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Compression for quantum population coding

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arXiv 2017年

作者： Yang, Yuxiang Bai, Ge Chiribella, Giulio Hayashi, Masahito Department of Computer Science University of Hong Kong Pokfulam Road Hong Kong HKU Shenzhen Institute of Research and Innovation Kejizhong 2nd Road Shenzhen China Department of Computer Science University of Oxford Parks Road Oxford United Kingdom Canadian Institute for Advanced Research CIFAR Program in Quantum Information Science Department of Computer Science University of Hong Kong Pokfulam Road Hong Kong Graduate School of Mathematics Nagoya University Furocho Chikusaku Nagoya464-860 Japan Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 117542 Singapore

We study the compression of n quantum systems, each prepared in the same state belonging to a given parametric family of quantum states. For a family of states with f independent parameters, we devise an asymptotically faithful protocol that requires a hybrid memory of size (f/2) log n, including both quantum and classical bits. Our construction uses a quantum version of local asymptotic normality and, as an intermediate step, solves the problem of compressing displaced thermal states of n identically prepared modes. In both cases, we show that (f/2) log n is the minimum amount of memory needed to achieve asymptotic faithfulness. In addition, we analyze how much of the memory needs to be quantum. We find that the ratio between quantum and classical bits can be made arbitrarily small, but cannot reach zero: unless all the quantum states in the family commute, no protocol using only classical bits can be faithful, even if it uses an arbitrarily large number of classical bits. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum optics

Retracted: Efforts to Overcome Cyber Crime Actions in Indonesia

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Retracted: Efforts to Overcome Cyber Crime Actions in Indone...

2018 Workshop on Multidisciplinary and Its Applications: Applied mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Hatta, Muhammad Rajamanickam, Ramalinggam Abdullah, Dahlan Hartono, H. Bunga, Marten Adji, Hari Sapto Amiruddin, A. Djanggih, Hardianto Hipan, Nasrun Salle, S. Salmawati, S. Azis, Abdul Wahab, Mirnawanti Karinda, Kisman Saleh, A.A. Sudarsana, I Ketut Purnomo, Agung Anam, Fatkul Rianita, Dian Department of Criminal Law Universitas Malikusssaleh Aceh Indonesia Faculty of Law National University of Malaysia Selangor Malaysia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Law Universitas Gorontalo Indonesia Department of Law Universitas Tompotika Luwuk Banggai Indonesia Department of Law Universitas Muhammadiyah Luwuk Banggai Indonesia Department of Law Universitas Muslim Indonesia Indonesia Department of State Adminstration Sekolah Tinggi Ilmu Administrasi YAPPI Makassar Indonesia Department of Management Sekolah Tinggi Ilmu Ekonomi AMKOP Makassar Indonesia Department of Goverment Studies Universitas Muhammadiyah Luwuk Banggai Indonesia Statistics Financial and Social Sciences Research Group Indonesia Department of Religious Education Institut Hindu Dharma Negeri Denpasar Denpasar Indonesia Entrepreneurship Program Bina Nusantara Institute of Creative Technology Malang Indonesia Department of Mathematics Education Universitas Wijaya Kusuma Surabaya Indonesia Department of Administration University of Lancang Kuning Riau Indonesia

The presence of the internet can penetrate the boundaries between countries and accelerate the spread and exchange of information throughout the world. Although there are many positive impacts of internet use, there are also negative impacts that disturb the community. One can easily become a criminal (cyber crime) only by creating blogs, accounts, applications, programs, sites in various mass media and social media to commit fraud, data theft, illegal use of credit cards, the spread of pornographic content, online gambling, online prostitution, hate speech, radicalism, terrorism and so on. To overcome crime in the virtual space, the government has issued Law No. 19 of 2016 concerning Amendments to Law No. 11 of 2008 concerning Information and Electronic Transactions. But not all internet users know and understand the substance of the law. Therefore, the government, employers and institutions that are engaged in information and communication technology have the responsibility to socialize the law to the public to prevent crime in the virtual space. © Published under licence by IOP Publishing Ltd.

