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arXiv 2025年

作者： Li, Guanzhong Li, Lvzhou Luo, Jingquan Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China

We study the phase discrimination problem, in which we want to decide whether the eigenphase θ ∈ (−π,π] of a given eigenstate |ψ〉 with eigenvalue eiθ is zero or not, using applications of the unitary U provided as a black box oracle. We propose a quantum algorithm named quantum phase discrimination(QPD) for this task, with optimal query complexity Θ(1/λ log 1 /δ) to the oracle U, where λ is the gap between zero and nonzero eigenphases and δ the allowed one-sided error. The quantum circuit is simple, consisting of only one ancillary qubit and a sequence of controlled-U interleaved with single qubit Y rotations, whose angles are given by a simple analytical formula. quantum phase discrimination could become a fundamental subroutine in other quantum algorithms, as we present two applications to quantum search on graphs: 1. Spatial search on graphs. Inspired by the structure of QPD, we propose a new quantum walk model, and based on them we tackle the spatial search problem, obtaining a novel quantum search algorithm. For any graph with any number of marked vertices, the quantum algorithm that can find a marked vertex with probability Ω(1) in total evolution time (formula presented) and query complexity (formula presented), where λ is the gap between the zero and non-zero eigenvalues of the graph Laplacian and Ε is a lower bound on the proportion of marked vertices. 2. Path-finding on graphs. By using QPD, we reduce the query complexity of a path-finding algorithm proposed by Li and Zur [arxiv: 2311.07372] from O̴(n11) to O̴(n8), in a welded-tree circuit graph with Θ(n2n) vertices. Besides these two applications, we argue that more quantum algorithms might benefit from QPD. © 2025, CC BY.

关键词： quantum electronics

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Embedding All Feasible Solutions of Traveling Salesman Problem by Divide-and-Conquer quantum Search 4

Embedding All Feasible Solutions of Traveling Salesman Probl...

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4th IEEE International Conference on quantum computing and Engineering, QCE 2023

作者： Sato, Rei Saito, Kazuhiro Nikuni, Tetsuro Watabe, Shohei Kddi Reserch Inc. Quantum Computing Project Saitama Fujimino Japan Tokyo University of Science Faculty of Science Division I Department of Physics Tokyo Japan Shibaura Institute of Technology Faculty of Engineering Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350343236

quantum search algorithms, such as the Grover algorithm, are investigated as one of the ways to solve a traveling salesman problem (TSP). In TSP, the quantum search starts from an equal superposition of all feasible solutions. The embedding cost of all feasible solutions is up to exponential, i.e., O(n!) with n cities, and makes it difficult to solve large-scale TSP. Hence, preparing the initial state of TSP at a lower embedding cost is an important issue. Here, we propose a quantum search algorithm based on the divide-and-conquer approach, which divides each constraint term of the TSP into subproblems and applies the quantum search to each subproblem. We investigate the embedding quality of all feasible solutions by comparing our proposed method with the Grover algorithm regarding optimal iterations and success probability. The results show that our quantum divide-and-conquer approach can significantly reduce the embedding cost while the success probability decreases. © 2023 IEEE.

关键词： Traveling salesman problem

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Deep Learning for Channel Prediction in Non-Stationary Wireless Fading Environments

Deep Learning for Channel Prediction in Non-Stationary Wirel...

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2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Data Science and Quantum Computing ABV Indian Institute of Information Technology and Management Gwalior India

ISBN: (纸本)9798350379525

In non-stationary wireless fading channels deep learning models are effective in predicting channel states as indicated by this study. This work compared the LSTM and GRU models with autoregressive methods or Kalman filter, implying that deep learning is indeed able to capture temporal dependence between variables and was likely more adapted than linear method when dealing with many changes in dynamics. From the perspective of pre-processing data, keys like attention mechanism and transfer learning were decisive elements in helping them to improve prediction scores and make models more robust. These results showed that these enhanced procedures allow the models to generalise over a wide range of non-stationary situations, generating consistent performance in various diverse environments. This study indicates the promise of deep learning for enhancing wireless network operation, which could lead to greater self-awareness and utilization features in emerging future-generation wireless systems. © 2024 IEEE.

关键词： Prediction models

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Secrecy Capacity Optimization in RF/FSO Systems: Impact of Mixed Rayleigh and Log-Normal Fading with Atmospheric Turbulence

Secrecy Capacity Optimization in RF/FSO Systems: Impact of M...

