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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

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 *** 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 *** to another modality of light,photonic computing has been progressively applied in high-efficient neuromorphic ***,we innovate a reconfigurable lifelong-learning optical neural network(L2 ONN),for highly-integrated tens-of-task machine intelligence with elaborated algorithm-hardware *** 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 *** multi-task optical features are parallelly processed by multi-spectrum representations allocated with different *** 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 ***,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 *** 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

Multi-agent policy transfer via task relationship modeling

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science China(information sciences) 2024年第8期67卷 102-114页

作者： Rongjun QIN Feng CHEN Tonghan WANG Lei YUAN Xiaoran WU Yipeng KANG Zongzhang ZHANG Chongjie ZHANG Yang YU national Key laboratory for Novel Software technology Nanjing University Polixir Technologies School of Engineering and Applied sciences Harvard University Department of Computer science and technology Tsinghua University institute for Interdisciplinary information sciences Tsinghua University

Team adaptation to new cooperative tasks is a hallmark of human intelligence, which has yet to be fully realized in learning agents. Previous studies on multi-agent transfer learning have accommodated teams of different sizes but heavily relied on the generalization ability of neural networks for adapting to unseen tasks. We posit that the relationship among tasks provides key information for policy *** utilize this relationship for efficient transfer by attempting to discover and exploit the knowledge among tasks from different teams, proposing to learn an effect-based task representation as a common latent space among tasks, and using it to build an alternatively fixed training scheme. Herein, we demonstrate that task representation can capture the relationship among teams and generalize to unseen tasks. Thus, the proposed method helps transfer the learned cooperation knowledge to new tasks after training on a few source ***, the learned transferred policies help solve tasks that are difficult to learn from scratch.

关键词： multi-agent reinforcement learning cooperative transfer learning task relationship modeling multi-agent policy reuse multi-agent multi-task learning

Automatic velocity picking based on optimal key points tracking algorithm

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Petroleum science 2024年第2期21卷 903-917页

作者： Yong-Hao Wang Wen-Kai Lu Song-Bai Jin Yang Li Yu-Xuan Li Xiao-Feng Gu The institute for Artificial Intelligence(THUAI) Tsinghua UniversityBeijing100084China State Key laboratory of Intelligent technology and Systems Tsinghua UniversityBeijing100084China Beijing national Research Center for information science and technology(BNRist) Beijing100084China The Department of Automation Tsinghua UniversityBeijing100084China

Picking velocities from semblances manually is laborious and necessitates experience. Although various methods for automatic velocity picking have been developed, there remains a challenge in efficiently incorporating information from nearby gathers to ensure picked velocity aligns with seismic horizons while also improving picking accuracy. The conventional method of velocity picking from a semblance volume is computationally demanding, highlighting a need for a more efficient strategy. In this study, we introduce a novel method for automatic velocity picking based on multi-object tracking. This dynamic tracking process across different semblance panels can integrate information from nearby gathers effectively while maintaining computational efficiency. First, we employ accelerated density clustering on the velocity spectrum to discern cluster centers without the requirement for prior knowledge regarding the number of clusters. These cluster centers embody the maximum likelihood velocities of the main subsurface structures. Second, our proposed method tracks key points within the semblance volume. Kalman filter is adopted to adjust the tracking process, followed by interpolation on these tracked points to construct the final velocity model. Our synthetic data example demonstrates that our proposed algorithm can effectively rectify the picking errors of the clustering algorithm. We further compare the performances of the clustering method(CM), the proposed tracking method(TM), and the variational method(VM) on a field dataset from the Gulf of Mexico. The results attest that our method offers superior accuracy than CM, achieves comparable accuracy with VM, and benefits from a reduced computational cost.