关键词： computer crime

Lamé Parameter Estimation from Static Displacement Field Measurements in the Framework of Nonlinear Inverse Problems

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arXiv 2017年

作者： Hubmer, Simon Sherina, Ekaterina Neubauer, Andreas Scherzer, Otmar Johannes Kepler University Linz Doctoral Program Computational Mathematics Altenbergerstraße 69 LinzA-4040 Austria Technical University of Denmark Department of Applied Mathematics and Computer Science Asmussens Allé Kongens Lyngby 2800 Denmark Johannes Kepler University Linz Industrial Mathematics Institute Altenbergerstraße 69 LinzA-4040 Austria University of Vienna Computational Science Center Oskar Morgenstern-Platz 1 Vienna1090 Austria Johann Radon Institute Linz Altenbergerstraße 69 LinzA-4040 Austria

We consider a problem of quantitative static elastography, the estimation of the Lamé parameters from internal displacement field data. This problem is formulated as a nonlinear operator equation. To solve this equation, we investigate the Landweber iteration both analytically and numerically. The main result of this paper is the verification of a nonlinearity condition in an infinite dimensional Hilbert space context. This condition guarantees convergence of iterative regularization methods. Furthermore, numerical examples for recovery of the Lamé parameters from displacement data simulating a static elastography experiment are *** Codes 65J22, 65J15, 74G75 Copyright © 2017, The Authors. All rights reserved.

关键词： Inverse problems

Correction to: Analysis of the Regularization Parameters of Primal–Dual Interior Method for Convex Objectives Applied to 1H Low Field Nuclear Magnetic Resonance Data Processing

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Applied Magnetic Resonance 2018年第1期50卷 521-521页

作者： Campisi-Pinto, Salvatore Levi, Ofer Benson, Diamanta Cohen, Meir Resende, Maysa Teixeira Saunders, Michael Linder, Charles Wiesman, Zeev Phyto-Lipid Biotechnology Laboratory Department of Biotechnology Engineering Faculty of Engineering Sciences Ben-Gurion University of the Negev Beer-Sheva Israel Department of Mathematics and Computer Science Program of Industrial Engineering and Management The Open University Ra’anana Israel Department of Management Science and Engineering (MS&E) Stanford University Stanford USA

In the original publication, the acknowledgment section was not published and it is given below now.

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Noisy Hegselmann-Krause systems: Phase transition and the 2R-conjecture 55

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Noisy Hegselmann-Krause systems: Phase transition and the 2R...

55th IEEE Conference on Decision and Control, CDC 2016

作者： Wang, Chu Li, Qianxiao Weinan, E. Chazelle, Bernard Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Nokia Bell Labs 600 Mountain Avenue Murray HillNJ07974 United States Department of Mathematics Program in Applied and Computational Mathematics Princeton University NJ08540 United States Department of Computer Science Princeton University PrincetonNJ08540 United States

ISBN: (纸本)9781509018376

The classic Hegselmann-Krause (HK) model for opinion dynamics consists of a set of agents on the real line, each one instructed to move, at every time step, to the mass center of the agents within a fixed distance R. In this work, we investigate the effects of noise in the continuous-time version of the model as described by its mean-field Fokker-Planck equation. In the presence of a finite number of agents, the system exhibits a phase transition from order to disorder as the noise increases. We introduce an order parameter to track the phase transition and resolve the corresponding phase diagram. The system undergoes a phase transition for small R but none for larger R. Based on the stability analysis of the mean-field equation, we derive the existence of a forbidden zone for the disordered phase to emerge. We also provide a theoretical explanation for the well-known 2R conjecture, which states that, for a random initial distribution in a fixed interval, the final configuration consists of clusters separated by a distance of roughly 2R. Our theoretical analysis confirms previous simulations and predicts properties of the noisy HK model in higher dimension. © 2016 IEEE.

