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arXiv 2022年

作者： Cardani, L. Colantoni, I. Cruciani, A. De Dominicis, F. D’Imperio, G. Laubenstein, M. Mariani, A. Pagnanini, L. Pirro, S. Tomei, C. Casali, N. Ferroni, F. Frolov, D. Gironi, L. Grassellino, A. Junker, M. Kopas, C. Lachman, E. McRae, C.R.H. Mutus, J. Nastasi, M. Pappas, D.P. Pilipenko, R. Sisti, M. Pettinacci, V. Romanenko, A. Van Zanten, D. Vignati, M. Withrow, J.D. Zhelev, N.Z. INFN Sezione di Roma P.le Aldo Moro 2 RomeI-00185 Italy Consiglio Nazionale delle Ricerche Istituto di Nanotecnologia c/o Dip. Fisica Sapienza Università di Roma Rome00185 Italy Gran Sasso Science Institute L’Aquila67100 Italy INFN Laboratori Nazionali del Gran Sasso AQ AssergiI-67100 Italy Department of Physics and Engineering Physics Astronomy Queen’s University Kingston KingstonONK7L 3N6 Canada Fermi National Accelerator Laboratory BataviaIL60510 United States Dipartimento di Fisica Università di Milano-Bicocca MilanoI-20126 Italy INFN Sezione di Milano-Bicocca MilanoI-20126 Italy Rigetti Computing 2919 Seventh Street BerkeleyCA94710 United States National Institute of Standards and Technology BoulderCO80305 United States Department of Physics University of Colorado BoulderCO80309 United States Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States Dipartimento di Fisica Sapienza Università di Roma P.le Aldo Moro 2 RomeI-00185 Italy Physics Department University of Florida United States Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL60208 United States

Radioactivity was recently discovered as a source of decoherence and correlated errors for the real-world implementation of superconducting quantum processors. In this work, we measure levels of radioactivity present in a typical laboratory environment (from muons, neutrons, and γ-rays emitted by naturally occurring radioactive isotopes) and in the most commonly used materials for the assembly and operation of state-of-the-art superconducting qubits. We present a GEANT-4 based simulation to predict the rate of impacts and the amount of energy released in a qubit chip from each of the mentioned sources. We finally propose mitigation strategies for the operation of next-generation qubits in a radiopure environment. Copyright © 2022, The Authors. All rights reserved.

关键词： Radioactivity

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Jamming and force distribution in growing epithelial tissue

arXiv

引用

arXiv 2020年

作者： Madhikar, Pranav Åström, Jan Baumeier, Björn Karttunen, Mikko Department of Mathematics and Computer Science Institute for Complex Molecular Systems Eindhoven University of Technology Eindhoven5600 MB Netherlands CSC Scientific Computing Ltd Kägelstranden 14 Esbo02150 Finland Department of Chemistry The University of Western Ontario 1151 Richmond Street LondonONN6A5B7 Canada Department of Applied Mathematics The University of Western Ontario 1151 Richmond Street LondonONN6A5B7 Canada The Centre for Advanced Materials and Biomaterials Research The University of Western Ontario 1151 Richmond Street LondonONN6A3K7 Canada

We investigate morphologies of proliferating cellular tissues using a newly developed numerical simulation model for mechanical cell division and migration in 2D. The model is applied to a bimodal mixture consisting of stiff cells with a low growth potential and soft cells with a high growth potential;cancer cells are typically considered to be softer than healthy cells. In an even mixture, the soft cells develop into a tissue matrix and the stiff cells into a dendrite-like network structure. When soft cells are placed inside a tissue consisting of stiff cells (to model cancer growth), the soft cells develop to a fast growing tumor-like structure that gradually evacuates the stiff cell matrix. The model also demonstrates 1) how soft cells orient themselves in the direction of the largest effective stiffness as predicted by the theory of Bischofs and Schwarz (Proc. Natl. Acad. Sci U.S.A., 100, 9274-9279 (2003) and 2) that the orientation and force generation continue a few cell rows behind the soft-stiff interface. With increasing inter-cell friction, tumor growth slows down and cell death occurs. The contact force distribution between cells is demonstrated to be highly sensitive to cell type mixtures and cell-cell interactions, which indicates that local mechanical forces can be useful as a regulator of tissue formation. The results shed new light on established experimental data. Copyright © 2020, The Authors. All rights reserved.