关键词： Velocity picking Multi-object tracking Density clustering Kalman filter

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Electric field dependence of spin qubit in a Si-MOS quantum dot

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Chinese Physics B 2024年第6期33卷 248-253页

作者：马荣龙倪铭周雨晨孔真真王桂磊刘頔罗刚曹刚李海欧郭国平 CAS Key laboratory of Quantum information University of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Key laboratory of microelectronics Devices and Integrated technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Beijing Superstring Academy of Memory technology Beijing 100176China Hefei national laboratory University of Science and Technology of ChinaHefei 230088China Origin Quantum Computing Company Limited Hefei 230026China

Valley, the intrinsic feature of silicon, is an inescapable subject in silicon-based quantum computing. At the spin–valley hotspot, both Rabi frequency and state relaxation rate are significantly enhanced. With protection against charge noise, the valley degree of freedom is also conceived to encode a qubit to realize noise-resistant quantum ***, based on the spin qubit composed of one or three electrons, we characterize the intrinsic properties of valley in an isotopically enriched silicon quantum dot(QD) device. For one-electron qubit, we measure two electric-dipole spin resonance(EDSR) signals which are attributed to partial occupation of two valley states. The resonance frequencies of two EDSR signals have opposite electric field dependences. Moreover, we characterize the electric field dependence of the upper valley state based on three-electron qubit experiments. The difference of electric field dependences of the two valleys is 52.02 MHz/V, which is beneficial for tuning qubit frequency to meet different experimental requirements. As an extension of electrical control spin qubits, the opposite electric field dependence is crucial for qubit addressability,individual single-qubit control and two-qubit gate approaches in scalable quantum computing.

关键词： silicon-based quantum computing valley electric-dipole spin resonance

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Theoretical analysis of the elastic Kelvin-Helmholtz instability in explosive weldings

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Defence technology（防务技术） 2024年第2期32卷 521-528页

作者： Yuanbo Sun Jianning Gou Cheng Wang Qiang Zhou Rui Liu Pengwan Chen Tonghui Yang Xiang Zhao State Key laboratory of Explosion science and technology Beijing Institute of TechnologyBeijing100081China Beijing HIWING Scientific and Technological information institute Beijing100084China School of Aerospace Engineering Tsinghua UniversityBeijing100084China

By considering the joint effects of the Kelvin-Helmholtz(KH) and Rayleigh-Taylor(RT) instabilities, this paper presents an interpretation of the wavy patterns that occur in explosive welding. It is assumed that the elasticity of the material at the interface effectively determines the wavelength, because explosive welding is basically a solid-state welding process. To this end, an analytical model of elastic hydrodynamic instabilities is proposed, and the most unstable mode is selected in the solid phase. Similar approaches have been widely used to study the interfacial behavior of solid metals in high-energy-density physics. By comparing the experimental and theoretical results, it is concluded that thermal softening,which significantly reduces the shear modulus, is necessary and sufficient for successful welding. The thermal softening is verified by theoretical analysis of the increase in temperature due to the impacting and sliding of the flyer and base plates, and some experimental observations are qualitatively *** summary, the combined effect of the KH and RT instabilities in solids determines the wavy morphology, and our theoretical results are in good qualitative agreement with experimental and numerical observations.

关键词： Explosive welding Hydrodynamic instabilities Elasticity

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Broadband light-active optoelectronic FeFET memory for in-sensor non-volatile logic

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science China(information sciences) 2024年第9期67卷 346-347页

作者： Yong ZHANG Dongxin TAN Cizhe FANG Zheng-Dong LUO Qiyu YANG Qiao ZHANG Yu ZHANG Xuetao GAN Yan LIU Yue HAO Genquan HAN State Key Discipline laboratory of Wide Band Gap Semiconductor technology School of MicroelectronicsXidian University Hangzhou institute of technology Xidian University Key laboratory of Light Field Manipulation and information Acquisition Ministry of Industry and Information Technologyand Shaanxi Key Laboratory of Optical Information Technology School of Physical Science and TechnologyNorthwestern Polytechnical University

Machine vision has become crucial in the modern intelligence era, especially in rapidly developing applications such as autonomous vehicles and robotic visual sensors [1].With the ever-increasing requirements of visua... 详细信息

