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arXiv 2017年

作者： Chi, Zhenhua Chen, Xuliang An, Chao Yang, Liuxiang Zhao, Jinggeng Feng, Zili Zhou, Yonghui Zhou, Ying Gu, Chuanchuan Zhang, Bowen Yuan, Yifang Kenney-Benson, Curtis Yang, Wenge Wu, Gang Wan, Xiangang Shi, Youguo Yang, Xiaoping Yang, Zhaorong Key Laboratory of Materials Physics Institute of Solid State Physics Chinese Academy of Sciences Hefei230031 China Anhui Province Key Laboratory of Condensed Matter Physics at Extreme Conditions High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China Beijing100094 China Department of Physics Harbin Institute of Technology Harbin150080 China Natural Science Research Center Academy of Fundamental and Interdisciplinary Sciences Harbin Institute of Technology Harbin150080 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100190 China Department of Physics and Engineering Zhengzhou University Zhengzhou450052 China HPCAT Geophysical Laboratory Carnegie Institution of Washington ArgonneIL60439 United States Shanghai201203 China Institute of High Performance Computing 1 Fusionopolis Way 16-16 Connexis Singapore138632 Singapore National Laboratory of Solid State Microstructures College of Physics Nanjing University Nanjing210093 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China

Topological semimetal, a novel state of quantum matter hosting exotic emergent quantum phenomena dictated by the non-trivial band topology, has emerged as a new frontier in condensed-matter physics. Very recently, a coexistence of triply degenerate points of band crossing and Weyl points near the Fermi level was theoretically predicted and immediately experimentally verified in single crystalline molybdenum phosphide (MoP). Here we show in this material the high-pressure electronic transport and synchrotron X-ray diffraction (XRD) measurements, combined with density functional theory (DFT) calculations. We report the emergence of pressure-induced superconductivity in MoP with a critical temperature Tc of about 2 K at 27.6 GPa, rising to 3.7 K at the highest pressure of 95.0 GPa studied. No structural phase transitions is detected up to 60.6 GPa from the XRD. Meanwhile, the Weyl points and triply degenerate points topologically protected by the crystal symmetry are retained at high pressure as revealed by our DFT calculations. The coexistence of three-component fermion and superconductivity in heavily pressurized MoP offers an excellent platform to study the interplay between topological phase of matter and superconductivity. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum theory

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Stretchable Solar Cells: Stretchable GaAs Photovoltaics with Designs That Enable high Areal Coverage (Adv. Mater. 8/2011)

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Advanced Materials 2011年第8期23卷

作者： Jongho Lee Jian Wu Mingxing Shi Jongseung Yoon Sang‐Il Park Ming Li Zhuangjian Liu Yonggang Huang John A. Rogers Department of Materials Science and Engineering Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana Illinois 61801 USA Department of Civil and Environmental Engineering Northwestern University Evanston IL 60208 USA Institute of High Performance Computing Singapore 138631 Singapore Department of Engineering Mechanics Dalian University of Technology Dalian 116024 China Departments of Civil and Environmental Engineering and Mechanical Engineering Northwestern University Evanston Illinois 60208 USA Department of Materials Science and Engineering Chemistry Mechanical Science and Engineering Electrical and Computer Engineering Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana Illinois 61801 USA

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Organ‐Mounted Electronics: An Universal and Easy‐to‐Use Model for the Pressure of Arbitrary‐Shape 3D Multifunctional Integumentary Cardiac Membranes (Adv. Healthcare Mater. 8/2016)

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Advanced Healthcare Materials 2016年第8期5卷

作者： Yewang Su Zhuangjian Liu Lizhi Xu State Key Laboratory of Nonlinear Mechanics Institute of Mechanics Chinese Academy of Sciences Beijing 100190 China Department of Civil and Environmental Engineering Northwestern University Evanston IL 60208 USA Institute of High Performance Computing A*Star 138632 Singapore Department of Chemical Engineering and Department of Materials Science and Engineering University of Michigan Ann Arbor MI 48109 USA Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana IL 61801 USA

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Generating ultradense pair beams using 400 GeV/c protons

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Physical Review Research 2021年第2期3卷 023103-023103页