关键词： Mixtures

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Roadmap on Atomic-scale Semiconductor Devices

arXiv

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arXiv 2025年

作者： Schofield, Steven R. Fisher, Andrew J. Ginossar, Eran Lyding, Joseph W. Silver, Richard Fei, Fan Namboodiri, Pradeep Wyrick, Jonathan Masteghin, M.G. Cox, D.C. Murdin, B.N. Clowes, S.K. Keizer, Joris G. Simmons, Michelle Y. Stemp, Holly G. Morello, Andrea Voisin, Benoit Rogge, Sven Wolkow, Robert A. Livadaru, Lucian Pitters, Jason Stock, Taylor J.Z. Curson, Neil J. Butera, Robert E. Pavlova, Tatiana V. Jakob, A.M. Spemann, D. Räcke, P. Schmidt-Kaler, F. Jamieson, D.N. Pratiush, Utkarsh Duscher, Gerd Kalinin, Sergei V. Kazazis, Dimitrios Constantinou, Procopios Aeppli, Gabriel Ekinci, Yasin Owen, James H.G. Fowler, Emma Moheimani, S.O. Reza Randall, John N. Misra, Shashank Ivie, Jeffrey Allemang, Christopher R. Anderson, Evan M. Bussmann, Ezra Campbell, Quinn Gao, Xujiao Lu, Tzu-Ming Schmucker, Scott W. London Centre for Nanotechnology University College London 17-19 Gordon St WC1H 0AH United Kingdom Department of Physics and Astronomy University College London WC1E 6BT United Kingdom School of Mathematics and Physics University of Surrey United Kingdom Department of Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States Atom Scale Device Group National Institute of Standards and Technology GaithersburgMD20899 United States Advanced Technology Institute University of Surrey GU2 7XH United Kingdom School of Physics University of New South Wales Sydney Australia School of Electrical Engineering & Telecommunications UNSW Sydney Australia Silicon Quantum Computing Pty Ltd Sydney Australia Australia University of Alberta Department of Physics EdmontonT6G 2E1 Canada National Research Council of Canada Quantum and Nanotechnologies Research Centre 11421 Saskatchewan Drive NW EdmontonT6G 2M9 Canada Department of Electronic and Electrical Engineering University College London WC1E 7JE United Kingdom Laboratory for Physical Sciences University of Maryland College ParkMD20740 United States Prokhorov General Physics Institute The Russian Academy of Sciences Vavilov str. 38 Moscow119991 Russia School of Physics The University of Melbourne ParkvilleVIC3010 Australia Leipzig04318 Germany Universität Leipzig Felix Bloch Institute for Solid State Physics Applied Quantum Systems Leipzig04103 Germany QUANTUM Institut für Physik Johannes Gutenberg-Universität Mainz Mainz55128 Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Paul Scherrer Institute Villigen5232 Switzerland Zürich8093 Switzerland Zyvex Labs 1301 N. Plano Road RichardsonTX75081 United States University of Texas DallasTX United States Sandia National Laboratories 1515 Eubank Blvd. SE AlbuquerqueNM87185 United States

Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing technologies. The proposal to use nuclear and electronic spins of donor atoms in silicon, introduced by Kane in 1998, sparked a new research field focused on the precise positioning of individual impurity atoms for quantum devices, utilising scanning tunnelling microscopy and ion implantation. This roadmap article reviews the advancements in the 25 years since Kane’s proposal, the current challenges, and the future directions in atomic-scale semiconductor device fabrication and measurement. It covers the quest to create a silicon-based quantum computer and expands to include diverse material systems and fabrication techniques, highlighting the potential for a broad range of semiconductor quantum technological applications. Key developments include phosphorus in silicon devices such as single-atom transistors, arrayed few-donor devices, one- and two-qubit gates, three-dimensional architectures, and the development of a toolbox for future quantum integrated circuits. The roadmap also explores new impurity species like arsenic and antimony for enhanced scalability and higher-dimensional spin systems, new chemistry for dopant precursors and lithographic resists, and the potential for germanium-based devices. Emerging methods, such as photon-based lithography and electron beam manipulation, are discussed for their disruptive potential. This roadmap charts the path toward scalable quantum computing and advanced semiconductor quantum technologies, emphasising the critical intersections of experiment, technological development, and theory. © 2025, CC BY.

关键词： Qubits

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Lattice QCD and Particle Physics

arXiv

引用

arXiv 2022年

作者： Kronfeld, Andreas S. Bhattacharya, Tanmoy Blum, Thomas Christ, Norman H. DeTar, Carleton Detmold, William Edwards, Robert Hasenfratz, Anna Lin, Huey-Wen Mukherjee, Swagato Orginos, Konstantinos Brower, Richard Cirigliano, Vincenzo Davoudi, Zohreh Jóo, Bálint Jung, Chulwoo Lehner, Christoph Meinel, Stefan Neil, Ethan T. Petreczky, Peter Richards, David G. Bazavov, Alexei Catterall, Simon Dudek, Jozef J. El-Khadra, Aida X. Engelhardt, Michael Fleming, George T. Giedt, Joel Gupta, Rajan Hansen, Maxwell T. Izubuchi, Taku Karsch, Frithjof Laiho, Jack Liu, Keh-Fei Meyer, Aaron S. Rinaldi, Enrico Savage, Martin Schaich, David Shanahan, Phiala E. Sharpe, Stephen R. Sufian, Raza Syritsyn, Sergey Van de Water, Ruth S. Wagman, Michael L. Weinberg, Evan Witzel, Oliver Aubin, Christopher Boyle, Peter Chandrasekharan, Shailesh Cloët, Ian C. Constantinou, Martha Cushman, Kimmy DeGrand, Thomas Fodor, Zoltan Foreman, Sam Gottlieb, Steven Hoying, Daniel Jang, Yong-Chull Jay, William I. Jin, Xiao-Yong Kelly, Christopher Kuti, Julius Lamm, Henry Lin, Meifeng Lin, Yin Lytle, Andrew T. Mackenzie, Paul Mandula, Jeffrey Meurice, Yannick Monahan, Christopher Morningstar, Colin Osborn, James C. Park, Sungwoo Simone, James N. Strelchenko, Alexei Tomii, Masaaki Vaquero, Alejandro Vranas, Pavlos Wang, Bigeng Wilcox, Walter Yoon, Boram Zhao, Yong Theory Division Fermi National Accelerator Laboratory BataviaIL60510 United States Group T-2 Los Alamos National Laboratory Los AlamosNM87545 United States Department of Physics University of Connecticut StorrsCT06269 United States RIKEN BNL Research Center Brookhaven National Laboratory UptonNY11973 United States Department of Physics Columbia University New YorkNY10027 United States Department of Physics and Astronomy University of Utah Salt Lake CityUT84112 United States Center for Theoretical Physics Massachusetts Institute of Technology CambridgeMA02139 United States The NSF Institute for Artificial Intelligence and Fundamental Interactions Theory Center Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States Department of Physics University of Colorado BoulderCO80309 United States Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Physics Department Brookhaven National Laboratory UptonNY11973 United States Department of Physics College of William & Mary WilliamsburgVA23187 United States Department of Physics Center for Computational Science Boston University BostonMA02215 United States Institute of Nuclear Theory University of Washington SeattleWA98195 United States Department of Physics Maryland Center for Fundamental Physics University of Maryland College ParkMD20742 United States Oak Ridge Leadership Computing Facility Oak Ridge National Laboratory Oak RidgeTN37831 United States Fakultät für Physik Universität Regensburg RegensburgD-93040 Germany Department of Physics University of Arizona TucsonAZ85721 United States Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Physics Syracuse University SyracuseNY13244 United States Department of Physics University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Physics New Mexic

