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Unveiling Hidden Magnon Modes in van der Waals Magnets via Gain-Assisted Strong Photon-Magnon Coupling 认领 引用
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作者 Yitong Sun Xudong Wang +6 位作者 Yue Zhao Yufeng Tian Jinwei Rao Shishen Yan Bingbing Lyu Yilin Wang Lihui Bai 《Chinese Physics Letters》 SCIE EI CAS CSCD 2026年第6期119-123,I0115-I0120,共5页
Magnonic systems based on two-dimensional van der Waals(vdW)magnets offer a versatile platform for hybridizing magnons with photons,phonons,and electrons,promising advancements in information processing.A key challeng... Magnonic systems based on two-dimensional van der Waals(vdW)magnets offer a versatile platform for hybridizing magnons with photons,phonons,and electrons,promising advancements in information processing.A key challenge,however,is the detection and manipulation of magnons due to their ultra-weak signals in atomically thin samples.To overcome this,we integrate a van der Waals antiferromagnet,CrCl3,with a high-quality-factor active cavity operating at cryogenic temperatures.Utilizing the cavity’s gain and self-sustained oscillation,we uncover multiple magnon modes previously inaccessible in conventional measurements.Specifically,we observe two low-damping magnon modes near the acoustic mode of CrCl3,with damping rates three orders of magnitude lower.This exceptionally low damping enables strong cavity photon-magnon coupling,yielding two distinct bistable regions upon magnetic field sweep.Additionally,we also observe a ferromagnetic magnon mode located significantly below the Kittel frequency,twice the antiferro-magnetic-ferromagnetic transition field.Our work establishes a gain-assisted strong-coupling approach as a powerful tool for probing magnon dynamics in two-dimensional vdW magnets,opening new avenues for engineering magnonic states for future information technologies. 展开更多
关键词 cryogenic temperatures magnon modes detection manipulation magnons magnonic systems hybridizing magnons van der waals magnets photon magnon coupling information processinga
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Structure-and cost-aware partitioning for large graphs over geo-distributed datacenters 认领 引用
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作者 Delong MA Ye YUAN +2 位作者 Hangxu JI Yishu WANG Yuliang MA 《Frontiers of Computer Science》 SCIE EI CAS CSCD 2026年第2期181-183,共3页
1Introduction Graph partitioning is essential for large-scale distributed graph processing,as partitioning strategies directly affect graph algorithm performance[1].To ensure reliability and scalability,many graphbase... 1Introduction Graph partitioning is essential for large-scale distributed graph processing,as partitioning strategies directly affect graph algorithm performance[1].To ensure reliability and scalability,many graphbased applications[2](e.g.,Facebook,Weibo)deploy their services over geo-distributed datacenters(DCs),posing challenges for existing partition methods.These methods may struggle with heterogeneity(e.g.,network bandwidth)or overlook structural properties(e.g.,community structure)during optimization. 展开更多
关键词 aware cost partition methodsthese graph processingas partitioning graphbased applications egfacebookweibo deploy graph partitioning graph algorithm
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Memristor-Based Artificial Neural Networks for Hardware Neuromorphic Computing 认领 引用 被引量：2
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作者 Boyan Jin Zhenlong Wang +1 位作者 Tianyu Wang Jialin Meng 《Research》 SCIE EI CSCD 2026年第2期715-740,共26页
Artificial neural networks have long been studied to emulate the cognitive capabilities of the human brain for artificial intelligence(Al)computing.However,as computational demands intensify,conventional hardware base... Artificial neural networks have long been studied to emulate the cognitive capabilities of the human brain for artificial intelligence(Al)computing.However,as computational demands intensify,conventional hardware based on transistor and complementary metal oxide semiconductor(CMos)technology faces substantial limitations due to the separation of memory and processing,a challenge commonly known as the von Neumann bottleneck.In this review,we examine how memristors,which are novel nonvolatile memory devices that exhibit memory-dependent resistance,can be harnessed to build more efficient and scalable neural networks.We provide a comprehensive background on the evolution of neural network models and memristors,as well as introduce the principles of memristive devices,which mimic the dynamic behavior of biological synapses.Various neural network architectures,including convolutional,recurrent,and spiking models,are discussed,highlighting the advantages of integrating memristors for in-memory computing and parallel processing.Our review further examines key mechanisms such as synaptic plasticity,encompassing both long-term potentiation and depression,as well as emerging learning algorithms that leverage memristive behavior.Finally,we identify current challenges,such as achieving ultra-low power consumption,high device uniformity,and seamless system integration,and propose future directions in materials science,device engineering,system integration,and industrialization.These advances suggest that memristor-based neural networks may pave the way for next-generation Al systems that combine low power consumption with high computational performance,ultimately bridging the gap between biological and electronic information processing. 展开更多
