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Energy harvesting in 5G networks: Taxonomy, requirements, challenges, and future directions

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arXiv 2019年

作者： Imran, Muhammad Khan, Latif U. Yaqoob, Ibrar Ahmed, Ejaz Qureshi, Muhammad Ahsan Ahmed, Arif College of Applied Computer Science King Saud University Riyadh Saudi Arabia Department of Telecommunication Engineering University of Engineering & Technology Mardan Pakistan Department of Computer Science and Engineering Kyung Hee University Yongin-si17104 Korea Republic of University of Malaya Kuala Lumpur50603 Malaysia Faculty of Computing and Information technology University of Jeddah Khulais Saudi Arabia Department of Computer Science & Engineering National Institute of Technology Silchar Silchar India

Consciousness of energy saving is increasing in fifth-generation (5G) wireless networks due to the high energy consumption issue. Energy harvesting technology is a possible appealing solution for ultimately prolonging the lifetime of devices and networks. Although considerable research efforts have been conducted in the context of using energy harvesting technology in 5G wireless networks, these efforts are in their infancy, and a tutorial on this topic is still lacking. This study aims to discuss the beneficial role of energy harvesting technology in 5G networks. We categorize and classify the literature available on energy harvesting in 5G networks by devising a taxonomy based on energy sources;energy harvesting devices, phases, and models;energy conversion methods, and energy propagation medium. The key requirements for enabling energy harvesting in 5G networks are also outlined. Several core research challenges that remain to be addressed are discussed. Furthermore, future research directions are provided. Copyright © 2019, The Authors. All rights reserved.

关键词： Energy harvesting

Machine Learning in Nuclear Physics

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arXiv 2021年

作者： Boehnlein, Amber Diefenthaler, Markus Sato, Nobuo Schram, Malachi Ziegler, Veronique Fanelli, Cristiano Hjorth-Jensen, Morten Horn, Tanja Kuchera, Michelle P. Lee, Dean Nazarewicz, Witold Ostroumov, Peter Orginos, Kostas Poon, Alan Wang, Xin-Nian Scheinker, Alexander Smith, Michael S. Pang, Long-Gang Thomas Jefferson National Accelerator Facility 12000 Jefferson Avenue Newport NewsVA United States Laboratory for Nuclear Science Massachusetts Institute of Technology CambridgeMA02139 United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions United States Facility for Rare Isotope Beams Department of Physics and Astronomy Michigan State University MI48824 United States Department of Physics Center for Computing in Science Education University of Oslo OsloN-0316 Norway Department of Physics The Catholic University of America N. E. Washington DC20064 United States Department of Physics Department of Mathematics & Computer Science Davidson College NC28035 United States Department of Physics William & Mary WilliamsburgVA United States Nuclear Science Division Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA94720 United States Accelerator Operations and Technology Division Applied Electrodynamics Group Los Alamos National Laboratory Los AlamosNM87544 United States Physics Division Oak Ridge National Laboratory Oak RidgeTN37831-6354 United States Key Laboratory of Quark and Lepton Physics Institute of Particle Physics Central China Normal University Wuhan430079 China

Advances in machine learning methods provide tools that have broad applicability in scientific research. These techniques are being applied across the diversity of nuclear physics research topics, leading to advances that will facilitate scientific discoveries and societal applications. This Colloquium provides a snapshot of nuclear physics research which has been transformed by machine learning techniques. © 2021, CC BY.

关键词： Machine learning

Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

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Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

Approximate complex amplitude encoding algorithm and its application to data classification problems

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arXiv 2022年

作者： Mitsuda, Naoki Ichimura, Tatsuhiro Nakaji, Kouhei Suzuki, Yohichi Tanaka, Tomoki Raymond, Rudy Tezuka, Hiroyuki Onodera, Tamiya Yamamoto, Naoki Sumitomo Mitsui Trust Bank Ltd. 1-4-1 Marunouchi Chiyoda-ku Tokyo100-8233 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223-8522 Japan Department of Chemistry University of Toronto TorontoONM5G 1Z8 Canada 1-1-1 Umezono Ibaraki Tsukuba305-8568 Japan Mitsubishi UFJ Financial Group Inc. MUFG Bank Ltd. 2-7-1 Marunouchi Chiyoda-ku Tokyo100-8388 Japan IBM Quantum IBM Japan 19-21 Nihonbashi Hakozaki-cho Chuo-ku Tokyo103-8510 Japan Department of Computer Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Advanced Research Laboratory Technology Infrastructure Center Sony Group Corporation Technology Platform 1-7-1 Konan Minato-ku Tokyo108-0075 Japan Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223- 8522 Japan Department of Applied Physics and Physico-Informatics Keio University Hiyoshi 3-14-1 Kohoku-ku Kanagawa Yokohama223-8522 Japan

