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Separability-entanglement classifier via machine learning

Physical Review A 2018年第1期98卷 012315-012315页

作者： Sirui Lu Shilin Huang Keren Li Jun Li Jianxin Chen Dawei Lu Zhengfeng Ji Yi Shen Duanlu Zhou Bei Zeng Department of Physics Tsinghua University Beijing 100084 China Institute for Quantum Computing University of Waterloo Waterloo Ontario Canada N2L 3G1 Institute for Interdisciplinary Information Sciences Tsinghua University Beijing 100084 China Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and Technology Shenzhen 518055 China Department of Mathematics & Statistics University of Guelph Guelph Ontario Canada N1G 2W1 Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Centre for Quantum Software and Information School of Software Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Department of Statistics and Actuarial Science University of Waterloo Waterloo Ontario Canada N2L 3G1 Institute of Physics Chinese Academy of Sciences Beijing 100190 China

The problem of determining whether a given quantum state is entangled lies at the heart of quantum information processing. Despite the many methods—such as the positive partial transpose criterion and the k-symmetric extendibility criterion—to tackle this problem, none of them enables a general, practical solution due to the problem's NP-hard complexity. Explicitly, separable states form a high-dimensional convex set of vastly complicated structures. In this work, we build a different separability-entanglement classifier underpinned by machine learning techniques. We use standard tools from machine learning to learn the entanglement feature of arbitrary given quantum states. We perform substantial numerical tests on two-qubit and two-qutrit systems, and the results indicate that our method can outperform the existing methods in generic cases in terms of both speed and accuracy. This opens up avenues to explore quantum entanglement via the machine learning approach.

关键词： Machine learning Quantum entanglement

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Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project

Architecture-aware design and implementation of CNN algorith...

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International Conference on Microelectronics, ICM

作者： Paolo Meloni Daniela Loi Gianfranco Deriu Andy D. Pimentel Dolly Saprat Maura Pintort Battista Biggio Oscar Ripolles David Solans Francesco Conti Luca Benini Todor Stefanov Svetlana Minakova Bernhard Moser Natalia Shepeleva Michael Masin Francesca Palumbo Nikos Fragoulis Ilias Theodorakopoulos Department of Electrical and Electronic Engineering University of Cagliari Italy Institute of Informatics University of Amsterdam The Netherlands Pluribus One Italy CA Technologies Spain Integrated Systems Laboratory ETH Zurich Switzerland Institute of Advanced Computer Science Leiden University The Netherlands Software Competence Center Hagenberg Austria IBM Research - Haifa Israel IDEA Lab University of Sassari Italy IRIDA Labs Computer Vision Systems Greece

ISBN: (纸本)9781538681688;9781538681671

The use of Deep Learning (DL) algorithms is increasingly evolving in many application domains. Despite the rapid growing of algorithm size and complexity, performing DL inference at the edge is becoming a clear trend to cope with low latency, privacy and bandwidth constraints. Nevertheless, traditional implementation on low-energy computing nodes often requires experience-based manual intervention and trial-and-error iterations to get to a functional and effective solution. This work presents a computer-aided design (CAD) support for effective implementation of DL algorithms on embedded systems, aiming at automating different design steps and reducing cost. The proposed tool flow comprises capabilities to consider architecture-and hardware-related variables at very early stages of the development process, from pre-training hyperparameter optimization and algorithm configuration to deployment, and to adequately address security, power efficiency and adaptivity requirements. This paper also presents some preliminary results obtained by the first implementation of the optimization techniques supported by the tool flow.

关键词： Tools Inference algorithms Engines computer architecture Computational modeling Microelectronics Training

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Multiobjective optimization differential evolution enhanced with principle component analysis for constrained optimization

arXiv

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arXiv 2018年

作者： Huang, Wei Xu, Tao He, Jun Li, Kangshun Tianjin Key Laboratory of Intelligent and Novel Software Technology School of Computer Science and Engineering Tianjin University of Technology China Department of Computer Science Aberystwyth University AberystwythSY23 3DB United Kingdom School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China

