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Sharp transitions in rotating turbulent convection: Lagrangian acceleration statistics reveal a second critical Rossby number

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arXiv 2019年

作者： Alards, Kim M.J. Kunnen, Rudie P.J. Stevens, Richard J.A.M. Lohse, Detlef Toschi, Federico Clercx, Herman J.H. Fluid Dynamics Laboratory and J.M. Burgers Center for Fluid Dynamics Department of Applied Physics Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Physics of Fluids Group Max Planck Center for Complex Fluid Dynamics J.M. Burgers Center for Fluid Dynamics and MESA+ Research Institute Department of Science and Technology University of Twente P.O. Box 217 Enschede7500 AE Netherlands Max Planck Institute for Dynamics and Self-Organization Am Fassberg 17 Göttingen37077 Germany Centre of Analysis Scientific Computing and Applications W&I Department of Mathematics and Computer Science Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Istituto per le Applicazioni del Calcolo Consiglio Nazionale delle Ricerche Via dei Taurini 19 Rome00185 Italy

In Rayleigh–Bénard convection (RBC) for fluids with Prandtl number Pr 1, rotation beyond a critical (small) rotation rate is known to cause a sudden enhancement of heat transfer which can be explained by a change in the character of the boundary layer (BL) dynamics near the top and bottom plates of the convection cell. Namely, with increasing rotation rate, the BL signature suddenly changes from Prandtl–Blasius type to Ekman type. The transition from a constant heat transfer to an almost linearly increasing heat transfer with increasing rotation rate is known to be sharp and the critical Rossby number Roc occurs typically in the range 2.3 Roc 2.9 (for Rayleigh number Ra = 1.3×109, Pr = 6.7, and a convection cell with aspect ratio Γ = HD = 1, with D the diameter and H the height of the cell). The explanation of the sharp transition in the heat transfer points to the change in the dominant flow structure. At 1/Ro . 1/Roc (slow rotation), the well-known large-scale circulation (LSC) is found: a single domain-filling convection roll made up of many individual thermal plumes. At 1/Ro 1/Roc (rapid rotation), the LSC vanishes and is replaced with a collection of swirling plumes that align with the rotation axis. In this paper, by numerically studying Lagrangian acceleration statistics, related to the small-scale properties of the flow structures, we reveal that this transition between these different dominant flow structures happens at a second critical Rossby number, Roc2 ≈ 2.25 (different from Roc1 ≈ 2.7 for the sharp transition in the Nusselt number Nu;both values for the parameter settings of our present numerical study). When statistical data of Lagrangian tracers near the top plate are collected, it is found that the root-mean-square (rms) values and the kurtosis of the horizontal acceleration of these tracers show a sudden increase at Roc2. To better understand the nature of this transition we compute joint statistics of the Lagrangian velocity and acceleration of f

关键词： Flow structure

Analyzing feature space via pauli decomposition for quantum classifier

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arXiv 2019年

作者： Suzuki, Yudai Yano, Hiroshi Gao, Qi Uno, Shumpei Tanaka, Tomoki Akiyama, Manato Yamamoto, Naoki Department of Mechanical Engineering Keio University Hiyoshi 3-14-1 Kohoku Yokohama223-8522 Japan Department of Information and Computer Science Keio University Hiyoshi 3-14-1 Kohoku Yokohama223-8522 Japan Quantum Computing Center Keio University Hiyoshi 3-14-1 Kohoku Yokohama223-8522 Japan Department of Biosciences and Informatics Keio University Hiyoshi 3-14-1 Kohoku Yokohama223-8522 Japan Mitsubishi Chemical Corporation Science & Innovation Center 1000 Kamoshida-cho Aoba-ku Yokohama227-8502 Japan Mizuho Information & Research Institute Inc. 2-3 Kanda-Nishikicho Chiyoda-ku Tokyo101-8443 Japan Mitsubishi UFJ Financial Group Inc. and MUFG Bank Ltd. 2-7-1 Marunouchi Chiyoda-ku Tokyo100-8388 Japan Department of Applied Physics and Physico-Informatics Keio University 3-14-1 Kohoku Hiyoshi Yokohama223- 8522 Japan

