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Readiness of Quantum Optimization Machines for Industrial Applications

Physical Review Applied 2019年第1期12卷 014004-014004页

作者： Alejandro Perdomo-Ortiz Alexander Feldman Asier Ozaeta Sergei V. Isakov Zheng Zhu Bryan O’Gorman Helmut G. Katzgraber Alexander Diedrich Hartmut Neven Johan de Kleer Brad Lackey Rupak Biswas Quantum Artificial Intelligence Lab. NASA Ames Research Center Moffett Field California 94035 USA USRA Research Institute for Advanced Computer Science (RIACS) Mountain View California 94043 USA Zapata Computing Inc. 439 University Avenue Office 535 Toronto Ontario M5G 1Y8 Canada Department of Computer Science University College London WC1E 6BT London United Kingdom Palo Alto Research Center 3333 Coyote Hill Road Palo Alto California 94304 USA QC Ware Corp. 125 University Avenue Suite 260 Palo Alto California 94301 USA Google Inc. 8002 Zurich Switzerland Department of Physics and Astronomy Texas A&M University College Station Texas 77843-4242 USA Berkeley Center for Quantum Information and Computation Berkeley California 94720 USA Department of Chemistry University of California Berkeley California 94720 USA 1QB Information Technologies (1QBit) Vancouver British Columbia V6B 4W4 Canada Santa Fe Institute 1399 Hyde Park Road Santa Fe New Mexico 87501 USA Fraunhofer IOSB-INA Lemgo Germany Google Inc. Venice California 90291 USA Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Departments of Computer Science and Mathematics University of Maryland College Park Maryland 20742 USA Mathematics Research Group National Security Agency Ft. George G. Meade Maryland 20755 USA Exploration Technology Directorate NASA Ames Research Center Moffett Field California 94035 USA

There have been multiple attempts to demonstrate that quantum annealing and, in particular, quantum annealing on quantum-annealing machines, has the potential to outperform current classical optimization algorithms implemented on CMOS technologies. The benchmarking of these devices has been controversial. Initially, random spin-glass problems were used, however, these were quickly shown to be not well suited to detect any quantum speedup. Subsequently, benchmarking shifted to carefully crafted synthetic problems designed to highlight the quantum nature of the hardware while (often) ensuring that classical optimization techniques do not perform well on them. Even worse, to date a true sign of improved scaling with the number of problem variables remains elusive when compared to classical optimization techniques. Here, we analyze the readiness of quantum-annealing machines for real-world application problems. These are typically not random and have an underlying structure that is hard to capture in synthetic benchmarks, thus posing unexpected challenges for optimization techniques, both classical and quantum alike. We present a comprehensive computational scaling analysis of fault diagnosis in digital circuits, considering architectures beyond D-Wave quantum annealers. We find that the instances generated from real data in multiplier circuits are harder than other representative random spin-glass benchmarks with a comparable number of variables. Although our results show that transverse-field quantum annealing is outperformed by state-of-the-art classical optimization algorithms, these benchmark instances are hard and small in the size of the input, therefore representing the first industrial application ideally suited for testing near-term quantum annealers and other quantum algorithmic strategies for optimization problems.

关键词： Adiabatic quantum optimization Quantum algorithms Quantum benchmarking Quantum information architectures & platforms Quantum Monte Carlo

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A prediction model of edge gas flow development state based on BP neural network 5

A prediction model of edge gas flow development state based ...

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5th International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017

作者： Zhang, Jialiang An, Jianqi Wu, Min Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

The development and distribution states of the blast furnace (BF) gas flow determine whether the reaction in the furnace can proceed normally and decide the utilization efficiency of the carbon in the furnace and the stable smooth operation of the furnace. The internal environment of BF is closed with high temperature and high pressure, which causes that the relationship between the development situation of edge gas flow of the BF and the BF operation is uncertain. In this paper, a prediction model of edge gas flow development state based on BP neural network (BPNN) is proposed, clarifying the relationship between the development state of edge gas flow and the edge burden parameters. Firstly, this paper gets the relative operation factors of effecting the development situation of edge gas flow through analyzing the process mechanism of the BF ironmaking, and proposes the development index of edge gas flow and the heat load of cooling stave to measure the development state of the edge gas flow. Secondly, the intrinsic correlation between the data is verified, and the data are analyzed by Spearman's rank correlation coefficient (SRCC) analysis. Finally, according to the analysis results, combined with the burden mechanism, the edge gas flow prediction model is established to realize the prediction of the development state of the edge gas flow. The calculation of the data collected in the metallurgy scene of the BF suggested that this prediction model of the edge gas flow development state of the BF could describe the relationship between BF operation parameters and the developing state of the edge gas flow.

