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Conversion of a single-layer ANN to photonic SNN for pattern recognition

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Science China(Information Sciences) 2024年第1期67卷 261-270页

作者： Yanan HAN Shuiying XIANG Tianrui ZHANG Yahui ZHANG Xingxing GUO Yuechun SHI state key laboratory of Integrated Service Networks State Key Discipline Laboratory of Wide Bandgap Semiconductor TechnologyXidian University Yongjiang laboratory

This work presents a complete conversion scheme for photonic spiking neural networks(SNNs).We verified that the output of an artificial neural network(ANN) trained with the simulated optical activation function can be directly converted into the spike rate of a photonic spiking neuron *** reveal the feasibility of hardware implementation,we considered the effects of different bit precisions of data and weight,noise level,and bias current mismatch on the converted *** proposed scheme was evaluated using the Deterding vowel,IRIS,TIDIGITS,and MNIST datasets for pattern recognition,and achieved mean accuracies of 95.80%,98.67%,96.19%,and 92.33%,*** proposed scheme can convert an ANN into a photonic SNN with almost no precision loss,and the performance was comparable to that of an ANN trained with the rectified linear unit *** proposed scheme can enable the high-performance implementation of photonic SNNs.

关键词： photonic SNN conversion optical computing pattern recognition artificial neural network

Wall temperature effects on the stability of leeward vortices of a blunt inclined cone

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Acta Mechanica Sinica 2024年第7期40卷 29-42页

作者： Ligeng Zhang Bingbing Wan Siwei Dong Jianqiang Chen Xi Chen state key laboratory of Aerodynamics Mianyang 621000China

Streamwise vortex instability is one of the most potent mechanisms for the transition of the three-dimensional boundary *** using the global stability analysis methods,stability characteristics of the leeward vortex over a blunt cone with an angle of attack under a typical wind tunnel condition are studied and are compared to the case with a smaller wall temperature ratio(corresponding to a flight condition).The vortical structure features inward and outward vortices,similar to that in the flight *** the flight condition,the outward vortices appear stronger than the inward vortices,resulting in stronger outer-mode *** the inner mode is heavily stabilized compared to the flight condition,it can still radiate apparent *** acoustic sources are computed based on Lighthill's acoustic analogy,showing that the entropy term measuring the deviation from the isentropic relation is *** Mack second mode is shown to most likely trigger the transition in the flight condition,it is absent in the wind tunnel condition,and a shear-layer mode turns out to be the most dangerous ***,the instability frequencies and growth rates of the wind tunnel case are much smaller than those of the flight case,indicating that wall heating may stabilize the leeward vortices.

关键词： Instability of streamwise vortices Hypersonic boundary layer flow Spatial BiGlobal method PSE3D method

Experimental and numerical demonstration of hierarchical time-delay reservoir computing based on cascaded VCSELs with feedback and multiple injections

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Science China(Information Sciences) 2024年第2期67卷 279-290页

作者： Xingxing GUO Shuiying XIANG Xingyu CAO Biling GU state key laboratory of Integrated Service Networks Xidian University state key Discipline laboratory of Wide Bandgap Semiconductor Technology School of MicroelectronicsXidian University

In this paper, we propose and demonstrate experimentally and numerically a hierarchical timedelay optical reservoir computing(RC) system based on cascaded vertical-cavity surface-emitting lasers(VCSELs) with feedback and multiple injections. The prediction performance characteristics of the hierarchical time-delay RC system based on cascaded VCSELs under different reservoir layers are ***, the prediction performance of the hierarchical time-delay RC system is first improved and saturates as the number of reservoir layers increases. Besides, the impacts of key factors on predicting the hierarchical time-delay RC system are also analyzed in detail experimentally and numerically. This proposed hierarchical time-delay RC system based on VCSELs is useful for the further development of RC systems and may be beneficial to improve the ability of RC systems to solve more complex problems.

