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arXiv 2022年

作者： Chen, Yaojian Liu, Yong Shi, Xinmin Song, Jiawei Liu, Xin Gan, Lin Guo, Chu Fu, Haohuan Gao, Jie Chen, Dexun Yang, Guangwen Tsinghua University Beijing China National Supercomputing Center Wuxi Zhejiang Lab Hangzhou China Information Engineering University Zhengzhou China National Supercomputing Center Wuxi China Tsinghua University National Supercomputing Center Wuxi China National Research Centre of Parallel Engineering and Technology Beijing China Tsinghua University National Supercomputing Center Wuxi Zhejiang Lab Hangzhou China

High-performance classical simulator for quantum circuits, in particular the tensor network contraction algorithm, has become an important tool for the validation of noisy quantum computing. In order to address the memory limitations, the slicing technique is used to reduce the tensor dimensions, but it could also lead to additional computation overhead that greatly slows down the overall performance. This paper proposes novel lifetime-based methods to reduce the slicing overhead and improve the computing efficiency, including an interpretation method to deal with slicing overhead, an in-place slicing strategy to find the smallest slicing set and an adaptive tensor network contraction path refiner customized for Sunway architecture. Experiments show that in most cases the slicing overhead with our in-place slicing strategy would be less than the cotengra , which is the most used graph path optimization software at present. Finally, the resulting simulation time is reduced to 96.1s for the Sycamore quantum processor RQC, with a sustainable single-precision performance of 308.6Pflops using over 41M cores to generate 1M correlated samples, which is more than 5 times performance improvement compared to 60.4 Pflops in 2021 Gordon Bell Prize work. © 2022, CC BY.

关键词： Timing circuits

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Device-Type Profiling for Network Access Control Systems using Clustering-Based Multivariate Gaussian Outlier Score 5

Device-Type Profiling for Network Access Control Systems usi...

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5th International Conference on Future Networks and Distributed Systems: The Premier Conference on Smart Next Generation Networking Technologies, ICFNDS 2021

作者： Muhammad, Musa Daniel Ani, Uchenna Abdullahi, Aminu Aliyu Radanliev, Petar Faculty of Engineering Environment and Computing Coventry University Scarborough United Kingdom Petras National Centre of Excellence for IoT Systems Cyber Security Department of Science Technology Engineering and Public Policy University College London United Kingdom Department of Computer Science Dutse Nigeria Oxford E-Research Centre Department of Engineering Sciences Oxford United Kingdom

ISBN: (纸本)9781450387347

Behaviour profiling is used in organisations to identify the working patterns of agents: humans or devices. It can be used to detect abnormal patterns of devices in an organisation's BYOD network to help control network access. Although BYOD offers great benefits of improving productivity and job satisfaction while reducing cost, it bears some security issues around access control with limitations in addressing insider threat scenarios. This means that motivated and determined attackers with valid access credentials can exploit the weaknesses to compromise the system. The limitation of mobile devices can mean that traditional network access control mechanism are ineffective in addressing insider threats, and can impact on device capacity and functionality. Thus, it is crucial to explore other ways of identifying insider threats from anomalous device behaviours. We propose a device-type profiling for threat detection which uses packet inter-arrival time patterns of devices for automatic identification of abnormal device-types. Experimental tests using clustering-based multivariate gaussian outlier score (CMGOS) to clearly distinguish and label normal and abnormal inter-arrival time patterns yielded promising results. This affirms the effectiveness of the proposed approach to support system administrators in monitoring and detecting insider threats for timely and effective access control response. © 2021 ACM.

关键词： Access control

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Optimizing Variable-Strength Combinatorial Test Suite Generation via Fuzzy Adaptive Sine Cosine Algorithm (FASCA)

Optimizing Variable-Strength Combinatorial Test Suite Genera...

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Cyber Security and Computing (CyberComp), International Conference on

作者： Nur Syabila Zabidi Noraini Ibrahim Mazidah Mat Rejab MasrulEhsan Mamat Sumaira Nazir Nurul Hawani Mat Tuselim Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia (UTHM) Parit Raja Batu Pahat MALAYSIA Department of Software Engineering National University of Modern Languages Islamabad PAKISTAN Business Intelligence Section Industrial Research Management Centre SIRIM Berhad Shah Alam MALAYSIA

ISBN: (数字)9798350387728

ISBN: (纸本)9798350387735

Combinatorial test suite generation is a critical aspect of software testing, particularly for systems with variable-strength interactions. Traditional optimization algorithms often struggle to efficiently generate minimal test suites while maintaining coverage. This research introduces the Fuzzy Adaptive Sine Cosine Algorithm (FASCA), a variant of the Sine Cosine Algorithm (SCA), tailored specifically for optimizing variable-strength combinatorial test suite generation. FASCA incorporates fuzzy adaptation mechanisms to dynamically balance exploration and exploitation, addressing the limitations of standard SCA in handling diverse interaction strengths. Experimental evaluations demonstrate that FASCA significantly reduces test suite size and execution time compared to the original SCA, offering a more efficient solution for combinatorial test optimization. These results highlight FASCA's potential as a robust tool for enhancing the efficiency of software testing processes.

