Hardware-algorithm collaborative computing with photonic spiking neuron chip based on integrated Fabry-P\'erot laser with saturable absorber

Photonic neuromorphic computing has emerged as a promising avenue toward building a low-latency and energy-efficient non-von-Neuman computing system. Photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to realize high-performance neuromorphic computing. However, the nonlinear computation of PSNN remains a significant challenging. Here, we proposed and fabricated a photonic spiking neuron chip based on an integrated Fabry-P\'erot laser with a saturable absorber (FP-SA) for the first time. The nonlinear neuron-like dynamics including temporal integration, threshold and spike generation, refractory period, and cascadability were experimentally demonstrated, which offers an indispensable fundamental building block to construct the PSNN hardware. Furthermore, we proposed time-multiplexed spike encoding to realize functional PSNN far beyond the hardware integration scale limit. PSNNs with single/cascaded photonic spiking neurons were experimentally demonstrated to realize hardware-algorithm collaborative computing, showing capability in performing classification tasks with supervised learning algorithm, which paves the way for multi-layer PSNN for solving complex tasks.Comment: 10 pages, 8 figure

The Trajectory of Chinese Doctoral Education and Scientific Research

Dramatic enrollment expansion at the undergraduate level and institutional diversification are characteristics frequently used to describe major trends in China's massive higher education system. A less understood phenomenon is the relatively new and rapid establishment of graduate level programs that have implications for national economic development. As described in this study, beginning in the early 1980s, the Chinese government launched the first of a number of reforms meant to encourage the development of graduate programs and to change the face of China's higher education system. These programs were a substantial success. The quick development of the Ph.D. programs and the increasing number of students are part of a larger effort by the national government to increase China's national economic competitiveness and to both retain talent and attract Chinese nationals with graduate degrees to return to a robust economy with growing universities and research centers. At the same time, Chinese graduate education is still developing, and it faces many challenges. There is a need to both increase enrollment and to significantly improve the quality of its faculty and academic programs, with a focus on increasing the ability of students to pursue both scientific research and their knowledge of other nations and cultures

Getting Graduates to Come HomeNot So Easy

China seeks to attract its best professors who are teaching in other countries to return home. This is not an easy task. The problems and dilemmas are analyzed

The Choice and Accumulation of Decision-Making Data in Engineering Project Management

There are massive amounts of process data in the usual course of doing engineering. How to choose and accumulate these data to provide reference for newly-built projects in designing and building is a question that project superintendents face. We propose to construct a knowledge management platform for engineering project management to realize the potential of the accumulated decision-making data and study data classification and knowledge management, using architectural engineering data as an example

Efficiency limits for space multi-junction concentrator solar cells

Efficiency limits of single-junction and multi-junction concentrator solar cells are established from the thermodynamic principle of detailed balance. The maximum efficiency limit of single-junction solar cells is35% at500 suns, while that of2-junction solar cells which meet the current matching condition is46%. At the same condition, the maximum efficiency limit of3-junction solar cells with GaAs as middle subcell is52%.?2011 IEEE

Design of a Morphing Skin with Shape Memory Alloy Based on Equivalent Thermal Stress Approach

Shape memory alloy (SMA) is one of the potential driving devices for morphing aircraft due to its advantages of pseudoelasticity, superelasticity, and shape memory effect. Precise and fast analysis of SMA has simultaneously become a key requirement for industrial applications. In this study, a user-defined material subroutine (UMAT) was implemented and successfully applied in a three-dimensional numerical simulation in ABAQUS based on the extended Boyd–Lagoudas model. In addition to the conventional detwinned martensite (Md) and austenite (A), twinned martensite (Mt) was also considered to model the practical transformation accurately. Then, the equivalent thermal strain approach was adopted to simplify the simulation complexity with UMAT. By resetting the thermal expansion coefficient, the thermal strain equivalent to the original phase transformation strain was generated. The approach was validated in two cases, showing consistent results with the extended Boyd–Lagoudas model and reduction in time consumption by 89.1%. Lastly, an active morphing skin integrating the single-range SMA and a stainless-steel plate was designed to realize two-way morphing. The calculated arc height variation of the skin was 3.74 mm with a relative error of 1.84% compared to the experimental result of 3.81 mm. The coupled use of UMAT and the equivalent thermal stress approach helped to reduce the challenge in modeling SMA