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Real-Time Decoding for Fault-Tolerant quantum computing: Progress, Challenges and Outlook

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arXiv 2023年

作者： Battistel, Francesco Chamberland, Christopher Johar, Kauser Overwater, Ramon W.J. Sebastiano, Fabio Skoric, Luka Ueno, Yosuke Usman, Muhammad Qblox Elektronicaweg 10 Delft2628 XG Netherlands AWS Center for Quantum Computing PasadenaCA91125 United States IQIM California Institute of Technology PasadenaCA91125 United States Riverlane Ltd Cambridge United Kingdom QuTech Department of Quantum and Computer Engineering Delft University of Technology Delft2600 GA Netherlands Graduate School of Information Science and Technology The University of Tokyo Tokyo Japan Department of Computer Engineering Technical University of Munich Garching Germany School of Physics The University of Melbourne Parkville3010 Australia Data61 CSIRO Clayton3168 Australia

quantum computing is poised to solve practically useful problems which are computationally intractable for classical supercomputers. However, the current generation of quantum computers are limited by errors that may only partially be mitigated by developing higher-quality qubits. quantum error correction (QEC) will thus be necessary to ensure fault tolerance. QEC protects the logical information by cyclically measuring syndrome information about the errors. An essential part of QEC is the decoder, which uses the syndrome to compute the likely effect of the errors on the logical degrees of freedom and provide a tentative correction. The decoder must be accurate, fast enough to keep pace with the QEC cycle (e.g., on a microsecond timescale for superconducting qubits) and with hard real-time system integration to support logical operations. As such, real-time decoding is essential to realize fault-tolerant quantum computing and to achieve quantum advantage. In this work, we highlight some of the key challenges facing the implementation of real-time decoders while providing a succinct summary of the progress to-date. Furthermore, we lay out our perspective for the future development and provide a possible roadmap for the field of real-time decoding in the next few years. As the quantum hardware is anticipated to scale up, this perspective article will provide a guidance for researchers, focusing on the most pressing issues in real-time decoding and facilitating the development of solutions across quantum and computer science. Copyright © 2023, The Authors. All rights reserved.

关键词： Fault tolerance

Impact of vegetation albedo on the habitability of Earth-like exoplanets

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arXiv 2024年

作者： Bisesi, Erica Murante, Giuseppe Provenzale, Antonello Biasiotti, Lorenzo von Hardenberg, Jost Ivanovski, Stavro Maris, Michele Monai, Sergio Silva, Laura Simonetti, Paolo Vladilo, Giovanni INAF − Astronomical Observatory of Trieste Via G. Tiepolo 11 Trieste34143 Italy CNR − Institute of Geosciences and Earth Resources via G. Moruzzi 1 Pisa56124 Italy Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34151 Italy ICSC − National Research Center in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 BO Casalecchio di Reno40033 Italy University of Trieste Piazzale Europa 1 Trieste34127 Italy Polytechnic University of Turin − DIATI Corso Duca degli Abruzzi 24 Turin10129 Italy CNR − Institute of Atmospheric Science and Climate Corso Fiume 4 Turin10133 Italy

Vegetation can modify the planetary surface albedo via the Charney mechanism, as plants are usually darker than the bare surface of the continents. We updated ESTM (Earth-like Surface Temperature Model) to incorporate the presence, distribution and evolution of two dynamically competing vegetation types that resemble grasslands and trees (the latter in the double stages of life: adults and seedlings). The newly developed model was applied to estimate how the climate-vegetation system reaches equilibrium across different rocky planetary configurations, and to assess its impact on temperature and habitability. With respect to a world with bare granite continents, the effect of vegetation-albedo feedback is to increase the average surface temperature. Since grasses and trees exhibit different albedos, they affect temperature to different degrees. The ultimate impact on climate depends on the outcome of the competition between these vegetation types. The change in albedo due to vegetation extends the habitable zone and enhances the overall planetary habitability beyond its traditional outer edge. This effect is especially relevant for planets that have a larger extension of continents than Earth. For Earth, the semi-major axis d = 1.04 UA represents the turning point where vegetation enhances habitability from h = 0.0 to h = 0.485 (in the grass-dominance case), to h = 0.584 (in the case of coexistence between grasses and trees), and to h = 0.612 (in the tree-dominance case). This illustrates the transition from a snowball state to a planet with intermediate habitability at the outer edge of the circumstellar habitability zone. Copyright © 2024, The Authors. All rights reserved.