关键词： Ferroelectric RAM

Retinomorphic X-ray detection using perovskite with hydrionconductive organic cations

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The Innovation 2024年第4期5卷 111-117,110页

作者： Hang Yin Jincong Pang Shan Zhao Haodi Wu Zihao Song Xing Li Zhiping Zheng Ling Xu Jiang Tang Guangda Niu Wuhan national laboratory for Optoelectronics and School of Optical and Electronic information Huazhong University of Science and TechnologyWuhan 430074China Optical Valley laboratory Wuhan 430074China institute of microelectronics of the Chinese Academy of sciences Beijing 100029China Research institute of Huazhong University of science and technology in Shenzhen Shenzhen 518057China

X-ray detection is crucial across various sectors,but traditional techniques face challenges such as inefficient data transmission,redundant sensing,high power consumption,and *** innovative idea of a retinomorphic X-ray detector shows great ***,its implementation has been hindered by the absence of active layers capable of both detecting X-rays and serving as memory *** response to this critical gap,our study integrates hybrid perovskite with hydrion-conductive organic cations to develop a groundbreaking retinomorphic X-ray *** novel device stands at the nexus of technological innovation,utilizing X-ray detection,memory,and preprocessing capabilities within a single hardware *** core mechanism underlying this innovation lies in the transport of electrons and holes within the metal halide octahedral frameworks,enabling precise X-ray ***,the hydrion movement through organic cations endows the device with short-term resistive memory,facilitating rapid data processing and ***,our retinomorphic X-ray detector boasts an array of formidable features,including reconfigurable shortterm memory,a linear response curve,and an extended retention *** practical terms,this translates into the efficient capture of motion projections with minimal redundant data,achieving a compression ratio of 18.06%and an impressive recognition accuracy of up to 98.6%.In essence,our prototype represents a paradigm shift in X-ray detection *** its transformative capabilities,this retinomorphic hardware is poised to revolutionize the existing X-ray detection landscape.

关键词： perovskite conductive redundant

Observation of stabilized negative capacitance effect in hafnium-based ferroic films

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Materials Futures 2024年第1期3卷 1-9页

作者： Leilei Qiao Ruiting Zhao Cheng Song Yongjian Zhou Qian Wang Tian-Ling Ren Feng Pan Key laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084People’s Republic of China institute of microelectronics&Beijing national Research Center for information science and technology(BNRist) Tsinghua UniversityBeijing 100084People’s Republic of China

A negative capacitance(NC)effect has been proposed as a critical pathway to overcome the‘Boltzmann tyranny’of electrons,achieve the steep slope operation of transistors and reduce the power dissipation of current semiconductor *** particular,the ferroic property in hafnium-based films with fluorite structure provides an opportunity for the application of the NC effect in electronic ***,to date,only a transient NC effect has been confirmed in hafnium-based ferroic materials,which is usually accompanied by hysteresis and is detrimental to low-power transistor *** stabilized NC effect enables hysteresis-free and low-power transistors but is difficult to observe and demonstrate in hafnium-based *** difficulty is closely related to the polycrystalline and multi-phase structure of hafnium-based films fabricated by atomic layer deposition or chemical solution ***,we prepare epitaxial ferroelectric Hf_(0.5)Zr_(0.5)O_(2) and antiferroelectric ZrO_(2) films with single-phase structure and observe the capacitance enhancement effect of Hf_(0.5)Zr_(0.5)O_(2)/Al_(2)O_(3) and ZrO_(2)/Al_(2)O_(3) capacitors compared to that of the isolated Al_(2)O_(3) capacitor,verifying the stabilized NC *** capacitance of Hf_(0.5)Zr_(0.5)O_(2) and ZrO_(2) is evaluated as−17.41 and−27.64 pF,*** observation of the stabilized NC effect in hafnium-based films sheds light on NC studies and paves the way for low-power transistors.

关键词： negative capacitance effect fluorite structure hafnium-based ferroelectrics antiferroelectric