关键词： Fuzzy logic Heuristic algorithms Software algorithms Metaheuristics Switches Minimax techniques Linguistics Inference algorithms Standards Gravity

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Benchmarking a Quantum Random Number Generator with Machine Learning

Benchmarking a Quantum Random Number Generator with Machine ...

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Conference on Quantum Information and Measurement, ICQI 2021

作者： Haw, Jing Yan Truong, Nhan Duy Ng, Hong Jie Ho, Raymond Assad, Syed Wang, Chao Lam, Ping Koy Kavehei, Omid Department of Electrical & Computer Engineering National University of Singapore 117583 Singapore Centre for Quantum Computation and Communication Technology Department of Quantum Science Australian National University CanberraACT2601 Australia Australian Research Council Training Centre for Innovative BioEngineering The University of Sydney NSW2006 Australia NeuroSyd Lab School of Biomedical Engineering Faculty of Engineering The University of Sydney NSW2006 Australia

We develop a predictive machine learning (ML) analysis to examine the uniformity and unpredictability aspects of a random number generator. We show that our tool is capable of uncovering hidden correlations and experi... 详细信息

ISBN: (纸本)9781957171012

关键词： Machine learning

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Fixed-Length Arbitrary-Phase Tunable NRI-TL Metamaterial Phase Shifter for Antenna Beam-Steering Applications

Fixed-Length Arbitrary-Phase Tunable NRI-TL Metamaterial Pha...

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European Conference on Antennas and Propagation, EuCAP

作者： Asif Bilal Abdul Quddious Atsushi Kanno Tetsuya Kawanishi Marco A. Antoniades Stavros Iezekiel EMPHASIS Research Centre University of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Chair for RF and Photonics Engineering Technische Universitat Dresden Dresden Germany National Institute of Information and Communications Technology Tokyo Japan Japan Graduate School of Engineering Nagoya Institute of Technology Aichi Japan School of Fundamental Science and Engineering Waseda University Tokyo Japan Department of Electrical Computer & Biomedical Engineering Ryerson University Toronto ON Canada

A fixed-length arbitrary-phase tunable phase shifter, based on the concept of negative-refractive-index transmission-line (NRI-TL) metamaterials for sub-6 GHz antenna beam steering applications is proposed. The design consists of a fixed microstrip transmission line which is reconfigured by loading varactor diodes in both the series and shunt branches. A continuously tunable phase of 210° at 3.2 GHz for the transmitted signal is achieved at the output by varying the biasing voltage from 0 – 7 V for the varactor diodes. The insertion loss varies from 0.9 – 2.5 dB for the design in the frequency range of 3.2 – 3.6 GHz. The total length of the tunable NRI-TL metamaterial phase shifter is λg/4.

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Using Free Space Optics for Beamsteering of 5G Metasurface Antenna

Using Free Space Optics for Beamsteering of 5G Metasurface A...

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IEEE Photonics Conference (IPC)

作者： A. Bilal A. Quddious M. A. Antoniades A. Kanno P.T. Dat K. Inagaki T. Kawanishi S. Iezekiel Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus EMPHASIS Research Centre University of Cyprus Nicosia Cyprus Chair for RF and Photonics Engineering Technische Universität Dresden Germany Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada National Institute of Information and Communications Technology Tokyo Japan Graduate School of Engineering Nagoya Institute of Technology Aichi Japan Faculty of Science and Engineering Waseda University Tokyo Japan

Beamsteering of a sub-6 GHz 5G metasurface antenna is achieved via free space optical control. A scanning angle of 66 ° is demonstrated at 3.25 GHz. The antenna consists of varactor-based phase shifters, whose vo...

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Creation and control of high-dimensional multi-partite classically entangled light

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Light(Science & Applications) 2021年第5期10卷 796-805页

作者： Yjie Shen Iaac Nape Xilin Yang Xing Fu Mali Gong Darryl Naidoo Andrew Forbes School of Physics University of the WitwatersrandPrivate Bag 3Wits 2050South Africa State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua University100084 BeijingChina Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Key Laboratory of Photonic Control Technology(Tsinghua University) Ministry of Education100084 BeijingChina CSIR National Laser Centre PO Box 395Pretoria 0001South Africa Optoelectronics Research Centre University of SouthamptonSouthampton S0171BJUK

Vector beams,non-separable in spatial mode and polarisation,have emerged as enabling tools in many diverse applications,from communication to *** applicability has been achieved by sophisticated laser designs controlling the spin and orbital angular momentum,but so far is restricted to only two-dimensional *** we demonstrate the first vectorially structured light created and fully controlled in eight dimensions,a new *** externally modulate our beam to control,for the frst time,the complete set of classical Greenberger-Horne-Zeilinger(GHZ)states in paraxial structured light beams,in analogy with high-dimensional multi-partite quantum entangled states,and introduce a new tomography method to verify their *** complete theoretical framework reveals a rich parameter space for further extending the dimensionality and degrees of freedom,opening new pathways for vetorilly structured light in the classical and quantum regimes.