Multiobjective optimization evolutionary algorithms have been successfully applied to solving constrained optimization problems. This paper proposes a new multiobjective optimization differential evolution algorithm for constrained optimization. Through a study of fitness landscapes using principle component analysis, we discover a statistic method of identifying the valley direction in a valley landscape. Based on this discovery, a new search operator called PCA-projection is constructed which projects an individual to a position along the valley direction. Then multiobjective optimization differential evolution using this projection operator is designed for constrained optimization. A comparative experiment has been implemented between the proposed algorithm and a state-of-the-art multiobjective differential evolution algorithm on a standard set of 24 benchmarks. Experimental results show that the new algorithm makes a significant improvement in terms of solution accuracy. The proposed algorithm is also competitive with ten evolutionary algorithms participated in an IEEE CEC 2006 competition and is ranked third in terms of the final rank. Copyright © 2018, The Authors. All rights reserved.

关键词： Multiobjective optimization

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On Algebraic Immunity of Trace Inverse Functions on Finite Fields of Characteristic Two

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Journal of systems science & Complexity 2016年第1期29卷 272-288页

作者： FENG Xiutao GONG Guang Key Laboratory of Mathematics Mechanization Academy of Mathematics and Systems ScienceChinese Academy of Sciences State Key Laboratory of Information Security(Institute of Information Engineering Chinese Academy of Sciences) Department of Electrical and Computer Engineering University of Waterloo

The trace inverse functions Tr(λx^(-1)) over the finite field F_(2~n) are a class of very important Boolean functions and are used in many stream ciphers such as SFINKS,RAKAPOSHI,the simple counter stream cipher(SCSC) presented by Si W and Ding C(2012),*** order to evaluate the security of those ciphers in resistance to(fast) algebraic attacks,the authors need to characterize algebraic properties of Tr(λx^(-1)).However,currently only some bounds on algebraic immunity of Tr(λx^(-1)) are given in the public literature,for example,the NGG upper bound and the Bayev lower bound,*** paper gives the exact value of the algebraic immunity of Tr(λx^(-1)) over F_(2~n),that is,AI(Tr(λx^(-1))) =[2n^(1/2)]- 2,where n ≥ 2,A ∈ F_(2~n) and λ≠ 0,which shows that Dalai's conjecture on the algebraic immunity of Tr(λx^(-1)) is *** is more,the authors demonstrate some weak properties of Tr(λx^(-1)) against fast algebraic attacks.

关键词： Algebraic immunity boolean functions fast algebraic attacks trace inverse functions

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GRID: A Student Project to Monitor the Transient Gamma-Ray Sky in the Multi-Messenger Astronomy Era