关键词： Vegetation

Nonreciprocal coherent coupling of nanomagnets by exchange spin waves

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Nano Research 2021年第7期14卷 2133-2138页

作者： Hanchen Wang Jilei Chen Tao Yu Chuanpu Liu Chenyang Guo Song Liu Ka Shen Hao Jia Tao Liu Jianyu Zhang Marco A.Cabero Z Qiuming Song Sa Tu Mingzhong Wu Xiufeng Han Ke Xia Dapeng Yu Gerrit E.W.Bauer Haiming Yu Fert Beijing Institute School of Integrated Circuit Science and EngineeringBeijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China Max Planck Institute for the Structure and Dynamics of Matter 22761 HamburgGermany Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsUniversity of Chinese Academy of SciencesChinese Academy of SciencesBeijing 100190China Shenzhen Institute for Quantum Science and Engineering(SIQSE) and Department of PhysicsSouthern University of Science and Technology(SUSTech)Shenzhen 518055China Department of Physics Beijing Normal UniversityBeijing 100875China Department of Physics Colorado State UniversityFort CollinsColorado 80523USA Kavli Institute of Nanoscience Delft University of Technology2628 CJ DelftThe Netherlands Institute for Materials Research WPI-AIMR and CSNRTohoku UniversitySendai 980-8577Japan Zernike Institute for Advanced Materials University of GroningenGroningenNijenborgh 49747 AG GroningenThe Netherlands

Nanomagnets are widely used to store information in non-volatile spintronic *** waves can transfer information with low-power consumption as their propagations are independent of charge ***,to dynamically couple two distant nanomagnets via spin waves remains a major challenge for *** we experimentally demonstrate coherent coupling of two distant Co nanowires by fast propagating spin waves in an yttrium iron garnet thin film with sub-50 nm *** in two nanomagnets are unidirectionally phase-locked with phase shifts controlled by magnon spin torque and spin-wave *** coupled system is finally formulated by an analytical theory in terms of an effective non-Hermitian *** results are attractive for analog neuromorphic computing that requires unidirectional information transmission.

关键词： spintronics nanomagnets spin waves coherent coupling nonreciprocity

Entanglement-Induced Barren Plateaus

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PRX quantum 2021年第4期2卷 040316-040316页

作者： Carlos Ortiz Marrero Mária Kieferová Nathan Wiebe Data Sciences and Analytics Group Pacific Northwest National Laboratory Richland Washington 99354 USA Centre for Quantum Computation and Communication Technology Centre for Quantum Software and Information University of Technology Sydney New South Wales 2007 Australia Department of Computer Science University of Toronto Ontario M5S 1A1 Canada High Performance Computing Group Pacific Northwest National Laboratory Richland Washington 99354 USA

We argue that an excess in entanglement between the visible and hidden units in a quantum neural network can hinder learning. In particular, we show that quantum neural networks that satisfy a volume law in the entanglement entropy will give rise to models that are not suitable for learning with high probability. Using arguments from quantum thermodynamics, we then show that this volume law is typical and that there exists a barren plateau in the optimization landscape due to entanglement. More precisely, we show that for any bounded objective function on the visible layers, the Lipshitz constants of the expectation value of that objective function will scale inversely with the dimension of the hidden subsystem with high probability. We show how this can cause both gradient-descent and gradient-free methods to fail. We note that similar problems can happen with quantum Boltzmann machines, although stronger assumptions on the coupling between the hidden and/or visible subspaces are necessary. We highlight how pretraining such generative models may provide a way to navigate these barren plateaus.

关键词： Machine learning quantum algorithms

Electron-Induced Nonmonotonic Pressure Dependence of the Lattice Thermal Conductivity of θ-TaN

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Physical Review Letters 2024年第11期132卷 116301-116301页

作者： Ashis Kundu Yani Chen Xiaolong Yang Fanchen Meng Jesús Carrete Mukul Kabir Georg K. H. Madsen Wu Li Institute for Advanced Study Shenzhen University Shenzhen 518060 China Department of Physics Indian Institute of Science Education and Research (IISER) Pune P.O. 411008 India Eastern Institute for Advanced Study Eastern Institute of Technology Ningbo 315200 China College of Physics and Center of Quantum Materials and Devices Chongqing University Chongqing 401331 China Research Computing and Data Clemson University Clemson South Carolina 29634 USA Center for Functional Nanomaterials Brookhaven National Laboratory Upton New York 11973 United States Instituto de Nanociencia y Materiales de Aragón (INMA) CSIC-Universidad de Zaragoza E-50009 Zaragoza Spain Institute of Materials Chemistry TU Wien A-1060 Vienna Austria