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Quantum stopwatch: How to store time in a quantum memory

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arXiv 2017年

作者： Yang, Yuxiang Chiribella, Giulio Hayashi, Masahito Department of Computer Science University of Hong Kong Pokfulam Road Hku Shenzhen Institute of Research and Innovation Yuexing 2nd Rd Nanshan Shenzhen518057 Department of Computer Science University of Oxford Parks Road Oxford Canadian Institute for Advanced Research Cifar Program in Quantum Information Science TorontoONM5G 1Z8 School of Mathematics Nagoya University Nagoya Centre for Quantum Technologies National University of Singapore Singapore

Quantum mechanics imposes a fundamental tradeo between the accuracy of time measurements and the size of the systems used as clocks. When the measurements of different time intervals are combined, the errors due to the finite clock size accumulate, resulting in an overall inaccuracy that grows with the complexity of the setup. Here we introduce a method that in principle eludes the accumulation of errors by coherently transferring information from a quantum clock to a quantum memory of the smallest possible size. Our method could be used to measure the total duration of a sequence of events with enhanced accuracy, and to reduce the amount of quantum communication needed to stabilize clocks in a quantum network. Copyright © 2017, The Authors. All rights reserved.

关键词： Clocks

Corrigendum: Loss of LDAH associated with prostate cancer and hearing loss

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Human molecular genetics 2019年第10期28卷 1753-1754页

作者： Benjamin B Currall Ming Chen Richard C Sallari Maura Cotter Kristen E Wong Nahid G Robertson Kathryn L Penney Andrea Lunardi Markus Reschke Ann E Hickox Yanbo Yin Garrett T Wong Jacqueline Fung Kerry K Brown Robin E Williamson Nicholas A Sinnott-Armstrong Tammy Kammin Andrew Ivanov Cinthya J Zepeda-Mendoza Jun Shen Bradley J Quade Sabina Signoretti Kathleen S Arnos Alexander S Banks Nikolaos Patsopoulos M Charles Liberman Manolis Kellis Pier Paolo Pandolfi Cynthia C Morton Department of Obstetrics Gynecology and Reproductive Biology Brigham and Women's Hospital Boston MA USA. Harvard Medical School Boston MA USA. Cancer Research Institute Department of Medicine and Pathology Beth Israel Deaconess Medical Center Boston MA USA. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA. Center for Molecular Oncologic Pathology Dana Farber Cancer Institute Boston MA USA. Channing Division of Network Medicine Department of Medicine Brigham and Women's Hospital Boston MA USA. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA. Program in Speech and Hearing Bioscience and Technology Harvard-MIT Division of Health Sciences and Technology Cambridge MA USA. Eaton-Peabody Laboratory Massachusetts Eye and Ear Infirmary Boston MA USA. Department of Otology and Laryngology Harvard Medical School Boston MA USA. Department of Neurology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Department of Genetics Harvard Medical School Boston MA USA. Department of Pathology Brigham and Women's Hospital Boston MA USA. Laboratory for Molecular Medicine Partners HealthCare Personalized Medicine Cambridge MA USA. Harvard Medical School Center for Hereditary Deafness Boston MA USA. Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA. Department of Science Technology & Mathematics Gallaudet University Washington DC USA. Division of Endocrinology Diabetes and Hypertension Department of Medicine Brigham and Women's Hospital Boston MA USA. Division of Genetics Department of Medicine Brigham and Women's Hospital Boston MA USA. Division of Evolution and Genomic Sciences Manchester Academic Health Science Centre University of Manchester Manchester M13 9NT UK.

