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science China(information sciences) 2024年第2期67卷 267-278页

作者： Guofang YU Renrong LIANG Haiming ZHAO Lei XIAO Jie CUI Yue ZHAO Wenpu CUI Jing WANG Jun XU Jun FU Tianling REN School of Integrated Circuits Tsinghua University Beijing national Research Center for information science technology Tsinghua University

Surface acoustic wave(SAW) resonators with an ultrahigh Q-factor are designed and fabricated on silicon-based gallium nitride(GaN/Si). The temperature-dependent performance is characterized over a wide range, from 10 to 500 K. Finite element analysis is employed to guide the design of the SAW resonator from indications of the Rayleigh mode and weak propagation direction dependence of SAW in the c-plane of GaN/Si. The SAW resonator with 100 pairs of interdigital transducers(IDT), 100 pairs of grating reflectors(GR) for each side, aperture size of 80 μm, metallization ratio of 0.5, and electrode width of 500 nm resonates at 1.9133 GHz accordingly with an ultrahigh Q-factor of 7622 at room temperature, which contributes the fr× Qr, up to 14.583×1012Hz. A resonator operating over 10 to 500 K indicates an approximately linear decreasing temperature dependence above 280 K while being approximately constant below 40 K. The fitting to resonator characteristics using the modified Butterworth Van Dyke(m BVD) model reveals a reduction in both the electrode and mechanical losses while worsening the dielectric loss with cooling down.

关键词： GaN/Si SAW resonator ultrahigh Q-factor temperature-dependent performance mBVD losses

Understanding adversarial attacks on observations in deep reinforcement learning

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science China(information sciences) 2024年第5期67卷 69-83页

作者： You QIAOBEN Chengyang YING Xinning ZHOU Hang SU Jun ZHU Bo ZHANG Department of Computer science and technology Beijing National Research Center for Information Science and Technology Tsinghua-Bosch Joint Center for Machine Learning Institute for Artificial Intelligence Tsinghua University Peng Cheng laboratory

Deep reinforcement learning models are vulnerable to adversarial attacks that can decrease the cumulative expected reward of a victim by manipulating its observations. Despite the efficiency of previous optimization-based methods for generating adversarial noise in supervised learning, such methods might not achieve the lowest cumulative reward since they do not generally explore the environmental dynamics.Herein, a framework is provided to better understand the existing methods by reformulating the problem of adversarial attacks on reinforcement learning in the function space. The reformulation approach adopted herein generates an optimal adversary in the function space of targeted attacks, repelling them via a generic two-stage framework. In the first stage, a deceptive policy is trained by hacking the environment and discovering a set of trajectories routing to the lowest reward or the worst-case performance. Next, the adversary misleads the victim to imitate the deceptive policy by perturbing the observations. Compared to existing approaches, it is theoretically shown that our adversary is strong under an appropriate noise level. Extensive experiments demonstrate the superiority of the proposed method in terms of efficiency and effectiveness, achieving state-of-the-art performance in both Atari and MuJoCo environments.

关键词： deep learning reinforcement learning adversarial robustness adversarial attack

Photonic neuromorphic architecture for tens-of-task lifelong learning

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Light(science & Applications) 2024年第3期13卷 519-530页

作者： Yuan Cheng Jianing Zhang Tiankuang Zhou Yuyan Wang Zhihao Xu Xiaoyun Yuan Lu Fang Sigma laboratory Department of Electronic EngineeringTsinghua UniversityBeijing 100084China Beijing national Research Center for information science and technology(BNRist) Beijing 100084China Institute for Brain and Cognitive science Tsinghua University(THUIBCS)Beijing 100084China

Scalable,high-capacity,and low-power computing architecture is the primary assurance for increasingly manifold and large-scale machine learning tasks.Traditional electronic artificial agents by conventional power-hungry processors have faced the issues of energy and scaling walls,hindering them from the sustainable performance improvement and iterative multi-task learning.Referring to another modality of light,photonic computing has been progressively applied in high-efficient neuromorphic systems.Here,we innovate a reconfigurable lifelong-learning optical neural network(L2 ONN),for highly-integrated tens-of-task machine intelligence with elaborated algorithm-hardware codesign.Benefiting from the inherent sparsity and parallelism in massive photonic connections,L2 ONN learns each single task by adaptively activating sparse photonic neuron connections in the coherent light field,while incrementally acquiring expertise on various tasks by gradually enlarging the activation.The multi-task optical features are parallelly processed by multi-spectrum representations allocated with different wavelengths.Extensive evaluations on freespace and on-chip architectures confirm that for the first time,L2 ONN avoided the catastrophic forgetting issue of photonic computing,owning versatile skills on challenging tens-of-tasks(vision classification,voice recognition,medical diagnosis,etc.)with a single model.Particularly,L2 ONN achieves more than an order of magnitude higher efficiency than the representative electronic artificial neural networks,and 14×larger capacity than existing optical neural networks while maintaining competitive performance on each individual task.The proposed photonic neuromorphic architecture points out a new form of lifelong learning scheme,permitting terminal/edge AI systems with light-speed efficiency and unprecedented scalability.