关键词： vertical-cavity surface-emitting laser reservoir computing neuromorphic photonics time-delay system information processing

A credible traffic prediction method based on self-supervised causal discovery

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Science China(Information Sciences) 2024年第5期67卷 244-258页

作者： Dan WANG Yingjie LIU Bin SONG state key laboratory of Integrated Services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(QoS) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(SSTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. Experimental results demonstrate the effectiveness of the SSTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised

A passive wireless surface acoustic wave(SAW)sensor system for detecting warfare agents based on fluoroalcohol polysiloxane film

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Microsystems & Nanoengineering 2024年第1期10卷 67-78页

作者： Yong Pan Cancan Yan Xu Gao Junchao Yang Tengxiao Guo Lin Zhang Wen Wang state key laboratory of NBC Protection for Civil Beijing 102205China Institute of acoustics Chinese Academy of SciencesBeijing 100190China The School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100049China

Long-term monitoring of environmental warfare agengts is a challenge for chemical gas *** address this issue,we developed a 433 MHz passive wireless surface acoustic wave(WSAW)gas sensor for dimethyl methylphosphonate(DMMP)*** WSAW gas sensor includes a YZ lithium niobate(LiNbO_(3))substrate with metallic interdigital transducers(IDTs)etched on it,and an antenna was placed near the IDT.A DMMP-sensitive viscoelastic polymer fluoroalcoholpolysiloxane(SXFA)film was prepared on a LiNbO_(3) substrate,and mode modeling coupling was used to optimize the design *** sensor can function properly in an environments between−30℃ and 100℃ with humidity less than 60%*** the wireless transmission distance was within the range of 0-90 cm,the sensor noise increased with distance,and the stability was less than 32°/*** optimizing the film thickness of SXFA,a relationship was observed between sensor sensitivity and film *** the film thickness of SXFA reached 450 nm,the optimal value was *** a distance of 20 cm between the transmitting and receiving antennas,DMMP was detected at different concentrations with the developed WSAW gas *** lower detection limit of DMMP was 0.48 mg/m^(3),the sensitivity of the sensor was 4.63°/(mg/m^(3)),and repeatable performance of the sensor was confirmed.

关键词： film alcohol passive

Micelle-directed self-assembly of single-crystal-like mesoporous stoichiometric oxides for high-performance lithium storage

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National Science Review 2024年第4期11卷 195-205页

作者： Yanhua Wan Changyao Wang Xingmiao Zhang Yang Yin Mengmeng Liu Bing Ma Linlin Duan Yuzhu Ma Wei Zhang Changlin Zheng Dongliang Chao Fei Wang Yongyao Xia Wei Li Department of Chemistry Laboratory of Advanced Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials State Key Laboratory of Molecular Engineering of Polymers College of Chemistry and Materials ScienceFudan University state key laboratory of Surface Physics and Department of Physics Fudan University

Due to their uncontrollable assembly and crystallization process,the synthesis of mesoporous metal oxide single crystals remains a formidable ***,we report the synthesis of single-crystal-like mesoporous Li2TiSiO5by using soft micelles as *** key lies in the atomic-scale self-assembly and step-crystallization processes,which ensure the formation of single-crystal-like mesoporous Li2TiSiO5microparticles via an oriented attachment growth mechanism under the confinement of an in-situ formed carbon *** mesoporous Li2TiSiO5anode achieves a superior rate capability(148 mAh g-1at5.0 A g-1) and outstanding long-term cycling stability(138 mAh g-1after 3000 cycles at 2.0 A g-1) for lithium storage as a result of the ultrafast Li+diffusion caused by penetrating mesochannels and nanosized crystal frameworks（5-10 nm）.In comparison,bulk Li2TiSiO5exhibits poor rate capability and cycle performance due to micron-scale diffusion *** method is very simple and reproducible,heralding a new way of designing and synthesizing mesoporous single crystals with controllable frameworks and chemical functionalities.

关键词： mesoporous materials micelles single-crystal-like Li2TiSiO5 lithium-ion batteries

Pipeline thickness estimation using the dispersion of higher-order SH guided waves

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Chinese Physics B 2024年第7期33卷 389-396页

作者：代政辰刘金霞龙云飞张建海 Tribikram Kundu 崔志文 Department of acoustics and Microwave Physics College of PhysicsJilin UniversityChangchun 130012China School of Mechanical and Aerospace Engineering Jilin UniversityChangchun 130025China Department of Civil and Architectural Engineering and Mechanics University of ArizonaTucsonArizona 85721USA College of Aerospace and Mechanical Engineering University of ArizonaTucsonAZ 85721USA state key laboratory of acoustics Institute of AcousticsChinese Academy of SciencesBeijing 100190China