关键词 memristors artificial neural networks emulate cognitive capabilities human brain nonvolatile memory devices von neumann bottleneckin separation memory processinga complementary metal oxide semiconductor cmos technology hardware neuromorphic computing
Facile Strategies for Incorporating Chiroptical Activity into Organic Optoelectronic Devices 认领 引用 被引量：1
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作者 Hanna Lee Danbi Kim +1 位作者 Jeong Ho Cho Jung Ah Lim 《Accounts of Materials Research》 CAS CSCD 2025年第4期434-446,共13页
CONSPECTUS:Chiral optoelectronics,which utilize the unique interactions between circularly polarized(CP)light and chiral materials,open up exciting possibilities in advanced technologies.These devices can detect,emit,... CONSPECTUS:Chiral optoelectronics,which utilize the unique interactions between circularly polarized(CP)light and chiral materials,open up exciting possibilities in advanced technologies.These devices can detect,emit,or manipulate light with specific polarization,enabling applications in secure communication,sensing,and data processing.A key aspect of chiral optoelectronics is the ability to generate or detect optical and electrical signals by controlling or distinguishing CP light based on its polarization direction.This capability is rooted in the selective interaction of CP light with the stereogenic(non-superimposable)molecular geometry of chiral substances,wherein the polarization of CP light aligns with the intrinsic asymmetry of the material.Among the diverse chiral materials explored for this purpose,π-conjugated molecules offer special advantages due to their tunable optoelectronic properties,efficient light−matter interactions,and cost-effective processability.Recent advancements inπ-conjugated molecule research have demonstrated their ability to generate strong chiroptical responses,thereby paving the way for compact and multifunctional device designs.Building on these unique advantages,π-conjugated molecules have advanced organic electronics into rapidly evolving technological fields.The combination of chiralπ-conjugated molecules with organic electronics is anticipated to simplify the fabrication of chiroptical devices,thereby lowering technical barriers and accelerating progress in chiral optoelectronics.This Account introduces strategies for incorporating chiroptical activity into organic optoelectronic devices,focusing on two main approaches:direct incorporation of chiroptical activity intoπ-conjugated polymer semiconductors and integration of chiral organic nanoarchitectures with conventional organic optoelectronic devices.In the first approach,we especially highlight simple methods to induce chiroptical activity in various achiralπ-conjugated polymers through the transfer of chirality from small chiral molecules.This hybrid approach effectively combines the excellent electrical properties and various optical transition properties of achiral polymers with the strong chiroptical activity of small molecules.Moreover,we address a fundamental challenge in achieving chiroptical transitions in planarπ-conjugated polymers,demonstrating the development of low-bandgapπ-conjugated polymers that exhibit both strong chiroptical activity and excellent electrical performance.Another approach,incorporating chiroptical activity into existing organic optoelectronic devices,which have already achieved significant performance advances,presents an effective strategy for high-performance chiral optoelectronics.For this purpose,we introduce the use of supramolecular assemblies ofπ-conjugated molecules to impart chiroptical responses into high-performance optoelectronic systems,utilizing efficient charge transfer of photoexcited electrons in chiroptical supramolecular nanoarchitectures.Additionally,we explore the integration of organic chiral photonic structure into organic optoelectronic systems,which act as optical filters tailored for CP light.These architectures offer unique advantages,including easy processability and seamless compatibility with existing organic electronic platforms.By bridging concepts from chiral organic optoelectronic materials and advanced organic electronics,this work outlines actionable approaches for advancing chiral optoelectronic technologies.These strategies underscore the versatility ofπ-conjugated molecules while also expanding the framework for next-generation applications.As the field of chiral optoelectronics evolves,integrating chiroptical functionalities into organic devices will facilitate transformative innovations in quantum computing,biosensing,and photonic encryption. 展开更多
关键词 secure communicationsensingand controlling distinguishing cp light chiral optoelectronics generate detect optical electrical signals data processinga manipulate light advanced technologiesthese chiral materialsopen
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