MPI在蒙特卡罗程序GMT中的应用和发展

针对ADS颗粒靶概念的研究和设计,中国科学院近代物理研究所自主研发了蒙特卡罗模拟软件GMT。为了提高GMT程序的计算效率,研究了MPI在GMT中的应用和发展,实现了大规模随机数在进程中的随机分配,并采用快速读写文件的方式替代了MPI相关数据通信函数,极大地提高了计算效率。并研究了不同规模计算实例进程数、加速比、效率之间的关系,确定了最大加速进程数及并行效率最高时的进程数,为科研工作者在计算资源和计算效率之间选择最优计算方案提供了科学依据。MPI在GMT中的成功应用使计算资源得到了充分、高效的利用,极大地提高了计算效率,解决了蒙特卡罗方法中大规模事件模拟计算时间长、计算不稳定等问题,在散裂靶大规模扫描计算中发挥了重要的作用。For the research and design of the ADS granular-flow target concept, the Institute of Modern Physics, CAS has developed a Monte Carlo simulation software (GPU-accelerated Monte Carlo Transport program, GMT). In order to improve the computational efficiency of the GMT program, development and application of MPI in GMT were studied, to realize random distribution of the large-scale random number in the sub processes. Rapid reading and writing files were employed instead of the MPI data communication function, which greatly improves the computational efficiency. Different scale calculations were performed to study the relationship of process instance number, speedup to find the maximum acceleration process number and the number of processes when parallel efficiency is highest, which provides a scientific basis for researchers to optimize the computational program between computational resources and computation efficiency. The successful application of MPI in GMT, utilizes the computing resources fully and efficiently, improves the computational efficiency, solve the long time cost and unstable problem of Monte Carlo method in large-scale event simulations, plays an important role in the large-scale scanning calculation of the spallation target.     

原子核等多体系统低激发态的系统研究

讨论了Casten的NpNn系统学、壳模型的配对近似方法应用及多体系统的某些固有性质,主要侧重于这3个问题研究的物理基础和意义。I would like to discuss low-lying systematics of NnNp suggested by Rick Casten, Nucleon-pair approximation of the nuclear shell model and its applications, and intrinsic properties of many-body systems in the presence of random interactions. I shall emphasize on backgrounds and perspectives of these problems, and summarize our basic understanding on these problems, after many efforts made by my collaborators and me.     

蒙特卡罗模拟中三维介质辐射对称性检验

蒙特卡罗方法是数值模拟中一个很常用的计算方法,应用范围很广泛,并常常作为数值仿真算法的基准.概率模型和伪随机数发生器是蒙特卡罗法中两个很重要的组成部分,它们决定了蒙特卡罗法的正确性和计算精度.本文提出了一种比较充分的检验方法-三维介质辐射对称性检验法,它可在不同条件下对各种伪随机数程序进行无限制的检验,在更精细的层次上区分伪随机数发生器的优劣,同时还可检验概率模型的正确性.     

Numerical analysis of uncertain temperature field by stochastic finite difference method

Based on the combination of stochastic mathematics and conventional finite difference method,a new numerical computing technique named stochastic finite difference for solving heat conduction problems with random physical parameters,initial and boundary conditions is discussed.Begin with the analysis of steady-state heat conduction problems,difference discrete equations with random parameters are established,and then the computing formulas for the mean value and variance of temperature field are derived by the second-order stochastic parameter perturbation method.Subsequently,the proposed random model and method are extended to the field of transient heat conduction and the new analysis theory of stability applicable to stochastic difference schemes is developed.The layer-by-layer recursive equations for the first two probabilistic moments of the transient temperature field at different time points are quickly obtained and easily solved by programming.Finally,by comparing the results with traditional Monte Carlo simulation,two numerical examples are given to demonstrate the feasibility and effectiveness of the presented method for solving both steady-state and transient heat conduction problems.     

闪光X射线照相蒙特卡罗程序的并行化

研究了闪光X射线辐射照像蒙特卡罗程序(FXRMC)在MPI平台下的并行计算实现,给出了实现过程中并行随机数的产生方法。对并行程序的测试结果表明:并行程序与串行程序结果一致,加速比比较理想,呈线性增长,并行效率在16个处理器上可达80%以上。算例的结果说明了并行化可有效地解决程序计算散射技术性能时的耗时问题,从而有效化解FXRMC耗时和大规模计算的困难,提高了FXRMC程序的计算规模和计算速度,达到了研究要求。 (Institute of Fluid Physics, CAEP, P. O. Box 919-105, Mianyang 621900, China)     

随机矩阵的本征值外推性质

外推近似方法在原子核壳模型上取得了一些成功,然而人们对于其原理知道得比较少。这里主要研究并讨论了随机两体系综和高斯正交系综最小本征值。利用截断空间的外推解释了高斯正交系综下的外推公式以及随机两体系综下本征值外推收敛的鲁棒性,即对于壳模型有效相互作用而言,用外推法预言最低本征值收敛性很好。Although the extrapolation method of diagonalizing the nuclear shell model Hamiltonian is successful, its foundation has not yet been understand very well. In this paper, we study this approach by using random matrices with the focus on gaussian ensemble and two-body random ensemble. We derive the formula of the extrapolation method of diagonalizing the matrices of Gaussian orthogonal ensemble, and discuss the robustness of the extrapolation property by two-body random ensemble. We point out that the extrapolation method of diagonalizing the shell model Hamiltonian works better with the realistic interaction than other interactions.     