关键词： life neural versatile

Near-field wideband beam training for ELAA with uniform circular array

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science China(information sciences) 2024年第6期67卷 370-383页

作者： Yuhao CHEN Linglong DAI Department of Electronic Engineering Tsinghua UniversityBeijing National Research Center for Information Science and Technology (BNRist)

Extremely large-scale antenna array(ELAA) at millimeter wave(mmWave) and Terahertz(THz)band has been considered a key technology for combating high attenuation in high-frequency bands in future6G communications. Uniform circular arrays(UCAs) have attracted much attention because of their ability to provide flat beamforming gain at all angles. To realize efficient beamforming, beam training is widely used to acquire channel state information. However, with a large antenna number, the beam training overhead in ELAA systems becomes overwhelming. Moreover, with a large bandwidth, the beam defocus effect severely degrades beam training accuracy. To address these issues, this paper proposes a frequency-dependent focusing(FDF)-based beam training scheme to realize effective beam training in near-field wideband ELAA systems with UCA. Specifically, we first analyze the FDF property of UCA, where signals at different subcarriers can simultaneously focus on different distances. Then, by exploiting the FDF property to search different distances using different subcarriers simultaneously, we design a hierarchical codebook and propose an FDFbased beam training scheme. To reveal the effectiveness of the proposed scheme, we compare its necessary beam training overhead with that of existing schemes. Finally, the simulation results demonstrate that the proposed scheme can achieve accurate beam training in near-field wideband UCA systems with a low beam training overhead.

关键词： extremely large-scale antenna array (ELAA) uniform circular array (UCA) near-field wideband beam training

Recent progress in single crystal perovskite X-ray detectors

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science China(information sciences) 2024年第3期67卷 5-19页

作者： Xiao LIU Jun REN Yu-Ang CHEN Xiangshun GENG Dan XIE Tian-Ling REN School of Integrated Circuits tsinghua University Beijing national Research Center for information science and technology (BNRist)

Perovskites have attracted extensive attention as radiation detection material due to their long carrier diffusion length and lifetime, high absorption coefficient, and flexible manufacturing process. Compared with polycrystalline structures, single crystal perovskites improve the performance of optoelectronic devices due to their low defect state density, better photoelectric characteristics, and chemical stability.Herein, we review the recent progress of single crystal perovskite X-ray detectors. First, we briefly introduced the basic concepts, detection mechanisms, figure of merits of perovskite X-ray detectors, and the preparation methods of single crystal perovskites. Then, we summarized the significant advancements in single crystal perovskite X-ray detectors in recent times. Finally, we discussed the critical challenges and some practicable solutions for developing high-performance X-ray detectors.

关键词： single crystal perovskites carrier transport radiation detection X-ray detectors X-ray imaging

Quantized anomalous Hall resistivity achieved in molecular beam epitaxy-grown Mn Bi2Te4 thin films

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national science Review 2024年第2期11卷 24-32页

作者： Yunhe Bai Yuanzhao Li Jianli Luan Ruixuan Liu Wenyu Song Yang Chen Peng-Fei Ji Qinghua Zhang Fanqi Meng Bingbing Tong Lin Li Yuying Jiang Zongwei Gao Lin Gu Jinsong Zhang Yayu Wang Qi-Kun Xue Ke He Yang Feng Xiao Feng State Key laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Institute of Physics Chinese Academy of Sciences School of Materials science and Engineering Tsinghua University Beijing Academy of Quantum information sciences Frontier science Center for Quantum information Hefei national laboratory Southern University of science and technology

The intrinsic magnetic topological insulator MnBi2Te4provides a feasible pathway to the high-temperature quantum anomalous Hall（QAH） effect as well as various novel topological quantum phases. Although quantized transport properties have been observed in exfoliated MnBi2Te4thin flakes, it remains a big challenge to achieve molecular beam epitaxy（MBE）-grown MnBi2Te4thin films even close to the quantized regime. In this work, we report the realization of quantized anomalous Hall resistivity in MBE-grown MnBi2Te4thin films with the chemical potential tuned by both controlled in situ oxygen exposure and top gating. We find that elongated post-annealing obviously elevates the temperature to achieve quantization of the Hall resistivity, but also increases the residual longitudinal resistivity, indicating a picture of high-quality QAH puddles weakly coupled by tunnel barriers. These results help to clarify the puzzles in previous experimental studies on MnBi2Te4and to find a way out of the big difficulty in obtaining MnBi2Te4samples showing quantized transport properties.