Lattice field theory provides a mathematically rigorous definition of quantum field theory, including gauge theories. The rigor provides a platform for computation of strongly-coupled gauge theories, not only quantum chromodynamics (QCD) at long-distances but also strongly-coupled sectors that might lie beyond the Standard Model (BSM) of particle physics. Indeed, the interpretation of many experiments in particle physics, nuclear physics, and astrophysics relies, often crucially, on results from lattice QCD or BSM. In quark-flavor physics, lattice QCD is essential for grounding theoretical predictions. Together with experimental measurements, lattice QCD is used to determine many of the fundamental parameters of the Standard Model's flavor sector: five out of six quark masses and the three mixing angles and CP-violating phase of the Cabibbo-Kobayashi-Maskawa (CKM) matrix. Further Standard-Model predictions requiring lattice QCD are for processes that could reveal signatures of new physics. This area of lattice QCD has become a precision science, as has the determination of the strong coupling, αs, which is key in many areas, for example for understanding Higgs-boson decay to gluons. Lattice-QCD calculations of the hadronic contributions to the anomalous magnetic moment of the muon are another area for which precision is both mandatory and achievable. While these contributions can be estimated via a combination of certain measurements and general theoretical concepts, a direct ab initio calculation from QCD is desirable to confirm robustly the tantalizingly large discrepancy between experiment and the Standard Model. Other indirect searches for new physics are complementary to quark-flavor physics and the muon anomalous magnetic moment. Lattice QCD is an essential tool for understanding newly discovered hadrons with quark content different from the usual baryons and mesons. Lattice-QCD calculations are needed to interpret bounds on electric dipole moments, proton dec

关键词： Calculations

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DESIGNING AND IMPLEMENTING AN ARABIC PROGRAMMING LANGUAGE FOR TEACHING PUPILS

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Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University 2019年第3期54卷

作者： Razaq, Hussam Hatem Abdul Gaser, Ayedh Shahadha Mohammed, Mazin Abed Yassen, Esam Taha Mostafad, Salama A. Zeebaree, Subhi R.M. Ibrahim, Dheyaa Ahmed Abd Ghania, Mohd Khanapi Farhan, Rabah N. College of Computer Science & Information Technology University of Anbar Anbar Iraq Information Technology Centre University of Anbar Anbar Iraq Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor86400 Malaysia Duhok Polytechnic University Tishk International University Duhok Erbil Iraq Computer Engineering Techniques Department Imam Ja'afar Al-Sadiq University Baghdad Iraq Biomedical Computing and Engineering Technologies Applied Research Group Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka Melaka Malaysia

Observation has been made that in Arab countries, students find it challenging to learn to program in a different language other than Arabic. Existing literature contains only a few Arabic programming languages, most of which have never been or have partially been executed. In this article, a novel Arabic programming language known as Alf..Eih language is proposed. The proposed programming language is to be used in teaching pupils and schoolchildren in Arabic countries programming. This Arabic Programming language converts the Arabic language presumed to code in (C++ language) with its implementation. After the code written in Arabic passes through the first three stages of compiler (lexical, syntax and semantic), the final phase converts code to (C++). Alf..Eih language covers many of the directives in the presumed Arabic Language such as, header file, functions, if condition, loops and etc. © 2019 science Press. All rights reserved.

