检索结果-内蒙古大学图书馆

arXiv 2019年

作者： Zhou, Tong Zhu, Xie-Gang Tong, Mingyu Zhang, Yun Luo, Xue-Bing Xie, Xiangnan Feng, Wei Chen, Qiuyun Tan, Shiyong Wang, Zhen-Yu Jiang, Tian Lai, Xin-Chun Yang, Xuejun State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China Science and Technology on Surface Physics and Chemistry Laboratory Jiangyou Sichuan621908 China National Innovation Institute of Defense Technology Academy of Military Sciences PLA China Beijing100010 China Institute of Materials China Academy of Engineering Physics Mianyang Sichuan621700 China College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha410073 China Academy of Military Sciences PLA China Beijing100010 China Beijing Academy of Quantum Information Sciences Beijing100084 China

Type-II nodal line semimetal (NLS) is a new quantum state hosting one-dimensional closed loops formed by the crossing of two bands which have the same sign in their slopes along the radial direction of the loop. According to the theoretical prediction, Mg3Bi2 is an ideal candidate for studying the type-II NLS by tuning its spin-orbit coupling (SOC). In this paper, high quality Mg3Bi2 films are grown by molecular beam epitaxy (MBE). By in-situ angle resolved photoemission spectroscopy (ARPES), a pair of surface resonance bands (SRBs) around point is clearly seen. It shows that Mg3Bi2 films grown by MBE is Mg(1)-terminated by comparing the ARPES data with the first principles calculations results. And, the temperature dependent weak anti-localization (WAL) effect in Mg3Bi2 films is observed under low magnetic field, which shows a clear two dimensional (2D) e-e scattering characteristics by fitting with the Hikami-Larkin-Nagaoka (HLN) model. Combining with ARPES, magneto-transport measurements and the first principles calculations, this work proves that Mg3Bi2 is a semimetal with topological surface states TSSs, which paves the way for Mg3Bi2 as an ideal materials platform for studying the exotic features of type-II nodal line semimetals (NLSs) and the topological phase transition by tuning its SOC. Copyright © 2019, The Authors. All rights reserved.

关键词： Binary alloys

来源：评论

学校读者我要写书评

暂无评论

Optical control of single-photon negative-feedback avalanche diode detector

arXiv

引用

arXiv 2019年

作者： Gras, Gaëtan Sultana, Nigar Huang, Anqi Jennewein, Thomas Bussières, Félix Makarov, Vadim Zbinden, Hugo ID Quantique SA CarougeCH-1227 Switzerland Group of Applied Physics University of Geneva GenevaCH-1211 Switzerland Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Russian Quantum Center Skolkovo Moscow121205 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai201315 China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia

We experimentally demonstrate optical control of negative-feedback avalanche diode (NFAD) detectors using bright light. We deterministically generate fake single-photon detections with a better timing precision than normal operation. This could potentially open a security loophole in quantum cryptography systems. We then show how monitoring the photocurrent through the avalanche photodiode can be used to reveal the detector is being blinded. Copyright © 2019, The Authors. All rights reserved.

关键词： Feedback

来源：评论

学校读者我要写书评

暂无评论

Field‐Effect Transistors: Low‐Symmetry PdSe2 for high performance Thermoelectric Applications (Adv. Funct. Mater. 52/2020)

引用

Advanced Functional Materials 2020年第52期30卷 2070347-2070347页

作者： Yunshan Zhao Peng Yu Gang Zhang Minglei Sun Dongzhi Chi Kedar Hippalgaonkar John T. L. Thong Jing Wu NNU‐SULI Thermal Energy Research Center (NSTER) & Center for Quantum Transport and Thermal Energy Science (CQTES) School of Physics and Technology Nanjing Normal University Nanjing 210023 China Institute of Materials Research and Engineering A*STAR (Agency for Science Technology and Research) 2 Fusionopolis Way Innovis #08‐03 Singapore 138634 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore School of Materials Science and Engineering State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat‐Sen University Guangzhou 510275 P. R. China Institute of High Performance Computing Singapore 138632 Singapore Department of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore

In article number 2004896, John T. L. Thong, Jing Wu, and co‐workers investigate thermoelectric transport in novel 2D palladium diselenide (PdSe2) with a low‐symmetry pentagonal lattice. Due to its sensitive dependence on the interlayer coupling originating from the special lattice structure, the thermoelectric performance can be largely enhanced. The high band convergence and quantum confinement through thickness engineering advance and broaden the applications of thermoelectric such as in soft robotics, health monitoring, and human‐machine interfaces.

