Pseudo Random Coins Show More Heads Than Tails

Tossing a coin is the most elementary Monte-Carlo experiment. In a computer the coin is replaced by a pseudo random number generator. It can be shown analytically and by exact enumerations that popular random number generators are not capable of imitating a fair coin: pseudo random coins show more “heads” than “tails.” This bias explains the empirically observed failure of some random number generators in random walk experiments. It can be traced down to the special role of the value zero in the algebra of finite fields.     

High-voltage pulse production using transformer-coupled LC vectorinversion generators

The analysis, design, and operation of high-voltage, transformer-coupled LC vector inversion generators are presented and discussed. The transformer-coupled LC inversion generator is easy to construct and, compared with Marx-type generators and conventional LC vector inversion generators, requires only one inversion switch, independent of the number of voltage multiplication stages. The transformer-coupled LC generator, therefore, satisfies a niche area need for some high-voltage pulse applications. The primary factor that limits the performance of the transformer-coupled LC generator is magnetic saturation in the transformer core. This investigation develops theoretical scaling relationships for magnetic saturation in the transformer core and other performance-limiting factors. The results of transformer-coupled LC vector inversion generator numerical simulations are also compared with theoretical results     

结构材料辐照损伤的分子动力学程序GPU并行化及优化

基于NIVIDIA公司的CUDA架构对结构材料辐照损伤的分子动力学程序在单个GPU上进行并行化,并对影响程序运行效率的相关因素进行分析和测试.经过一系列优化,当粒子数为两百万时,对比单CPU的执行时间,优化后的GPU程序其双精度加速比可达112倍,单精度加速比达到了三百倍,为后续扩展多GPU结构材料辐照损伤的分子动力学程序奠定基础.     

图形处理器并行计算用于离子发动机粒子模拟

 为了研究离子发动机羽流对航天器的影响,采用质点网格-蒙特卡罗碰撞方法对离子发动机羽流中的交换电荷离子进行了模拟。利用计算设备统一架构技术,开发出一套基于图形处理器的并行粒子模拟程序。随机数生成采用并行MT19937伪随机数生成器算法,电场方程使用完全近似存储格式的代数多重网格法求解。r-z轴对称坐标系中,在z=0 m处获得的电流密度均值为4.5×10^-5 A/m²,图形处理器所得结果与中央处理器模拟结果吻合。在16核心的NVIDIA GeForce 9400 GT图形显示卡上,取得相对于Intel Core 2 E6300中央处理器4.5~10.0倍的加速比。     

Side Channel Passive Quantum Key Distribution with One Uninformative State

In most of quantum key distribution schemes, real random number generators are required on both sides for preparation and measurement bases choice. In this paper, via entangled photon pairs, we present a side channel passive quantum key distribution scheme, in which random number generator is unneeded on the receiver side. On the sender Alice side, along with massive of signal photons, small amount of uninformative photons are randomly sent to her partner Bob for eavesdropper-presence testing and error estimation. While on the other side channel, without using random number generator Bob do not actively measure the income signals randomly in two non-orthogonal bases. Instead, he just passively register photon click events, in two settled symmetric (i.e.X) bases, and the raw key(click events) is the probable outcomes of a special quantum measurement module constructed by Alice and Bob. Further, security analysis and formulas of security bounds for this scheme is also investigated under reasonable assumptions. Our work shows that the uninformative state employed in this paper is powerful to fight against eavesdropper Eve.     

Stochastic simulations on the cellular wave computers

The computational paradigm represented by Cellular Neural/nonlinear Networks (CNN) and the CNN Universal Machine (CNN-UM) as a Cellular Wave Computer, gives new perspectives for computational physics. Many numerical problems and simulations can be elegantly addressed on this fully parallelized and analogic architecture. Here we study the possibility of performing stochastic simulations on this chip. First a realistic random number generator is implemented on the CNN-UM, and then as an example the two-dimensional Ising model is studied by Monte Carlo type simulations. The results obtained on an experimental version of the CNN-UM with 128 ×128 cells are in good agreement with the results obtained on digital computers. Computational time measurements suggest that the developing trend of the CNN-UM chips — increasing the lattice size and the number of local logic memories — will assure an important advantage for the CNN-UM in the near future.     

Discontinuity detection in multivariate space for stochastic simulations

Edge detection has traditionally been associated with detecting physical space jump discontinuities in one dimension, e.g. seismic signals, and two dimensions, e.g. digital images. Hence most of the research on edge detection algorithms is restricted to these contexts. High dimension edge detection can be of significant importance, however. For instance, stochastic variants of classical differential equations not only have variables in space/time dimensions, but additional dimensions are often introduced to the problem by the nature of the random inputs. The stochastic solutions to such problems sometimes contain discontinuities in the corresponding random space and a prior knowledge of jump locations can be very helpful in increasing the accuracy of the final solution. Traditional edge detection methods typically require uniform grid point distribution. They also often involve the computation of gradients and/or Laplacians, which can become very complicated to compute as the number of dimensions increases. The polynomial annihilation edge detection method, on the other hand, is more flexible in terms of its geometric specifications and is furthermore relatively easy to apply. This paper discusses the numerical implementation of the polynomial annihilation edge detection method to high dimensional functions that arise when solving stochastic partial differential equations.     