A method for analyzing the feature space used in the quantum classifier on the basis of Pauli decomposition is developed. In particular, for 2-dimensional input datasets, the method boils down to a general formula that easily computes a lower bound of the exact training accuracy, which eventually helps us to see whether the feature space constructed with the selected feature map is suitable for linearly separating the dataset. The effectiveness of this formula is demonstrated, with the special type of five feature maps and four 2-dimensional non-linear datasets. Copyright © 2019, The Authors. All rights reserved.

关键词： Classification (of information)

PETSc/TS: A modern scalable ODE/DAE solver library

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arXiv 2018年

作者： Abhyankar, Shrirang Brown, Jed Constantinescu, Emil M. Ghosh, Debojyoti Smith, Barry F. Zhang, Hong Energy Systems Division Argonne National Laboratory 9700 South Cass Avenue LemontIL60439-5844 United States Department of Computer Science University of Colorado Boulder 430 UCB BoulderCO80309 United States Mathematics and Computer Science Division Argonne National Laboratory 9700 South Cass Avenue LemontIL60439-4844 United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory 7000 East Avenue LivermoreCA94550 United States

High-quality ordinary differential equation (ODE) solver libraries have a long history, going back to the 1970s. Over the past several years we have implemented, on top of the PETSc linear and nonlinear solver package, a new general-purpose, extensive, extensible library for solving ODEs and differential algebraic equations (DAEs). Package includes support for both forward and adjoint sensitivities that can be easily utilized by the TAO optimization package, which is also part of PETSc. The ODE/DAE integrator library strives to be highly scalable but also to deliver high efficiency for modest-sized problems. The library includes explicit solvers, implicit solvers, and a collection of implicit-explicit solvers, all with a common user interface and runtime selection of solver types, adaptive error control, and monitoring of solution progress. The library also offers enormous exibility in selection of nonlinear and linear solvers, including the entire suite of PETSc iterative solvers, as well as several parallel direct solvers. Copyright © 2018, The Authors. All rights reserved.

关键词： Ordinary differential equations

Measurement of the atmospheric muon neutrino flux with KM3NeT/ORCA6 38

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Measurement of the atmospheric muon neutrino flux with KM3Ne...

38th International Cosmic Ray Conference, ICRC 2023

作者： Stavropoulos, Dimitris Tzamariudaki, Ekaterini Drakopoulou, Evangelia Markou, Christos Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, E. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Basegmez du Pree, S. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Decoene, V. Del Burgo, R. Di Cerbo, U.M. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diaz, C. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, B. Gutiérrez, M. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. National Technical University of Athens School of Applied Mathematical and Physical Sciences Zografou Campus 9 Iroon Polytechniou str Zografou Athens15780 Greece INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece University of Granada Dept. of Computer Architecture and Technology/CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP 20722 Nantes44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1009

The KM3NeT/ORCA detector (Oscillation Research with Cosmics in the Abyss) is an array of Digital Optical Modules, spheres that host 31 photomultiplier tubes, tied together in vertical structures, the Detection Units, which are anchored on the seabed. Such an array configuration can detect neutrino events from the Cherenkov radiation emitted by the secondary particles induced by neutrino interactions in the abyssal depths of the Mediterranean Sea. The KM3NeT/ORCA detector is being deployed at a depth of 2450 m offshore Toulon, France with the determination of the Neutrino Mass Ordering being the main physics goal of the detector. The aim of this work is the study of atmospheric neutrinos with energies at the 1-100 GeV range, in order to obtain information on the atmospheric muon neutrino flux in this energy range, in which only few measurements exist by other experiments. An analysis of data collected with the 6-Detection Unit configuration of KM3NeT/ORCA (KM3NeT/ORCA6) is being presented in this contribution. The data analyzed corresponds to a time period of one and a half year. The procedure for the selection of a high-purity atmospheric neutrino sample, using a Machine Learning classifier (Boosted Decision Tree), is described. Subsequently, an unfolding scheme is used to obtain an estimation of the atmospheric muon neutrino flux in bins of energy in the region of interest. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Neutron flux

Search for a diffuse astrophysical neutrino flux with KM3NeT/ARCA using data of 2021-2022 38

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Search for a diffuse astrophysical neutrino flux with KM3NeT...