关键词： Semantics

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Optically-heralded entanglement of superconducting systems in quantum networks

arXiv

引用

arXiv 2020年

作者： Krastanov, Stefan Raniwala, Hamza Holzgrafe, Jeffrey Jacobs, Kurt Lončar, Marko Reagor, Matthew J. Englund, Dirk R. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States U.S. Army Research Laboratory Computational and Information Sciences AdelphiMD20783 United States Department of Physics University of Massachusetts at Boston BostonMA02125 United States Rigetti Computing 775 Heinz Ave BerkeleyCA94710 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

Networking superconducting quantum computers is a longstanding challenge in quantum science. The typical approach has been to cascade transducers: converting to optical frequencies at the transmitter and to microwave frequencies at the receiver. However, the small microwave-optical coupling and added noise have proven formidable obstacles. Instead, we propose optical networking via heralding end-to-end entanglement with one detected photon and teleportation. This new protocol can be implemented on standard transduction hardware, while providing significant performance improvements over transduction. In contrast to cascaded direct transduction, our scheme absorbs the low optical-microwave coupling efficiency into the heralding step, thus breaking the rate-fidelity trade-off. Moreover, this technique unifies and simplifies entanglement generation between superconducting devices and other physical modalities in quantum networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Economic and social effects

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Multivariate Deep Causal Network for Time Series Forecasting in Interdependent Networks 57

Multivariate Deep Causal Network for Time Series Forecasting...

引用

57th IEEE Conference on Decision and Control, CDC 2018

作者： Madhavi, K. S. Lalitha Gilanifar, Mostafa Zhou, Yuxun Ozguven, Eren E. Arghandeh, Reza Department of Industrial and Manufacturing Eng Department of Civil and Environmental Eng Florida State University Department of Electrical Eng TallahasseeFL32310 United States Computer Science Dept University of California Department of Electrical Eng BerkeleyCA94720 United States Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Norway

ISBN: (纸本)9781538613955

A novel multivariate deep causal network model (MDCN) is proposed in this paper, which combines the theory of conditional variance and deep neural networks to identify the cause-effect relationship between different interdependent time-series. The MCDN validation is conducted by a double step approach. The self validation is performed by information theory - based metrics, and the cross validation is achieved by a foresting application that combines the actual interdependent electricity, transportation, and weather datasets in the City of Tallahassee, Florida, USA. © 2018 IEEE.

关键词： Information theory

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Khuri-Treiman analysis of J/ψ → π+π−π0

arXiv

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arXiv 2023年

作者： Albaladejo, M. Gonzàlez-Solís, S. Bibrzycki, L. Fernández-Ramírez, C. Hammoud, N. Mathieu, V. Mikhasenko, M. Montaña, G. Perry, R.J. Pilloni, A. Rodas, A. Smith, W.A. Szczepaniak, A. Winney, D. Centro Mixto CSIC-Universidad de Valencia ValenciaE-46071 Spain Theoretical Division Los Alamos National Laboratory Los AlamosNM87545 United States AGH University of Krakow Faculty of Physics and Applied Computer Science al. Adama Mickiewicza 30 Kraków30-059 Poland MadridE-28040 Spain Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico Institute of Nuclear Physics Polish Academy of Sciences Kraków31-342 Poland Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona E08028 Spain Departamento de Física Teórica Universidad Complutense de Madrid IPARCOS Madrid28040 Spain ORIGINS Excellence Cluster Garching85748 Germany Ludwig-Maximilians-Universität Munich80539 Germany Theory Center Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States Dipartimento di Scienze Matematiche e Informatiche Scienze Fisiche e Scienze della Terra Uni-versità degli Studi di Messina MessinaI-98122 Italy INFN Sezione di Catania CataniaI-95123 Italy Department of Physics Indiana University BloomingtonIN47405 United States Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China

We study the decay J/ψ → π+π−π0 within the framework of the Khuri-Treiman equations. We find that the BESIII experimental di-pion mass distribution in the ρ(770)-region is well reproduced with a once-subtracted P-wave amplitude. Furthermore, we show that F-wave contributions to the amplitude improve the description of the data in the ππ mass region around 1.5 GeV. We also present predictions for the J/ψ → π0γ∗ transition form factor. © 2023, CC BY.

