介观电路中量子纠缠的经典对应

从量子力学诞生日起,它的经典对应(或类比)一直是物理学家关心的话题.本文以介观电路量子化的框架中,带有互感的两个介观电容-电感(LC)电路为例,首次讨论了量子纠缠的经典类比(或对应)问题.先用有序算符内的积分理论证明其互感是产生量子纠缠的源头;再推导出求解特征频率的公式,就发现它与一个经典系统的小振动频率的表达式有相似之处,该经典系统组成如下:两个墙壁各连一个相同的弹簧,两个弹簧之间接着一个滑动小车可以在光滑的桌面上运动,小车挂有一根单摆.用分析力学求此系统的小振动频率,发现与上述介观电路的特征频率形式类似,单摆的摆动会造成小车来回振动,摆、小车和弹簧的互相牵制效应反映了小车和摆的"纠缠".     

Vacuum-gap-based lumped element Josephson parametric amplifier

We propose a lumped element Josephson parametric amplifier with vacuum-gap-based capacitor.The capacitor is made of quasi-floating aluminum pad and on-chip ground.We take a fabrication process compatible with air-bridge technology,which makes our design adaptable for future on-chip integrated quantum computing system.Further engineering the input impedance,we obtain a gain above 20 dB over 162-MHz bandwidth,along with a quasi quantum-limit noise performance.This work should facilitate the development of quantum information processing and integrated superconducting circuit design.     

Assessment of Noise Exposure of Sawmill Workers in Southwest,Nigeria

Economic wood processing employs the use of industrial machines for cutting, shaping, milling, and sawing timber, thereby leading to the generation of high levels of noise. Published data from empirical studies have categorized noise as an environmental hazard of global significance. Furthermore, noise exposure limits for different industries and all the industrial machines available has not been formally established as it presently exists in developed nations around the world. Therefore, this study assessed the daily exposure of sawmills workers to noise in Southwestern Nigeria. Reconnaissance surveys were first carried out in Osun, Oyo, Ondo, Ekiti, Lagos, and Ogun States to select sawmills that were fully operational and fit for the study. Two fully functional sawmills in two cities of each State were eventually selected for data collection, making a total of 24 sawmills, while the Circular Machines (CM), Planer Machines (PM), and Band-saw Machines (BM) were the machines in each sawmill considered. Two machines each of CM, PM, and BM were considered in each sawmill, making a total of forty-eight (48) machines each of CM, PM, and BM. Sound data were collected between 7 am and 7 pm each day for six days (between Monday and Saturday) using Extech 407732 sound level meter and all stabilized measurements were taken three times at different intervals. The data collected were in three different periods: Machine No-work Period (NP_m), Machine Idle Period (IP_m), and Machine Working Period (WP_m). A two–way Analysis of Variance (ANOVA) was carried out at P < 0.05 to determine whether there is a significant difference in the sound level average before and after the break, for both the idle and working periods of the three machines considered. This was also done to determine whether there is a significant difference between the sound level average of the results collected during idle and working periods of the three machines. Noise Pollution Levels (L_np) ranged from 83.20 dB (PM) to 107.65 (BM) and 93.42 (CM and PM) – 116.00 (BM) respectively, while IP_m also gave the least noise pollution level of 95.79 dB and WP_m gave the highest level of 102.88 dB. The results revealed that all the machines’ L_np values in the working period are more than the 90 dB acceptable limit the recommendation value of 90 dB while 89.6% of CMs, 75% of PMs, and 89.6% of BM had their L_np above 90 dB in the idle period respectively. The minimum and the maximum noise dose levels for IP_m, WP_m and overall are 0.09 (BM) and 2.37 (CM), 0.50 (CM), and 4.77 (PM) and 0.69 (BM) and 6.64 (PM) respectively. The study found out that the fundamental contributing factors to the high noise levels in sawmills are poor machine maintenance, use of old and obsolete machines, poor housekeeping strategy, limited space, workers’ negligence, lack of PPE, and lack of occupational safety training. The study recommends that proper workplace practices such as use of personal protective equipment, new and modern machines, training, and occupational safety programmes be implemented in the considered sawmills.     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

Synergistic Effects of Pseudocolor Imaging,Differentiation, and Square and Logarithmic Conversion on Accuracy of Quantification of Chemical Characteristics Using Test Strips and Similar Products