38th International Cosmic Ray Conference, ICRC 2023

作者： Tsourapis, Vasileios Drakopoulou, Evangelia Markou, Christos Sinopoulou, Anna Tzamariudaki, Ekaterini Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, E. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Basegmez du Pree, S. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Decoene, V. Del Burgo, R. Di Cerbo, U.M. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diaz, C. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, B. Gutiérrez, M. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. NCSR "Demokritos" Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece National Technical University of Athens School of Applied Mathematical and Physical Sciences Zografou Campus 9 Iroon Polytechniou str Zografou Athens15780 Greece INFN Sezione di Catania Via Santa Sofia Catania64 - 95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain University of Granada Dept. of Computer Architecture and Technology/CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP Nantes20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1

KM3NeT is a research infrastructure hosting two neutrino detectors which are currently under construction in the Mediterranean Sea. The KM3NeT/ARCA detector focuses on the detection of high energy neutrinos (>TeV) from astrophysical sources. In this contribution, an analysis of the data obtained during 2021-2022, using machine learning techniques, is presented. The potential of KM3NeT/ARCA to detect a diffuse flux of astrophysical neutrinos at the early stages of the detector construction is reported. The results of this analysis are presented. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Astrophysics

Multi-node Big Data VM Platform and Job Submission Portlet

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Multi-node Big Data VM Platform and Job Submission Portlet

International Conference on applied computing and Information Technology/International Conference on Computational science and Intelligence (ACIT-CSI)

作者： Chien-Heng Wu Wen-Yi Chang Whey-Fone Tsai Franco Lin Ching-Fang Lee Chao-Tung Yang High Performance Computing and Applications National Applied Research Laboratories Hsinchu Taiwan Cloud Computing and System Integration National Center for High-Performance Computing National Applied Research Laboratories Hsinchu Taiwan Computer Science Department TungHai University Taichung Taiwan

ISBN: (纸本)9781538633038

The present study utilizes VirtualBox virtual environment technology to develop the personal and compact size of multi-node big data VM platform with Spark and Hadoop cluster that can effectively replicate and provides an environment for developers to easily design and implement Spark and Hadoop Map/Reduce programming. By using the multi-node Hadoop VM system, developers can conduct Map/Reduce programing completely the same as that in the real multi-node Hadoop cluster. To demonstrate its capability and applicability, this study performs the benchmark by using the big data VM platform and a physical Multi-Node Hadoop Cluster. Based on the standard WordCount benchmarking, the computing time of the physical multi-node Hadoop cluster is 3.7 times faster than that of VM Hadoop cluster. The benchmark results show that the big data VM platform is an ideal platform for the portal and Map/Reduce programming, Spark programming and testing purposes, and the physical Hadoop cluster is the most appropriate for production runs. In addition, the big data VM platform contains a web portal development module designed to support applications that implement big data computing services for the engineering and science users. Such applications are inherently complex, potentially accessing data from a variety of sources and distributing applications to a variety of clients. This portal development module can act as multiple roles in many projects such as personal portals, small business portals, enterprise portals, educational portal, infrastructure portal, and other types of portals. Finally, the big data VM platform, in term of a big data development platform, is ready for users to download. The first author of this paper would like to give a demonstration for the proposed multi-node big data VM platform.

