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Architectures for multinode Superconducting Quantum computers

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arXiv 2022年

作者： Ang, James Carini, Gabriella Chen, Yanzhu Chuang, Isaac Demarco, michael Austin Economou, Sophia E. Eickbusch, Alec Faraon, Andrei Fu, Kai-mei Girvin, Steven m. Hatridge, michael Houck, Andrew Hilaire, Paul Krsulich, Kevin Li, Ang Liu, Chenxu Liu, Yuan martonosi, margaret mcKay, David C. misewich, James Ritter, mark Schoelkopf, Robert J. Stein, Samuel A. Sussman, Sara Tang, Hong X. Tang, Wei Tomesh, Teague Tubman, Norm m. Wang, Chen Wiebe, Nathan Yao, Yong-Xin Yost, Dillon C. Zhou, Yiyu Pacific Northwest National Laboratory RichlandWA99354 United States Brookhaven National Laboratory UptonNY11973 United States Department of Physics Virginia Tech BlacksburgVA24061 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Yale Quantum Institute Yale University New HavenCT06511 United States Departments of Applied Physics and Physics Yale University New HavenCT06520 United States Laboratory of Applied Physics California Institute of Technology PasadenaCA United States Department of Physics University of Washington SeattleWA98195 United States Department of Physics and Astronomy University of Pittsburgh PittsburghPA15260 United States Department of Electrical Engineering Princeton University Princeton United States IBM Quantum IBM T.J. Watson Research Center Yorktown HeightsNY10598 United States Department of Computer Science Princeton University PrincetonNJ08544 United States Departments of Electrical Engineering Yale University New HavenCT06511 United States Exploration Technology Directorate NASA Ames Research Center Moffett FieldCA94035 United States Department of Physics University of Massachusetts-Amherst AmherstMA01003 United States Department of Computer Science University of Toronto TorontoONM5S1J7 Canada Ames National Laboratory Iowa State University AmesIA50011 United States KBR 601 Jefferson St. HoustonTX77002 United States

many proposals to scale quantum.technology rely on modular or distributed designs where individual quantum processors, called nodes, are linked together to form one large multinode quantum computer (mNQC). One scalable method to construct an mNQC is using superconducting quantum systems with optical interconnects. However, a key limiting factor of these machines will be internode gates, which may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require a range of techniques, including improvements in entanglement generation, the use of entanglement distillation, and optimized software and compilers, and it remains unclear how improvements to these components interact to affect overall system performance, what performance from each is required, or even how to quantify the performance of a component. In this paper, we employ a ‘co-design’ inspired approach to quantify overall mNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. In the particular case of superconducting mNQCs with microwave-to-optical interconnects, we uncover a tradeoff between entanglement generation and distillation that threatens to degrade mNQC performance. We show how to navigate this tradeoff in the context of algorithm performance, layout how compilers and software should optimize the balance between local gates and internode gates, and discuss when noisy quantum internode links have an advantage over purely classical links. Using these results, we introduce a research roadmap for the realization of early mNQCs, which illustrates potential improvements to the hardware and software of mNQCs and outlines criteria for evaluating the improvement landscape, from progress in entanglement generation to the use of quantum memory in entanglement distillation and dedicated algorithms such as distributed quantum phase estimation. While we focus on superconducting

关键词： Distillation

CEPC technical Design Report

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Radiation Detection technology and methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert maarten Boonekamp marcello Borri Angelo Bosotti Vincent Boudry mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai Wujun Cai Yijian Cai Yizhou Cai Yuchen Cai Haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen mali Chen mingjun Chen mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen Xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho ming-Chung Chu Xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De maria Nicola De Filippis Christophe De La Taille Francesca De mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang University HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China University of Geosciences Beijing China University of Geosciences WuhanHubei China University of Mining and Technology XuzhouJiangsu China West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing Chulalongkorn University Bangkok City University of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China University Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 mW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 mW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

Extraction of Relationship Between Characters in Narrative Summaries

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Extraction of Relationship Between Characters in Narrative S...