arXiv

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arXiv 2019年

作者： Wen, Jiaxing Long, Xiangyun Zheng, Xutao An, Yu Cai, Zhengyang Cang, Jirong Che, Yuepeng Chen, Changyu Chen, Liangjun Chen, Qianjun Chen, Ziyun Cheng, Yingjie Deng, Litao Deng, Wei Ding, Wenqing Du, Hangci Duan, Lian Gan, Quan Gao, Tai Gao, Zhiying Han, Wenbin Han, Yiying He, Xinbo He, Xinhao Hou, Long Hu, Fan Hu, Junling Huang, Bo Huang, Dongyang Huang, Xuefeng Jia, Shihai Jiang, Yuchen Jin, Yifei Li, Ke Li, Siyao Li, Yurong Liang, Jianwei Liang, Yuanyuan Lin, Wei Liu, Chang Liu, Gang Liu, Mengyuan Liu, Rui Liu, Tianyu Liu, Wanqiang Lu, Di'an Lu, Peiyibin Lu, Zhiyong Luo, Xiyu Ma, Sizheng Ma, Yuanhang Mao, Xiaoqing Mo, Yanshan Nie, Qiyuan Qu, Shuiyin Shan, Xiaolong Shi, Gengyuan Song, Weiming Sun, Zhigang Tan, Xuelin Tang, Songsong Tao, Mingrui Wang, Boqin Wang, Yue Wang, Zhiang Wu, Qiaoya Wu, Xuanyi Xia, Yuehan Xiao, Hengyuan Xie, Wenjin Xu, Dacheng Xu, Rui Xu, Weili Yan, Longbiao Yan, Shengyu Yang, Dongxin Yang, Hang Yang, Haoguang Yang, Yi-Si Yang, Yifan Yao, Lei Yu, Huan Yu, Yangyi Zhang, Aiqiang Zhang, Bingtao Zhang, Lixuan Zhang, Maoxing Zhang, Shen Zhang, Tianliang Zhang, Yuchong Zhao, Qianru Zhao, Ruining Zheng, Shiyu Zhou, Xiaolong Zhu, Runyu Zou, Yu An, Peng Cai, Yifu Chen, Hongbing Dai, Zigao Fan, Yizhong Feng, Changqing Feng, Hua Gao, He Huang, Liang Kang, Mingming Li, Lixin Li, Zhuo Liang, Enwei Lin, Lin Lin, Qianqian Liu, Congzhan Liu, Hongbang Liu, Xuewen Liu, Yinong Lu, Xiang Mao, Shude Shen, Rongfeng Shu, Jing Su, Meng Sun, Hui Tam, Pak-Hin Tang, Chi-Pui Tian, Yang Wang, Fayin Wang, Jianjun Wang, Wei Wang, Zhonghai Wu, Jianfeng Wu, Xuefeng Xiong, Shaolin Xu, Can Yu, Jiandong Yu, Wenfei Yu, Yunwei Zeng, Ming Zeng, Zhi Zhang, Bin-Bin Zhang, Bing Zhao, Zongqing Zhou, Rong Zhu, Zonghong Department of Engineering Physics Center for Astrophysics Tsinghua University Beijing100084 China Science and Technology on Plasma Physics Laboratory Laser Fusion Research Center Chinese Academy of Engineering Physics Mianyang621900 China Department of Physics Center for Astrophysics Tsinghua University Beijing100084 China Guangxi Key Laboratory for Relativistic Astrophysics Department of Physics Guangxi University NanningGuangxi530004 China School of Electronic and Information Engineering Ningbo University of Technology NingboZhejiang315211 China Department of Instruments Science & Engineering Shanghai Jiaotong University Shanghai200240 · China School of Materials Science & Chemical Engineering Ningbo University Ningbo315211 China School of Astronomy and Space Science Nanjing University NanjingJiangsu210093 China School of Aerospace Engineering Tsinghua University Beijing100084 China College of Physical Science and Technology Sichuan University Chengdu610065 China School of Physics and Astronomy Sun Yat-Sen University Zhuhai519082 China Department of Astronomy Xiamen University XiamenFujian361005 China School of Mathematics and Physics University of Science and Technology Beijing Beijing100083 China Department of Foreign Languages and Literatures Tsinghua University Beijing100084 China Department of Electrical Engineering Tsinghua University Beijing100084 China School of Software Tsinghua University Beijing100084 China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Department of Modern Physics School of Physical Sciences University of Science and Technology of China HefeiAnhui230026 China Department of Astronomy Beijing Normal University Beijing100875 China Department of Astronomy School of Physical Sciences University of Science and Technology of China HefeiAnhui230026 China Purple Mountain Observatory Chinese Academy of Sciences Nanjing210008 China Department of Astrono

The Gamma-Ray Integrated Detectors (GRID) is a space mission concept dedicated to monitoring the transient gamma-ray sky in the energy range from 10 keV to 2 MeV using scintillation detectors onboard CubeSats in low Earth orbits. The primary targets of GRID are the gamma-ray bursts (GRBs) in the local universe. The scientific goal of GRID is, in synergy with ground-based gravitational wave (GW) detectors such as LIGO and VIRGO, to accumulate a sample of GRBs associated with the merger of two compact stars and study jets and related physics of those objects. It also involves observing and studying other gamma-ray transients such as long GRBs, soft gamma-ray repeaters, terrestrial gamma-ray flashes, and solar flares. With multiple CubeSats in various orbits, GRID is unaffected by the Earth occultation and serves as a full-time and all-sky monitor. Assuming a horizon of 200 Mpc for ground-based GW detectors, we expect to see a few associated GW-GRB events per year. With about 10 CubeSats in operation, GRID is capable of localizing a faint GRB like 170817A with a 90% error radius of about 10 degrees, through triangulation and flux modulation. GRID is proposed and developed by students, with considerable contribution from undergraduate students, and will remain operated as a student project in the future. The current GRID collaboration involves more than 20 institutes and keeps growing. On August 29th, the first GRID detector onboard a CubeSat was launched into a Sun-synchronous orbit and is currently under test. Copyright © 2019, The Authors. All rights reserved.

