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15th International Conference on Machine Learning and computing, ICMLC 2023

作者： Zhao, Liqiang Qi, Kaiyuan Su, Zhiyuan Pang, Liye Zhang, Lianfa Wu, Dong Cloud Computing R&D Department of Jinan Inspur Data Technology State Key Laboratory of High-end Server & Storage Technology China

ISBN: (纸本)9781450398411

Disk failure prediction is of great significance for ensuring the business continuity and data reliability of cloud data centers. Algorithm performance will directly affect operation and maintenance costs and user experience. Nowadays, many disk manufacturers use the threshold of S.M.A.R.T. data to check disk fault detection or make prediction, but the detection accuracy of this method is low. This paper proposes a disk fault prediction method based on deep learning, using deep residual network to extract high-dimensional hidden features;and using deep neural network combined with integrated tree model tool XGBoost to perform Failure prediction. Moreover, we use AutoML strategy based on improved GA to get the best model structure. Experiments based on Backblaze data show that this method has better prediction performance. Compared with pure XGboost methods, it can better reduce the false alarm rate about 50% and improve the accuracy rate, while maintaining a strong generalization ability. © 2023 ACM.

关键词： Fault detection

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Efficient quantum process tomography for Clifford circuits

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Physical Review A 2023年第3期108卷 032419-032419页

作者： Shichuan Xue Guangyao Huang Yong Liu Dongyang Wang Weixu Shi Yingwen Liu Xiang Fu Anqi Huang Mingtang Deng Junjie Wu Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha 410073 China

A Clifford circuit is a pivotal tool in quantum computing and has extensive applications in quantum error correction codes and topological quantum computing. Hence, it is essential to benchmark and verify the effect of Clifford circuits against noise and errors. Standard quantum process tomography is a fundamental technique for fully characterizing quantum dynamics, but at the cost of exponential time, space, and computation with an increasing number of qubits. Here, we propose an efficient quantum process tomography method for Clifford circuits. Combining with the stabilizer formalism, we prove theoretically that, for an n-qubit Clifford circuit, our method merely needs m ancillary qubits and ⌈n/m⌉ input stabilizer states to obtain the quantum process. Numerical simulation results show that our method could perfectly rebuild the unknown Clifford quantum circuit with fidelity over 99.99% to six qubit cases. Our work provides an efficient and practical approach to benchmark and verify Clifford circuits.

关键词： Quantum circuits Quantum information processing Quantum simulation Quantum tomography

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A Novel Class of Energy-Preserving Runge-Kutta Methods for the Korteweg-de Vries Equation

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Numerical Mathematics(Theory,Methods and Applications) 2022年第3期15卷 768-792页

作者： Yue Chen Yuezheng Gong Qi Hong Chunwu Wang Department of Mathematics Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) MIITNanjing 211106China Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing 210023China

In this paper,we present a quadratic auxiliary variable approach to develop a new class of energy-preserving Runge-Kutta methods for the Korteweg-de Vries *** quadratic auxiliary variable approach is first proposed to reformulate the original model into an equivalent system,which transforms the energy conservation law of the Korteweg-de Vries equation into two quadratic invariants of the reformulated *** the symplectic Runge-Kutta methods are directly employed for the reformulated model to arrive at a new kind of time semi-discrete schemes for the original *** consistent initial conditions,the proposed methods are rigorously proved to maintain the original energy conservation law of the Korteweg-de Vries *** addition,the Fourier pseudo-spectral method is used for spatial discretization,resulting in fully discrete energy-preserving *** implement the proposed methods effectively,we present a very efficient iterative technique,which not only greatly saves the calculation cost,but also achieves the purpose of practically preserving *** numerical results are addressed to confirm the expected order of accuracy,conservative property and efficiency of the proposed algorithms.

关键词： Quadratic auxiliary variable approach symplectic Runge-Kutta scheme energypreserving algorithm Fourier pseudo-spectral method

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SSP IMEX Runge-Kutta WENO Scheme for Generalized Rosenau-KdV-RLW Equation

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数学研究 2022年第1期55卷 1-21页

作者： Muyassar Ahmat Jianxian Qiu School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen UniversityXiamen 361005China

In this article,we present a third-order weighted essentially non-oscillatory(WENO)method for generalized Rosenau-KdV-RLW *** third order finite difference WENO reconstruction and central finite differences are applied to discrete advection terms and other terms,respectively,in spatial *** order to achieve the third order accuracy both in space and time,four stage third-order L-stable SSP Implicit-Explicit Runge-Kutta method(Third-order SSP EXRK method and third-order DIRK method)is applied to temporal *** high order accuracy and essentially non-oscillatory property of finite difference WENO reconstruction are shown for solitary wave and shock wave for Rosenau-KdV and Rosenau-KdV-RLW *** efficiency,reliability and excellent SSP property of the numerical scheme are demonstrated by several numerical experiments with large CFL number.