关键词： Seismic waves

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Dynamics in near-threshold J/ψ photoproduction

arXiv

引用

arXiv 2023年

作者： Winney, D. Fernández-Ramírez, C. Pilloni, A. Blin, A.N. Hiller Albaladejo, M. Bibrzycki, L. Hammoud, N. Liao, J. Mathieu, V. Montaña, G. Perry, R.J. Shastry, V. Smith, W.A. Szczepaniak, A.P. Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China MadridE-28040 Spain Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico Dipartimento di Scienze Matematiche e Informatiche Scienze Fisiche e Scienze della Terra Università degli Studi di Messina MessinaI-98166 Italy INFN Sezione di Catania CataniaI-95123 Italy Institute for Theoretical Physics Regensburg University RegensburgD-93040 Germany Institute for Theoretical Physics Tübingen University TübingenD-72076 Germany Centro Mixto CSIC-Universidad de Valencia ValenciaE-46071 Spain AGH University of Krakow Faculty of Physics and Applied Computer Science KrakówPL-30-059 Poland Institute of Nuclear Physics Polish Academy of Sciences Kraków31-342 Poland Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Department of Physics Indiana University BloomingtonIN47405 United States Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona E-08028 Spain Departamento de Física Teórica Universidad Complutense de Madrid IPARCOS MadridE-28040 Spain Theory Center Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States Institute of Physics Jan Kochanowski University KielcePL-25-406 Poland

The study of J/ψ photoproduction at low energies has consequences for the understanding of multiple aspects of nonperturbative QCD, ranging from mechanical properties of the proton, to the binding inside nuclei, and the existence of hidden-charm pentaquarks. Factorization of the photon-cc¯ and nucleon dynamics or Vector Meson Dominance are often invoked to justify these studies. Alternatively, open-charm intermediate states have been proposed as the dominant mechanism underlying J/ψ photoproduction. As the latter violates this factorization, it is important to estimate the relevance of such contributions. We analyse the latest differential and integrated photoproduction cross sections from the GlueX and J/ψ–007 experiments. We show that the data can be adequately described by a small number of partial waves, which we parameterize with generic models enforcing low-energy unitarity. The results suggest a nonnegligible contribution from open-charm intermediate states. Furthermore, most of the models present an elastic scattering length incompatible with previous extractions based on Vector Meson Dominance, and thus call into question its applicability to heavy mesons. Our results indicate a wide array of physics possibilities that are compatible with present data and need to be disentangled. Copyright © 2023, The Authors. All rights reserved.

关键词： Factorization

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AI-based Reconstruction for Fast MRI – A Systematic Review and Meta-analysis

arXiv

引用

arXiv 2021年

作者： Chen, Yutong Schönlieb, Carola-Bibiane Liò, Pietro Leiner, Tim Dragotti, Pier Luigi Wang, Ge Rueckert, Daniel Firmin, David Yang, Guang National Heart & Lung Institute Imperial College London LondonSW3 6NP United Kingdom Cardiovascular Research Centre Royal Brompton Hospital LondonSW3 6NP United Kingdom Faculty of Biology University of Cambridge CambridgeCB2 1RX United Kingdom Department of Applied Mathematics and Theoretical Physics University of Cambridge CambridgeCB3 0WA United Kingdom Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom Utrecht University Medical Centre Utrecht3584 CX Netherlands Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2BU United Kingdom Biomedical Imaging Center Rensselaer Polytechnic Institute TroyNY12180 United States Department of Computing Imperial College London LondonSW7 2BU United Kingdom Institute for Medical Informatics Statistics and Epidemiology Technical University of Munich Munich81675 Germany

Compressed sensing (CS) has been playing a key role in accelerating the magnetic resonance imaging (MRI) acquisition process. With the resurgence of artificial intelligence, deep neural networks and CS algorithms are being integrated to redefine the state of the art of fast MRI. The past several years have witnessed substantial growth in the complexity, diversity, and performance of deep learning-based CS techniques that are dedicated to fast MRI. In this meta-analysis, we systematically review the deep learning-based CS techniques for fast MRI, describe key model designs, highlight breakthroughs, and discuss promising directions. We have also introduced a comprehensive analysis framework and a classification system to assess the pivotal role of deep learning in CS-based acceleration for MRI. © 2021, CC BY-NC-ND.

关键词： Compressed sensing

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