关键词： 2D field‐effect transistors palladium diselenide pentagonal crystals thermoelectric devices

来源：评论

学校读者我要写书评

暂无评论

Controlling single-photon detector ID210 with bright light

arXiv

引用

arXiv 2019年

作者： Chistiakov, Vladimir Huang, Anqi Egorov, Vladimir Makarov, Vadim Faculty of Photonics and Optical Information ITMO University St. Petersburg Russia Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Russian Quantum Center Skolkovo Moscow143025 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai201315 China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada

We experimentally demonstrate that a single-photon detector ID210 commercially available from ID Quantique is vulnerable to blinding and can be fully controlled by bright illumination. In quantum key distribution, this vulnerability can be exploited by an eavesdropper to perform a faked-state attack giving her full knowledge of the key without being noticed. We consider the attack on standard BB84 protocol and a subcarrier-wave scheme, and outline a possible countermeasure. Copyright © 2019, The Authors. All rights reserved.

关键词： Avalanche photodiodes

来源：评论

学校读者我要写书评

暂无评论

Laser-Seeding Attack in Quantum Key Distribution

引用

Physical Review Applied 2019年第6期12卷 064043-064043页

作者： Anqi Huang Álvaro Navarrete Shi-Hai Sun Poompong Chaiwongkhot Marcos Curty Vadim Makarov Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 People’s Republic of China Institute for Quantum Computing University of Waterloo Waterloo Ontario Canada N2L 3G1 EI Telecomunicación Department of Signal Theory and Communications University of Vigo Vigo E-36310 Spain School of Physics and Astronomy Sun Yat-Sen University Zhuhai 519082 People’s Republic of China Department of Physics and Astronomy University of Waterloo Waterloo Ontario Canada N2L 3G1 Russian Quantum Center Skolkovo Moscow 121205 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai 201315 People’s Republic of China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow 119049 Russia

Quantum key distribution (QKD) based on the laws of quantum physics allows the secure distribution of secret keys over an insecure channel. Unfortunately, imperfect implementations of QKD compromise its information-theoretical security. Measurement-device-independent quantum key distribution (MDI QKD) is a promising approach to remove all side channels from the measurement unit, which is regarded as the “Achilles’ heel” of QKD. An essential assumption in MDI QKD is, however, that the sources are trusted. Here we experimentally demonstrate that a practical source based on a semiconductor laser diode is vulnerable to a laser-seeding attack, in which light injected from the communication line into the laser results in an increase of the intensities of the prepared states. The unnoticed increase of intensity may compromise the security of QKD, as we show theoretically for the prepare-and-measure decoy-state BB84 and MDI QKD protocols. Our theoretical security analysis is general and can be applied to any vulnerability that increases the intensity of the emitted pulses. Moreover, a laser-seeding attack might be launched as well against decoy-state-based quantum cryptographic protocols beyond QKD.

关键词： Optical quantum information processing Optoelectronics Photonics Quantum algorithms Quantum communication Quantum cryptography Semiconductor quantum optics Photodiodes

来源：评论

学校读者我要写书评

暂无评论

Exploring Low Internal Reorganization Energies for Silicene Nanoclusters

引用

Physical Review Applied 2018年第5期9卷 054012-054012页

作者： Ricardo Pablo-Pedro Hector Lopez-Rios Jose-L. Mendoza-Cortes Jing Kong Serguei Fomine Troy Van Voorhis Mildred S. Dresselhaus Department of Chemistry Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge Massachusetts 02139 USA Instituto de Investigaciones en Materiales Universidad Nacional Autónoma de México Apartado Postal 70-360 CU Coyoacán Ciudad de México 04510 México Department of Chemical and Biomedical Engineering FAMU-FSU Joint College of Engineering Tallahassee Florida 32310 USA Department of Physics and Department of Scientific Computing Materials Science and Engineering High Performance Material Institute Condensed Matter Theory National High Magnetic Field Laboratory Florida State University Tallahassee Florida 32310 USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA

This paper is a contribution to the Physical Review Applied collection in memory of Mildred S. Dresselhaus.