关键词： Rosenau-KdV-RLW equation WENO reconstruction finite difference method SSP implicit-explicit Runge-Kutta method

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Person Re-Identification Based on Multi-Spectrum Information Aggregation Transformers

Person Re-Identification Based on Multi-Spectrum Information...

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International Conference on Image, Vision and computing (ICIVC)

作者： Yuxuan Zhang Huibin Tan Long Lan Jing Ren Xiao Teng State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

Convolutional Neural Networks (CNNs) have achieved remarkable success in various image-related tasks. However, CNNs' chunking approach of sliding windows over pixels hinders its ability to learn sequential semantic information. To address this issue, researchers have proposed models that integrate Transformers to aggregate features across different resolutions, taking advantage of the Transformer's strengths. Hierarchical Aggregation Transformer (HAT) is one such model that integrates low-level and high-level details, showing a great effect on person re-identification. Based on HAT, we propose the Multi-Spectrum Information Aggregation Transformers (MIAT), which enhances the low-level structural information captured by CNNs through a frequency channel attention module that extracts multi-spectral features. By leveraging discrete cosine transform (DCT), more detailed features can be learned to improve person re-identification, enabling better discernment of distinguishing features between different individuals. Through extensive experimentation, we validate our model's performance on two widely employed person re-identification datasets and demonstrate its superiority over existing advanced methods.

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Bioinspired sensing-memory-computing integrated vision systems: biomimetic mechanisms, design principles, and applications

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Science China(Information Sciences) 2024年第5期67卷 5-27页

作者： Yujie HUANG Yinlong TAN Yan KANG Yabo CHEN Yuhua TANG Tian JIANG Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology College of Advanced Interdisciplinary Studies National University of Defense Technology Institute for Quantum Science and Technology College of ScienceNational University of Defense Technology

With the explosion of sensory data in the Internet of Things(Io T) era, conventional machine vision systems are becoming increasingly difficult to meet the requirements of high efficiency, low energy consumption, and low latency due to their inherent shortcomings of separate sensing, memory, and computing units. Inspired by the retina and neuromorphic computing, the sensing-memory-computing integrated vision system(SMCVS) that features low power consumption, low latency, and high parallelism has been considered a promising technology to surpass the von Neumann architecture and realize strong artificial ***, novel materials like two-dimensional semiconductors and quantum dots with novel optoelectronic performance provide hardware carriers for implementing integrated sensing-memory-computing architectures,attracting considerable attention. This paper reviews the recent research progress in bioinspired vision systems in terms of biomimetic mechanisms, design principles, computational architectures, and ***, the biomimetic mechanisms are illustrated to guide the design of high-performance artificial visual perception systems. Then the research progress of optoelectronic-synapse-based bioinspired vision systems in the device principles and applications including image filtering, color recognition, visual adaptation, and motion detection are summarized. Finally, the challenges and future developing directions of the SMCVS are provided regarding bionic application, architecture design, and device fabrication.

关键词： sensing-memory-computing architecture neuromorphic computing retinomorphic device image recognition visual system

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high ORDER FINITE DIFFERENCE HERMITE WENO FAST SWEEPING METHODS FOR STATIC HAMILTON-JACOBI EQUATIONS

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Journal of Computational Mathematics 2023年第6期41卷 1064-1092页

作者： Yupeng Ren Yulong Xing Jianxian Qiu School of Mathematical Sciences Xiamen UniversityXiamenFujian 361005China Department of Mathematics The Ohio State UniversityColumbusOH 43210USA School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen UniversityXiamenFujian 361005China

In this paper,we propose a novel Hermite weighted essentially non-oscillatory(HWENO)fast sweeping method to solve the static Hamilton-Jacobi equations *** the HWENO reconstruction procedure,the proposed method is built upon a new finite difference fifth order HWENO scheme involving one big stencil and two small ***,one major novelty and difference from the traditional HWENO framework lies in the fact that,we do not need to introduce and solve any additional equations to update the derivatives of the unknown functionϕ.Instead,we use the currentϕand the old spatial derivative ofϕto update *** traditional HWENO fast sweeping method is also introduced in this paper for comparison,where additional equations governing the spatial derivatives ofϕare *** novel HWENO fast sweeping methods are shown to yield great savings in computational time,which improves the computational efficiency of the traditional HWENO *** addition,a hybrid strategy is also introduced to further reduce computational *** numerical experiments are provided to validate the accuracy and efficiency of the proposed approaches.