关键词： Big Data Portals Sparks Programming Benchmark testing Microsoft Windows Java

Argumentation-Based security for social good

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arXiv 2017年

作者： Karafili, Erisa Kakas, Antonis C. Spanoudakis, Nikolaos I. Lupu, Emil C. Department of Computing Imperial College London United Kingdom Department of Computer Science University of Cyprus Applied Mathematics and Computers Lab. Technical University of Crete

The increase of connectivity and the impact it has in every day life is raising new and existing security problems that are becoming important for social good. We introduce two particular problems: Cyber attack attribution and regulatory data sharing. For both problems, decisions about which rules to apply, should be taken under incomplete and context dependent information. The solution we propose is based on argumentation reasoning, that is a well suited technique for implementing decision making mechanisms under conflicting and incomplete information. Our proposal permits us to identify the attacker of a cyber attack and decide the regulation rule that should be used while using and sharing data. We illustrate our solution through concrete examples. Copyright © 2017, The Authors. All rights reserved.

关键词： Crime

Quantum speedup in solving the maximal-clique problem

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Physical Review A 2018年第3期97卷 032344-032344页

作者： Weng-Long Chang Qi Yu Zhaokai Li Jiahui Chen Xinhua Peng Mang Feng Department of Computer Science National Kaohsiung University of Applied Sciences Kaohsiung City 80778 Taiwan China CAS Key Laboratory of Microscale Magnetic Resonance and Department of Modern Physics University of Science and Technology of China Hefei 230026 China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Hefei 230026 China Institute for Quantum Computing and Department of Physics and Astronomy University of Waterloo Waterloo Ontario Canada N2L 3G1 Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha 410081 China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071 China Department of Physics Zhejiang Normal University Jinhua 321004 China

The maximal-clique problem, to find the maximally sized clique in a given graph, is classically an NP-complete computational problem, which has potential applications ranging from electrical engineering, computational chemistry, and bioinformatics to social networks. Here we develop a quantum algorithm to solve the maximal-clique problem for any graph G with n vertices with quadratic speedup over its classical counterparts, where the time and spatial complexities are reduced to, respectively, O(2n) and O(n2). With respect to oracle-related quantum algorithms for the NP-complete problems, we identify our algorithm as optimal. To justify the feasibility of the proposed quantum algorithm, we successfully solve a typical clique problem for a graph G with two vertices and one edge by carrying out a nuclear magnetic resonance experiment involving four qubits.

关键词： Quantum algorithms Computational complexity

Quantum Error Correction Decoheres Noise

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Physical Review Letters 2018年第19期121卷 190501-190501页

作者： Stefanie J. Beale Joel J. Wallman Mauricio Gutiérrez Kenneth R. Brown Raymond Laflamme Institute for Quantum Computing and Department of Physics and Astronomy University of Waterloo Waterloo Ontario N2L 3G1 Canada Institute for Quantum Computing and Department of Applied Mathematics University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Physics College of Science Swansea University Singleton Park Swansea SA2 8PP United Kingdom Escuela de Química Universidad de Costa Rica San José 2060 Costa Rica Department of Electrical and Computer Engineering Chemistry and Physics Duke University Durham North Carolina 27708 USA Perimeter Institute for Theoretical Physics Waterloo N2L 2Y5 Ontario Canada

Typical studies of quantum error correction assume probabilistic Pauli noise, largely because it is relatively easy to analyze and simulate. Consequently, the effective logical noise due to physically realistic coherent errors is relatively unknown. Here, we prove that encoding a system in a stabilizer code and measuring error syndromes decoheres errors, that is, causes coherent errors to converge toward probabilistic Pauli errors, even when no recovery operations are applied. Two practical consequences are that the error rate in a logical circuit is well quantified by the average gate fidelity at the logical level and that essentially optimal recovery operators can be determined by independently optimizing the logical fidelity of the effective noise per syndrome.

关键词： Quantum channels Quantum communication Quantum computation Quantum error correction Quantum fluctuations & noise Quantum information processing Quantum measurements Quantum memories Quantum theory Surface code quantum computing