作者： C. D. Arrowsmith N. Shukla N. Charitonidis R. Boni H. Chen T. Davenne A. Dyson D. H. Froula J. T. Gudmundsson B. T. Huffman Y. Kadi B. Reville S. Richardson S. Sarkar J. L. Shaw L. O. Silva P. Simon R. M. G. M. Trines R. Bingham G. Gregori Department of Physics University of Oxford Parks Road Oxford OX1 3PU United Kingdom CINECA High-Performance Computing Department Via Magnanelli 6/3 40033 Casalecchio di Reno - Bologna Italy European Organization for Nuclear Research (CERN) CH-1211 Geneva 23 Switzerland University of Rochester Laboratory for Laser Energetics Rochester New York 14623 USA Lawrence Livermore National Laboratory 7000 East Avenue Livermore California 94550 USA Rutherford Appleton Laboratory Chilton Didcot OX11 0QX United Kingdom Science Institute University of Iceland Dunhaga 3 IS-107 Reykjavik Iceland Department of Space and Plasma Physics School of Electrical Engineering and Computer Science KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Max-Planck-Institut für Kernphysik Saupfercheckweg 1 D-69117 Heidelberg Germany Atomic Weapons Establishment Aldermaston Reading Berkshire RG7 4PR United Kingdom GoLP/Instituto de Plasmas e Fusão Nuclear Instituto Superior Técnico Universidade de Lisboa 1049-001 Lisboa Portugal Department of Physics University of Strathclyde Glasgow G4 0NG United Kingdom

An experimental scheme is presented for generating low-divergence, ultradense, relativistic, electron-positron beams using 400 GeV/c protons available at facilities such as HiRadMat and AWAKE at CERN. Preliminary Monte Carlo and particle-in-cell simulations demonstrate the possibility of generating beams containing 1013–1014 electron-positron pairs at sufficiently high densities to drive collisionless beam-plasma instabilities, which are expected to play an important role in magnetic field generation and the related radiation signatures of relativistic astrophysical phenomena. The pair beams are quasineutral, with size exceeding several skin depths in all dimensions, allowing the examination of the effect of competition between transverse and longitudinal instability modes on the growth of magnetic fields. Furthermore, the presented scheme allows for the possibility of controlling the relative density of hadrons to electron-positron pairs in the beam, making it possible to explore the parameter spaces for different astrophysical environments.

关键词： Beam instabilities Cosmic ray acceleration Cosmic ray composition & spectra Cosmic ray sources Gamma ray astronomy Gamma ray bursts high-energy-density plasmas laboratory studies of space & astrophysical plasmas Optical, UV, & IR astronomy Plasma instabilities Plasma-beam interactions Relativistic multiple-particle dynamics

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Preparing a commercial quantum key distribution system for certification against implementation loopholes

arXiv

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arXiv 2023年

作者： Makarov, Vadim Abrikosov, Alexey Chaiwongkhot, Poompong Fedorov, Aleksey K. Huang, Anqi Kiktenko, Evgeny Petrov, Mikhail Ponosova, Anastasiya Ruzhitskaya, Daria Tayduganov, Andrey Trefilov, Daniil Zaitsev, Konstantin Russian Quantum Center Skolkovo Moscow121205 Russia Vigo Quantum Communication Center University of Vigo VigoE-36310 Spain NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia Department of Physics Faculty of Science Mahidol University Bangkok10400 Thailand Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Bangkok10110 Thailand QRate Skolkovo Moscow143026 Russia Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Steklov Mathematical Institute Russian Academy of Sciences Moscow119991 Russia atlanTTic Research Center University of Vigo VigoE-36310 Spain School of Telecommunication Engineering Department of Signal Theory and Communications University of Vigo VigoE-36310 Spain National Research University Higher School of Economics Moscow101000 Russia

A commercial quantum key distribution (QKD) system needs to be formally certified to enable its wide deployment. The certification should include the system’s robustness against known implementation loopholes and attacks that exploit them. Here we ready a fiber-optic QKD system for this procedure. The system has a prepare-and-measure scheme with decoy-state BB84 protocol, polarisation encoding, qubit source rate of 312.5 MHz, and is manufactured by QRate. We detail its hardware and post-processing. We analyse the hardware for known implementation loopholes, search for possible new loopholes, and discuss countermeasures. We then amend the system design to address the highest-risk loopholes identified. We also work out technical requirements on the certification lab and outline its possible structure. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum cryptography