关键词： Flow of gases

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Micro-Bump Assignment for Efficient Routing on Re-Distribution Layer (RDL) in 3D-ICs

Micro-Bump Assignment for Efficient Routing on Re-Distributi...

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IEEE India Council International Conference

作者： Sabyasachee Banerjee Subhashis Majumder Saikat Basu Bhargab B. Bhattacharya Department of Computer Science and Engineering Heritage Institute of Technology Nanotechnology Research Triangle Advanced Computing and Microelectronics Unit Indian Statistical Institute

ISBN: (纸本)9781538643198

RDL (Re-Distribution Layers) routing from the IO pads to micro-bumps plays an important role for transmitting signal between two adjacent layers in 3D IC. The quality of RDL-routing strongly depends on the positions of micro-bumps between two adjacent dies. Initially, I/O pads are assigned to micro-bumps and then single-layer routing is performed over the two RDLs that are adjacent to two respective layers. We propose an improved method for RDL-routing in 3D IC. Experimental results show that 100% routahility can be achieved with reduced wire-length for all five test-cases that we have studied.

关键词： TSV Micro-bump RDL routing

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image computing and computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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Estimating the Cost of Generic Quantum Pre-image Attacks on SHA-2 and SHA-3 1

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23rd International Conference on Selected Areas in Cryptography, SAC 2016

作者： Amy, Matthew Di Matteo, Olivia Gheorghiu, Vlad Mosca, Michele Parent, Alex Schanck, John David R. Cheriton School of Computer Science University of Waterloo Waterloo Canada Department of Physics and Astronomy University of Waterloo Waterloo Canada Department of Combinatorics and Optimization University of Waterloo Waterloo Canada Institute for Quantum Computing University of Waterloo Waterloo Canada Perimeter Institute for Theoretical Physics Waterloo Canada Canadian Institute for Advanced Research Toronto Canada

ISBN: (数字)9783319694535

ISBN: (纸本)9783319694528

We investigate the cost of Grover’s quantum search algorithm when used in the context of pre-image attacks on the SHA-2 and SHA-3 families of hash functions. Our cost model assumes that the attack is run on a surface code based fault-tolerant quantum computer. Our estimates rely on a time-area metric that costs the number of logical qubits times the depth of the circuit in units of surface code cycles. As a surface code cycle involves a significant classical processing stage, our cost estimates allow for crude, but direct, comparisons of classical and quantum algorithms. We exhibit a circuit for a pre-image attack on SHA-256 that is approximately 2153.8 surface code cycles deep and requires approximately 2.12.6 logical qubits. This yields an overall cost of 2.166.4 logical-qubit-cycles. Likewise we exhibit a SHA3-256 circuit that is approximately 2.146.5 surface code cycles deep and requires approximately 2.20 logical qubits for a total cost of, again, 2.166.5logical-qubit-cycles. Both attacks require on the order of 2128 queries in a quantum black-box model, hence our results suggest that executing these attacks may be as much as 275 billion times more expensive than one would expect from the simple query analysis. © 2017, Springer International Publishing AG.

关键词： Hash functions

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MOT Knowledge Model Integration Rules for Knowledge Warehousing

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Procedia computer science 2017年 112卷 544-553页

作者： Rim Ayadi Yasser Hachaichi Jamel Feki Multimedia InfoRmation Systems and Advanced Computing Laboratory University of Sfax Sfax Tunisia Department of Computer Science and Quantitative Methods Higher Institute of Business Administration of Sfax Faculty of Computing and IT University of Jeddah Jeddah Saudi Arabia

A knowledge warehousing process aims to build an intelligent decision support system. It collects, homogenizes, integrates and stores knowledge for a decision-making process. In this paper, we are interested in knowledge integration. More accurately, we propose an integration process for knowledge homogenized/modeled according to the MOT (Modeling with Object Types) knowledge model. This integration process consists of three ordered steps based on the type of schemas to integrate and their similarity. For this process, we define five integration rules based on semantic relationships between elements of MOT knowledge models, and then we develop an algorithm using these integration rules.