Quantum computing has a potential to accelerate data processing efficiency, especially in machine learning, by exploiting special features such as the quantum interference. The major challenge in this application is that, in general, the task of loading a classical data vector into a quantum state requires an exponential number of quantum gates. The approximate amplitude encoding (AAE) method, which uses a variational means to approximately load a given real-valued data vector into the amplitude of a quantum state, was recently proposed as a general approach to this problem mainly for near-term devices. However, AAE cannot load a complex-valued data vector, which narrows its application range. In this work, we extend AAE so that it can handle a complex-valued data vector. The key idea is to employ the fidelity distance as a cost function for optimizing a parametrized quantum circuit, where the classical shadow technique is used to efficiently estimate the fidelity and its gradient. We apply this algorithm to realize the complex-valued-kernel binary classifier called the compact Hadamard classifier, and then we present a numerical experiment showing that it enables classification of the Iris dataset and credit card fraud detection. Copyright © 2022, The Authors. All rights reserved.

关键词： Cost functions

Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper

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arXiv 2022年

作者： Dorigo, Tommaso Giammanco, Andrea Vischia, Pietro Aehle, Max Bawaj, Mateusz Boldyrev, Alexey de Castro Manzano, Pablo Derkach, Denis Donini, Julien Edelen, Auralee Fanzago, Federica Gauger, Nicolas R. Glaser, Christian Baydin, Atılım G. Heinrich, Lukas Keidel, Ralf Kieseler, Jan Krause, Claudius Lagrange, Maxime Lamparth, Max Layer, Lukas Maier, Gernot Nardi, Federico Pettersen, Helge E.S. Ramos, Alberto Ratnikov, Fedor Röhrich, Dieter de Austri, Roberto Ruiz del Árbol, Pablo Martínez Ruiz Savchenko, Oleg Simpson, Nathan Strong, Giles C. Taliercio, Angela Tosi, Mia Ustyuzhanin, Andrey Zaraket, Haitham Istituto Nazionale di Fisica Nucleare Sezione di Padova Italy Université Catholique de Louvain Belgium Scientific Computing Technische Universität Kaiserslautern Germany Università di Perugia INFN Sezione di Perugia Italy HSE University Russia Université Clermont Auvergne Laboratoire de Physique de Clermont CNRS IN2P3 France SLAC National Accelerator Laboratory United States Department of Physics and Astronomy Uppsala University Sweden Department of Computer Science University of Oxford United Kingdom Physik-Department Technische Universität München Germany Center for Technology and Transfer University of Applied Sciences Worms Germany CERN Switzerland NHETC Dept. of Physics and Astronomy Rutgers University United States Università di Napoli "Federico II" Italy Germany Università degli Studi di Padova Italy Department of Oncology and Medical Physics Haukeland University Hospital Norway Instituto de Física Corpuscular UV-CSIC Spain Department of Physics and Technology University of Bergen Norway Instituto de Física de Cantabria UC-CSIC Spain Lund University Sweden Multi-Disciplinary Physics Laboratory Optics and Fiber Optics Group Faculty of Sciences Lebanese University Lebanon Lebanon

The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a superhuman task, given the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, "experience-driven" layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized by means of a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters. In this document we lay down our plans for the design of a modular and versatile modeling tool for the end-to-end optimization of complex instruments for particle physics experiments as well as industrial and medical applications that share the detection of radiation as their basic ingredient. We consider a selected set of use cases to highlight the specific needs of different applications. Copyright © 2022, The Authors. All rights reserved.

关键词： Medical applications

Quantum Games and Interactive Tools for Quantum Technologies Outreach and Education

