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.     

基于评价信息随机化的群体评价方法与应用

针对群体评价中共识集结的相关问题,从仿真的视角讨论了评价信息随机化的群体共识聚合求解方法。首先,面向实数类型的评价信息,将精确性的数据给予一定的宽松性处理,进一步结合正态分布的3σ原则,利用随机模拟的方式集结出带有概率特征的可能性排序;其次,面向区间数类型的评价信息,整合出各子区间发生概率不同的区间数评价信息,在充分随机模拟的情况下,给出了带有优胜概率特征的可能性排序。最后,通过相应的算例进行求解分析,说明了该方法的可行性和有效性。基于群体共识视角,针对实数和区间数两种类型的评价信息,分别进行相应的随机化处理,并为进一步探索区间数的分布形式提供了一种新的研究思路。     

Stochastic stabilization of hybrid neural networks by periodically intermittent control based on discrete-time state observations

This paper is concerned with stabilization of hybrid neural networks by intermittent control based on continuous or discrete-time state observations. By means of exponential martingale inequality and the ergodic property of the Markov chain, we establish a sufficient stability criterion on hybrid neural networks by intermittent control based on continuous-time state observations. Meantime, by M-matrix theory and comparison method, we show that hybrid neural networks can be stabilized by intermittent control based on discrete-time state observations. Finally, two examples are presented to illustrate our theory.     

气相色谱-负化学源质谱法测定船舶压载水中4种三卤甲烷北大核心CSCD

我国每年的船舶压载水排放量巨大,压载水中含有浮游生物、病原体及其幼虫或孢子等,若处理不当,会对排放水域的生态环境造成严重影响。排放压载水前常使用电解法对其进行处理,电解产生的次氯酸钠溶液,能有效杀灭残余的微生物。但电解后会产生副产物三卤甲烷(THMs),其对人体有一定的健康风险,建立船舶压载水中三卤甲烷的测定方法具有重要意义。该研究建立了采用气相色谱-负化学源质谱(GC-NCI-MS)测定船舶压载水中4种三卤甲烷(包括三氯甲烷、二氯一溴甲烷、一氯二溴甲烷、三溴甲烷)的分析方法。船舶压载水样品经过顶空进样技术处理后,通过DB-5MS UI毛细管色谱柱(30 m×0.25 mm×1.0μm)分离,气相色谱-负化学源质谱仪测定,在选择离子扫描(SIM)模式下分析,采用外标法进行定量。4种三卤甲烷在0.2~50μg/L范围内线性关系良好,相关系数(r)≥0.995,定量限(S/N=10)为0.1~0.2μg/L,在0.2、0.5、2.0μg/L 3个加标水平下,4种THMs的平均回收率为90.3%~106.8%,相对标准偏差(RSD)为1.4%~6.2%。该方法准确、稳定、可靠,可用于测定船舶压载水中4种THMs的含量。使用建立的测定方法对36个船舶压载水进行测定,三溴甲烷、二溴一氯甲烷、一溴二氯甲烷与三氯甲烷的检出率分别为83.3%、69.4%、22.2%和19.4%,检出值分别为34.25~221.5μg/L、3.52~41.87μg/L、1.52~8.56μg/L和0.02~5.46μg/L。     

锰氧化物中氧空位的构建及其催化氧化苯系物作用机制研究进展

作为一种过渡金属氧化物,锰氧化物以其多晶型、储/释氧能力强、蕴含丰富氧物种、结构缺陷可控等优点被广泛应用于苯系物的热催化氧化。其中,具有众多特性的氧空位能有效促进苯系物的完全催化氧化,因而成为各界研究的焦点。我们综述了常见的氧空位构建方法及表征技术,并总结了在苯系物催化氧化过程中,锰氧化物中氧空位的几种重要作用机制对催化活性和抗水性能的积极影响。最后文章对氧空位构建新方法、形成机理、具体过程及其在锰氧化物热催化氧化苯系物领域中的应用进行了总结和展望。     

