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Robust three-qubit search algorithm in Rydberg atoms via geometric control

Physical Review A 2022年第5期106卷 052610-052610页

作者： Bing-Bing Liu Zheng Shan M.-R. Yun D.-Y. Wang B.-J. Liu L.-L. Yan M. Feng S.-L. Su Key Laboratory of Material Physics Ministry of Education School of Physics and Microelectronics Zhengzhou University Zhengzhou 450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 Henan China Department of Physics Southern University of Science and Technology Shenzhen Guangdong 518055 China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Innovation Academy of Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan 430071 China Research Center for Quantum Precision Measurement Guangzhou Institute of Industry Technology Guangzhou 511458 China Department of Physics Zhejiang Normal University Jinhua 321004 China

Rydberg atoms possess long coherence time and inherent scalability, which makes it promising to implement quantum algorithms. An exact and robust quantum search algorithm (SA) is essential to some practical applications. Here we propose a multisolution three-qubit SA by employing quantum circuit and geometric operations, in which the target states can be successfully searched with the fidelity of at least 99.8% and the geometric operators guarantee robustness against systematic errors. In particular, the geometric three-qubit gate operators employed reduce the implementation time and help to resist against the detrimental influence of decoherence. Moreover, our scheme can be straightforwardly extended to multiqubit cases. We have carried out numerical simulations based on the master equation to illustrate the superiority of our scheme. We consider that our study provides an alternative method for executing quantum SAs with high success probability.

关键词： Geometric & topological phases Optimization problems Quantum algorithms Rydberg atoms & molecules

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Characterization and construction of optimal binary linear codes with one-dimensional hull

arXiv

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arXiv 2022年

作者： Li, Shitao Shi, Minjia Kim, Jon-Lark The School of Mathematical Sciences Anhui University Hefei230601 China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education The School of Mathematical Sciences Anhui University Hefei230601 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China The Department of Mathematics Sogang University Seoul Korea Republic of

The hull of a linear code over finite fields is the intersection of the code and its dual, and linear codes with small hulls have applications in computational complexity and information protection. Linear codes with the smallest hull are LCD codes, which have been widely studied. Recently, several papers were devoted to related LCD codes over finite fields with size greater than 3 to linear codes with one-dimensional or higher dimensional hull. Therefore, an interesting and non-trivial problem is to study binary linear codes with one-dimensional hull with connection to binary LCD codes. The objective of this paper is to study some properties of binary linear codes with one-dimensional hull, and establish their relation with binary LCD codes. Some interesting inequalities are thus obtained. Using such a characterization, we study the largest minimum distance done(n, k) among all binary linear [n, k] codes with one-dimensional hull. We determine the largest minimum distances done(n, n − k) for k ≤ 5 and done(n, k) for k ≤ 4 or 14 ≤ n ≤ 24. We partially determine the exact value of done(n, k) for k = 5 or 25 ≤ n ≤ *** Codes 94B05, 15B05, 12E10 Copyright © 2022, The Authors. All rights reserved.

关键词： Optimal systems

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High Temperature Strengthening Mechanism of Pure Zn with Trace Mn Addition

SSRN

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SSRN 2023年

作者： Li, Meng Xue, Zhe Shi, Zhang-Zhi Wang, Yi-Nan Dai, Fu-Zhi Zhang, Li-Zhi Zhou, Shao-Xiong Huang, Bing-Xin Guan, Zhen-Peng Wang, Lu-Ning State Key Laboratory for Advanced Metals and Materials Key Laboratory for Advanced Materials Processing of Ministry of Education Beijing Laboratory of Metallic Materials and Processing for Modern Transportation School of Materials Science and Engineering University of Science and Technology Beijing Beijing100083 China Orthopedics Department Peking University ShouGang Hospital Beijing100144 China Artificial Intelligence for Science Institute Beijing100871 China School of Mathematical Sciences Peking University Beijing100871 China Central Iron and Steel Research Institute Beijing100081 China

This work reveals how trace Mn significantly improves high temperature strength of pure Zn. The peak stress of pure Zn increases from 46 MPa to 84 MPa at 300 °C/0.1 s-1after 0.8 wt.% Mn addition. The Zn-0.8Mn alloy has a bimodal grain structure with fine grains surrounding a coarse grain. Transmission electron microscopy results show that Mn addition promotes activation of non-basal slip and pile-up of dislocations near coarse/fine grain boundary or MnZn13/Zn interface. First-principles calculations indicate that Mn addition can reduce stacking fault energy values of basal and prismatic slip systems of Zn, therefore activating slip. Piled dislocations generate forward and back stresses, resulting in hetero-deformation induced strengthening. It gives us the inspiration for improving strength of Zn alloys through bimodal grain structural design. © 2023, The Authors. All rights reserved.