International Conference on Emerging Trends and Innovations In engineering And technological Research (ICETIETR)

作者： m Nijila m T Kala M. Tech Computational Linguistics Computer Science & Engineering Department Govt. Engineering College Palakkad India

ISBN: (纸本)9781538657454

Distinguishing relationships between people plays a vital role in understanding of narratives. We can experience different kinds of relationships like family, friendship, hostility, romantic love, etc. We know that Narratives are rich reflections of such relationships. Also extraction of relationship between characters is more helpful in understanding the person's actions, goals and behavior. In actual case relationships between people changes over time. So considering the dynamic nature of relationships will provide a better understanding of narratives. Existing research on analysis of people's relationships in the text has been limited Two simple schemes that use traditional machine learning algorithms. Relevant to this context, this paper proposes a system for extracting interpersonal relationships using deep learning concept convolutional neural network (CNN). The proposed approach produces a better performance over the competitive baseline model.

关键词： Feature extraction Convolutional neural networks Social network services motion pictures market research technological innovation

Detection and Analysis of Human Emotions through Voice and Speech Pattern Processing

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arXiv 2017年

作者： Dasgupta, Poorna Banerjee M.Tech Computer Science and Engineering Nirma Institute of Technology AhmedabadGujarat India

The ability to modulate vocal sounds and generate speech is one of the features which set humans apart from other living beings. The human voice can be characterized by several attributes such as pitch, timbre, loudness, and vocal tone. It has often been observed that humans express their emotions by varying different vocal attributes during speech generation. Hence, deduction of human emotions through voice and speech analysis has a practical plausibility and could potentially be beneficial for improving human conversational and persuasion skills. This paper presents an algorithmic approach for detection and analysis of human emotions with the help of voice and speech processing. The proposed approach has been developed with the objective of incorporation with futuristic artificial intelligence systems for improving human-computer interactions. Copyright © 2017, The Authors. All rights reserved.

关键词： Speech processing

Reconfigurable Network-on-Chip for 3D Neural Network Accelerators 18

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Reconfigurable Network-on-Chip for 3D Neural Network Acceler...

International Symposium on Networks-on-Chip (NOCS)

作者： Arash Firuzan mehdi modarressi masoud Daneshtalab midia Reshadi Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran School of Electrical and Computer Engineering IPM School of Computer Science Tehran Iran Intelligent Future Tech. Mälardalen University Sweden

ISBN: (纸本)9781538648933

Parallel hardware accelerators for large-scale neural networks typically consist of several processing nodes, arranged as a multi- or many-core system-on-chip, connected by a network-on-chip (NoC). Recent proposals also benefit from the emerging 3D memory-on-logic architectures to provide sufficient bandwidth for neural networks. Handling the heavy traffic between neurons and memory and also the multicast-based inter-neuron traffic, which often varies over time, is the most challenging design consideration for the networks-on-chip in such accelerators. To address these issues, a reconfigurable network-on-chip architecture for 3D memory-on-logic neural network accelerators is presented in this paper. The reconfigurable NoC can adapt its topology to the on-chip traffic patterns. It can be also configured as a tree-like structure to support multicast-based neuron-to-neuron and memory-to-neuron traffic of neural networks. The evaluation results show that the proposed architecture can better manage the multicast-based traffic of neural networks than some state-of-the-art topologies and considerably increase throughput and power efficiency.

关键词： Network topology Topology Neurons Biological neural networks computer architecture Switches

Energy Conversion: Radio Frequency Driven Heating of Catalytic Reactors for Portable Green Chemistry (Adv. Sustainable Syst. 11/2020)

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Advanced Sustainable Systems 2020年第11期4卷

作者： Nutan Patil Naveen K. mishra mohammad A. Saed micah J. Green Benjamin A. Wilhite Artie McFerrin Department of Chemical Engineering Texas A&M University 3122 TAMU College Station TX 77843–3122 USA Department of Electrical and Computer Engineering Texas Tech Lubbock TX 79409 USA Department of Material Science and Engineering Artie McFerrin Department of Chemical Engineering Texas A&M University 3122 TAMU College Station TX 77843–3122 USA

Effect of graphene, SiC and graphite addition on hardness, microstructure and electrical conductivity of microwave sintered copper mmCs fabricated by powder metallurgy route

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Journal of Physics: Conference Series 2019年第1期1355卷

作者： Ayyappadas, C Shanu, O S Vijayan, Abhilash mohammed, Irfan A Vishnu, V Shamnadh, m Assistant professor Department of Mechanical Engineering NSS College of Engineering Palakkad Kerala-678008 India M.Tech student Computer Integrated Manufacturing Department of Mechanical Engineering TKM College of Engineering Kerala-691005 India Assistant professor Computer Integrated Manufacturing Department of Mechanical Engineering TKM College of Engineering Kollam Kerala-691005 India