关键词： Gravity waves

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

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Classical and Quantum Gravity 2023年第8期40卷 085015-085015页

作者： H Abe T Akutsu M Ando A Araya N Aritomi H Asada Y Aso S Bae Y Bae R Bajpai K Cannon Z Cao E Capocasa M Chan C Chen D Chen K Chen Y Chen C-Y Chiang Y-K Chu S Eguchi M Eisenmann Y Enomoto R Flaminio H K Fong Y Fujii Y Fujikawa Y Fujimoto I Fukunaga D Gao G-G Ge S Ha I P W Hadiputrawan S Haino W-B Han K Hasegawa K Hattori H Hayakawa K Hayama Y Himemoto N Hirata C Hirose T-C Ho B-H Hsieh H-F Hsieh C Hsiung H-Y Huang P Huang Y-C Huang Y-J Huang D C Y Hui S Ide K Inayoshi Y Inoue K Ito Y Itoh C Jeon H-B Jin K Jung P Jung K Kaihotsu T Kajita M Kakizaki M Kamiizumi N Kanda T Kato K Kawaguchi C Kim J Kim J C Kim Y-M Kim N Kimura T Kiyota Y Kobayashi K Kohri K Kokeyama A K H Kong N Koyama C Kozakai J Kume Y Kuromiya S Kuroyanagi K Kwak E Lee H W Lee R Lee M Leonardi K L Li P Li L C -C Lin C-Y Lin E T Lin F-K Lin F-L Lin H L Lin G C Liu L-W Luo M Ma’arif E Majorana Y Michimura N Mio O Miyakawa K Miyo S Miyoki Y Mori S Morisaki N Morisue Y Moriwaki K Nagano K Nakamura H Nakano M Nakano Y Nakayama T Narikawa L Naticchioni L Nguyen Quynh W-T Ni T Nishimoto A Nishizawa S Nozaki Y Obayashi W Ogaki J J Oh K Oh M Ohashi T Ohashi M Ohkawa H Ohta Y Okutani K Oohara S Oshino S Otabe K-C Pan A Parisi J Park F E Pe na Arellano S Saha Y Saito K Sakai T Sawada Y Sekiguchi L Shao Y Shikano H Shimizu K Shimode H Shinkai T Shishido A Shoda K Somiya I Song R Sugimoto J Suresh T Suzuki H Tagoshi H Takahashi R Takahashi S Takano H Takeda M Takeda K Tanaka T Tanaka S Tanioka A Taruya T Tomaru T Tomura L Trozzo T Tsang J-S Tsao S Tsuchida T Tsutsui D Tuyenbayev N Uchikata T Uchiyama A Ueda T Uehara K Ueno G Ueshima T Ushiba M H P M van Putten J Wang T Washimi C Wu H Wu T Yamada K Yamamoto T Yamamoto K Yamashita R Yamazaki Y Yang S Yeh J Yokoyama T Yokozawa T Yoshioka H Yuzurihara S Zeidler M Zhan H Zhang Y Zhao Z-H Zhu The KAGRA Collaboration Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo 152-8551 Japan Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences Yuseong-gu Daejeon 34047 Republic of Korea School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Beijing 100875 People’s Republic of China Department of Applied Physics Fukuoka University Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy National Tsing Hua University Hsinchu 30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City 32001 Taiwan Department of Physics National Tsing Hua University Hsinchu 30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Univ. Grenoble Alpes Laboratoire d’Annecy de Physique des Particules (LAPP) Université Savoie M

During April 7–21 2020, KAGRA conducted its first scientific observation in conjunction with the GEO600 detector. The dominant noise sources during this run were found to be suspension control noise in the low-frequency range and acoustic noise in the mid-frequency range. In this study, we show that their contributions in the observational data can be reduced by a signal processing method called independent component analysis (ICA). The model of ICA is extended from that studied in the initial KAGRA data analysis to account for frequency dependence, while the linearity and stationarity of the coupling between the interferometer and the noise sources are still assumed. We identify optimal witness sensors in the application of ICA, leading to successful mitigation of these two dominant contributions. We also analyze the stability of the transfer functions for the entire two weeks of data to investigate the applicability of the proposed subtraction method in gravitational wave searches.

