Generation of entangled coherent-squeezed states: their entanglement and nonclassical properties

In this paper, after a brief review on the coherent states and squeezed states, we introduce two classes of entangled coherent-squeezed states. Next, in order to generate the introduced entangled states, we present a theoretical scheme based on the resonant atom-field interaction. In the proposed model, a \(\varLambda \)-type three-level atom interacts with a two-mode quantized field in the presence of two strong classical fields. Then, we study the amount of entanglement of the generated entangled states using the concurrence and linear entropy. Moreover, we evaluate a few of their nonclassical properties such as photon statistics, second-order correlation function, and quadrature squeezing and establish their nonclassicality features.     

Generation and entanglement of multi-dimensional multi-mode coherent fields in cavity QED

We introduce generalized multi-mode superposition of multi-dimensional coherent field states and propose a generation scheme of such states in a cavity QED scenario. An appropriate encoding of information on these states is employed, which maps the states to the Hilbert space of some multi-qudit states. The entanglement of these states is characterized based on such proper encodings. A detailed study of entanglement in general multi-qudit coherent states is presented, and in addition to establishing some explicit expressions for quantifying entanglement of such systems, several important features of entanglement in these system states are exposed. Furthermore, the effects of both cavity decay and channel noise on these system states are studied and their properties are illustrated.     

Practical entanglement distillation scheme using recurrence method and quantum low density parity check codes

Many entanglement distillation schemes use either universal random hashing or breeding as their final step to obtain almost perfect shared EPR pairs. In spite of a high yield, the hardness of decoding a random linear code makes the use of random hashing and breeding infeasible in practice. In this pilot study, we analyze the performance of the recurrence method, a well-known entanglement distillation scheme, with its final random hashing or breeding procedure being replaced by various efficiently decodable quantum codes. Among all the replacements investigated, the one using a certain adaptive quantum low density parity check (QLDPC) code is found to give the highest yield for Werner states over a wide range of noise level—the yield for using this QLDPC code is higher than the first runner up by more than 25% over a wide parameter range. In this respect, the effectiveness of using QLDPC codes in practical entanglement distillation is illustrated.     

Generation of continuous variable squeezing and entanglement of trapped ions in time-varying potentials

We investigate the generation of squeezing and entanglement for the motional degrees of freedom of ions in linear traps, confined by time-varying and oscillating potentials, comprised of a DC and an AC component. We show that high degrees of squeezing and entanglement can be obtained by controlling either the DC or the AC trapping component (or both), and by exploiting transient dynamics in regions where the ions’ motion is unstable, without any added optical control. Furthermore, we investigate the time-scales over which the potentials should be switched in order for the manipulations to be most effective.     

Direct measure of genuine tripartite entanglement independent from bipartite constructions

A new and direct measure (without bipartite measures) of genuine entanglement in tripartite systems based on the volume of the negative part of the Wigner function is proposed. We analyze comparatively this quantity and the different types of entanglement present in two major classes (GHZ and W classes) formed in the coherent state basis.     

Estimating negative variance components from Gaussian and non-Gaussian data: A mixed models approach

The occurrence of negative variance components is a reasonably well understood phenomenon in the case of linear models for hierarchical data, such as variance-component models in designed experiments or linear mixed models for longitudinal data. In many cases, such negative variance components can be translated as negative within-unit correlations. It is shown that negative variance components, with corresponding negative associations, can occur in hierarchical models for non-Gaussian outcomes as well, such as repeated binary data or counts. While this feature poses no problem for marginal models, in which the mean and correlation functions are modeled directly and separately, the issue is more complicated in, for example, generalized linear mixed models. This owes in part to the non-linear nature of the link function, non-constant residual variance stemming from the mean-variance link, and the resulting lack of closed-form expressions for the marginal correlations. It is established that such negative variance components in generalized linear mixed models can occur in practice and that they can be estimated using standard statistical software. Marginal-correlation functions are derived. Important implications for interpretation and model choice are discussed. Simulations and the analysis of data from a developmental toxicity experiment underscore these results.     

Linear non-Gaussian causal discovery from a composite set of major US macroeconomic factors

In this paper, we develop an effective approach to model linear non-Gaussian causal relationships among a composite set of major US macroeconomic factors. The proposed approach first models the linear relationships of the factors using the Vector Autoregression (VAR) model, then the casual relationships are discovered using the linear non-Gaussian Structural Equation Modeling (SEM) method. One advantage of our hybrid approach is that the contemporaneous causal order of macroeconomic variables which is important for VAR practitioners is obtained naturally as a result of the computation. Applying our approach to 11 major US macroeconomic factors reveals that the federal funds rate has the dominating power in the set. This outcome purely based on the underlying data without any prior knowledge is in line with previous studies using other empirical approaches where prior knowledge is often essential. We also provide a global picture depicting the interaction among all the macroeconomic factors of concern, which are often approached individually or in small grouping in the economic research literature in the past and not studied in a unified view as in our approach.     