GALAXY CLUSTERS DISCOVERED VIA THE THERMAL SUNYAEV-ZEL’DOVICH EFFECT IN THE 500-SQUARE-DEGREE SPTPOL SURVEY

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arXiv 2023年

作者： Bleem, Lindsey E. Klein, M. Abbott, T.M.C. Ade, P.A.R. Aguena, M. Alves, O. Anderson, A.J. Andrade-Oliveira, F. Ansarinejad, B. Archipley, M. Ashby, M.L.N. Austermann, J.E. Bacon, D. Beall, J.A. Bender, A.N. Benson, B.A. Bianchini, F. Bocquet, S. Brooks, D. Burke, D.L. Calzadilla, M. Carlstrom, J.E. Carnero Rosell, A. Carretero, J. Chang, C.L. Chaubal, P. Chiang, H.C. Chou, T.-L. Citron, R. Corbett Moran, C. Costanzi, M. Crawford, T.M. Crites, A.T. da Costa, L.N. de Haan, T. De Vicente, J. Desai, S. Dobbs, M.A. Doel, P. Everett, W. Ferrero, I. Flaugher, B. Floyd, B. Friedel, D. Frieman, J. Gallicchio, J. Garc’ia-Bellido, J. Gatti, M. George, E.M. Giannini, G. Grandis, S. Gruen, D. Gruendl, R.A. Gupta, N. Gutierrez, G. Halverson, N.W. Hinton, S.R. Holder, G.P. Hollowood, D.L. Holzapfel, W.L. Honscheid, K. Hrubes, J.D. Huang, N. Hubmayr, J. Irwin, K.D. Mena-Fern’andez, J. James, D.J. Kéruzoré, F. Knox, L. Kuehn, K. Lahav, O. Lee, A.T. Lee, S. Li, D. Lowitz, A. Marshal, J.L. McDonald, M. McMahon, J.J. Menanteau, F. Meyer, S.S. Miquel, R. Mohr, J.J. Montgomery, J. Myles, J. Natoli, T. Nibarger, J.P. Noble, G.I. Novosad, V. Ogando, R.L.C. Padin, S. Patil, S. Pereira, M.E.S. Pieres, A. Plazas Malag’on, A.A. Pryke, C. Reichardt, C.L. Rodr’iguez-Monroy, M. Romer, A.K. Ruhl, J.E. Saliwanchik, B.R. Salvati, L. Sanchez, E. Saro, A. Schaffer, K.K. Schrabback, T. Sevilla-Noarbe, I. Sievers, C. Smecher, G. Smith, M. Somboonpanyakul, T. Stalder, B. Stark, A.A. Suchyta, E. Swanson, M.E.C. Tarle, G. To, C. Tucker, C. Veach, T. Vieira, J.D. Vincenzi, M. Wang, G. Weller, J. Whitehorn, N. Wiseman, P. Wu, W.L.K. Yefremenko, V. Zebrowski, J.A. Zhang, Y. High-Energy Physics Division Argonne National Laboratory 9700 South Cass Avenue. LemontIL60439 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States University Observatory Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich81679 Germany Max-Planck-Institut für extraterrestrische Physik Giessenbachstr. Garching85748 Germany Cerro Tololo Inter-American Observatory NSF’s National Optical-Infrared Astronomy Research Laboratory Casilla 603 La Serena Chile School of Physics and Astronomy Cardiff University CardiffCF24 3YB United Kingdom Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil Department of Physics University of Michigan 450 Church Street Ann ArborMI48109 United States Fermi National Accelerator Laboratory MS209 P.O. Box 500 BataviaIL60510 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia Department of Astronomy University of Illinois Urbana-Champaign 1002 West Green Street UrbanaIL61801 United States Center for AstroPhysical Surveys National Center for Supercomputing Applications UrbanaIL61801 United States Center for Astrophysics | Harvard & Smithsonian Optical and Infrared Astronomy Division CambridgeMA01238 United States NIST Quantum Devices Group 325 Broadway Mailcode 817.03 BoulderCO80305 United States Department of Physics University of Colorado BoulderCO80309 United States Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall StanfordCA94305 United States Department of Physics Stanford University 382 Via Pueblo Mall StanfordCA94305 United States SLAC National Accelera

We present a catalog of 689 galaxy cluster candidates detected at significance ξ > 4 via their thermal Sunyaev-Zel’dovich (SZ) effect signature in 95 and 150 GHz data from the 500-square-degree SPTpol survey. We use optical and infrared data from the Dark Energy Camera and the Wide-field Infrared Survey Explorer (WISE) and Spitzer satellites, to confirm 544 of these candidates as clusters with ∼ 94% purity. The sample has an approximately redshift-independent mass threshold at redshift z > 0.25. The confirmed sample spans 1.5 × 1014 500c 14M/h70 and 0.03 14M/h70 and median redshift z = 0.7;21% of the confirmed clusters are at z > 1. We use external radio data from the Sydney University Molonglo Sky Survey (SUMSS) to estimate contamination to the SZ signal from synchrotron sources. The contamination reduces the recovered ξ by a median value of 0.032, or ∼ 0.8% of the ξ = 4 threshold value, and ∼ 7% of candidates have a predicted contamination greater than ∆ξ = 1. With the exception of a small number of systems (CMB-arcmin at 150 (95) GHz and an effective angular resolution of 1.′2 (1.′7). The SPTpol products are available at https://***/public/data/sptpol_500d_clusters/***, and the NASA LAMBDA website. An interactive sky server with the SPTpol maps and Dark Energy Survey data release 2 images is also available at NCSA https://***. © 2023, CC BY.