SU (2) lattice gauge theory simulations on Fermi GPUs

In this work we explore the performance of CUDA in quenched lattice SU (2) simulations. CUDA, NVIDIA Compute Unified Device Architecture, is a hardware and software architecture developed by NVIDIA for computing on the GPU. We present an analysis and performance comparison between the GPU and CPU in single and double precision. Analyses with multiple GPUs and two different architectures (G200 and Fermi architectures) are also presented. In order to obtain a high performance, the code must be optimized for the GPU architecture, i.e., an implementation that exploits the memory hierarchy of the CUDA programming model.     

Physical generation of random numbers using an asymmetrical Boolean network

Autonomous Boolean networks (ABNs) have been successfully applied to the generation of random number due to their complex nonlinear dynamics and convenient on-chip integration. Most of the ABNs used for random number generators show a symmetric topology, despite their oscillations dependent on the inconsistency of time delays along links. To address this issue, we suggest an asymmetrical autonomous Boolean network (aABN) and show numerically that it provides large amplitude oscillations by using equal time delays along links and the same logical gates. Experimental results show that the chaotic features of aABN are comparable to those of symmetric ABNs despite their being made of fewer nodes. Finally, we put forward a random number generator based on aABN and show that it generates the random numbers passing the NIST test suite at 100 Mbits/s. The unpredictability of the random numbers is analyzed by restarting the random number generator repeatedly. The aABN may replace symmetrical ABNs in many applications using fewer nodes and, in turn, reducing power consumption.     

High-order finite-element seismic wave propagation modeling with MPI on a large GPU cluster

We implement a high-order finite-element application, which performs the numerical simulation of seismic wave propagation resulting for instance from earthquakes at the scale of a continent or from active seismic acquisition experiments in the oil industry, on a large cluster of NVIDIA Tesla graphics cards using the CUDA programming environment and non-blocking message passing based on MPI. Contrary to many finite-element implementations, ours is implemented successfully in single precision, maximizing the performance of current generation GPUs. We discuss the implementation and optimization of the code and compare it to an existing very optimized implementation in C language and MPI on a classical cluster of CPU nodes. We use mesh coloring to efficiently handle summation operations over degrees of freedom on an unstructured mesh, and non-blocking MPI messages in order to overlap the communications across the network and the data transfer to and from the device via PCIe with calculations on the GPU. We perform a number of numerical tests to validate the single-precision CUDA and MPI implementation and assess its accuracy. We then analyze performance measurements and depending on how the problem is mapped to the reference CPU cluster, we obtain a speedup of 20x or 12x.     

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.     

多路Marx并联高压脉冲电源研究

脉冲功率技术在工业和生物医学领域有着广泛的应用,很多应用场合要求输出数百安培的高压脉冲。固态Marx发生器虽已研究多年,但是被广泛采用直插封装的IGBT和MOSFET功率半导体开关管的额定电流通常都低于100 A,无法满足低阻抗负载的应用需求。为提高输出脉冲电流幅值,提出两种多路Marx发生器并联的脉冲电源的拓扑结构,第一种方案采用多路Marx发生器直接并联,第二种是共用一组充电开关管的多路Marx发生器并联。由FPGA提供充放电控制信号,采用串芯磁环隔离驱动方案实现带负压偏置的同步驱动,主电路选用开通速度快、通流能力强的IGBT为主开关的半桥式固态方波Marx电路。实验结果表明,6路16级Marx直接并联的脉冲发生器能输出重频100 Hz高压方波脉冲幅值可达10 kV,在30Ω负载侧输出峰值电流可达300 A,上升时间230 ns。共用充电开关管的6路4级Marx并联发生器在5Ω电阻负载上的输出电流峰值可达300 A,最大输出电流可达460 A,上升时间272 ns。表明多路Marx发生器并联可以有效地减小系统内阻,提高系统带载能力;改进后的并联方案实现大电流脉冲输出的同时,所采用的开关管数量减小近一半,提高了系统的抗干扰能力的同时,降低了脉冲电源的成本;且增加级间并联导线可进一步改善均流效果。     

随机相位和随机频率微波加热效应的数值模拟

 利用时域有限差分法（FDTD）并结合蛙跳技术，通过联合求解Maxwell方程组和热传导方程，模拟了水的微波加热过程，计算了烧杯中的水的温度分布；研究了随机相位和随机频率微波功率源合成时水的加热情况，对比了随机相位和随机频率非相干微波功率源与相干微波功率源作用下水的吸热和温升。计算结果表明，随机相位功率源进行合成时，烧杯中的水温分布更均匀，水所吸收的热量也较相干功率源合成加热时有较大增加；而随机频率功率源进行合成时，加热效果没有明显的变化。     

The intermittency of vector fields and random-number generators

We examine how well natural random-number generators can reproduce the intermittency phenomena that arise in the transfer of vector fields in random media. A generator based on the analysis of financial indices is suggested as the most promising random-number generator. Is it shown that even this generator, however, fails to reproduce the phenomenon long enough to confidently detect intermittency, while the C++ generator successfully solves this problem. We discuss the prospects of using shell models of turbulence as the desired generator.     