萃取抽提混合二乙苯中间二乙苯的研究

采用单级循环汽液平衡釜测定混合二乙苯不同组分与溶剂之间的汽液平衡数据,计算间二乙苯与主要组分之间的相对挥发度,并与模拟结果进行对比,确定萃取精馏分离的最佳溶剂。采用Aspen Plus软件进行模拟研究,考察了理论板数、塔顶采出比、溶剂比、回流比等因素对分离过程的影响。模拟结果表明,在理论板数为80块、进料位置为第40块、塔顶采出料比为0.7:1、溶剂比为5:1及回流比为5:1的优化条件下,间二乙苯质量含量由59.00%提高到79.00%,收率达到93.73%以上。本文研究为进一步萃取和结晶提取间二乙苯提供条件。     

稀醋酸共沸精馏脱水工艺的模拟

醋酸是一种重要的化工原料,其水溶液广泛存在于各类工业过程中。由于醋酸与水会缔合使得两者的相对挥发度不大,生产中用于分离醋酸/水的工艺能耗较高,因此研究者和工业界都在寻求更好的分离方法。本文以醋酸正丙酯做挟带剂,应用Aspen Plus流程模拟软件,汽相逸度采用Hayden-O’Connell方程,液相活度系数采用NRTL方程计算,实现了稀醋酸共沸精馏脱水工艺的模拟。本文详细讨论了全塔理论板数、进料位置、回流比等因素对脱水塔性能的影响。结果表明,在理论板数50块,回流比3.2,醋酸进30块板,挟带剂与进料比0.15条件下,塔釜得到醋酸浓度高于95%。模拟结果对醋酸脱水工艺的设计和改造具有重要的指导意义。     

Selection and order statistics from correlated normal random variables

This paper investigates order statistics from correlated normal random variables and its application, namely, ranking and selection. We propose a new approach to estimate the percentage points (quantiles) of the correlated normal distributions. The new approach is flexible and can be used to estimate the critical constants for the problem at hand, even when the correlations are unknown or unequal. An experimental performance evaluation demonstrates the validity and efficiency of the procedures.     

Extracting statistics indicators from tables of basic structure

The problem of extracting statistical data from a table of a basic structure is considered. The problem of extracting statistical indicators is formally stated. The method for extracting statistical data that analyzes the content of table cells is described. Algorithms for cell type recognition, table structure restoration, and a fuzzy search of the content of text cells are proposed.     

Parameterisation and efficient MCMC estimation of non-Gaussian state space models

The impact of parameterisation on the simulation efficiency of Bayesian Markov chain Monte Carlo (MCMC) algorithms for two non-Gaussian state space models is examined. Specifically, focus is given to particular forms of the stochastic conditional duration (SCD) model and the stochastic volatility (SV) model, with four alternative parameterisations of each model considered. A controlled experiment using simulated data reveals that relationships exist between the simulation efficiency of the MCMC sampler, the magnitudes of the population parameters and the particular parameterisation of the state space model. Results of an empirical analysis of two separate transaction data sets for the SCD model, as well as equity and exchange rate data sets for the SV model, are also reported. Both the simulation and empirical results reveal that substantial gains in simulation efficiency can be obtained from simple reparameterisations of both types of non-Gaussian state space models.     

Protecting entanglement from correlated amplitude damping channel using weak measurement and quantum measurement reversal

Quantum Information Processing - Based on the quantum technique of weak measurement, we propose a scheme to protect the entanglement from correlated amplitude damping decoherence. In contrast to...     

Identification and prediction of a class of non-Gaussian time-series via transformation

Whereas optimal prediction of Gaussian sequences requires the employment of a linear filter with consistently identifiable parameters and with Gaussian white noise input, the optimal predictor of non-Gaussian sequences is n nonlinear filter, having an independent noise input. Since the latter cannot be identified directly without prior knowledge of the non-linearity, the optimal linear predictor is usually identified where a non-Gaussian white noise input is considered and which is fully optimal only when that input turns out to be independent in all moments. However, if the non-Gaussian sequence is the outcome of a Gaussian sequence passed through a zero memory non-linearity or through non-linear measurement elements, a transformation of the non-Gaussian sequence into a Gaussian one is possible, such that optimal non-linear prediction may be approximated to any required degree, as is shown by the analysis of the present work. Furthermore, the parameters of that predictor may be consistently identified in the absence of any parameter information.     