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2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

This paper investigates the secrecy capacity optimization in RF/FSO systems with mixed Rayleigh and log-normal fading, while masking eavesdroppers channel state information () as well as suffering from atmospheric turbulence. We explore the impact of several parameters including beamforming angles, modulation schemes and hybrid RF/FSO link configurations through a combination of simulations as well as analytical models. Secrecy capacity is enhanced for an improved SNR and vice versa under higher turbulence conditions and cooler influents eavesdropped scenarios. Performance of the hybrid RF/FSO systems dominates considerably over single-link solutions, especially at longer distances. All these mechanisms appreciably increase the secrecy capacity, while beamforming and advanced modulation techniques offer most of the improvement. The study also demonstrates the interdependencies of system parameters, providing guidelines for designing secure communication systems under different environmental and operational conditions. © 2024 IEEE.

关键词： Beamforming

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Toward to Real Low-Resolution Person Re-identification: A New Dataset and Baseline

Toward to Real Low-Resolution Person Re-identification: A Ne...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Sun, Dongting Yang, Lulu Lan, Long Luo, Zhigang College of Computer Science and Technology National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Person re-identification(re-id) aims at querying and identifying the same target pedestrian in multiple non-overlapping cameras. However, in real scenarios, many person images captured by surveillance cameras tend to have low resolution due to camera hardware, shooting distance, viewing angle, etc. Many existing re-id methods mainly address the crossresolution person re-id problem, i.e., the high-low resolution mismatch problem. In contrast, the problem of matching low-resolution (LR) gallery images and query images with each other has been less studied. In this paper, we address this problem by developing a new gun-ball camera-based person re-id dataset and designing a LR re-id baseline model for this dataset to tackle the LR person matching problem. Extensive experiments validate the effectiveness of the proposed LR baseline model. © 2022 IEEE.

关键词： Cameras

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Verifiable quantum Homomorphic Encryption

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IEEE Journal on Selected Areas in Communications 2025年

作者： Li, Qin Wang, Yuxun Chen, Lingli Li, Lvzhou Xiangtan University School of Computer Science Xiangtan411105 China Sun Yat-sen University School of Computer Science and Engineering Institute of quantum computation and Computer Theory Guangzhou510006 China

quantum homomorphic encryption (QHE) can allow clients to directly perform quantum computation on encrypted data with the assistance of a remote quantum server. However, existing QHE schemes often overlook the crucial property of verifiability which enables clients to validate the correctness of computation results provided by the server. In this paper, we propose a verifiable QHE scheme based on the universal quantum gate set {H,P,Toffoli}. At first, a specialized gadget is designed to eliminate the errors that may arise during the homomorphic evaluation of non-Clifford Toffoli gates in a non-interactive manner. Furthermore, the designed gadget is versatile and can be seamlessly integrated into an existing QHE scheme that implements quantum gates in another universal quantum gate set {H,T,CNOT} to homomorphically evaluate more quantum gates. Subsequently, a verifiable method is introduced to the QHE scheme based on {H,P,Toffoli} for the client to detect whether the server is honest during the homomorphic computation by employing three types of indistinguishable quantum circuits. © 1983-2012 IEEE.

关键词： Qubits

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Role of J/ψ production in electron-ion collisions

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Physical Review D 2025年第1期111卷 L011501-L011501页

作者： Zexuan Chu Jinhui Chen Xiang-Peng Wang Hongxi Xing Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics Fudan University Shanghai 200433 China Shanghai Research Center for Theoretical Nuclear Physics NSFC and Fudan University Shanghai 200438 China Technical University of Munich TUM School of Natural Sciences Physics Department James-Franck-Strasse 1 85748 Garching Germany Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum Matter South China Normal University Guangzhou 510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear Science Southern Nuclear Science Computing Center South China Normal University Guangzhou 510006 China Southern Center for Nuclear-Science Theory (SCNT) Institute of Modern Physics Chinese Academy of Sciences Huizhou 516000 China

Within the framework of nonrelativistic QCD (NRQCD) effective field theory, we study the leptoproduction of J/ψ at next-to-leading order in perturbative QCD for both unpolarized and polarized electron-ion collisions. We demonstrate that the J/ψ-tagged deep inelastic scattering in the future Electron-Ion Collider can be served as a golden channel for reasons including constraining NRQCD long-distance matrix elements, probing the nuclear gluon distribution functions, as well as investigating the gluon helicity distribution inside a longitudinal polarized proton.