关键词： Electron-phonon coupling Electronic materials 2-dimensional systems Elemental semiconductors Nanoclusters Nanoribbon Silicene Density functional theory

来源：评论

学校读者我要写书评

暂无评论

Quantum nanophotonics in two-dimensional materials

arXiv

引用

arXiv 2021年

作者： Reserbat-Plantey, Antoine Epstein, Itai Torre, Iacopo Costa, Antonio T. Gonçalves, P.A.D. Mortensen, N. Asger Polini, Marco Song, Justin C.W. Peres, Nuno M.R. Koppens, Frank H.L. 08860 Spain Department of Physical Electronics School of Electrical Engineering Tel Aviv University Tel Aviv6997801 Israel International Iberian Nanotechnology Laboratory Braga4715-330 Portugal Center for Nano Optics University of Southern Denmark Odense MDK-5230 Denmark Danish Institute for Advanced Study University of Southern Denmark Odense MDK-5230 Denmark Center for Nanostructured Graphene Technical University of Denmark LyngbyDK-2800 Kgs Denmark Dipartimento di Fisica dell'Università di Pisa Largo Bruno Pontecorvo 3 PisaI-56127 Italy School of Physics and Astronomy University of Manchester Oxford Road ManchesterM13 9PL United Kingdom Istituto Italiano di Tecnologia Graphene Labs Via Morego 30 GenovaI-16163 Italy Division of Physics and Applied Physics Nanyang Technological University Singapore637371 Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore138632 Singapore Centro de Física das Universidades Do Minho e Porto and Departamento de Fisica and QuantaLab Universidade Do Minho Campus de Gualtar Braga4710-057 Portugal ICREA - Institució Catalana de Recerca i Estudis Avançats Barcelona08000 Spain

The field of 2D materials-based nanophotonics has been growing at a rapid pace, triggered by the ability to design nanophotonic systems with in-situ control1, unprecedented degrees of freedom, and to build material heterostructures from bottom up with atomic precision2. A wide palette of polaritonic classes3-6 have been identified, comprising ultra-confined optical fields, even approaching characteristic length-scales of a single atom7. These advances have been a real boost for the emerging field of quantum nanophotonics, where the quantum mechanical nature of the electrons and/or polaritons and their interactions become relevant. Examples include, quantum nonlocal effects8-11, ultrastrong light-matter interactions11-16, Cherenkov radiation13,17,18, access to forbidden transitions11, hydrodynamic effects19-21, single-plasmon nonlinearities22,23, polaritonic quantization24, topological effects etc.3,4. In addition to these intrinsic quantum nanophotonic phenomena, the 2D material system can also be used as a sensitive probe for the quantum properties of the material that carries the nanophotonics modes, or quantum materials in its vicinity. Here, polaritons act as a probe for otherwise invisible excitations, e.g. in superconductors25, or as a new tool to monitor the existence of Berry curvature in topological materials and superlattice effects in twisted 2D materials. In this article, we present an overview of the emergent field of 2D-material quantum nanophotonics, and provide a future perspective on the prospects of both fundamental emergent phenomena and emergent quantum technologies, such as quantum sensing, single-photon sources and quantum emitters manipulation. We address four main implications (cf. Figure 1): i) quantum sensing, featuring polaritons to probe superconductivity and explore new electronic transport hydrodynamic behaviours, ii) quantum technologies harnessing single-photon generation, manipulation and detection using 2D materials, iii) polariton

关键词： Particle beams

来源：评论

学校读者我要写书评

暂无评论

Not just privacy: Improving performance of private deep learning in mobile cloud

arXiv

引用

arXiv 2018年

作者： Wang, Ji Zhang, Jianguo Bao, Weidong Zhu, Xiaomin Cao, Bokai Yu, Philip S. College of Systems Engineering National University of Defense Technology Changsha China Department of Computer Science University of Illinois at Chicago Chicago United States College of Systems Engineering State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Facebook Inc. Menlo Park United States Department of Computer Science University of Illinois at Chicago Chicago United States Institute for Data Science Tsinghua University Beijing China

The increasing demand for on-device deep learning services calls for a highly efficient manner to deploy deep neural networks (DNNs) on mobile devices with limited capacity. The cloud-based solution is a promising approach to enabling deep learning applications on mobile devices where the large portions of a DNN are offloaded to the cloud. However, revealing data to the cloud leads to potential privacy risk. To benefit from the cloud data center without the privacy risk, we design, evaluate, and implement a cloud-based framework Arden which partitions the DNN across mobile devices and cloud data centers. A simple data transformation is performed on the mobile device, while the resource-hungry training and the complex inference rely on the cloud data center. To protect the sensitive information, a lightweight privacy-preserving mechanism consisting of arbitrary data nullification and random noise addition is introduced, which provides strong privacy guarantee. A rigorous privacy budget analysis is given. Nonetheless, the private perturbation to the original data inevitably has a negative impact on the performance of further inference on the cloud side. To mitigate this influence, we propose a noisy training method to enhance the cloud-side network robustness to perturbed data. Through the sophisticated design, Arden can not only preserve privacy but also improve the inference performance. To validate the proposed Arden, a series of experiments based on three image datasets and a real mobile application are conducted. The experimental results demonstrate the effectiveness of Arden. Finally, we implement Arden on a demo system to verify its practicality. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Preface