Test strips and similar products are highly feasible tools for the rapid and approximate determination of chemical characteristics. Although the application of both the quantitative observation of coloration and regression modeling has recently enabled these products to become quantitative tools, their precision and accuracy may be further improved. In this study, the pseudocolor imaging of the coloration image, derivative spectrophotometry-like differentiation of the coloration values, and logarithmic conversion of the raw and derivative values were compared in terms of the precision and accuracy of the quantitative determination of corrosiveness, glucose, nitrate, and pH using the products. The best regression models for the determination were provided by the combination of pseudocolor imaging and differentiation (nitrate and pH); pseudocolor imaging, differentiation, and square-conversion (corrosiveness); or all of the techniques (glucose). When compared to the use of the original 10 raw coloration variables of red-green-blue, cyan-magenta-yellow-key black, and L*a*b* color models only, the above combinations improved the normalized mean absolute error from 14.8% to 3.09% (corrosiveness), 6.33% to 3.15% (glucose), 7.46% to 4.56% (nitrate), and 3.22% to 0.94% (pH). These achievements were largely attributed to the combination of multiple variables that have non-linear and nonmonotonic relationships with the chemical characteristics.     

柱面微通道板的制备及其性能研究

针对未来空间天文学应用的超分辨率光谱成像仪器的需求，对低噪声柱面微通道板（MCP）的制备方法及其性能进行了研究. 提出了一种将光学抛光与热成型相结合的新的柱面MCP制备方法，利用不含放射性元素的低噪声MCP玻璃，制备出曲率半径为400mm、尺寸为30mm′46mm、长径比为80:1、通道直径12.5mm、通道间距15mm的柱面MCP，并将其与感应电荷楔条形阳极（WSA）组成光子计数探测器，对其暗计数率、分辨率进行了检测，暗计数率约为0.1counts/cm2×s.     

Enhancing optomechanical force sensing via precooling and quantum noise cancellation

We theoretically investigate optomechanical force sensing via precooling and quantum noise cancellation in two coupled cavity optomechanical systems.We show that force sensing based on the reduction of noise can be used to dramatically enhance the force sensing and that the precooling process can eifectively improve the quantum noise cancellation.Specifically,we examine the effect of optomechanical cooling and noise reduction on the spectral density of the noise of the force measurement;these processes can significantly enhance the performance of optomechanical force sensing,and setting up the system in the resolved sideband regime can lead to an optimization of the cooling processes in a hybrid system.Such a scheme serves as a promising platform for quantum back-action-evading measurements of the motion and a framework for an optomechanical force sensor.     

风力机叶片气动噪声的影响参数*

随着风力机的大型化，风电机组对环境的影响不容忽视，必须对风力机气动噪声进行预测和控制。选取基于NACA、DU翼型的某风力机叶片作为研究基准，采用修正BPM半经验模型计算叶片的气动噪声特性，通过改变翼型族、弦长、机组运行状态、风切变指数、来流风向参数，研究叶片外形几何参数、机组运行工况对叶片气动噪声源的影响。计算结果从多个角度总结出水平轴风力机叶片气动噪声的变化规律，为开发高效低噪风电叶片提供参考。     

Quantitative leak test for microholes and microtears in whole gloves and glove pieces

The current leak tests for gloves are qualitative. The developed quantitative leak test uses vacuum pressure to draw measured volumes of water to detect microholes/tears in whole gloves and glove pieces. A modified plastic vacuum desiccator interfaced with a Frazier air permeability tester allowed exposure of disposable unsupported/unlined/powderless Kimtech Blue nitrile to 50 mL of water for glove pieces or to 600 mL within a whole glove at vacua of 8–9 in. (20–23 cm) and 11–12 in. (28–30 cm) water gauge, respectively. Punctures of known dimensions were made before testing in specific glove areas using 21-, 22-, 26-, 30-, and 33-gauge needles (outer/inner diameters in micrometres of 873/514, 794/413, 635/311, 476/127, 318/159 and 238/133, respectively). The length of the punctures varied from 0.13 ± 0.01 to 0.80 ± 0.11 mm. Flow rates of water through the holes/tears ranged from 2.5 ± 0.4 to 106 ± 7 mL/min for glove pieces. For whole gloves, the ranges were from 31 ± 9 to 543 ± 110 mL/min in the palm area; and 0.23 ± 0.06 to 82 ± 18 mL/min in the finger/fingertip area. The method quantified tear lengths as short as 0.13 ± 0.01 mm.     

水下对转螺旋桨流致辐射噪声机理与预报方法*

水下对转螺旋桨流致辐射噪声的预报对于水下目标的特征提取和分类识别具有重要意义。由桨叶的旋转引起的湍流场是水下对转螺旋桨流致辐射噪声的源场。分述了水下对转螺旋桨湍流边界层脉动、旋转干涉效应和空化效应引发的水动力噪声机制和研究进展,比较了目前工程应用中的3种对转螺旋桨流致辐射噪声预报方法的特点。在分析对转螺旋桨流致辐射噪声数值预报难点的基础上,综述了对转螺旋桨流致辐射噪声计算方法的研究进展,指出间接数值模拟方法是工程中进行对转螺旋桨流致辐射噪声预报的有效方法。