蒙特卡罗模拟中相关变量随机数序列的产生方法

蒙特卡罗模拟有时需要对多维相关随机变量进行模拟抽样．本文介绍基于Choesky因子线性变换一非线性变换产生具有指定边缘分布和相关系数的多维相关随机变量抽样序列的一般方法,给出一种简单易行的高效数值实现途径和一些模拟结果．模拟结果表明,该方法产生的各随机变量抽样序列间具有预期要求的相关性,并能通过指定边缘分布Kolmogorov—Smimov非参数假设检验．对该方法应用中的一些限制问题进行了讨论．     

Justification of a Monte Carlo Algorithm for the Diffusion-Growth Simulation of Helium Clusters in Materials

A theoretical analysis of a Monte Carlo （MC） method for the simulation of the diffusion-growth of helium clusters in materials is presented. This analysis is based on an assumption that the diffusion-growth process consists of first stage, during which the clusters diffuse freely, and second stage in which the coalescence occurs with certain probability. Since the accuracy of MC simulation results is sensitive to the coalescence probability, the MC calculations in the second stage is studied in detail. Firstly, the coalescence probability is analytically formulated for the one-dimensional diffusion-growth ease. Thereafter, the one-dimensional results are employed to justify the MC simulation. The choice of time step and the random number generator used in the MC simulation are discussed.     

Stochastic period-doubling bifurcation analysis of stochastic Bonhoeffer--van der Pol system

In this paper, the Chebyshev polynomial approximation is applied to the problem of stochastic period-doubling bifurcation of a stochastic Bonhoeffer--van der Pol (BVP for short) system with a bounded random parameter. In the analysis, the stochastic BVP system is transformed by the Chebyshev polynomial approximation into an equivalent deterministic system, whose response can be readily obtained by conventional numerical methods. In this way we have explored plenty of stochastic period-doubling bifurcation phenomena of the stochastic BVP system. The numerical simulations show that the behaviour of the stochastic period-doubling bifurcation in the stochastic BVP system is by and large similar to that in the deterministic mean-parameter BVP system, but there are still some featured differences between them. For example, in the stochastic dynamic system the period-doubling bifurcation point diffuses into a critical interval and the location of the critical interval shifts with the variation of intensity of the random parameter. The obtained results show that Chebyshev polynomial approximation is an effective approach to dynamical problems in some typical nonlinear systems with a bounded random parameter of an arch-like probability density function.     

微机上实用蒙特卡罗抽样库

描述一个实用蒙特卡罗抽样库(MCSL).它可以提供:伪随机数产生的优良算法和程序;重要分布的最佳随机抽样方法和程序;在粒子输运问题中位置、能量、方向的常用分布的抽样程序.还配有一个专门的抽样库检验系统.它在微机上运行,安装简单,使用方便,有较强的实用性和可移植性.     

From Random Numbers to Random Objects

Many security-related scenarios including cryptography depend on the random generation of passwords, permutations, Latin squares, CAPTCHAs and other types of non-numerical entities. Random generation of each entity type is a different problem with different solutions. This study is an attempt at a unified solution for all of the mentioned problems. This paper is the first of its kind to pose, formulate, analyze and solve the problem of random object generation as the general problem of generating random non-numerical entities. We examine solving the problem via connecting it to the well-studied random number generation problem. To this end, we highlight the challenges and propose solutions for each of them. We explain our method using a case study; random Latin square generation.     

Image encryption using random sequence generated from generalized information domain

A novel image encryption method based on the random sequence generated from the generalized information domain and permutation–diffusion architecture is proposed. The random sequence is generated by reconstruction from the generalized information file and discrete trajectory extraction from the data stream. The trajectory address sequence is used to generate a P-box to shuffle the plain image while random sequences are treated as keystreams. A new factor called drift factor is employed to accelerate and enhance the performance of the random sequence generator. An initial value is introduced to make the encryption method an approximately one-time pad. Experimental results show that the random sequences pass the NIST statistical test with a high ratio and extensive analysis demonstrates that the new encryption scheme has superior security.     

