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Progress on the antiferromagnetic topological insulator MnBi2Te4

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National Science Review 2024年第2期11卷 33-49页

作者： Shuai Li Tianyu Liu Chang Liu Yayu Wang Hai-Zhou Lu X.C.Xie Department of Physics Harbin Institute of Technology Shenzhen institute for quantum Science and Engineering and Department of Physics Southern University of Science and Technology(SUSTech) quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area(Guangdong) Shenzhen Key Laboratory of quantum Science and Engineering International quantum Academy Beijing Academy of quantum Information Sciences Beijing Key Laboratory of Optoelectronic Functional Materials&Micro-Nano devices Department of Physics Renmin University of China State Key Laboratory of Low Dimensional quantum Physics Department of PhysicsTsinghua University Frontier Science Center for quantum Information Hefei National Laboratory International Center for quantum Materials School of Physics Peking University institute for Nanoelectronic devices and quantum computing Fudan University

Topological materials, which feature robust surface and/or edge states, have now been a research focus in condensed maTher physics. They represent a new class of materials exhibiting nontrivial topological phases,and provide a platform for exploring exotic transport phenomena, such as the quantum anomalous Hall effect and the quantum spin Hall effect. Recently, magnetic topological materials have attracted considerable interests due to the possibility to study the interplay between topological and magnetic *** particular, the quantum anomalous Hall and axion insulator phases can be realized in topological insulators with magnetic order. MnBi2Te4, as the first intrinsic antiferromagnetic topological insulator discovered, allows the examination of existing theoretical predictions; it has been extensively studied, and many new discoveries have been made. Here we review the progress made on MnBi2Te4from both experimental and theoretical aspects. The bulk crystal and magnetic structures are surveyed first, followed by a review of theoretical calculations and experimental probes on the band structure and surface states, and a discussion of various exotic phases that can be realized in MnBi2Te4. The properties of MnBi2Te4thin films and the corresponding transport studies are then reviewed, with an emphasis on the edge state transport. Possible future research directions in this field are also discussed.

关键词： MnBi2Te4 magnetic topological insulator antiferromagnetic quantum anomalous Hall effect axion insulator

Finding Ordered State in a Disordered Jungle

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Chinese Physics Letters 2024年第4期41卷 124-125页

作者：周晓东沈健 State Key Laboratory of Surface Physics and institute for Nanoelectronic devices and quantum computing Fudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation Center Fudan UniversityShanghai 201210China Shanghai Research Center for quantum Sciences Shanghai 201315China

A rich portfolio of emergent phenomena has been discovered in twisted two-dimensional(2D)moirésystems,including strongly correlated insulators,[1]superconductivity,[2]integer and fractional Chern insulators(ChIs),[3-... 详细信息

关键词： integer twisted ferroelectric

Nonreciprocal generation of Schrodinger cat state induced by topology

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Science China(Physics,Mechanics & Astronomy) 2024年第4期67卷 23-30页

作者： Zi-Hao Li Li-Li Zheng Ying Wu Xin-You Lü School of Physics and institute for quantum Science and Engineering Huazhong University of Science and Technologyand Wuhan Institute of Quantum TechnologyWuhan 430074China Key Laboratory of Optoelectronic Chemical Materials and devices of Ministry of Education Jianghan UniversityWuhan 430074China

The Schrodinger cat state produced differently in two directions is anticipated to be a critical quantum resource in quantum information *** exploring the interplay between quantum nonreciprocity and topology in a one-dimensional microcavity array,we obtain the Schrodinger cat state(a pure quantum state)in a chosen direction at the edge cavity,whereas a classical state in the other *** nonreciprocal generation of the cat state originates from the topologically protected chiralitymode excitation in the nontrivial phase,but in the trivial phase,the nonreciprocal generation of cat state ***,our proposal is switchable by tuning the parameters so that a topological phase transition ***,the obtained cat state has nonreciprocal high fidelity,nonclassicality,and quantum coherence,which are sufficient to be used in various one-way quantum technologies,e.g.,invisible quantum sensing,noise-tolerant quantum computing,and chiral quantum *** work provides a general approach to control quantum nonreciprocities with the topological effect,which substantially broadens the fields of nonreciprocal photonics and topological physics.

关键词： Schr?dinger cat state nonreciprocity topology

Polarization-dependent photoinduced metal–insulator transitions in manganites

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Science Bulletin 2024年第2期69卷 183-189页

作者： Lina Deng Weiye Zhang Hanxuan Lin Lifen Xiang Ying Xu Yadi Wang Qiang Li Yinyan Zhu Xiaodong Zhou Wenbin Wang Lifeng Yin Hangwen Guo Chuanshan Tian Jian Shen State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computingand Department of PhysicsFudan UniversityShanghai 200433China Shanghai Research Center for quantum Sciences Shanghai 201315China Zhangjiang Fudan International Innovation Center Fudan UniversityShanghai 201210China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum PhysicsShanghai 201315China

In correlated oxides,collaborative manipulation on light intensity,wavelength,pulse duration and polarization has yielded many exotic discoveries,such as phase transitions and novel quantum *** view of potential optoelectronic applications,tailoring long-lived static properties by light-induced effects is highly *** far,the polarization state of light has rarely been reported as a control parameter for this ***,we report polarization-dependent metal-to-insulator transition(MIT)in phaseseparated manganite thin films,introducing a new degree of freedom to control static ***,we observed giant photoinduced resistance jumps with striking features:(1)a single resistance jump occurs upon a linearly polarized light incident with a chosen polarization angle,and a second resistance jump occurs when the polarization angle changes;(2)the amplitude of the second resistance jump depends sensitively on the actual change of the polarization *** transmittance measurements reveal that the origin of the above phenomena is closely related to the coexistence of anisotropic *** results represent a first step to utilize light polarization as an active knob to manipulate static phase transitions,pointing towards new pathways for nonvolatile optoelectronic devices and sensors.