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VFlash: Virtualized Flash for Optimizing the I/O Performance in Mobile Devices

VFlash: Virtualized Flash for Optimizing the I/O Performance...

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作者： Chen, Renhai Wang, Yi Hu, Jingtong Liu, Duo Shao, Zili Guan, Yong Beijing Advanced Innovation Center for Imaging Technology Beijing100048 China College of Information Engineering Capital Normal University Beijing China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74074 United States College of Computer Science Chongqing University Chongqing400044 China Embedded Systems and CPS Laboratory Department of Computing Hong Kong Polytechnic University Hong Kong

I/O is becoming one of major performance bottlenecks in NAND-flash-based mobile devices. Novel nonvolatile memories (NVMs), such as phase change memory and spin-transfer torque random access memory, can provide fast read/write operations. In this paper, we propose a unified NVM/flash architecture to improve the I/O performance. A transparent scheme, virtualized flash (vFlash), is also proposed to manage the unified architecture. Within vFlash, interapp and intra-app techniques are proposed to optimize the application performance by exploiting the historical locality and I/O access patterns of applications. Since vFlash is on the bottom of the I/O stack, the application features will be lost. Therefore, we also propose a cross-layer technique to transfer the application information from the application layer to the vFlash layer. The proposed scheme is evaluated based on an Android platform, and the experimental results show that the proposed scheme can effectively improve the I/O performance of mobile devices. © 1982-2012 IEEE.

关键词： Phase change memory

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AtLAST science Overview Report

arXiv

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arXiv 2024年

作者： Booth, Mark Klaassen, Pamela Cicone, Claudia Mroczkowski, Tony Cordiner, Martin A. Di Mascolo, Luca Johnstone, Doug van Kampen, Eelco Lee, Minju M. Liu, Daizhong Orlowski-Scherer, John Saintonge, Amélie Smith, Matthew W.L. Thelen, Alexander Wedemeyer, Sven Akiyama, Kazunori Andreon, Stefano Arzoumanian, Doris Bakx, Tom J.L.C. Bot, Caroline Bower, Geoffrey Brajša, Roman Chen, Chian-Chou da Cunha, Elisabete Eden, David Ettori, Stefano Gaches, Brandt Hatziminaoglou, Evanthia Luppe, Patricia Magnelli, Benjamin Marshall, Jonathan P. Montenegro-Montes, Francisco Miguel Niemack, Michael Nixon, Conor de Pater, Imke Perrott, Yvette Raimundo, Sandra I. Redaelli, Elena Richards, Anita Rybak, Matus Šarčević, Nikolina Semenov, Dmitry Spezzano, Silvia Srinivasan, Sundar Stanke, Thomas Andreani, Paola Beltrán, Maria T. Butler, Bryan J. Cantalupo, Sebastiano Dagostino, Miguel Chavez Duarte-Cabral, Ana Emonts, Bjorn Fletcher, Leigh Gary, Dale E. Gunar, Stanislav Hacar, Alvaro Hagedorn, Bendix Kaminski, Tomek Kirton, Fiona de Kleer, Katherine Kontar, Eduard Kuan, Yi-Jehng Lightfoot, John Lopez-Rodriguez, Enrique Lundgren, Andreas Milam, Stefanie N. Mohan, Atul Moreno, Raphael Motorina, Galina G. Moullet, Arielle Pattle, Kate Pellizzoni, Alberto Peretto, Nicolas Ramasawmy, Joanna Ricci, Claudio Rigby, Andrew J. Sánchez-Monge, Álvaro Saberi, Maryam Shimojo, Masumi Simionescu, Aurora Thompson, Mark Traficante, Alessio Vignali, Cristian White, Stephen M. UK Astronomy Technology Centre Royal Observatory Edinburgh Blackford Hill EdinburghEH9 3HJ United Kingdom Institute of Theoretical Astrophysics University of Oslo PO Box 1029 Blindern Oslo0315 Norway Karl-Schwarzschild-Strasse 2 Garching85748 Germany Astrochemistry Laboratory NASA Goddard Space Flight Center Code 691 GreenbeltMD20771 United States Laboratoire Lagrange Université Côte d’Azur Observatoire de la Côte d’Azur CNRS Blvd de l’Observatoire CS 34229 Nice06304 cedex 4 France Astronomy Unit Department of Physics University of Trieste via Tiepolo 11 Trieste34131 Italy INAF – Osservatorio Astronomico di Trieste via Tiepolo 11 Trieste34131 Italy IFPU – Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34014 Italy NRC Herzberg Astronomy and Astrophysics 5071 West Saanich Rd VictoriaBCV9E 2E7 Canada Department of Physics and Astronomy University of Victoria VictoriaBCV8P 5C2 Canada Denmark DTU-Space Technical University of Denmark Elektrovej 327 Kgs. LyngbyDK2800 Denmark Max-Planck-Institut für extraterrestrische Physik Giessenbachstrasse 1 Garching BayernD-85748 Germany Purple Mountain Observatory Chinese Academy of Sciences 10 Yuanhua Road Nanjing210008 China Department of Physics and Astronomy University of Pennsylvania 209 South 33rd Street PhiladelphiaPA19104 United States Department of Physics and Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Auf dem Hügel 69 BonnD-53121 Germany School of Physics & Astronomy Cardiff University The Parade CardiffCF24 3AA United Kingdom Division of Geological and Planetary Sciences California Institute of Technology PasadenaCA91125 United States Rosseland Centre for Solar Physics Institute of Theoretical Astrophysics University of Oslo Postboks 1029 Blindern OsloN-0315 Norway Haystack Observatory Massachusetts Institute of Technology 99 Millstone Road WestfordMA01886 United States National Astronomical Observatory of