Thickness measurement plays an important role in the monitoring of pipeline corrosion damage. However, the requirement for prior knowledge of the shear wave velocity in the pipeline material for popular ultrasonic thickness measurement limits its widespread application. This paper proposes a method that utilizes cylindrical shear horizontal(SH) guided waves to estimate pipeline thickness without prior knowledge of shear wave velocity. The inversion formulas are derived from the dispersion of higher-order modes with the high-frequency approximation. The waveform of the example problems is simulated using the real-axis integral method. The data points on the dispersion curves are processed in the frequency domain using the wave-number method. These extracted data are then substituted into the derived formulas. The results verify that employing higher-order SH guided waves for the evaluation of thickness and shear wave velocity yields less than1% error. This method can be applied to both metallic and non-metallic pipelines, thus opening new possibilities for health monitoring of pipeline structures.

关键词： pipeline wall thickness higher-order modes SH guided waves dispersion

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Rapid and controllable in-situ self-assembly of main-group metal nanofilms for highly efficient CO_(2)electroreduction to liquid fuel in flow cells

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Nano Research 2024年第6期17卷 5718-5725页

作者： Miao Wang Huaizhu Wang Yaoda Wang Junchuan Liang Mengfei Zhu Jiarui Li Zuoxiu Tie Zhong Jin state key laboratory of Coordination Chemistry MOE Key Laboratory of Mesoscopic ChemistryMOE Key Laboratory of High Performance Polymer Materials and TechnologyJiangsu Key Laboratory of Advanced Organic MaterialsTianchang New Materials and Energy Technology Researc

The electrocatalytic reduction of CO_(2)is a promising pathway to generate renewable fuels and ***,its advancement is impeded by the absence of electrocatalysts with both high selectivity and ***,we present a scalable in-situ thermal evaporation technique for synthesizing series of Bi,In,and Sn nanofilms on carbon felt(CF)substrates with a high-aspect-ratio *** resulting main-group metal nanofilms exhibit a homogeneously distributed and highly exposed catalyst surface with ample active sites,thereby promoting mass transport and ad-/desorption of reaction *** from the unique fractal morphology,the Bi nanofilms deposited on CF exhibit optimal catalytic activities for CO_(2)electroreduction among the designed metal nanofilms electrodes,with the highest Faradaic efficiency of 96.9%for formate production at−1.3 V *** hydrogen electrode(RHE)in *** an industrially relevant current density of 221.4 mA·cm−2 in flow cells,the Bi nanofilms retain a high Faradaic efficiency of 81.7%at−1.1 V(***)and a good long-term stability for formate ***,a techno-economic analysis(TEA)model shows the potential commercial viability of electrocatalytic CO_(2)conversion into formate using the Bi nanofilms *** results offer a green and convenient approach for in-situ fabrication of stable and inexpensive thin-film catalysts with a fractal structure applicable to various industrial settings.

关键词： CO_(2)electroreduction non-noble metal nanofilms flow cells efficiency and selectivity techno-economic analysis

Recent advances in protein conformation sampling by combining machine learning with molecular simulation

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Chinese Physics B 2024年第3期33卷 80-87页

作者：唐一鸣杨中元姚逸飞周运谈圆王子超潘瞳熊瑞孙俊力韦广红 Department of Physics State Key Laboratory of Surface Physicsand Key Laboratory for Computational Physical Sciences (Ministry of Education)Shanghai 200438China

The rapid advancement and broad application of machine learning(ML)have driven a groundbreaking revolution in computational *** of the most cutting-edge and important applications of ML is its integration with molecular simulations to improve the sampling efficiency of the vast conformational space of large *** review focuses on recent studies that utilize ML-based techniques in the exploration of protein conformational *** first highlight the recent development of ML-aided enhanced sampling methods,including heuristic algorithms and neural networks that are designed to refine the selection of reaction coordinates for the construction of bias potential,or facilitate the exploration of the unsampled region of the energy ***,we review the development of autoencoder based methods that combine molecular simulations and deep learning to expand the search for protein ***,we discuss the cutting-edge methodologies for the one-shot generation of protein conformations with precise Boltzmann ***,this review demonstrates the promising potential of machine learning in revolutionizing our insight into the complex conformational ensembles of proteins.

关键词： machine learning molecular simulation protein conformational space enhanced sampling

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