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Correction to: A digital rights management system based on a scalable blockchain

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Peer-to-Peer Networking and Applications 2021年第4期14卷 1869-1869页

作者： Garba, Abba Dwivedi, Ashutosh Dhar Kamal, Mohsin Srivastava, Gautam Tariq, Muhammad Hasan, M. Anwar Chen, Zhong Key Laboratory of High Confidence Software Technologies Peking University MoE Beijing China Department of Computer Science and Technology EECS Peking University Beijing China Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark Department of Electrical Engineering National University of Computer and Emerging Sciences Peshawar Pakistan Department of Mathematics and Computer Science Brandon University Brandon Canada Research Center for Interneural Computing China Medical University Taichung Republic of China Princeton University Princeton USA Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

A Correction to this paper has been published: https://***/10.1007/s12083-021-01098-2

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Randomised benchmarking for characterizing and forecasting correlated processes

arXiv

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arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Roadmap on Perovskite Light-Emitting Diodes

arXiv

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arXiv 2023年

作者： Chen, Ziming Hoye, Robert L.Z. Yip, Hin-Lap Fiuza-Maneiro, Nadesh López-Fernández, Iago Otero-Martínez, Clara Polavarapu, Lakshminarayana Mondal, Navendu Mirabelli, Alessandro Anaya, Miguel Stranks, Samuel D. Liu, Hui Shi, Guangyi Xiao, Zhengguo Kim, Nakyung Kim, Yunna Shin, Byungha Shi, Jinquan Liu, Mengxia Zhang, Qianpeng Fan, Zhiyong Loy, James C. Zhao, Lianfeng Rand, Barry P. Arfin, Habibul Saikia, Sajid Nag, Angshuman Zou, Chen Lin, Lih Y. Xiang, Hengyang Zeng, Haibo Liu, Denghui Su, Shi-Jian Wang, Chenhui Zhong, Haizheng Xuan, Tong-Tong Xie, Rong-Jun Bao, Chunxiong Gao, Feng Gao, Xiang Qin, Chuanjiang Kim, Young-Hoon Beard, Matthew C. Department of Chemistry Centre for Processible Electronics Imperial College London LondonW12 0BZ United Kingdom Inorganic Chemistry Laboratory Department of Chemistry University of Oxford South Parks Road OxfordOX1 3QR United Kingdom Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Materials Science and Engineering City University of Hong Kong Hong Kong Hong Kong School of Energy and Environment City University of Hong Kong Hong Kong Hong Kong CINBIO Universidade de Vigo Materials Chemistry and Physics Group Department of Physical Chemistry Campus Universitario As Lagoas Marcosende Vigo36310 Spain Department of Chemical Engineering and Biotechnology University of Cambridge CambridgeCB3 0AS United Kingdom Department of Physics CAS Key Laboratory of Strongly Coupled Quantum Matter Physics University of Science and Technology of China Anhui Hefei230026 China Daejeon34141 Korea Republic of Department of Electrical Engineering Yale University New HavenCT06511 United States Energy Sciences Institute Yale University West HavenCT06516 United States Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Hong Kong Department of Physics Princeton University PrincetonNJ08544 United States Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States Andlinger Center for Energy and the Environment Princeton University PrincetonNJ08544 United States Pune411008 India Zhejiang University Zhejiang Hangzhou310058 China University of Washington SeattleWA98195 United States MIIT Key Laboratory of Advanced Display Materials and Devices Institute of Optoelectronics & Nanomaterials College of Materials Science and Engineering Nanjing University of Science and Technology Nanjing210094 China State Key Laboratory of Luminescent Materials and Devices Institute of Polymer Opto

In recent years, the field of metal-halide perovskite emitters has rapidly emerged as a new community in solid-state lighting. Their exceptional optoelectronic properties have contributed to the rapid rise in external... 详细信息