Submillimeter and millimeter wavelengths provide a unique view of theUniverse, from the gas and dust that fills and surrounds galaxies to thechromosphere of our own Sun. Current single-dish facilities have presented atantalising view of the brightest (sub-)mm sources, and interferometers haveprovided the exquisite resolution necessary to analyse the details in smallfields, but there are still many open questions that cannot be answered withcurrent facilities. In this report we summarise the science that is guiding thedesign of the Atacama Large Aperture Submillimeter Telescope (AtLAST). Wedemonstrate how tranformational advances in topics including star formation inhigh redshift galaxies, the diffuse circumgalactic medium, Galactic ecology,cometary compositions and solar flares motivate the need for a 50m, single-dishtelescope with a 1-2 degree field of view and a new generation of highlymultiplexed continuum and spectral cameras. AtLAST will have the resolution todrastically lower the confusion limit compared to current single-dishfacilities, whilst also being able to rapidly map large areas of the sky anddetect extended, diffuse structures. Its high sensitivity and large field ofview will open up the field of submillimeter transient science by increasingthe probability of serendipitous detections. Finally, the science cases listedhere motivate the need for a highly flexible operations model capable of shortobservations of individual targets, large surveys, monitoring programmes,target of opportunity observations and coordinated observations with otherobservatories. AtLAST aims to be a sustainable, upgradeable, multipurposefacility that will deliver orders of magnitude increases in sensitivity andmapping speeds over current and planned submillimeter observatories. © 2024, CC BY.

关键词： Photons

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Overview of KAGRA : Data transfer and management

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Progress of Theoretical and Experimental Physics 2023年第10期2023卷