Recent theoretical and experimental research suggests that θ-TaN is a semimetal with high thermal conductivity (κ), primarily due to the contribution of phonons (κph). By using first-principles calculations, we show a nonmonotonic pressure dependence of the κ of θ-TaN. κph first increases until it reaches a maximum at around 60 GPa, and then decreases. This anomalous behavior is a consequence of the competing pressure responses of phonon-phonon and phonon-electron interactions, in contrast to the known materials BAs and BP, where the nonmonotonic pressure dependence is caused by the interplay between different phonon-phonon scattering channels. Although TaN has phonon dispersion features similar to BAs at ambient pressure, its response to pressure is different and an overall stiffening of the phonon branches takes place. Consequently, the relevant phonon-phonon scattering weakens as pressure increases. However, the increased electronic density of states near the Fermi level, and specifically the emergence of additional pockets of the Fermi surface at the high-symmetry L point in the Brillouin zone, leads to a substantial increase in phonon-electron scattering at high pressures, driving a decrease in κph. At intermediate pressures (∼20–70 GPa), the κ of TaN surpasses that of BAs. Our Letter provides deeper insight into phonon transport in semimetals and metals where phonon-electron scattering is relevant.

关键词： Electron-phonon coupling High-pressure studies Lattice dynamics Lattice thermal conductivity Nitrides Semimetals Boltzmann theory First-principles calculations

Cancelable finger vein authentication using multidimensional scaling based on deep learning

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Egyptian Informatics Journal 2025年 30卷

作者： Mohamed Hammad Mohammed ElAffendi Ahmed A. Abd El-Latif EIAS Data Science Lab College of Computer and Information Sciences and Center of Excellence in Quantum and Intelligent Computing Prince Sultan University Riyadh 11586 Saudi Arabia Department of Information Technology Faculty of Computers and Information Menoufia University Shibin El Kom 32511 Egypt Department of Mathematics and Computer Science Faculty of Science Menoufia University 32511 Egypt

In the field of identity verification and identification, biometrics has evolved as a reliable approach for identifying individuals based on their unique physical or behavioral characteristics. The utilization of finger vein authentication has generated significant attention as a biometric modality owing to its strong resilience, resistance against spoofing attacks, and consistent patterns. In this work, we proposed a novel cancelable finger vein authentication system using multidimensional scaling (MDS) based on deep learning. Our method addressed the limitations of previous biometric authentication systems by integrating MDS with a lightweight convolutional neural network (CNN) model for feature extraction. The cancelable approach ensured privacy and security by generating distinct templates for each user. We evaluated our system on three publicly available datasets for finger veins using various performance metrics, including accuracy, precision, recall, and equal error rate (EER). The results demonstrated the effectiveness of our method, which achieved high accuracy, low error rates, and strong performance in diversity and irreversibility tests. Additionally, our system maintained high authentication accuracy while preserving user privacy, making it suitable for practical applications in biometric authentication.

关键词： Authentication Cancelable Deep Learning Finger Vein Multidimensional Scaling

Counting stabilizer codes for arbitrary dimension

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arXiv 2022年

作者： Singal, Tanmay Chiang, Che Hsu, Eugene Kim, Eunsang Goan, Hsi-Sheng Hsieh, Min-Hsiu Institute of Physics Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University GrudziĄdzka 5/7 Toruń87-100 Poland Department of Physics Center for Theoretical Physics National Taiwan University Taipei10617 Taiwan Quantum information center Chung Yuan Christian University No. 200 Zhongbei Rd. Zhongli Dist. Taoyuan City320314 Taiwan Department of mathematical Data Science Hanyang University Gyeonggi-do Ansan15588 Korea Republic of Center for Quantum Science and Engineering National Taiwan University Taipei10617 Taiwan Physics Division National Center for Theoretical Sciences Taipei10617 Taiwan Hon Hai Quantum Computing Research Center Taipei Taiwan