Steady-State Source Flow in Heterogeneous Porous Media

The flow of fluids in heterogeneous porous media is modelled by regarding the hydraulic conductivity as a stationary random space function. The flow variables, the pressure head and velocity field are random functions as well and we are interested primarily in calculating their mean values. The latter had been intensively studied in the past for flows uniform in the average. It has been shown that the average Darcy's law, which relates the mean pressure head gradient to the mean velocity, is given by a local linear relationship. As a result, the mean head and velocity satisfy the local flow equations in a fictitious homogeneous medium of effective conductivity. However, recent analysis has shown that for nonuniform flows the effective Darcy's law is determined by a nonlocal relationship of a convolution type. Hence, the average flow equations for the mean head are expressed as a linear integro-differential operator. Due to the linearity of the problem, it is useful to derive the mean head distribution for a flow by a source of unit discharge. This distribution represents a fundamental solution of the average flow equations and is called the mean Green function G _d (x). The mean head G _d(x) is derived here at first order in the logconductivity variance for an arbitrary correlation function (x) and for any dimensionality d of the flow. It is obtained as a product of the solution G _d ⁽⁰⁾(x) for source flow in unbounded domain of the mean conductivity K _A and the correction _d (x) which depends on the medium heterogeneous structure. The correction _d is evaluated for a few cases of interest.Simple one-quadrature expressions of _d are derived for isotropic two- and three-dimensional media. The quadratures can be calculated analytically after specifying (x) and closed form expressions are derived for exponential and Gaussian correlations. The flow toward a source in a three-dimensional heterogeneous medium of axisymmetric anisotropy is studied in detail by deriving ₃ as function of the distance from the source x and of the azimuthal angle . Its dependence on x, on the particular (x) and on the anisotropy ratio is illustrated in the plane of isotropy (=0) and along the anisotropy axis ( = /2).The head factor k ^* is defined as a ratio of the head in the homogeneous medium to the mean head, k ^*=G _d ⁽⁰⁾/G _d= _d ^–1. It is shown that for isotropic conductivity and for any dimensionality of the flow the medium behaves as a one-dimensional and as an effective one close and far from the source, respectively, that is, lim _x0 k ^*(x) = K _H/K _A and lim _x k ^*(x) = K ^efu/K _A, where K _A and K _H are the arithmetic and harmonic conductivity means and K ^efu is the effective conductivity for uniform flow. For axisymmetric heterogeneity the far-distance limit depends on the direction. Thus, in the coordinate system of (x) principal directions the limit values of k ^* are obtained as . These values differ from the corresponding components of the effective conductivities tensor for uniform flow for = 0 and /2, respectively. The results of the study are applied to solving the problem of the dipole well flow. The dependence of the mean head drop between the injection and production chambers on the anisotropy of the conductivity and the distance between the chambers is analyzed.     

Log-likelihood maximization and response surface in reliability assessment

Nonlinear dynamics problems can generally be solved only in a numerical way. This prevents from a direct application of standard reliability methods. A technique which makes use of iterated response-surface analytical approximations of the system performance function was therefore proposed in view of reliability assessment. The limitation of this technique was of working in a standard normalized space, so that appropriate space transformations are preliminarly required.This paper shows how this response-surface iterative scheme can also be used in the original space of the random variables, provided a maximum log-likelihood constrained optimization problem is solved. Moreover, asymptotic theory also provides a better estimate of the probability of failure of the dynamical system against any assigned limit state.     

点支承四边自由各向异性平行四边形板自由振动、屈曲和弯曲分析

一个精确的重富立叶级数解析解用于分析四边形自由的点支横观各向异性平行四边形板的自由振动、屈曲和弯曲。解析解用叠加法得到,此解收敛迅速。与现有结果的比较证实了由本法得到的解析解的精确性。文后用图表给出高精度的自由振动、屈曲和弯曲计算结果。     

圆柱绕流尾迹中相干结构对湍流特性的影响

实验研究了圆柱尾迹中相干结构对湍流平均量的影响.用一个X热线在距离圆柱体y/d=4测量参考信号,用X热线和冷线相结合的三线探头测量从x/d=10～40的圆柱绕流尾迹中的速度和温度脉动,用条件平均的方法研充圆柱绕流近尾迹中的相干结构,并对相干结构对动量和热量的湍流输运过程的影响进行初步分析.结果表明:相干结构对尾迹中速度的横向脉动影响最大;相干结构对湍流参数的影响随x/d的变化明显.该工作还对相干结构引起的湍动能产生率变成负和逆温度梯度输运现象做了定性的解释.     

负压爆炸载荷和数据采集间隔对弹性开孔板动应力集中的影响

基于ANSYS 7.0/LS-DYNA程序,对3 m3 m四边简支,厚度0.025 m,中心开有0.3 m0.3 m方孔的弹性板,在正压和负压三角爆炸载荷作用下的应力响应进行了分析,利用能量密度时间分布函数（TDFED）确定了动应力集中因子,并给出其计算步骤。计算结果表明计算总时间和数据采集时间间隔对动应力集中因子影响较大,而负压荷载影响较小。