Quantum Bayesian computation

Quantum Bayesian computation is an emerging field that levers the computational gains available from quantum computers. They promise to provide an exponential speed-up in Bayesian computation. Our article adds to the literature in three ways. First, we describe how quantum von Neumann measurement provides quantum versions of popular machine learning algorithms such as Markov chain Monte Carlo and deep learning that are fundamental to Bayesian learning. Second, we describe quantum data encoding methods needed to implement quantum machine learning including the counterparts to traditional feature extraction and kernel embeddings methods. Third, we show how quantum algorithms naturally calculate Bayesian quantities of interest such as posterior distributions and marginal likelihoods. Our goal then is to show how quantum algorithms solve statistical machine learning problems. On the theoretical side, we provide quantum versions of high dimensional regression, Gaussian processes and stochastic gradient descent. On the empirical side, we apply a quantum FFT algorithm to Chicago house price data. Finally, we conclude with directions for future research.     

容量矩阵法在涡方法中的应用

本文将容量矩阵技术与快速Fourier变换相结合求解非矩形域的Poisson方程,再与格子涡方法相结合,发展了一套求解复杂外形的快速涡方法。作为算例,计算了有厚度平板和楔形体的分离流动,得到了满意的结果。特别是在垂直平板绕流中,模拟出了由于剪切层不稳定性引起的小涡结构。     

基于傅立叶变换的SVJ模型的欧式期权定价

为了更加精确的计算期权价格,将结合随机波动和跳扩散模型(以下简称SVJ模型)以更好的描述期权标的资产价格过程,然而这样的价格过程无法得到概率密度函数的封闭形式,而只能得到包含特殊函数和无限求和的复杂的表达式.不过它们的特征函数都是封闭且是唯一的,因而可以通过它们的特征函数,并运用两种傅立叶变换的方法来求出期权价格.其中FFT算法计算的结果将与Monte Carlo模拟得出的结果进行比较,然后再将SVJ模型的计算结果和Black-Scholes模型进行比较.     

A spectral element method using the modal basis and its application in solving second‐order nonlinear partial differential equations

We present a high‐order spectral element method (SEM) using modal (or hierarchical) basis for modeling of some nonlinear second‐order partial differential equations in two‐dimensional spatial space. The discretization is based on the conforming spectral element technique in space and the semi‐implicit or the explicit finite difference formula in time. Unlike the nodal SEM, which is based on the Lagrange polynomials associated with the Gauss–Lobatto–Legendre or Chebyshev quadrature nodes, the Lobatto polynomials are used in this paper as modal basis. Using modal bases due to their orthogonal properties enables us to exactly obtain the elemental matrices provided that the element‐wise mapping has the constant Jacobian. The difficulty of implementation of modal approximations for nonlinear problems is treated in this paper by expanding the nonlinear terms in the weak form of differential equations in terms of the Lobatto polynomials on each element using the fast Fourier transform (FFT). Utilization of the Fourier interpolation on equidistant points in the FFT algorithm and the enough polynomial order of approximation of the nonlinear terms can lead to minimize the aliasing error. Also, this approach leads to finding numerical solution of a nonlinear differential equation through solving a system of linear algebraic equations. Numerical results for some famous nonlinear equations illustrate efficiency, stability and convergence properties of the approximation scheme, which is exponential in space and up to third‐order in time. Copyright © 2014 John Wiley & Sons, Ltd.     

Efficient integration for a class of highly oscillatory integrals

This paper presents some quadrature methods for a class of highly oscillatory integrals whose integrands may have singularities at the two endpoints of the interval. One is a Filon-type method based on the asymptotic expansion. The other is a Clenshaw-Curtis-Filon-type method which is based on a special Hermite interpolation polynomial and can be evaluated efficiently in O(N log N) operations, where N + 1 is the number of Clenshaw-Curtis points in the interval of integration. In addition, we derive the corresponding error bound in inverse powers of the frequency ω for the Clenshaw-Curtis-Filon-type method for the class of highly oscillatory integrals. The efficiency and the validity of these methods are testified by both the numerical experiments and the theoretical results.     

Finite difference method for 2-D and 3-D nonlinear free surface wave problems

A finite difference method is developed for the numerical modelling of the 2-D and 3-D unsteady potential flow generated by transient disturbances on the free surface, on which the nonlinear boundary conditions are fully satisfied. The unknown function is computed with an iteration scheme processing in a transformed time-invariant space. After the velocity is calculated, the location of the free surface is renewed and so is the value of velocity on it. The boundary-value problem of the governing equation is then solved at the next time step. The present method incorporates the FFT. Consequently, a tri-diagonal equation system is obtained which could be readily solved. The feasibility of this method has been demonstrated by 2-D and 3-D examples corresponding to different initial disturbances. This work is supported by the science foundation of Academia Sinica. The paper had been accepted by the XVIth International Congress of IUTAM, Lyngby, Denmark, August, 1984.     

一种基于谱线幅值归零的加窗插值 FFT 谐波检测方法

提出了一种基于谱线幅值归零的加窗插值 FFT 谐波检测方法用于分析复杂电网信号中的各次谐波。 该检测方法将每一次在离散频谱中找到的最大谱线及其左右两侧的数根谱线幅值归零,直到各次谐波分析完毕。 通过仿真实验分析了在基波频率稳定时对模拟信号的测量精度,研究了基波频率波动对谐波分析的影响。通过对EAST 实验数据的分析,验证了该谐波检测方法的可行性和高精度性。     

基于FFT的薄膜厚度干涉测量新方法

在研究二维FFT法进行干涉测试基本原理的基础上，提出一种基于二维FFT的薄膜厚度测量新方法。利用搭建的泰曼-格林型干涉系统，用CCD接收、采集卡采集，可获得被测膜层的干涉条纹图像。编制算法处理软件，可实现对干涉条纹图中薄膜边缘识别、区域延拓、滤波、波面统一等的处理，从而获得带有薄膜信息的面形分布，实现对薄膜样片厚度的自动化测量。研究结果表明：所测薄膜厚度的峰谷值为0．2562，均方根值为0．068λ，说明采用基于FFT的薄膜厚度干涉测量新方法测量薄膜厚度具有较高的精度。     

跳跃-扩散模型资产定价公式的数值计算方法

假定资产价格变化过程服从跳跃-扩散过程,那么基于它的欧式期权就满足一个偏积分-微分方程（PIDE）,本文利用差分法来离散这个PIDE方程,用两种迭代方法得到方程的数值解：基于雅可比正则分裂法和预条件共轭梯度法.