Optical modulation and digital demodulation of an in-plane moiré carrier

A rotational mismatch of gratings is used to generate a fringe carrier of an in-plane moiré pattern so that specimen deformation shows itself in the form of modulation of the carrier frequency. As both the unmodulated and modulated carriers are the patterns without fringe-loop or fringe-connection, they are automatically numbered with monotonical increasing orders by a digital image processing system without any ambiguity. The orders at every pixel of the image are determined by interpolation of the orders of the tracked fringes to establish two grey image files, from the difference of which, the orders of the in-plane displacement moiré are displayed with grey-level variation.     

The 3-D FEL pulse propagation equation: An analytical treatment in the low-gain and small-signal regime

Summary In this paper we show that the transverse mode evolution of a FEL operating with short pulses can be treated, in the small-signal and low-gain regime, using a relatively simple mathematical technique leading to a potentially fast numerical algorithm. We also point out that analytical solutions can be obtained for the cases where the slippage length is small compared to the longitudinal bunch length.     

弯曲模式声波在充液井孔中的传播

本文由波动方程讨论了充液井孔中,弯曲模式声波在弹性和非弹性、无限大井壁介质以及有限大井壁介质情况下沿井轴方向的传播。数值计算了它们的相速度频散曲线和井孔的频率响应特性,计算了衰减正弦信号在井孔中激励的波形。利用PZT压电晶片的弯曲振动模式,制作了偶极子测井换能器,在混凝土浇注的人工模拟井中进行了测试,试验结果与理论计算结果作了对比。     

电子束长程传输中离子通道的振荡特性研究

离子通道可以有效抑制电子束在等离子体环境内传输过程中的径向扩散,已有工作研究了离子通道对电子束的影响,但离子通道建立过程和暂态特性研究则更有助于理解和利用离子通道在电子束长程传输中的作用。本文利用PIC方法对离子通道的时空分布进行二维模拟,并基于单粒子理论推导出描述离子通道振荡的解析模型,对上述两种模型的结果相互校验。上述模型的计算结果表明,在长程传输过程中,相对论电子束在等离子体内部建立的离子通道是持续周期振荡的,电子束密度、电子束初始半径以及环境等离子体密度都会对离子通道的振荡规律产生影响,针对不同的等离子体环境选择合适的电子束参数可以有效提高离子通道的稳定性,进而提升传输过程中电子束的束流质量。     

减反膜对单晶硅太阳能电池性能的影响分析

在太阳能电池效率的评价中,电池材料、掺杂浓度、扩散长度等都是比较重要的参数,合理地改变相关参数可以优化太阳能电池的性能,提高电池效率。此外,在太阳能电池表面镀一层具有减反作用的光学薄膜（简称减反膜）也是提高电池效率的重要手段。以提高电池效率为目标,对单晶硅太阳能电池的掺杂浓度和扩散长度等微观参数进行计算优化,分析了掺杂浓度和扩散长度变化对电池效率的影响。并在此基础上分析了不同类型的减反膜对于电池效率的影响,给出了最佳减反膜材料及其膜系厚度,并且结合镀膜后电池量子效率的变化验证了其准确性。结果表明,在优化电池掺杂浓度和扩散长度的基础上,选择合适的减反膜,电池效率最高可达20.35%,相比于优化前提高了8.25%。     

Universality of entropy principle for a general diffeomorphism-covariant purely gravitational theory

Thermodynamics plays an important role in gravitational theories. It is a principle that is independent of gravitational dynamics, and there is still no rigorous proof to show that it is consistent with the dynamical principle. We consider a self-gravitating perfect fluid system with the general diffeomorphism-covariant purely gravitational theory. Based on the Noether charge method proposed by Iyer and Wald, considering static off/on-shell variational configurations, which satisfy the gravitational constraint equation, we rigorously prove that the extrema of the total entropy of a perfect fluid inside a compact region for a fixed total particle number demands that the static configuration is an on-shell solution after we introduce some appropriate boundary conditions, i.e., it also satisfies the spatial gravitational equations. This means that the entropy principle of the fluid stores the same information as the gravitational equation in a static configuration. Our proof is universal and holds for any diffeomorphism-covariant purely gravitational theories, such as Einstein gravity, \begin{document}$ f(R)$\end{document} gravity, Lovelock gravity, f(Gauss-Bonnet) gravity and Einstein-Weyl gravity. Our result indicates the consistency between ordinary thermodynamics and gravitational dynamics.     

向心加速度公式的教具制作及其教学研究——基于Tracker和Phyphox软件的定量探究

从教具制作、定量实验探究和教学启示等三方面来探究匀速圆周运动的向心加速度公式,即利用自制教具探究向心加速度αc与圆周运动半径r和角速度ω之间的定量关系.实验发现,结果非常好地符合理论预期.最后讨论了该教具所蕴含的教学启示,可以将其设计成适合高中物理教学的验证性、探究性实验及课外科创活动,从而培养学生的科学探究能力、科学...     

A composition-free parallel volume rendering method

Journal of Visualization - In the in situ visualization of large-scale simulation, if using the traditional sort-last parallel rendering method, the performance cannot be fully improved due to the...     

Analysis of Electromagnetic Information Leakage Based on Cryptographic Integrated Circuits

Cryptographic algorithm is the most commonly used method of information security protection for many devices. The secret key of cryptographic algorithm is usually stored in these devices’ registers. In this paper, we propose an electromagnetic information leakage model to investigate the relationship between the electromagnetic leakage signal and the secret key. The registers are considered as electric dipole models to illustrate the source of the electromagnetic leakage. The equivalent circuit of the magnetic field probe is developed to bridge the output voltage and the electromagnetic leakage signal. Combining them, the electromagnetic information leakage model’s function relationship can be established. Besides, an electromagnetic leakage model based on multiple linear regression is proposed to recover the secret key and the model’s effectiveness is evaluated by guess entropy. Near field tests are conducted in an unshielded ordinary indoor environment to investigate the electromagnetic side-channel information leakage. The experiment result shows the correctness of the proposed electromagnetic leakage model and it can be used to recover the secret key of the cryptographic algorithm.     

Minimum Message Length in Hybrid ARMA and LSTM Model Forecasting

Modeling and analysis of time series are important in applications including economics, engineering, environmental science and social science. Selecting the best time series model with accurate parameters in forecasting is a challenging objective for scientists and academic researchers. Hybrid models combining neural networks and traditional Autoregressive Moving Average (ARMA) models are being used to improve the accuracy of modeling and forecasting time series. Most of the existing time series models are selected by information-theoretic approaches, such as AIC, BIC, and HQ. This paper revisits a model selection technique based on Minimum Message Length (MML) and investigates its use in hybrid time series analysis. MML is a Bayesian information-theoretic approach and has been used in selecting the best ARMA model. We utilize the long short-term memory (LSTM) approach to construct a hybrid ARMA-LSTM model and show that MML performs better than AIC, BIC, and HQ in selecting the model—both in the traditional ARMA models (without LSTM) and with hybrid ARMA-LSTM models. These results held on simulated data and both real-world datasets that we considered.We also develop a simple MML ARIMA model.