关键词： Knowledge warehouse Knowledge integration MOT Knowledge Semantic relationships Integration rules

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Search for heavy neutral Higgs bosons produced in association with b-quarks and decaying into b-quarks at s=13 TeV with the ATLAS detector

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Physical Review D 2020年第3期102卷 032004-032004页

作者： G. Aad B. Abbott D. C. Abbott O. Abdinov A. Abed Abud K. Abeling D. K. Abhayasinghe S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya B. Achkar S. Adachi L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek J. Adelman M. Adersberger A. Adiguzel S. Adorni T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra F. Ahmadov W. S. Ahmed X. Ai G. Aielli S. Akatsuka T. P. A. Åkesson E. Akilli A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa D. Alexandre T. Alexopoulos A. Alfonsi M. Alhroob B. Ali G. Alimonti J. Alison S. P. Alkire C. Allaire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. A. Alshehri M. Alvarez Estevez D. Álvarez Piqueras M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso C. S. Amrouche F. An C. Anastopoulos N. Andari T. Andeen C. F. Anders J. K. Anders A. Andreazza V. Andrei C. R. Anelli S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo L. Aperio Bella G. Arabidze J. P. Araque V. Araujo Ferraz R. Araujo Pereira C. Arcangeletti A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster L. J. Armitage A. Armstrong O. Arnaez H. Arnold A. Artamonov G. Artoni S. Artz S. Asai N. Asbah E. M. Asimakopoulou L. Asquith K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani K. Augsten G. Avolio R. Avramidou M. K. Ayoub A. M. Azoulay G. Azuelos M. J. Baca H. Bachacou K. Bachas M. Backes F. Backman P. Bagnaia M. Bahmani H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines M. Bajic C. Bakalis O. K. Baker P. J. Bakker D. Bakshi Gupta S. Balaji E. M. Baldin P. Balek F. Balli W. K. Balunas J. Balz E. Banas A. Bandyopadhyay Sw. Banerjee A. A. E. Bannoura L. Barak W. M. Barbe E. L. Barberio D. Barberis M. Barbero T. Barillari CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Department of Physics University of Massachusetts Amherst Massachusetts USA Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan INFN Sezione di Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto ON Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne Illinois USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics University of Tokyo Tokyo Japan Institut für Physik Universität Mainz Mainz Germany IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA LPC Université Clermont Auvergne CNRS/IN2P3 Clermont-Ferrand France Institut

A search for heavy neutral Higgs bosons produced in association with one or two b-quarks and decaying to b-quark pairs is presented using 27.8 fb−1 of s=13 TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider during 2015 and 2016. No evidence of a signal is found. Upper limits on the heavy neutral Higgs boson production cross section times its branching ratio to bb¯ are set, ranging from 4.0 to 0.6 pb at 95% confidence level over a Higgs boson mass range of 450 to 1400 GeV. Results are interpreted within the two-Higgs-doublet model and the minimal supersymmetric Standard Model.

关键词： Extensions of Higgs sector Hypothetical scalars

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Erratum to: Measurement of differential cross sections and W+/W− cross-section ratios for W boson production in association with jets at = 8 TeV with the ATLAS detector

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Journal of High Energy Physics 2020年第10期2020卷 1-20页

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Afik, Y. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Alberghi, G. L. Albert, J. Albicocco, P. Alconada Verzini, M. J. Alderweireldt, S. C. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A. V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D. J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Araujo Ferraz, V. Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baas, A. E. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Bakker, P. J. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Bandyopadhyay, A. Banerjee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barkeloo, J. T. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska-Blenessy, Z. Baroncelli, A. Bar Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States of America Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz United States of America Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene United States of America Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas — LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston United States of America Joint Institute for Nuclear Research JINR Dubna Dubna Russia IN

Two additions impacting tables 3 and 4 in ref. [1] are presented in the following. No significant impact is found for other results or figures in ref. [1].

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Search for resonances decaying into a weak vector boson and a Higgs boson in the fully hadronic final state produced in proton−proton collisions at s=13 TeV with the ATLAS detector

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Physical Review D 2020年第11期102卷 112008-112008页