Copper mmCs reinforced with graphene, SiC and graphite flakes with varying mass fractions of 2.5, 5, and 7.5 wt% SiC, 2.5, 5, 7.5, and 10 wt% graphite and 0.2, 0.4, 0.6 and 0.8wt% graphene particles were fabricated through powder metallurgy route. The powder mixtures were blended and then compacted under a uniaxial pressure of 400mPa for both Cu-SiC and Cu-Gr composites and 600mpa for Cu-Gn composites. Green compacts were sintered by microwave (mW) sintering process. mW sintering was performed at 950°C in open atmosphere with a heating rate of 25°C/min for all composites. Densification parameter (DP) was determined for all mmCs and a reduction in DP values were observed with an increase in weight percentage of reinforcement particles as a result of increase in porosity. Higher mass fractions of reinforcement particles in the Cu matrix tend to offer a diffusion barrier to copper atoms. micro-structural analysis was performed using Optical and scanning electron microscope which revealed a homogeneous microstructure of all composites at low mass fractions of Sic, graphite and graphene. In order to detect the presence of any oxides of Cu and other elements, EDS analysis was carried out. Hardness data showed an increasing trend for Cu-SiC and Cu-Gn composites and a declining trend for Cu-Gr composites. Porosity has a significant effect on the electrical conductivity values of the composites.

关键词：

Building a quantum engineering undergraduate program

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arXiv 2021年

作者： Asfaw, Abraham Blais, Alexandre Brown, Kenneth R. Candelaria, Jonathan Cantwell, Christopher Carr, Lincoln D. Combes, Joshua Debroy, Dripto m. Donohue, John m. Economou, Sophia E. Edwards, Emily Fox, michael F.J. Girvin, Steven m. Ho, Alan Hurst, Hilary m. Jacob, Zubin Johnson, Blake R. Johnston-Halperin, Ezekiel Joynt, Robert Kapit, Eliot Klein-Seetharaman, Judith Laforest, martin Lewandowski, H.J. Lynn, Theresa W. mcRae, Corey Rae H. merzbacher, Celia michalakis, Spyridon Narang, Prineha Oliver, William D. Palsberg, Jens Pappas, David P. Raymer, michael G. Reilly, David J. Saffman, mark Searles, Thomas A. Shapiro, Jeffrey H. Singh, Chandralekha IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY United States Institut Quantique Département de Physique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada The Duke Quantum Center Department of Physics Department of Electrical and Computer Engineering Department of Chemistry Duke University DurhamNC27708 United States SystemX Program Department of Electrical Engineering Stanford University StanfordCA94305 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States The Quantum Engineering Program Department of Physics Colorado School of Mines GoldenCO80401 United States The Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States The Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada The Department of Physics Virginia Tech BlacksburgVA24061 United States The IQUIST University of Illinois Urbana-Champaign UrbanaIL61801 United States JILA National Institute of Standards and Technology The University of Colorado BoulderCO80309 United States Department of Physics University of Colorado Boulder BoulderCO80309 United States The Department of Physics Imperial College London Prince Consort Road LondonSW7 2AZ United Kingdom The Yale Quantum Institute Department of Physics Yale University New HavenCT06520 United States Google Research VeniceCA90291 United States The Department of Physics & Astronomy San José State University San JoséCA95192 United States The School of Electrical and Computer Engineering Purdue University Indiana West Lafayatte47907 United States The Department of Physics The Ohio State University ColumbusOH43210 United States The Department of Physics University of Wisconsin-Madison 1150 University Avenue MadisonWI53706 United States The Quantitative Biosciences and Engineering