In this work, we compute the number of [[n, k]]d stabilizer codes made up of ddimensional qudits, for arbitrary positive integers d. In a seminal work by Gross (Ref. [23]) the number of [[n, k]]d stabilizer codes was computed for the case when d is a prime (or the power of a prime, i.e., d = pm, but when the qudits are Galois-qudits). The proof in Ref. [23] is inapplicable to the non-prime case. For our proof, we introduce a group structure to [[n, k]]d codes, and use this in conjunction with the Chinese remainder theorem to count the number of [[n, k]]d codes. Our work overlaps with Ref. [23] when d is a prime and in this case our results match exactly, but the results differ for the more generic case. Despite that, the overall order of magnitude of the number of stabilizer codes scales agnostic of whether the dimension is prime or non-prime. This is surprising since the method employed to count the number of stabilizer states (or more generally stabilizer codes) depends on whether d is prime or not. The cardinality of stabilizer states, which was so far known only for the prime-dimensional case (and © 2022, CC BY.

关键词： Codes (symbols)

DQPS: An Intelligent Multi-Hop Computation Offloading Scheme for Workflow Applications in Vehicular Edge computing Networks

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IEEE Transactions on Consumer Electronics 2024年

作者： Lin, Bing Chen, Qiaoxin Chen, Xing Jia, Wen-Kang Lu, Yu Xiong, Neal N. Fujian Normal University College of Physics and Energy Fujian Provincial Key Laboratory of Quantum Manipulation and New Energy Materials Fuzhou350117 China Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering Fuzhou350117 China Peking University School of Computer Science 100871 China Xiamen University Department of Informatics and Communication Engineering Xiamen361005 China Fuzhou University College of Computer and Data Science Fuzhou350118 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350118 China Fujian Normal University College of Photonic and Electronic Engineering Fuzhou350117 China Fujian Normal University Concord University College Fuzhou350117 China Sul Ross State University Department of Computer Mathematical and Physical Sciences AlpineTX79830 United States

Vehicular Edge computing (VEC) is a feasible solution for autonomous driving as it can offload latency-sensitive and computation-intensive tasks from vehicle terminals to roadside units (RSUs) for real-time processing. Due to the high computational resource the workflow applications (i.e., autonomous driving) required, the small vehicle-to-RSUs communication range, and the scarce available resources for each vehicle, it might be difficult to accomplish complex workflow applications through the single-hop offloading paradigm in the Internet of Vehicles (IoV). In this paper, we propose a reinforcement learning (RL) based multi-hop computation offloading scheme for workflow applications to reduce their execution latency in the VEC networks, which considers the data dependency in workflow applications as well as the trust relationship and communication interference among RSUs. Firstly, a preprocessing method is employed to merge the cut-edges in a workflow to reduce the offloading scale of tasks and compress the encoding dimension of offloading solutions. Then, a Deep Q-network algorithm using Phase-optimal State update (DQPS) is proposed to update the offloading policy distribution, in which the deviation of the phase-optimal state from the current state is estimated as the reward of RL to promote the algorithm's convergence to adapt the dynamic VEC networks. Simulation results show that DQPS has the best performance compared to other benchmark schemes. Moreover, the latency of the identical applications can be reduced by 2.5%-25.3% through our offloading scheme with a multi-hop model compared to that with the single-hop paradigm in IoV. © 1975-2011 IEEE.

关键词： Computation offloading

Neural Posterior Estimation with guaranteed exact coverage: the ringdown of GW150914

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arXiv 2023年

作者： Crisostomi, Marco Dey, Kallol Barausse, Enrico Trotta, Roberto SISSA Via Bonomea 265 Trieste34136 Italy INFN Sezione di Trieste Italy IFPU - Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34014 Italy School of Physics Indian Institute of Science Education and Research Thiruvananthapuram Maruthamala PO Vithura Kerala Thiruvananthapuram695551 India Physics Department Imperial College London Prince Consort Rd LondonSW7 2AZ United Kingdom Centro Nazionale "High Performance Computer Big Data and Quantum Computing" Italy

We analyze the ringdown phase of the first detected black-hole merger, GW150914, using a simulation-based inference pipeline based on masked autoregressive flows. We obtain approximate marginal posterior distributions for the ringdown parameters, namely the mass, spin, and the amplitude and phases of the dominant mode and its first overtone. Thanks to the locally amortized nature of our method, we are able to calibrate our posteriors with injected simulations, producing posterior regions with guaranteed (i.e. exact) frequentist coverage of the true values. For GW150914, our calibrated posteriors provide only mild evidence (∼ 2σ) for the presence of an overtone, even if the ringdown is assumed to start at the peak of the amplitude. Copyright © 2023, The Authors. All rights reserved.

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