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arXiv 2022年

作者： Seskir, Zeki C. Migdal, Piotr Weidner, Carrie Anupam, Aditya Case, Nicky Davis, Noah Decaroli, Chiara Ercan, İlke Foti, Caterina Gora, Pawel Jankiewicz, Klementyna La Cour, Brian R. Malo, Jorge Yago Maniscalco, Sabrina Naeemi, Azad Nita, Laurentiu Parvin, Nassim Scafirimuto, Fabio Sherson, Jacob F. Surer, Elif Wootton, James Yeh, Lia Zabello, Olga Chiofalo, Marilù Karlsruhe Institute of Technology ITAS Karlstraße 11 Karlsruhe76133 Germany Quantum Flytrap ul. Ceglowska 29 Warsaw01-809 Poland Quantum Engineering Technology Laboratories H.H. Wills Physics Laboratory Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1FD United Kingdom Georgia Institute of Technology School of Literature Media and Communication 686 Cherry St NW AtlantaGA30313 United States The University of Texas at Austin Center for Quantum Research Applied Research Laboratories 10000 Burnet Rd AustinTX78758 United States National Quantum Computing Center Oxfordshire DidcotOX11 0GD United Kingdom TU Delft Department of Microelectronics Mekelweg 4 Delft2628 CD Netherlands QPlayLearn Aalto University InstituteQ - The Finnish Quantum Institute Department of Applied Physics AaltoFI-00076 11000 Finland Quantum AI Foundation Sanocka 9/103 Warsaw02-110 Poland University of Pisa Department of Physics Largo Bruno Pontecorvo 3 PisaI-56126 Italy University of Helsinki InstituteQ - The Finnish Quantum Institute Department of Physics Helsinki Finland Georgia Institute of Technology School of Electrical and Computer Engineering 777 Atlantic Drive NW AtlantaGA30332 United States Quarks Interactive Strada Bailor 93a Miercurea-Ciuc Harghita4500 Romania IBM Quantum IBM Research - Zurich Säumerstrasse 4 Rüschlikon8803 Switzerland ScienceAtHome Fuglesangs Allé 4 Aarhus8210 Denmark Aarhus University Institute for Physics and Astronomy Ny Munkegade 120 Aarhus8000 Denmark Middle East Technical University Graduate School of Informatics Department of Modeling and Simulation Üniversiteler Mah. Dumlupınar Blv. No:1 Ankara06800 Turkey University of Oxford Department of Computer Science Wolfson Building Parks Road OxfordOX1 3QD United Kingdom IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY10598 United States Offenburg University of Applied Sciences Department of Business and Industrial Eng

In this article, we provide an extensive overview of a wide range of quantum games and interactive tools that have been employed by the community in recent years. The paper presents selected tools, as described by their developers. The list includes Hello Quantum, Hello Qiskit, Particle in a Box, Psi and Delta, QPlayLearn, Virtual Lab by Quantum Flytrap, Quantum Odyssey, scienceAtHome, and The Virtual Quantum Optics Laboratory. Additionally, we present events for quantum game development: hackathons, game jams, and semester projects. Furthermore, we discuss the Quantum Technologies Education for Everyone (QUTE4E) pilot project, which illustrates an effective integration of these interactive tools with quantum outreach and education activities. Finally, we aim at providing guidelines for incorporating quantum games and interactive tools in pedagogic materials to make quantum technologies more accessible for a wider population. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum optics

A platform for high performance photon correlation measurements

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arXiv 2020年

作者： Zadeh, Iman Esmaeil Los, Johannes W.N. Gourgues, Ronan B.M. Chang, Jin Elshaari, Ali W. Zichi, Julien van Staaden, Yuri J. Swens, Jeroen Kalhor, Nima Guardiani, Antonio Meng, Yun Zou, Kai Dobrovolskiy, Sergiy Fognini, Andreas W. Schaart, Dennis R. Dalacu, Dan Poole, Philip J. Reimer, Michael E. Hu, Xiaolong Pereira, Silvania F. Zwiller, Val Dorenbos, Sander N. Optics Research Group ImPhys Department Faculty of Applied Sciences Delft University of Technology Delft2628 CJ Netherlands Single Quantum B.V. Delft2628 CJ Netherlands Optics Research Group Imphys Department Faculty of Applied Sciences Delft University of Technology Delft2628 CJ Netherlands Stockholm106 91 Sweden School of Precision Instrument and Optoelectronic Engineering Tianjin University Tianjin300072 China Key Laboratory of Optoelectronic Information Science and Technology Ministry of Education Tianjin300072 China Medical Physics & Technology Radiation Science & Technology Department Faculty of Applied Sciences Delft University of Technology National Research Council of Canada OttawaONK1A 0R6 Canada Institute for Quantum Computing Department of Electrical & Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