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Random feature amplification: feature learning and generalization in neural networks

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 14357-14405页

作者： Spencer Frei Niladri S. Chatterji Simons Institute for the Theory of Computing University of California Berkeley Berkeley CA Computer Science Department Stanford University Stanford CA

In this work, we provide a characterization of the feature-learning process in two-layer ReLU networks trained by gradient descent on the logistic loss following random initialization. We consider data with binary labels that are generated by an XOR-like function of the input features. We permit a constant fraction of the training labels to be corrupted by an adversary. We show that, although linear classifiers are no better than random guessing for the distribution we consider, two-layer ReLU networks trained by gradient descent achieve generalization error close to the label noise rate. We develop a novel proof technique that shows that at initialization, the vast majority of neurons function as random features that are only weakly correlated with useful features, and the gradient descent dynamics 'amplify' these weak, random features to strong, useful features.

关键词： feature learning generalization neural networks classification label noise

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Beating Classical Impossibility of Position Verification 13

Beating Classical Impossibility of Position Verification

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13th Innovations in Theoretical computer science Conference, ITCS 2022

作者： Liu, Jiahui Liu, Qipeng Qian, Luowen Department of Computer Science University of Texas AustinTX United States Simons Institute for the Theory of Computing BerkeleyCA United States Department of Computer Science Boston University MA United States

ISBN: (纸本)9783959772174

Chandran et al. (SIAM J. Comput.'14) formally introduced the cryptographic task of position verification, where they also showed that it cannot be achieved by classical protocols. In this work, we initiate the study of position verification protocols with classical verifiers. We identify that proofs of quantumness (and thus computational assumptions) are necessary for such position verification protocols. For the other direction, we adapt the proof of quantumness protocol by Brakerski et al. (FOCS'18) to instantiate such a position verification protocol. As a result, we achieve classically verifiable position verification assuming the quantum hardness of Learning with Errors. Along the way, we develop the notion of 1-of-2 non-local soundness for a natural non-local game for 1-of-2 puzzles, first introduced by Radian and Sattath (AFT'19), which can be viewed as a computational unclonability property. We show that 1-of-2 non-local soundness follows from the standard 2-of-2 soundness (and therefore the adaptive hardcore bit property), which could be of independent interest. © Jiahui Liu, Qipeng Liu, and Luowen Qian;licensed under Creative Commons License CC-BY 4.0

关键词： quantum cryptography

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AutoQ 2.0: From Verification of quantum Circuits to Verification of quantum Programs 31th

AutoQ 2.0: From Verification of Quantum Circuits to Verific...

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31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2025, which was held as part of the International Joint Conferences on theory and Practice of Software, ETAPS 2025

作者： Chen, Yu-Fang Chung, Kai-Min Hsieh, Min-Hsiu Huang, Wei-Jia Lengál, Ondřej Lin, Jyun-Ao Tsai, Wei-Lun Institute of Information Science Academia Sinica Taipei Taiwan Hon Hai Quantum Computing Research Center Taipei Taiwan Faculty of Information Technology Brno University of Technology Brno Czech Republic Innovation Frontier Institute of Research for Science and Technology & Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9783031906596

We present a verifier of quantum programs called AutoQ 2.0. quantum programs extend quantum circuits (the domain of AutoQ 1.0) by classical control flow constructs, which enable users to describe advanced quantum algorithms in a formal and precise manner. The extension is highly non-trivial, as we needed to tackle both theoretical challenges (such as the treatment of measurement, the normalization problem, and lifting techniques for verification of classical programs with loops to the quantum world), and engineering issues (such as extending the input format with a support for specifying loop invariants). We have successfully used AutoQ 2.0 to verify two types of advanced quantum programs that cannot be expressed using only quantum circuits: the repeat-until-success (RUS) algorithm and the weak-measurement-based version of Grover’s search algorithm. AutoQ 2.0 can efficiently verify all our benchmarks: all RUS algorithms were verified instantly and, for the weak-measurement-based version of Grover’s search, we were able to handle the case of 100 qubits in ∼20 minutes. © The Author(s) 2025.

关键词： Qubits

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