作者： G. Aad B. Abbott D. C. Abbott A. Abed Abud K. Abeling D. K. Abhayasinghe S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya B. Achkar L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek J. Adelman M. Adersberger A. Adiguzel S. Adorni T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra A. Ahmad F. Ahmadov W. S. Ahmed X. Ai G. Aielli S. Akatsuka M. Akbiyik T. P. A. Åkesson E. Akilli A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos A. Alfonsi F. Alfonsi M. Alhroob B. Ali S. Ali M. Aliev G. Alimonti C. Allaire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio F. Alonso C. Alpigiani E. Alunno Camelia M. Alvarez Estevez M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso C. S. Amrouche F. An C. Anastopoulos N. Andari T. Andeen J. K. Anders S. Y. Andrean A. Andreazza V. Andrei C. R. Anelli S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony E. Antipov M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio Bella N. Aranzabal Barrio V. Araujo Ferraz R. Araujo Pereira C. Arcangeletti A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster A. Armstrong O. Arnaez H. Arnold Z. P. Arrubarrena Tame G. Artoni H. Asada K. Asai S. Asai T. Asawatavonvanich N. Asbah E. M. Asimakopoulou L. Asquith J. Assahsah K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani K. Augsten V. A. Austrup G. Avolio M. K. Ayoub G. Azuelos H. Bachacou K. Bachas M. Backes F. Backman P. Bagnaia M. Bahmani H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines C. Bakalis O. K. Baker P. J. Bakker E. Bakos D. Bakshi Gupta S. Balaji R. Balasubramanian E. M. Baldin P. Balek F. Balli W. K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay Sw. Banerjee L. Barak W. M. Barbe E. L. Barberio D. Barberis M. Barbero CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Department of Physics University of Massachusetts Amherst Massachusetts USA CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto ON Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne Illinois USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Institut für Physik Universität Mainz Mainz Germany LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France LPC Université Clermont Auvergne CNRS/IN2P3 Clermont-Ferrand France Institute for Mathematics Astrophysics and Particle Physics Radboud University Nijmegen/Nikhef Nijmegen Netherlands Department of Physics Alexandru Ioan Cuza U

A search for heavy resonances decaying into a W or Z boson and a Higgs boson produced in proton−proton collisions at the Large Hadron Collider at s=13 TeV is presented. The analysis utilizes the dominant W→qq¯′ or Z→qq¯ and H→bb¯ decays with substructure techniques applied to large-radius jets. A sample corresponding to an integrated luminosity of 139 fb−1 collected with the ATLAS detector is analyzed and no significant excess of data is observed over the background prediction. The results are interpreted in the context of the heavy vector triplet model with spin-1 W′ and Z′ bosons. Upper limits on the cross section are set for resonances with mass between 1.5 and 5.0 TeV, ranging from 6.8 to 0.53 fb for W′→WH and from 8.7 to 0.53 fb for Z′→ZH at the 95% confidence level.

关键词： Hypothetical particle physics models Particle data analysis

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Erratum to: Search for diboson resonances in hadronic final states in 139 fb−1 of pp collisions at = 13 TeV with the ATLAS detector

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Journal of High Energy Physics 2020年第6期2020卷 1-19页

作者： Aad, G. Abbott, B. Abbott, D. C. Abdinov, O. Abed Abud, A. Abeling, K. Abhayasinghe, D. K. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B. S. Achkar, B. Adachi, S. Adam, L. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Adelman, J. Adersberger, M. Adiguzel, A. Adorni, S. Adye, T. Affolder, A. A. Afik, Y. Agapopoulou, C. Agaras, M. N. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahmadov, F. Ahmed, W. S. Ai, X. Aielli, G. Akatsuka, S. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Al Khoury, K. Alberghi, G. L. Albert, J. Alconada Verzini, M. J. Alderweireldt, S. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexandre, D. Alexopoulos, T. Alfonsi, A. Alhroob, M. Ali, B. Alimonti, G. Alison, J. Alkire, S. P. Allaire, C. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alvarez Estevez, M. Álvarez Piqueras, D. Alviggi, M. G. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Amrouche, C. S. An, F. Anastopoulos, C. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Andreazza, A. Andrei, V. Anelli, C. R. Angelidakis, S. Angerami, A. Anisenkov, A. V. Annovi, A. Antel, C. Anthony, M. T. Antonelli, M. Antrim, D. J. A. Anulli, F. Aoki, M. Aparisi Pozo, J. A. Aperio Bella, L. Arabidze, G. Araque, J. P. Araujo Ferraz, V. Araujo Pereira, R. Arcangeletti, C. Arce, A. T. H. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arling, J.-H. Armbruster, A. J. Armitage, L. J. Armstrong, A. Arnaez, O. Arnold, H. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Asimakopoulou, E. M. Asquith, L. Assamagan, K. Astalos, R. Atkin, R. J. Atkinson, M. Atlay, N. B. Atmani, H. Augsten, K. Avolio, G. Avramidou, R. Ayoub, M. K. Azoulay, A. M. Azuelos, G. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Backman, F. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A. J. Bailey, V. R. Baines, J. T. Bajic, M. Bakalis, C. Baker, O. K. Bakker, P. J. Bakshi Gupta, D. Balaji, S. Baldin, E. M. Balek, P. Balli, F. CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States of America Department of Physics University of Massachusetts Amherst United States of America Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan INFN Sezione di Pavia Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne United States of America INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics University of Tokyo Tokyo Japan Institut für Physik Universität Mainz Mainz Germany LAL Université Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Istanbul University Dept. of Physics Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cr

A mistake was identified for the paper [1] in the treatment of the radion [2] cross-sections, which resulted in multiple changes.

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