The rapidly growing quantum information science and engineering (QISE) industry will require both quantum-aware and quantum-proficient engineers at the bachelor's level. We provide a roadmap for building a quantum engineering education program to satisfy this need. For quantum-aware engineers, we describe how to design a first quantum engineering course accessible to all STEm students. For the education and training of quantum-proficient engineers, we detail both a quantum engineering minor accessible to all STEm majors, and a quantum track directly integrated into individual engineering majors. We propose that such programs typically require only three or four newly developed courses that complement existing engineering and science classes available on most larger campuses. We describe a conceptual quantum information science course for implementation at any post-secondary institution, including community colleges and military schools. QISE presents extraordinary opportunities to work towards rectifying issues of inclusivity and equity that continue to be pervasive within engineering. We present a plan to do so and describe how quantum engineering education presents an excellent set of education research opportunities. Finally, we outline a hands-on training plan on quantum hardware, a key component of any quantum engineering program, with a variety of technologies including optics, atoms and ions, cryogenic and solid-state technologies, nanofabrication, and control and readout electronics. Our recommendations provide a flexible framework that can be tailored for academic institutions ranging from teaching and undergraduate-focused two- and four-year colleges to research-intensive universities. © 2021, CC BY.

关键词： engineering education

Operational Research: methods and Applications

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arXiv 2023年

作者： Petropoulos, Fotios Laporte, Gilbert Aktas, Emel Alumur, Sibel A. Archetti, Claudia Ayhan, Hayriye Battarra, maria Bennell, Julia A. Bourjolly, Jean-marie Boylan, John E. Breton, michèle Canca, David Charlin, Laurent Chen, Bo Cicek, Cihan Tugrul Cox, Louis Anthony Currie, Christine S.m. Demeulemeester, Erik Ding, Li Disney, Stephen m. Ehrgott, matthias Eppler, martin J. Erdogan, Güneş Fortz, Bernard Franco, L. Alberto Frische, Jens Greco, Salvatore Gregory, Amanda J. Hämäläinen, Raimo P. Herroelen, Willy Hewitt, mike Holmström, Jan Hooker, John N. Işık, Tugçe Johnes, Jill Kara, Bahar Y. Karsu, Özlem Kent, Katherine Köhler, Charlotte Kunc, martin Kuo, Yong-Hong Letchford, Adam N. Leung, Janny Li, Dong Li, Haitao Lienert, Judit Ljubić, Ivana Lodi, Andrea Lozano, Sebastián Lurkin, Virginie martello, Silvano mcHale, Ian G. midgley, Gerald morecroft, John D.W. mutha, Akshay Oguz, Ceyda Petrovic, Sanja Pferschy, Ulrich Psaraftis, Harilaos N. Rose, Sam Saarinen, Lauri Salhi, Said Song, Jing-Sheng Sotiros, Dimitrios Stecke, Kathryn E. Strauss, Arne K. Tarhan, Istenç Thielen, Clemens Toth, Paolo Van Woensel, Tom Vanden Berghe, Greet Vasilakis, Christos Vaze, Vikrant Vigo, Daniele Virtanen, Kai Wang, Xun Weron, Rafal White, Leroy Yearworth, mike Yıldırım, E. Alper Zaccour, Georges Zhao, Xuying School of Management University of Bath Bath United Kingdom Makridakis Open Forecasting Center University of Nicosia Nicosia Cyprus Department of Decision Sciences HEC Montréal Montreal Canada Molde University College Molde Norway Cranfield School of Management Cranfield University Cranfield United Kingdom Department of Management Sciences University of Waterloo Waterloo Canada ESSEC Business School in Paris Department of Information Systems Decision Sciences and Statistics Cergy France H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta United States Centre for Decision Research Leeds University Business School University of Leeds Leeds United Kingdom Université du Québec à Montréal Montreal Canada Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University Lancaster United Kingdom School of Engineering Department of Industrial Engineering and Management Science I University of Seville Seville Spain Mila-Quebec AI Institute Montreal Canada Warwick Business School University of Warwick Coventry United Kingdom Department of Industrial Engineering Atilim University Ankara Turkey Department of Business Analytics University of Colorado School of Business Denver United States Cox Associates Denver United States Mathematical Sciences University of Southampton Southampton United Kingdom Faculty of Economics and Business Research Center for Operations Management KU Leuven Leuven Belgium Durham University Business School Durham University Durham United Kingdom Center for Simulation Analytics and Modelling University of Exeter Business School Exeter United Kingdom Department of Management Science Lancaster University Management School Lancaster University Lancaster United Kingdom University of St. Gallen St. Gallen Switzerland HEC - Management School of the University of Liège Liège Belgium Département d'Informatique Université Libre de Bruxelles Bruss

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes. © 2023, CC BY.

关键词： Decision making