关键词： quantum analogy dimensions

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CT-SDM: A Sampling Diffusion Model for Sparse-View CT Reconstruction Across Various Sampling Rates

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IEEE Transactions on Medical Imaging 2025年第6期44卷 2581-2593页

作者： Liutao Yang Jiahao Huang Guang Yang Daoqiang Zhang College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Bioengineering Department and Imperial-X Imperial College London London U.K. National Heart and Lung Institute Imperial College London London U.K. National Heart Cardiovascular Research Centre Royal Brompton Hospital London U.K. School of Biomedical Engineering and Imaging Sciences King’s College London London U.K.

Sparse views X-ray computed tomography has emerged as a contemporary technique to mitigate radiation dose. Because of the reduced number of projection views, traditional reconstruction methods can lead to severe artifacts. Recently, research studies utilizing deep learning methods has made promising progress in removing artifacts for Sparse-View Computed Tomography (SVCT). However, given the limitations on the generalization capability of deep learning models, current methods usually train models on fixed sampling rates, affecting the usability and flexibility of model deployment in real clinical settings. To address this issue, our study proposes a adaptive reconstruction method to achieve high-performance SVCT reconstruction at various sampling rate. Specifically, we design a novel imaging degradation operator in the proposed sampling diffusion model for SVCT (CT-SDM) to simulate the projection process in the sinogram domain. Thus, the CT-SDM can gradually add projection views to highly undersampled measurements to generalize the full-view sinograms. By choosing an appropriate starting point in diffusion inference, the proposed model can recover the full-view sinograms from various sampling rate with only one trained model. Experiments on several datasets have verified the effectiveness and robustness of our approach, demonstrating its superiority in reconstructing high-quality images from sparse-view CT scans across various sampling rates.

关键词： Image reconstruction Computed tomography Diffusion models Training Degradation Deep learning Image restoration X-ray imaging Iterative methods Deformation

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Towards practical and massively parallel quantum computing emulation for quantum chemistry

arXiv

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arXiv 2023年

作者： Shang, Honghui Fan, Yi Shen, Li Guo, Chu Liu, Jie Duan, Xiaohui Li, Fang Li, Zhenyu Institute of Computing Technology Chinese Academy of Sciences Beijing China Hefei National Laboratory University of Science and Technology of China Hefei230088 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China School of Software Shandong University Jinan China National Research Center of Parallel Computer Engineering and Technology Beijing China

Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, quantum resource is too scarce to support these explorations. Therefore, it is valuable to emulate quantum computing on classical computers for developing quantum algorithms and validating quantum hardware. However, existing simulators mostly suffer from the memory bottleneck so developing the approaches for large-scale quantum chemistry calculations remains challenging. Here we demonstrate a high-performance and massively parallel variational quantum eigensolver (VQE) simulator based on matrix product states, combined with embedding theory for solving large-scale quantum computing emulation for quantum chemistry on HPC platforms. We apply this method to study the torsional barrier of ethane and the quantification of the protein-ligand interactions. Our largest simulation reaches 1000 qubits, and a performance of 216.9 PFLOPS is achieved on a new Sunway supercomputer, which sets the state-of-the-art for quantum computing emulation for quantum chemistry. © 2023, CC BY.

关键词： Computational chemistry

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Enhanced quantum synchronization of a driven qubit under non-Markovian dynamics

arXiv

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arXiv 2023年

作者： Chen, Po-Wen Radhakrishnan, Chandrashekar Ali, Md. Manirul Department of Physics National Atomic Research Institute Taoyuan City325207 Taiwan Department of Computer Science and Engineering New York University Shanghai 567 West Yangsi Road Pudong Shanghai200124 China Centre for Quantum Science and Technology Chennai Institute of Technology Chennai600069 India

Synchronizing a few-level quantum system is of fundamental importance to the understanding of synchronization in the deep quantum regime. We investigate quantum phase synchronization of a two-level system (qubit) driven by a semiclassical laser field, in the presence of a general non-Markovian dissipative environment. The phase preference of the qubit is demonstrated through Husimi Q-function, and the existence of a limit cycle is also shown in our system. Synchronization of the qubit is quantified using the shifted phase distribution. The signature of quantum phase synchronization viz the Arnold tongue is obtained from the maximal value of the shifted phase distribution. Two distinct types of qubit dynamics is considered depending on the reservoir correlation time being very short and a situation when bath correlation time is finite. In the Markov regime of the environment, the phase preference of the qubit goes away in the long time limit, whereas the long-time phase localization persists in the non-Markovian regime. We also plot the maximum of the shifted phase distribution in two ways: (a) by varying the detuning and laser driving strength, and (b) by varying the system-bath coupling and laser driving strength. Various system-environment parameters determine the synchronization regions and the qubit phase synchronization is shown to be enhanced in the non-Markov regime. © 2023, CC BY.

关键词： Synchronization

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