作者： Akutsu, T Ando, M Arai, K Arai, Y Araki, S Araya, A Aritomi, N Asada, H Aso, Y Bae, S Bae, Y Baiotti, L Bajpai, R Barton, M A Cannon, K Cao, Z Capocasa, E Chan, M Chen, C Chen, K Chen, Y Chiang, C-Y Chu, H Chu, Y-K Eguchi, S Enomoto, Y Flaminio, R Fujii, Y Fujikawa, Y Fukunaga, M Fukushima, M Gao, D Ge, G Ha, S Hagiwara, A Haino, S Han, W-B Hasegawa, K Hattori, K Hayakawa, H Hayama, K Himemoto, Y Hiranuma, Y Hirata, N Hirose, E Hong, Z Hsieh, B Huang, G-Z Huang, H-Y Huang, P Huang, Y-C Huang, Y Hui, D C Y Ide, S Ikenoue, B Imam, S Inayoshi, K Inoue, Y Ioka, K Ito, K Itoh, Y Izumi, K Jeon, C Jin, H-B Jung, K Jung, P Kaihotsu, K Kajita, T Kakizaki, M Kamiizumi, M Kanda, N Kang, G Kawaguchi, K Kawai, N Kawasaki, T Kim, C Kim, J Kim, J C Kim, W S Kim, Y-M Kimura, N Kita, N Kitazawa, H Kobayashi, Y Kojima, Y Kokeyama, K Komori, K Kong, A K H Kotake, K Kozakai, C Kozu, R Kumar, R Kume, J Kuo, C Kuo, H-S Kuromiya, Y Kuroyanagi, S Kusayanagi, K Kwak, K Lee, H K Lee, H W Lee, R Leonardi, M Li, K L Lin, L C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H L Liu, G C Luo, L-W Majorana, E Marchio, M Michimura, Y Mio, N Miyakawa, O Miyamoto, A Miyazaki, Y Miyo, K Miyoki, S Mori, Y Morisaki, S Moriwaki, Y Nagano, K Nagano, S Nakamura, K Nakano, H Nakano, M Nakashima, R Nakayama, Y Narikawa, T Naticchioni, L Negishi, R Quynh, L Nguyen Ni, W-T Nishizawa, A Nozaki, S Obuchi, Y Ogaki, W Oh, J J Oh, K Oh, S H Ohashi, M Ohashi, T Ohishi, N Ohkawa, M Ohta, H Okutani, Y Okutomi, K Oohara, K Ooi, C Oshino, S Otabe, S Pan, K Pang, H Parisi, A Park, J Arellano, F E Peña Pinto, I Sago, N Saito, S Saito, Y Sakai, K Sakai, Y Sakuno, Y Sasaki, Y Sato, S Sato, T Sawada, T Sekiguchi, T Sekiguchi, Y Shao, L Shibagaki, S Shimizu, R Shimoda, T Shimode, K Shinkai, H Shishido, T Shoda, A Somiya, K Son, E J Sotani, H Sugimoto, R Suresh, J Suzuki, T Tagoshi, H Takahashi, H Takahashi, R Takamori, A Takano, S Takeda, H Takeda, M Tanaka, H Tanaka, K Tanaka, T Tanioka, S Martin, E N Tapia San Telada, S Tomaru, T Tomigami, Y Tomura, T Travasso, F Trozzo, L Tsang, T Ts Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research (ICRR) KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Hirosaki University 3 Bunkyo-cho Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) 245 Daehak-ro Yuseong-gu Daejeon 34141 Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University No. 19 Xinjiekou Street Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Rd. Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy Nation

KAGRA is a newly built gravitational wave observatory, a laser interferometer with a 3 km arm length, located in Kamioka, Gifu prefecture, Japan. In this article, we describe the KAGRA data management system, i.e., recording of data, transfer from the KAGRA experiment site to computing resources, as well as data distribution to tier sites, including international sites in Taiwan and Korea. The amount of KAGRA data exceeded 1.0 PiB and increased by about 1.5 TB per day during operation in 2020. Our system has succeeded in data management, and has achieved performance that can withstand observations after 2023, that is, a transfer rate of 20 MB s-1or more and file storage of sufficient capacity for petabyte class. We also discuss the sharing of data between the global gravitational-wave detector network with other experiments, namely LIGO and Virgo. The latency, which consists of calculation of calibrated strain data and transfer time within the global network, is very important from the view of multi-messenger astronomy using gravitational waves. Real-time calbrated data delivered from the KAGRA detector site and other detectors to our computing system arrive with about 4–15 seconds of latency. These latencies are sufficiently short compared to the time taken for gravitational wave event search computations. We also established a high-latency exchange of offline calibrated data that was aggregated with a better accuracy compared with real-time data.

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