of the peripheral auditory system.     

Fast Analysis of Molecular Dynamics Trajectories with Graphics Processing Units-Radial Distribution Function Histogramming

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU's memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm are presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 seconds per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis.     

A novel algorithm for the reduction of undersampling artefacts in magnetic resonance images

An innovative algorithm is presented which is effective in reducing the truncation artefacts occurring in magnetic resonance images due to missing k-space samples. The algorithm works first by filling the incomplete matrix of coefficients with zeroes and then adjusting, by an iterative process, the missing coefficients by performing a reduction of the undersampling artefacts. Then, this set of coefficients is used as a basis for a superresolution algorithm that estimates the missing coefficients by modeling the data as a linear combination of increasing and decreasing exponential functions using Prony's method. In fact, the Prony's method consists of the interpolation of a given data set with a sum of exponential functions: the MRI signals can be well represented as a sum of exponential functions and the missing data can be extrapolated by this representation. The algorithm has been proven to perform better than either a simple algorithm, which detects and then reduces the undersampling artefacts, or an algorithm that models the measured data with approximation functions. The presented algorithm is quite simple and is applicable both to missing rows (phase-frequency acquisitions) and to radial-missing angle (acquisition from projections) undersampling. Experimental results are reported; comparisons, made between the results obtained using the presented algorithm and the alternative methods described above, clearly demonstrate the superiority of the algorithm.