引用

CEUR Workshop Proceedings 2022年 3304卷

作者： Jia, Weijia Yin, Jian Hu, Shaolin Peng, Shaoliang Niu, Shaozhang Srinivasa Rao, P.C. Lu, Yao Mirsaeidi, Sohrab Cao, Bin Wu, Yilin Wang, Xingbo Subramaniyam, Kannimuthu Boddu, Raja Sarath Kumar Li, Zhonghua Tao, Qian Zhang, Lei Li, Yi Ding, Deqing Wang, Dahan Zhang, Ziyan AlShawabkeh, Mahmoud Aslam, Muhammad Dib, Omar Sahibuddin, Shamsul Bin Wagh, Sanjeev J. Pardalos, Panos M. Al-Sammarraie, Najeeb Abbas Liu, Linfeng Kong, Jin-Heung Borrego, Carlos Tahir, Sabeen Wu, Zhiheng Li, Jiongcheng Xu, Yong Xie, Zhi Wang, Jiahai Cai, Hongmin Yang, Yuedong Qin, Xiaolin Beijing Normal University Zhuhai China Sun Yat-sen University China Guangdong University of Petrochemical Technology China Hunan University China Beijing University of Posts and Telecommunications China India Beijing Jiaotong University China Hebei University of Technology China Guangdong University of Education China Foshan University China Karpagam College of Engineering India Lenora College of Engineerin India Yat-sen University Guangdong High Performance Computing Society China South China University of Technology China Henan University China Wenzhou University China National University of Defense Technology China Xiamen University of Technology China Hainan Tropical Ocean University China Guangxi Normal University for Nationalities China Wuhan University China Wenzhou-Kean University China School of Software Engineering Universiti Teknologi Malaysia Information Technology Government College of Engineering Karad India Department of Industrial & Systems Engineering University of Florida United States Al-Madinah International University Faculty of Computer and Information Technology Malaysia School of Computer Science and Technology Nanjing University of Posts and Telecommunications China School of Computer and Information Engineering Kwangwoon University Korea Republic of Departament Enginyeria of Information Comunicacions Autonomous University of Barcelona Spain Information Technology Department King AbdulAziz University Jeddah Saudi Arabia Institute of Manufacturing GDAS China Guangdong Planning and Designing Institute of Telecommunications Co. Ltd China Guangzhou Institutes of Biomedicine and Health Chinese Academy of Sciences China Cheng Du Information Technology of Chinese Academy of Sciences Co. Ltd China

来源：评论

学校读者我要写书评

暂无评论

Private model compression via knowledge distillation

arXiv

引用

arXiv 2018年

作者： Wang, Ji Bao, Weidong Sun, Lichao Zhu, Xiaomin Cao, Bokai Yu, Philip S. College of Systems Engineering National University of Defense Technology Changsha China Department of Computer Science University of Illinois at Chicago Chicago United States State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Facebook Inc. Menlo Park United States Institute for Data Science Tsinghua University Beijing China

The soaring demand for intelligent mobile applications calls for deploying powerful deep neural networks (DNNs) on mobile devices. However, the outstanding performance of DNNs notoriously relies on increasingly complex models, which in turn is associated with an increase in computational expense far surpassing mobile devices' capacity. What is worse, app service providers need to collect and utilize a large volume of users' data, which contain sensitive information, to build the sophisticated DNN models. Directly deploying these models on public mobile devices presents prohibitive privacy risk. To benefit from the on-device deep learning without the capacity and privacy concerns, we design a private model compression framework RONA. Following the knowledge distillation paradigm, we jointly use hint learning, distillation learning, and self learning to train a compact and fast neural network. The knowledge distilled from the cumbersome model is adaptively bounded and carefully perturbed to enforce differential privacy. We further propose an elegant query sample selection method to reduce the number of queries and control the privacy loss. A series of empirical evaluations as well as the implementation on an Android mobile device show that RONA can not only compress cumbersome models efficiently but also provide a strong privacy guarantee. For example, on SVHN, when a meaningful (9:83;10-6)-differential privacy is guaranteed, the compact model trained by RONA can obtain 20× compression ratio and 19× speed-up with merely 0.97% accuracy loss. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：