关键词： Contamination

Forecasting: theory and practice

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arXiv 2020年

作者： Petropoulos, Fotios Apiletti, Daniele Assimakopoulos, Vassilios Babai, Mohamed Zied Barrow, Devon K. Taieb, Souhaib Ben Bergmeir, Christoph Bessa, Ricardo J. Bijak, Jakub Boylan, John E. Browell, Jethro Carnevale, Claudio Castle, Jennifer L. Cirillo, Pasquale Clements, Michael P. Cordeiro, Clara Oliveira, Fernando Luiz Cyrino de Baets, Shari Dokumentov, Alexander Ellison, Joanne Fiszeder, Piotr Franses, Philip Hans Frazier, David T. Gilliland, Michael Gönül, M. Sinan Goodwin, Paul Grossi, Luigi Grushka-Cockayne, Yael Guidolin, Mariangela Guidolin, Massimo Gunter, Ulrich Guo, Xiaojia Guseo, Renato Harvey, Nigel Hendry, David F. Hollyman, Ross Januschowski, Tim Jeon, Jooyoung Jose, Victor Richmond R. Kang, Yanfei Koehler, Anne B. Kolassa, Stephan Kourentzes, Nikolaos Leva, Sonia Li, Feng Litsiou, Konstantia Makridakis, Spyros Martin, Gael M. Martinez, Andrew B. Meeran, Sheik Modis, Theodore Nikolopoulos, Konstantinos Önkal, Dilek Paccagnini, Alessia Panagiotelis, Anastasios Panapakidis, Ioannis Pavía, Jose M. Pedio, Manuela Pedregal, Diego J. Pinson, Pierre Ramos, Patrícia Rapach, David E. Reade, J. James Rostami-Tabar, Bahman Rubaszek, Michal Sermpinis, Georgios Shang, Han Lin Spiliotis, Evangelos Syntetos, Aris A. Talagala, Priyanga Dilini Talagala, Thiyanga S. Tashman, Len Thomakos, Dimitrios Thorarinsdottir, Thordis Todini, Ezio Arenas, Juan Ramón Trapero Wang, Xiaoqian Winkler, Robert L. Yusupova, Alisa Ziel, Florian School of Management University of Bath United Kingdom Politecnico di Torino Turin Italy Forecasting and Strategy Unit School of Electrical and Computer Engineering National Technical University of Athens Greece Kedge Business School France Department of Management Birmingham Business School University of Birmingham United Kingdom Belgium Faculty of Information Technology Monash University Melbourne Australia INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Social Statistics and Demography University of Southampton United Kingdom Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University United Kingdom School of Mathematics and Statistics University of Glasgow United Kingdom Department of Mechanical and Industrial Engineering University of Brescia Italy Magdalen College University of Oxford United Kingdom ZHAW School of Management and Law Zurich University of Applied Sciences Switzerland ICMA Centre Henley Business School University of Reading United Kingdom Faculdade de Ciências e Tecnologia Universidade do Algarve Portugal CEAUL Faculdade de Ciências Universidade de Lisboa Portugal Brazil Department of Business Informatics and Operations Management Faculty of Economics and Business Administration Universiteit Gent Belgium Let’s Forecast Australia Faculty of Economic Sciences and Management Nicolaus Copernicus University in Torun Poland Econometric Institute Erasmus School of Economics Rotterdam Netherlands Department of Econometrics and Business Statistics Monash University Melbourne Australia SAS United States Newcastle Business School Northumbria University Newcastle upon Tyne United Kingdom Department of Statistical Sciences University of Padua Italy Darden School of Business University of Virginia United States Finance Department Bocconi University Baffi-CAREFIN Centre Milan Italy Department of Tourism and Service Management MODUL Un

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2020, CC BY.

关键词： Forecasting