关键词： Perovskite

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Machine learning and high-throughput robust design of P3HT-CNT composite thin films for high electrical conductivity

arXiv

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arXiv 2020年

作者： Bash, Daniil Yongqiang, Cai Chellappan, Vijila Liang, Wong Swee Yang, Xu Kumar, Pawan Da, Tan Jin Abutaha, Anas Cheng, Jayce Fun, Lim Yee Tian, Siyu Ren, Danny Zekun Mekki-Barrada, Flore Wong, Wai Kuan Kumar, Jatin Khan, Saif Qianxiao, Li Buonassisi, Tonio Hippalgaonkar, Kedar Institute of Materials Research & Engineering Agency for Science Technology and Research 2 Fusionopolis Way 138634 Singapore Department of Chemistry National University of Singapore 3 Science Drive 3 117543 Singapore Department of Mathematics National University of Singapore 21 Lower Kent Ridge Rd 119077 Singapore School of Mathematical Sciences Laboratory of Mathematics and Complex Systems MOE Beijing Normal University Beijing100875 China University Hall Tan Chin Tuan Wing Level 04 #04-02 21 Lower Kent Ridge Road 119077 Singapore Qatar Environment and Energy Research Institute Hamad Bin Khalifa University Qatar Foundation Doha34110 Qatar Singapore-MIT Alliance for Research and Technology SMART 138602 Singapore Department of Chemical and Biomolecular Engineering National University of Singapore 117585 Singapore Institute of High Performance Computing 1 Fusionopolis Way #16-16 Connexis138632 Singapore Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering Nanyang Technological University Singapore639798 Singapore

Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that machine learning, combined with multi-labeled datasets, can additionally be used for scientific understanding and hypothesis testing. We introduce an automated flow system with high-throughput drop-casting for thin film preparation, followed by fast characterization of optical and electrical properties, with the capability to complete one cycle of learning of fully labeled ~160 samples in a single day. We combine regio-regular poly-3-hexylthiophene with various carbon nanotubes to achieve electrical conductivities as high as 1200 S/cm. Interestingly, a non-intuitive local optimum emerges when 10% of double-walled carbon nanotubes are added with long single wall carbon nanotubes, where the conductivity is seen to be as high as 700 S/cm, which we subsequently explain with high fidelity optical characterization. Employing dataset resampling strategies and graph-based regressions allows us to account for experimental cost and uncertainty estimation of correlated multi-outputs, and supports the proving of the hypothesis linking charge delocalization to electrical conductivity. We therefore present a robust machine-learning driven high-throughput experimental scheme that can be applied to optimize and understand properties of composites, or hybrid organic-inorganic materials. © 2020, CC-BY.

关键词： Thin films

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Semantic interoperability and characterization of data provenance in computational molecular engineering

arXiv

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arXiv 2019年

作者： Horsch, Martin Thomas Niethammer, Christoph Boccardo, Gianluca Carbone, Paola Chiacchiera, Silvia Chiricotto, Mara Elliott, Joshua D. Lobaskin, Vladimir Neumann, Philipp Schiffels, Peter Seaton, Michael A. Todorov, Ilian T. Vrabec, Jadran Cavalcanti, Welchy Leite STFC Daresbury Laboratory UK Research and Innovation Keckwick Ln Daresbury CheshireWA4 4AD United Kingdom High Performance Computing Center Stuttgart Nobelstr. 19 Stuttgart70569 Germany Department of Applied Science and Technology Institute of Chemical Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 Torino10129 Italy School of Chemical Engineering and Analytical Science University of Manchester Oxford Rd ManchesterM13 9PL United Kingdom School of Physics University College Dublin Dublin 4 Ireland Department of Informatics Universität Hamburg Bundesstr. 45a Hamburg20146 Germany Fraunhofer Institute for Manufacturing Technology and Advanced Materials Wiener Str. 12 Bremen28359 Germany Thermodynamics and Process Engineering Technische Universität Berlin Ernst-Reuter-Platz 1 Berlin10587 Germany

By introducing a common representational system for metadata that describe the employed simulation workflows, diverse sources of data and platforms in computational molecular engineering, such as workflow management systems, can become interoperable at the semantic level. To achieve semantic interoperability, the present work introduces two ontologies that provide a formal specification of the entities occurring in a simulation workflow and the relations between them: The software ontology VISO is developed to represent software packages and their features, and OSMO, an ontology for simulation, modelling, and optimization, is introduced on the basis of MODA, a previously developed semi-intuitive graph notation for workflows in materials modelling. As a proof of concept, OSMO is employed to describe a leading-edge application scenario of the TaLPas workflow management system. Copyright © 2019, The Authors. All rights reserved.

关键词： Ontology

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