关键词： intrinsic magnetic topological insulator quantized anomalous Hall resistivity molecular beam epitaxy quantized transport property

Demixing microwave signals using system-on-chip photonic processor

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Light(science & Applications) 2024年第3期13卷 399-401页

作者： Sheng Gao Chu Wu Xing Lin Department of Electronic Engineering Tsinghua University100084 BeijingChina Beijing national Research Center for information science and technology Tsinghua University100084 BeijingChina

The integrated photonic processor,co-packaged with electronic peripherals,is proposed for blind source separation of microwave signals,which separates signal-of-interest from dynamic interference with real-time adapta... 详细信息

关键词： processor microwave mixing

Quantum key distribution over a mimicked dynamic-scattering channel

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science China(information sciences) 2024年第4期67卷 323-330页

作者： Qi-Hang LU Fang-Xiang WANG Wei CHEN Hai-Yang FU Yin-Jie LU Shuang WANG De-Yong HE Zhen-Qiang YIN Guang-Can GUO Zheng-Fu HAN CAS Key laboratory of Quantum information University of Science and Technology of China CAS Center for Excellence in Quantum information and Quantum Physics University of Science and Technology of China Hefei national laboratory University of Science and Technology of China

Free-space quantum key distribution(QKD) plays an important role in the global quantum network. However, free space channels suffer from the atmospheric turbulence and scattering effects of haze,fog, and dust, which significantly weaken the performance of QKD or even block the secure quantum link.Here, we prove the performance of QKD over a dynamic scattering channel can be enhanced significantly using a fast wavefront shaping technique. The system achieves on average 10-dB enhancement of quantum transmission efficiency and establishes a secure quantum link for QKD. Our work demonstrates the feasibility of QKD through free-space dynamic scattering channels and enhances the deployment capability of complex-channel QKD system.

关键词： quantum key distribution free space channel channel turbulence channel scattering wavefront shaping

Breaking the efficiency limitations of dissipative Kerr solitons using nonlinear couplers

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science China(Physics,Mechanics & Astronomy) 2024年第3期67卷 88-94页

作者： Ming Li Xiao-Xiao Xue Yan-Lei Zhang Xin-Biao Xu Chun-Hua Dong Guang-Can Guo Chang-Ling Zou CAS Key laboratory of Quantum information University of Science and Technology of ChinaHefei 230026China CAS Centerfor Excellence in Quantum information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Department of Electronic Engineering Beijing National Research Center for Information Science and TechnologyTsinghua University Beijing 100084China

Dissipative Kerr solitons(DKS) have long been suffering from poor power conversion efficiency when driven by continuous-wave lasers. By deriving the critical coupling condition of a multimode nonlinear optics system in a generalized theoretical framework,two efficiency limitations of the conventional pump method of DKS are revealed: the effective coupling rate is too small and is also power-dependent. A general approach is provided to resolve this challenge by introducing two types of nonlinear couplers to couple the soliton cavity and CW input through nonlinear processes. The collective coupler opens multiple coupling channels and the self-adaptive coupler builds a power-independent effective external coupling rate to the DKS for approaching the generalized critical coupling condition, which promises near-unity power conversion efficiencies. For instance, a conversion efficiency exceeding 90% is predicted for aluminum nitride microrings with a nonlinear coupler utilizing second-harmonic generation. The mechanism applies to various nonlinear processes, including Raman and Brillouin scattering, and thus paves the way for micro-solitons toward practical applications.

关键词： Kerr frequency comb conversion efficiency nonlinear coupler

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Advances in neuromorphic computing:Expanding horizons for AI development through novel artificial neurons and in-sensor computing

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Chinese Physics B 2024年第3期33卷 1-23页

作者：杨玉波赵吉哲刘胤洁华夏扬王天睿郑纪元郝智彪熊兵孙长征韩彦军王健李洪涛汪莱罗毅 Department of Electronic Engineering Tsinghua UniversityBeijing 100084China Beijing national Research Center for information science and technology Tsinghua UniversityBeijing 100084China

AI development has brought great success to upgrading the information age.At the same time,the large-scale artificial neural network for building AI systems is thirsty for computing power,which is barely satisfied by the conventional computing hardware.In the post-Moore era,the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits(VLSIC)is challenging to meet the growing demand for AI computing power.To address the issue,technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture,and dealing with AI algorithms much more parallelly and energy efficiently.Inspired by the human neural network architecture,neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or devices.Although it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network(SNN),the development in this field has incubated promising technologies like in-sensor computing,which brings new opportunities for multidisciplinary research,including the field of optoelectronic materials and devices,artificial neural networks,and microelectronics integration technology.The vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive processing.This paper reviews firstly the architectures and algorithms of SNN,and artificial neuron devices supporting neuromorphic computing,then the recent progress of in-sensor computing vision chips,which all will promote the development of AI.

关键词： neuromorphic computing spiking neural network(SNN) in-sensor computing artificial intelligence

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