A broad range of scientific and industrial disciplines require precise optical measurements at very low light levels. Single-photon detectors combining high efficiency and high time resolution are pivotal in such experiments. By using relatively thick films of NbTiN (8-11 nm) and improving the pattern fidelity of the nano-structure of the superconducting nanowire single-photon detectors (SNSPD), we fabricated devices demonstrating superior performance over all previously reported detectors in the combination of efficiency and time resolution. Our findings prove that small variations in the nanowire width, in the order of a few nanometers, can lead to a significant penalty on their temporal response. Addressing these issues, we consistently achieved high time resolution (best device 7.7 ps, other devices ∼10-16 ps) simultaneously with high system detection efficiencies (80 − 90%) in the wavelength range of 780-1000 nm, as well as in the telecom bands (1310-1550 nm). The use of thicker films allowed us to fabricate large-area multi-pixel devices with homogeneous pixel performance. We first fabricated and characterized a 100 × 100 µm2 16-pixel detector and showed there was little variation among individual pixels. Additionally, to showcase the power of our platform, we fabricated and characterized 4-pixel multimode fiber-coupled detectors and carried out photon correlation experiments on a nanowire quantum dot resulting in g2(0) values lower than 0.04. The multi-pixel detectors alleviate the need for beamsplitters and can be used for higher order correlations with promising prospects not only in the field of quantum optics, but also in bio-imaging applications, such as fluorescence microscopy and positron emission tomography. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum optics

Electron-phonon coupling in d-electron solids: A temperature-dependent study of rutile TiO2 by first-principles theory and two-photon photoemission

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arXiv 2020年

作者： Shang, Honghui Argondizzo, Adam Tan, Shijing Zhao, Jin Rinke, Patrick Carbogno, Christian Scheffler, Matthias Petek, Hrvoje Fritz-Haber-Institut der Max-Planck-Gesellschaft Faradayweg 46 Berlin-DahlemD-14195 Germany Department of Physics and Astronomy Pittsburgh Quantum Institute University of Pittsburgh PittsburghPA15260 United States Department of Physics University of Science and Technology of China Hefei230026 China Department of Applied Physics Aalto University P.O. Box 11100 AaltoFI-00076 Finland State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

Rutile TiO2 is a paradigmatic transition-metal oxide with applications in optics, electronics, photocatalysis, etc., that are subject to pervasive electron-phonon interaction. To understand how energies of its electronic bands, and in general semiconductors or metals where the frontier orbitals have a strong d-band character, depend on temperature, we perform a comprehensive theoretical and experimental study of the effects of electron-phonon (e-p) interactions. In a two-photon photoemission (2PP) spectroscopy study we observe an unusual temperature dependence of electronic band energies within the conduction band of reduced rutile TiO2, which is contrary to the well-understood sp-band semiconductors and points to a so far unexplained dichotomy in how the e-p interactions affect differently the materials where the frontier orbitals are derived from the sp- and d orbitals. To develop a broadly applicable model, we employ state-of-the-art first-principles calculations that explain how phonons promote interactions between the Ti-3d orbitals of the conduction band within the octahedral crystal field. The characteristic difference in e-p interactions experienced by the Ti-3d orbitals of rutile TiO2 crystal lattice are contrasted with the more familiar behavior of the Si-2s orbitals of stishovite SiO2 polymorph, in which the frontier 2s orbital experiences a similar crystal field with the opposite effect. The findings of this analysis of how e-p interactions affect the d- and sp-orbital derived bands can be generally applied to related materials in a crystal field. The calculated temperature dependence of d-orbital derived band energies agrees well with and explains the temperature-dependent inter-d-band transitions recorded in 2PP spectroscopy of TiO2. The general understanding of how e-pinteractions affect d-orbital derived bands is likely to impact the understanding of temperature-dependent properties of highly correlated materials. Copyright © 2020, The Authors. All r

关键词： Temperature distribution

Emerging Research in the Security of Modern and Autonomous Vehicles

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Emerging Research in the Security of Modern and Autonomous V...

IEEE International Conference on Electro Information Technology

作者： Samir Tout Munther Abualkibash Pooja Patil School of Information Security & Applied Computing Department of Computer Science Eastern Michigan University

The last decade has witnessed considerable advancements in automating modern "connected" and Autonomous Vehicles (AVs), which are becoming an integral part of the modern transportation systems. Such advancements have been attributed to major strides in Machine Learning, Artificial Intelligence and processing technology. More importantly, the complexity of such systems and their lack of built-in security have brought to the spotlight the need for extensive research to understand the associated risks and propose mitigations for them. In this paper we briefly discuss the security aspects of modern vehicles and provide a concise literature review of the work that has been done in this domain. We focus on specific areas that are of interest to us and conclude by providing a plan for future related endeavors.

关键词： Vehicle Autonomous Security Networks Hacking