Generation of cartoon-style bas-reliefs from photographs

This paper describes a new algorithm that generates a cartoon-style bas-relief surface from photographs of general scenes. Most previous methods for bas-relief generation have focused on accurate restoration of input 3D models on a background plane. The generation of bas-reliefs with artistic effects has rarely been studied. Considering that non-photorealistic rendering (NPR) techniques are currently very popular and 3D printing technology is developing rapidly, extending NPR techniques to the generation of a bas-relief surface with artistic effects is natural and valuable. Furthermore, cartoon is a basic non-realistic and artistic style familiar to general users. From this motivation, our method focuses on generating a cartoon-style bas-relief surface. We use the lens blur function of Google Camera, which is a smartphone application, to obtain a photograph and its depth map as inputs. Using coherent line drawing and histogram-based quantization methods, we construct a depth map that contains the salient features of given input scenes in abstract form. Displacement mapping from the depth map onto a thin plane generates a cartoon-style bas-relief. Experimental results show that our method generates bas-relief surfaces that contain the characteristics of cartoons, such as coherent border lines and quantized layers.

     

计算机波形文件的声卡生成技术

本文介绍一种利用声卡特性生成各种波形的通用方法。它通过VB程序生成一定波形的一系列离散的数值存入声卡的音频文件中,再采用声卡播放输出该文件得到所期望的波形。     

Generation of text from logical formulae

The paper addresses the problem of generating sentences from logical formulae. It describes a simple and efficient algorithm for generating text which has been developed for use in machine translation, but will have wider application in natural language processing. An important property of the algorithm is that the logical form used to generate a sentence need not be one which could have been produced by parsing the sentence: formal equivalence between logical forms is allowed for. This is necessary for a machine translation system, such as the one envisaged in this paper, which uses single declarative grammars of individual languages, and declarative statements of translation equivalences for transfer. In such a system, it cannot be guaranteed that transfer will produce a logical form in the same order as would have been produced by parsing some target-language sentence, and it is not practicable to define a normal form for the logical forms. The algorithm is demonstrated using a categorial grammar and a simple indexed logic, as this allows a particularly clear and elegant formulation. It is shown that the algorithm can be adapted to phrase-structure grammars, and to more complex semantic representations than that used here.     

A new technique to sense non-Gaussian features of the sea surface from L-band bi-static GNSS reflections

We present a new technique to analyze L-band signals of the Global Navigation Satellite System (GNSS) that have rebounded off the sea surface, with the aim of retrieving information about surface roughness in the form of the effective Probability Density Function (PDF) of the slopes. Unlike earlier techniques, which parameterize the PDF (usually as normal bivariate distributions), this approach does not constrain the surface slopes' PDF to the shape of a particular analytical distribution. This may help to understand the real information content of L-band scattered signals, which is currently unclear. After validating the algorithm by means of end-to-end simulations, we have applied it to real data. The tests on real data show that the retrievals are robust, consistent with the results obtained with standard GNSS-reflection techniques, and in agreement with independent sources of information. Moreover, the retrieved slopes' PDF present non-Gaussian features, such as skewness. A more in-depth analysis to check whether the skewness is a geophysical signature or an artifact of the technique, shows that it maps with the up-/down-asymmetries introduced by surface forces. In particular, this is the first time that GNSS-reflections have sensed and identified the up- and down-wind signature on the surface, putting and end to the 180° ambiguity that was usually attributed to GNSS observations of directional roughness.     

生物细胞与组织超弱发光探测系统研制

为了实现对生物超弱发光现象的研究,研制该探测系统,以用于在常温下对生物样本的超弱发光现象进行测量。采用多种措施降低外界环境对探测系统的影响：选择灵敏度高、暗电流低的光电倍增管作为核心探测器件;制作测量系统专用暗箱保证测量环境的高信噪比和稳定性;设计了进行生物细胞与组织超弱发光实验的多波长激励光源。经过多次实验,系统在11.5℃环境温度下的本底噪声的平均值为43.5CPS,取得了较好的效果。系统信噪比高,稳定性好,能够在常温下对生物的超弱发光和延迟发光现象进行观察,达到了预期目的。     

甲醇精馏系统模拟与优化

本文应用过程模拟软件Aspen Plus,采用Wilson和PSRK相结合的物性方法,实现了对某厂甲醇四塔双效精馏系统的模拟.为降低生产成本,本文通过对系统模拟与分析,对生产的工艺流程进行进一步改进,并提出3个优化方案:(1)增加加压精馏塔侧线采出送常压精馏塔作为进料;(2)对常压精馏塔塔底和回收塔塔底部分废水进行循环;(3)采用加压精馏塔与预精馏塔双效精馏.经过模拟计算,改进后的新工艺流程在保证甲醇产品的产量与质量的前提下,共能节省公用工程热量21173 kW,节省公用工程冷量16268 kW,节省工业用水10375 kg/hr,污水处理量减少10 375 kg/hr.本文所选用的单元操作模型及物性方法对于模拟甲醇精馏系统是准确可靠的,因此本文所提出的优化方案能为甲醇工业生产节能、节水以及减少废水排放的改造和新工艺流程的开发提供理论依据.