Lie Algebras and Superalgebras Defined by a Finite Number of Relations: Computer Analysis

Abstract

The presentation of Lie (super)algebras by a finite set of generators and defining relations is one of the most general mathematical and algorithmic schemes of their analysis. It is very important, for instance, for investigation of the particular Lie (super)algebras arising in different (super)symmetric physical models. Generally, one can put the following question: what is the most general Lie algebra or superalgebra satisfying to the given set of Lie polynomial equations? To solve this problem, one has to perform a large volume of algebraic transformations which sharply increases with growth of the number of generators and relations. By this reason, in practice, one needs to use a computer algebra tool. We describe here an algorithm and its implementation in C for constructing the bases of finitely presented Lie (super)algebras and their commutator tables.     

涡发生器对高超声速轴对称进气道外部流动的影响

采用三维CFD黏性模拟考察涡发生器对高超声速轴对称进气道外部流动的影响.针对前缘钝化半径0.8 mm和3.2 mm的轴对称进气道外部流场,以涡发生器高度与当地位移边界层厚度比值为影响参数,考察流场结构与性能参数的影响规律.结果表明,涡发生器产生的干扰波系使得前缘激波向外偏移,下游近壁面流动与主流区出现明显的交换,下游流动出现明显的展向非均匀性.涡发生器对流动的影响沿流向逐渐减弱.在气流压缩性能方面,涡发生器下游压比、动压比沿流向开始增大,随后逐渐恢复到无涡发生器工况;Mach数、总压恢复系数开始降低,随后逐渐向无涡发生器工况趋近.涡发生器高度与当地位移边界层厚度的比值h可作为衡量其影响的重要参数.当h≤1.5时,进气道流场结构、性能参数的变化几乎可忽略,h≤3.0时进气道入口处性能参数几乎能够恢复到无涡发生器工况.      

Implementation of a quantum random number generator based on the optimal clustering of photocounts

To implement quantum random number generators, it is fundamentally important to have a mathematically provable and experimentally testable process of measurements of a system from which an initial random sequence is generated. This makes sure that randomness indeed has a quantum nature. A quantum random number generator has been implemented with the use of the detection of quasi-single-photon radiation by a silicon photomultiplier (SiPM) matrix, which makes it possible to reliably reach the Poisson statistics of photocounts. The choice and use of the optimal clustering of photocounts for the initial sequence of photodetection events and a method of extraction of a random sequence of 0’s and 1’s, which is polynomial in the length of the sequence, have made it possible to reach a yield rate of 64 Mbit/s of the output certainly random sequence.     

Nonequilibrium MHD plasma flow in a high-interaction disk generator

Nonequilibrium MHD plasma flow in a high-interaction disk-type MHD generator is examined by numerical simulations based on the two-temperature model equations. The simulations are performed for the generators driven by working gases: He-Cs and He-K. Homogeneous and inhomogeneous plasma behavior is observed with change of the load resistance, and it is found that the structures of the inhomogeneous plasma differ for different seed materials. The plasma structures associated with both the partial ionization instability and the magnetoacoustic instability are discussed for both plasmas     

Implementation and comparative study of random sequences for nonlinear least square data fitting

A numerical study of nonlinear least square data fitting using random numbers from the congruential generator and several quasi-random generators is presented. The results indicate that at least up to five dimensions some of the quasi-random sequences yield better accuracy than the congruential pseudo-random sequence. Some recommendations for selecting the generators of quasi-random sequences are also given.     

An insulated-gate bipolar transistor model based on the finite-volume charge method

A finite-volume charge method has been proposed to simulate PIN diodes and insulated-gate bipolar transistor (IGBT) devices using SPICE simulators by extending the lumped-charge method. The new method assumes local quasi-neutrality in the undepleted N^- base region and uses the total collector current, the nodal hole density and voltage as the basic quantities. In SPICE implementation, it makes clear and accurate definitions of three kinds of nodes — the carrier density nodes, the voltage nodes and the current generator nodes — in the undepleted N^- base region. It uses central finite difference to approximate electron and hole current generators and sets up the current continuity equation in a control volume for every carrier density node in the undepleted N^- base region. It is easy to increase the number of nodes to describe the fast spatially varying carrier density in transient processes. We use this method to simulate IGBT devices in SPICE simulators and get a good agreement with technology computer-aided design simulations.