关键词： Finite difference Hermite methods Weighted essentially non-oscillatory method Fast sweeping method Static Hamilton-Jacobi equations Eikonal equation

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Experimental demonstration of quantum transport enhancement using time-reversal symmetry breaking on a silicon photonic chip

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Science China(Physics,Mechanics & Astronomy) 2022年第10期65卷 2-9页

作者： Yang Wang Xinyao Yu Shichuan Xue Yizhi Wang Junwei Zhan Chao Wu Pingyu Zhu Qilin Zheng Miaomiao Yu Yingwen Liu Xiaogang Qiang Junjie Wu Xuejun Yang Ping Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China National Innovation Institute of Defense Technology Academy of Military SciencesBeijing 100071China National Laboratory of Solid State Microstructures and School of Physics Nanjing UniversityNanjing 210093China

The continuous-time quantum walk is a basic model for studying quantum transport and developing quantum-enhanced algorithms. Recent studies show that by introducing a phase into the standard continuous-time quantum walk model, the time-reversal symmetry can be broken without changing the Hermitian property of the Hamiltonian. The time-reversal symmetry breaking quantum walk shows advantages in quantum transport, such as perfect state transfer, directional control, transport speedup, and quantum transport efficiency enhancement. In this work, we implement the time-reversal symmetry breaking quantum walks on a reconfigurable silicon photonic chip and demonstrate the enhancement introduced by breaking time-reversal symmetry. Perfect state transfer on a three-site ring, a quantum switch implemented on a six-site graph, and transport speedup using a linear chain of triangles are demonstrated with high fidelity. Time-reversal asymmetry has also been used in a simplified light-harvesting model,implying the potential of time-reversal symmetry breaking in photosynthesis investigations.

关键词： quantum walk time-reversal asymmetry quantum transport

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Quantum algorithm and experimental demonstration for the subset sum problem

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Science China(Information Sciences) 2022年第8期65卷 261-274页

作者： Qilin ZHENG Pingyu ZHU Shichuan XUE Yang WANG Chao WU Xinyao YU Miaomiao YU Yingwen LIU Mingtang DENG Junjie WU Ping XU Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense Technology

To solve the subset sum problem, a well-known nondeterministic polynomial-time complete problem that is widely used in encryption and resource scheduling, we propose a feasible quantum algorithm that utilizes fewer qubits to encode and achieves quadratic speedup. Specifically, this algorithm combines an amplitude amplification algorithm with quantum phase estimation, and requires n + t + 1 qubits and O(2(0.5+o(1))n) operations to obtain the solution, where n is the number of elements, and t is the number of qubits used to store the eigenvalues. To verify the performance of the algorithm, we simulate the algorithm with the online quantum simulator of IBM named ibmq simulator using Qiskit and then run it on two IBM quantum computers called ibmq santiago and ibmq bogota. The experimental results indicate that compared with the brute force algorithm, the proposed algorithm results in quadratic acceleration for the problem of a set S with four elements and two subsets whose sum equals target w. Using the iterator twice, we obtain success probabilities of 0.940 ± 0.004, 0.751 ± 0.040, and 0.665 ± 0.060 on the simulator, ibmq santiago, and ibmq bogota, respectively, and the fidelity between the theoretical and experimental quantum states is calculated to be 0.944 ± 0.002, 0.753 ± 0.017, and 0.657 ± 0.028, respectively. If the error rates of the experimental quantum logic gates can be reduced, the success probabilities of the proposed algorithm on real quantum devices can be further improved.

关键词： quantum algorithm subset sum quadratic speedup encryption algorithm complexity

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Extremum-Preserving Correction of the Nine-Point Scheme for Diffusion Equation on Distorted Meshes

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Advances in Applied Mathematics and Mechanics 2023年第2期15卷 402-427页

作者： Wang Kong Zhenying Hong Guangwei Yuan Zhiqiang Sheng Department of Mathematics Nanjing University of Aeronautics and AstronauticsNanjingJiangsu 211106China Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) MIITNanjingJiangsu 211106China Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100871China

In this paper,we construct a new cell-centered nonlinear finite volume scheme that preserves the extremum principle for heterogeneous anisotropic diffusion equation on distorted *** introduce a new nonlinear approach to construct the conservative flux,that is,a linear second order flux is firstly given and a nonlinear conservative flux is then constructed by using an adaptive method and a nonlinear weighted *** new scheme does not need to use the convex combination of the cell-center unknowns to approximate the auxiliary unknowns,so it can deal with the problem with general discontinuous *** results show that our new scheme performs more robust than some existing schemes on highly distorted meshes.

关键词： Extremum-preserving correction diffusion equation distorted mesh nine-point scheme

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