Impact of gate-oxide tunneling on mixed-signal design and simulation of a nano-CMOS VCO

Design optimization for performance enhancement in analog and mixed-signal circuits is an active area of research as technology scaling is moving towards the nanometer scale. This paper presents an approach towards the efficient simulation and characterization of mixed-signal circuits, using a 45 nm CMOS voltage controlled oscillator (VCO) with frequency divider as a case study. The performance characteristics of the analog and digital blocks in the circuit are simulated and the accuracy issues arising due to separate analog and digital simulation engines are considered. The tremendous impact of gate tunneling current on device performance is quantitatively analyzed with the help of an “effective tunneling capacitance”, which allows accurate modeling and simulation of digital blocks with almost analog accuracy. To meet the design specifications of the analog VCO using digital CMOS technology, we follow a design of experiments (DOE) approach. The functional specifications of the VCO optimized in this design are the center frequency and minimization of overall power consumption as well as minimization of power due to gate-oxide tunneling current leakage, a component that was not important in previous generations of CMOS technologies but is dominant at 45 nm and below. Due to the large number of available design parameter (gate-oxide thickness and transistor sizes), the concurrent achievement of all optimization goals is difficult. A DOE approach is shown to be very effective and a viable alternative to standard design exploration in the nanometer regime.     

普通物理综合设计实验课教学方法改革初探

开设普通物理综合设计实验课程目的在于培养学生动手能力、分析问题解决问题能力和创新能力。本文以首都师范大学物理系开设的普通物理综合设计实验为例讨论了具体的教学方法和过程,首先通过设计大量的预习思考题提高学生预习的针对性和预习效果,通过分组讨论来理解实验原理,并给出设计思路,最后通过实际实验锻炼学生的动手能力。该方法取得了良好的教学效果。     

受迫振动实验中几个问题的探讨

就受迫振动实验中振动系统半宽带、品质因素及稳定受迫振动强迫力与阻力做功进行研究和探讨。     

浅谈大学生物理实验竞赛的组织及意义

主要对首届辽宁省大学生物理实验竞赛的组织设计、特点及意义等方面进行了总结和探讨,认为组织大学生物理实验竞赛对激发大学生对物理实验的兴趣与潜能、提高物理实验教学质量具有重要意义。     

Cross-Linking Nitroxide-Mediated Radical Copolymerization from a Bayesian Experimental Design Angle

Summary: In an attempt to collect “meaningful” experimental data in cross-linking nitroxide-mediated radical copolymerization of stryene and divinyl benzene, a Bayesian design approach was used to derive optimal experimental sequences to be carried out in the laboratory. Since a considerable amount of prior knowledge about this polymerization system was already available from previous experimental and modeling efforts, application of the Bayesian design of experiments seemed like a perfect approach. In addition, the implementation of the Bayesian approach would, in principle, result in running fewer experiments, hence saving considerable time and resources.     

A unified framework for constructing globally convergent algorithms for multidimensional coefficient inverse problems

We present a unified framework for constructing the globally convergent algorithms for a broad class of multidimensional coefficient inverse problems arising in natural science and industry. Based on the convexification approach, the unified framework substantiates the numerical solution of the corresponding problem of nonconvex optimization. A globally convergent iterative algorithm for an inverse problem of diffuse optical mammography is constructed. It utilizes the contraction property of a nonlinear operator resulting from applying the convexification approach. The effectiveness of this algorithm is demonstrated in computational experiments.     

Analytical and numerical inversion formulas in the Gaussian convolution by using the Paley–Wiener spaces

We shall discuss the relations among sampling theory (Sinc method), reproducing kernels and the Tikhonov regularization. Here, we see the important difference of the Sobolev Hilbert spaces and the Paley–Wiener spaces when we use their reproducing kernel Hibert spaces as approximate spaces in the Tikhonov regularization. Further, by using the Paley–Wiener spaces, we shall illustrate numerical experiments for new inversion formulas for the Gaussian convolution as a much more powerful and improved method by using computers. In this article, we shall be able to give practical numerical and analytical inversion formulas for the Gaussian convolution that is realized by computers.     

Calculus demonstrations using MATLAB

The note discusses ways in which technology can be used in the calculus learning process. In particular, five MATLAB programs are detailed for use by instructors or students that demonstrate important concepts in introductory calculus: Newton's method, differentiation and integration. Two of the programs are animated. The programs and the graphical user interface have been specifically designed to help the student understand the processes behind these important introductory concepts. Each program has a series of demonstrations that show unusual, difficult or important cases.     

Local Derivative-Free Approximation of Computationally Expensive Posterior Densities

Bayesian inference using Markov chain Monte Carlo (MCMC) is computationally prohibitive when the posterior density of interest, π, is computationally expensive to evaluate. We develop a derivative-free algorithm GRIMA to accurately approximate π by interpolation over its high-probability density (HPD) region, which is initially unknown. Our local approach reduces the waste of computational budget on approximation of π in the low-probability region, which is inherent in global experimental designs. However, estimation of the HPD region is nontrivial when derivatives of π are not available or are not informative about the shape of the HPD region. Without relying on derivatives, GRIMA iterates (a) sequential knot selection over the estimated HPD region of π to refine the surrogate posterior and (b) re-estimation of the HPD region using an MCMC sample from the updated surrogate density, which is inexpensive to obtain. GRIMA is applicable to approximation of general unnormalized posterior densities. To determine the range of tractable problem dimensions, we conduct simulation experiments on test densities with linear and nonlinear component-wise dependence, skewness, kurtosis and multimodality. Subsequently, we use GRIMA in a case study to calibrate a computationally intensive nonlinear regression model to real data from the Town Brook watershed. Supplemental materials for this article are available online.