混沌半导体激光器的弛豫振荡频率对随机序列速率的影响

利用光反馈半导体激光器产生的混沌激光作为随机数发生器的物理熵源, 分析了混沌信号自相关系数与随机序列游程数之间的联系, 在此基础上研究了激光器的弛豫振荡频率f_r与随机序列速率f_n在不同比值时, 序列游程数的变化情况. 研究发现, 当f_r/f_n=(2k+1)/4时, 随机序列的游程数容易满足NIST SP800-22随机数测试标准的要求. 当k=1时, 得到随机序列最大速率为f_n=4f_r/3.     

A hybrid-type quantum random number generator

This paper proposes a well-performing hybrid-type truly quantum random number generator based on the time interval between two independent single-photon detection signals, which is practical and intuitive, and generates the initial random number sources from a combination of multiple existing random number sources. A time-to-amplitude converter and multichannel analyzer are used for qualitative analysis to demonstrate that each and every step is random. Furthermore, a carefully designed data acquisition system is used to obtain a high-quality random sequence. Our scheme is simple and proves that the random number bit rate can be dramatically increased to satisfy practical requirements.     

Design and Test of an Integrated Random Number Generator with All-Digital Entropy Source

In the cybersecurity field, the generation of random numbers is extremely important because they are employed in different applications such as the generation/derivation of cryptographic keys, nonces, and initialization vectors. The more unpredictable the random sequence, the higher its quality and the lower the probability of recovering the value of those random numbers for an adversary. Cryptographically Secure Pseudo-Random Number Generators (CSPRNGs) are random number generators (RNGs) with specific properties and whose output sequence has such a degree of randomness that it cannot be distinguished from an ideal random sequence. In this work, we designed an all-digital RNG, which includes a Deterministic Random Bit Generator (DRBG) that meets the security requirements for cryptographic applications as CSPRNG, plus an entropy source that showed high portability and a high level of entropy. The proposed design has been intensively tested against both NIST and BSI suites to assess its entropy and randomness, and it is ready to be integrated into the European Processor Initiative (EPI) chip.     

Semiconductor Emitters in Entropy Sources for Quantum Random Number Generation

Random number generation (RNG) is needed for a myriad of applications ranging from secure communication encryption to numerical simulations to sports and games. However, generating truly random numbers can be elusive. Pseudorandom bit generation using computer algorithms provides a high random bit generation rate. Nevertheless, the reliance on predefined algorithms makes it deterministic and predictable once initial conditions are known. Relying on physical phenomena (such as measuring electrical noise or even rolling dice) can achieve a less predictable sequence of bits. Furthermore, if the physical phenomena originate from quantum effects, they can be truly random and completely unpredictable due to quantum indeterminacy. Traditionally, physical RNG is significantly slower than pseudorandom techniques. To meet the demand for high-speed RNG with perfect unpredictability, semiconductor light sources are adopted as parts of the sources of randomness, i.e., entropy sources, in quantum RNG (QRNG) systems. The high speed of their noise, the high efficiency, and the small scale of these devices make them ideal for chip-scale QRNG. Here, the applications and recent advances of QRNG are reviewed using semiconductor emitters. Finally, the performance of these emitters is compared and discuss their potential in future technologies.     

偏振光量子随机源

报道了一种基于偏振光量子的随机效应产生的随机源，这种方法利用了单个偏振光子在偏振分束镜表现出来的量子随机性.用同步符合单光子检测技术，对衰减的偏振单光子源在偏振分束镜表现的随机性进行检测，利用计算机和数据采集卡，获得了二元随机码.利用国际通用的随机数检测程序(ENT)对直接获得的数据进行随机性分析，结果完全满足真随机数的标准.     

物理真随机码发生器随机性分析

对物理随机码发生器的物理参量与其产生的随机码序列的随机性关系进行了分析.根据量子保密通信对随机码序列的随机性的要求,分析了常见的随机码发生器产生的随机码的随机性,给出了利用随机高斯噪音经比较器产生随机码的随机码发生器的随机性公式.     

线宽增强因子对光反馈半导体激光器混沌信号生成随机数性能的影响

基于光反馈半导体激光器产生的宽带混沌信号作为物理熵源生成物理随机数已得到广泛研究.线宽增强因子的存在会导致半导体激光器出现大量不稳定动态特性,因此,本文着重研究半导体激光器的线宽增强因子对生成随机数性能的影响.数值仿真结果表明:随着线宽增强因子的增加,光反馈半导体激光器输出混沌信号的延时峰值逐渐减小、最大李雅普诺夫指数逐渐增大.基于不同线宽增强因子下产生的混沌信号提取随机数,并利用NIST SP 800-22软件对生成随机数的性能进行测试.测试结果表明,选取线宽增强因子较大的半导体激光器产生混沌信号作为物理熵源易于生成性能良好的随机数.