关键词： Metal-insulator phase transitions Polarization of light Electronic phase separation Selective domain controllability

quantum self-attention neural networks for text classification

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Science China(Information Sciences) 2024年第4期67卷 301-313页

作者： Guangxi LI Xuanqiang ZHAO Xin WANG institute for quantum computing Baidu Research Centre for quantum Software and Information University of Technology Sydney QICI quantum Information and Computation Initiative Department of Computer ScienceThe University of Hong Kong Thrust of Artificial Intelligence Information HubHong Kong University of Science and Technology(Guangzhou)

An emerging direction of quantum computing is to establish meaningful quantum applications in various fields of artificial intelligence, including natural language processing(NLP). Although some efforts based on syntactic analysis have opened the door to research in quantum NLP(QNLP), limitations such as heavy syntactic preprocessing and syntax-dependent network architecture make them impracticable on larger and real-world data sets. In this paper, we propose a new simple network architecture, called the quantum selfattention neural network(QSANN), which can compensate for these limitations. Specifically, we introduce the self-attention mechanism into quantum neural networks and then utilize a Gaussian projected quantum self-attention serving as a sensible quantum version of self-attention. As a result, QSANN is effective and scalable on larger data sets and has the desirable property of being implementable on near-term quantum devices. In particular, our QSANN outperforms the best existing QNLP model based on syntactic analysis as well as a simple classical self-attention neural network in numerical experiments of text classification tasks on public data sets. We further show that our method exhibits robustness to low-level quantum noises and showcases resilience to quantum neural network architectures.

关键词： quantum neural networks self-attention natural language processing text classification parameterized quantum circuits

quantum control for time-dependent noise by inverse geometric optimization

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Science China(Physics,Mechanics & Astronomy) 2024年第9期67卷 51-57页

作者： Xiaodong Yang Yingcheng Li Ran Liu Xinfang Nie Tao Xin Dawei Lu Jun Li institute of quantum Precision Measurement State Key Laboratory of Radio Frequency Heterogeneous IntegrationCollege of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laboratory of Surface Physics Department of PhysicsCenter for Field Theory and Particle Physicsand Institute for Nanoelectronic Devices and Quantum ComputingFudan UniversityShanghai 200433China Shenzhen institute for quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area(Guangdong) Shenzhen 518045China

quantum systems are exceedingly difficult to engineer because they are sensitive to various types of *** particular,timedependent noises are frequently encountered in experiments but how to overcome them remains a challenging *** this work,we propose a flexible robust control technique to resist time-dependent noises based on inverse geometric optimization working in the filter-function *** basic idea is to parameterize the control filter function geometrically and minimize its overlap with the noise spectral *** then effectively reduces the noise susceptibility of the controlled system *** show that the proposed method can produce high-quality robust pulses for realizing desired quantum evolutions under realistic noise ***,we demonstrate this method in examples including dynamical decoupling and quantum sensing protocols to enhance their performances.

关键词： time-dependent noise robust control quantum gates and states dynamical decoupling quantum sensing

Physical neural networks with self-learning capabilities

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 23-42页

作者： Weichao Yu Hangwen Guo Jiang Xiao Jian Shen State Key Laboratory of Surface Physics and institute for Nanoelectronic devices and quantum computing Fudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation Center Fudan UniversityShanghai 201210China Department of Physics Fudan UniversityShanghai 200433China Shanghai Research Center for quantum Sciences Shanghai 201315China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093China

Physical neural networks are artificial neural networks that mimic synapses and neurons using physical systems or *** networks harness the distinctive characteristics of physical systems to carry out computations effectively,potentially surpassing the constraints of conventional digital neural networks.A recent advancement known as“physical self-learning”aims to achieve learning through intrinsic physical processes rather than relying on external *** article offers a comprehensive review of the progress made in implementing physical self-learning across various physical *** learning strategies that contribute to the realization of physical self-learning are *** challenges in understanding the fundamental mechanism of learning,this work highlights the progress towards constructing intelligent hardware from the ground up,incorporating embedded self-organizing and self-adaptive dynamics in physical systems.

关键词： self-learning physical neural networks neuromorphic computing physical learning

Diffractive neural networks with improved expressive power for gray-scale image classification

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Photonics Research 2024年第6期12卷 1159-1166页

作者： MINJIA ZHENG WENZHE LIU LEI SHI JIAN ZI State Key Laboratory of Surface Physics Key Laboratory of Micro-and Nano-Photonic Structures(Ministry of Education)and Department of PhysicsFudan UniversityShanghai 200433China institute for Nanoelectronic devices and quantum computing Fudan UniversityShanghai 200433China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China Shanghai Research Center for quantum Sciences Shanghai 210315China

In order to harness diffractive neural networks(DNNs)for tasks that better align with real-world computer vision requirements,the incorporation of gray scale is ***,DNNs are not powerful enough to accomplish gray-scale image processing tasks due to limitations in their expressive *** our work,we elucidate the relationship between the improvement in the expressive power of DNNs and the increase in the number of phase modulation layers,as well as the optimization of the Fresnel number,which can describe the diffraction *** demonstrate this point,we numerically trained a double-layer DNN,addressing the prerequisites for intensitybased gray-scale image ***,we experimentally constructed this double-layer DNN based on digital micromirror devices and spatial light modulators,achieving eight-level intensity-based gray-scale image classification for the MNIST and Fashion-MNIST data *** optical system achieved the maximum accuracies of 95.10%and 80.61%,respectively.

关键词： process mirror limitations

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