关键词： Binary alloys

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Covariance-Based Activity Detection in Cooperative Multi-Cell Massive MIMO: Scaling Law and Efficient Algorithms

arXiv

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arXiv 2023年

作者： Wang, Ziyue Liu, Ya-Feng Wang, Zhaorui Yu, Wei The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Shenzhen518172 China The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada

This paper focuses on the covariance-based activity detection problem in a multi-cell massive multiple-input multiple-output (MIMO) system. In this system, active devices transmit their signature sequences to multiple base stations (BSs), and the BSs cooperatively detect the active devices based on the received signals. While the scaling law for the covariance-based activity detection in the single-cell scenario has been extensively analyzed in the literature, this paper aims to analyze the scaling law for the covariance-based activity detection in the multi-cell massive MIMO system. Specifically, this paper demonstrates a quadratic scaling law in the multi-cell system, under the assumption that the path-loss exponent of the fading channel γ > 2. This finding shows that, in the multi-cell massive MIMO system, the maximum number of active devices that can be correctly detected in each cell increases quadratically with the length of the signature sequence and decreases logarithmically with the number of cells (as the number of antennas tends to infinity). Moreover, in addition to analyzing the scaling law for the signature sequences randomly and uniformly distributed on a sphere, the paper also establishes the scaling law for signature sequences based on a finite alphabet, which are easier to generate and store. Finally, this paper proposes two efficient accelerated coordinate descent (CD) algorithms with a convergence guarantee for solving the device activity detection problem. The first algorithm reduces the complexity of CD by using an inexact coordinate update strategy. The second algorithm avoids unnecessary computations of CD by using an active set selection strategy. Simulation results show that the proposed algorithms exhibit excellent performance in terms of computational efficiency and detection error probability. Copyright © 2023, The Authors. All rights reserved.

关键词： Fading channels

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NOMANet: A Graph Neural Network Enabled Power Allocation Scheme for NOMA

arXiv

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arXiv 2025年

作者： Hou, Yipu Lu, Yang Chen, Wei Ai, Bo Niyato, Dusit Ding, Zhiguo State Key Laboratory of Advanced Rail Autonomous Operation China School of Computer Science and Technology Beijing Jiaotong University Beijing100044 China School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China College of Computing and Data Science Nanyang Technological University 639798 Singapore Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates

This paper proposes a graph neural network (GNN) enabled power allocation scheme for non-orthogonal multiple access (NOMA) networks. In particular, a downlink scenario with one base station serving multiple users over several subchannels is considered, where the number of subchannels is less than the number of users, and thus, some users have to share a subchannel via NOMA. Our goal is to maximize the system energy efficiency subject to the rate requirement of each user and the overall budget. We propose a deep learning based approach termed NOMA net (NOMANet) to address the considered problem. Particularly, NOMANet is GNN-based, which maps channel state information to the desired power allocation scheme for all subchannels. The multi-head attention and the residual/dense connection are adopted to enhance the feature extraction. The output of NOMANet is guaranteed to be feasible via the customized activation function and the penalty method. Numerical results show that NOMANet trained unsupervised achieves performance close to that of the successive convex approximation method but with a faster inference speed by about 700 times. Besides, NOMANet is featured by its scalability to both users and subchannels. © 2025, CC BY.

关键词： Channel state information

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CADEC: A Combinatorial Auction for Dynamic Distributed DNN Inference Scheduling in Edge-Cloud Networks

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IEEE Transactions on Mobile computing 2025年

作者： Xu, Xiaolong Hu, Yuhao Cui, Guangming Qi, Lianyong Dou, Wanchun Nanjing University of Information Science and Technology School of Software Nanjing210044 China Nanjing University of Information Science and Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software China Nanjing University State Key Laboratory for Novel Software Technology China College of Computer science and technology Qingdao China Georgia State University Department of Computer Science United States

Deep Neural Network (DNN) Inference, as a key enabler of intelligent applications, is often computation-intensive and latency-sensitive. Combining the advantages of cloud computing (abundant computing resources) and edge computing (fast transmission), edge-cloud collaborative DNN inference is a powerful solution to these problems. However, in edge-cloud networks with heterogeneous resources, how to obtain reasonable decisions on server selection, model partition and resource allocation for efficient distributed DNN inference is a hard challenge. Furthermore, it is non-trivial to design suitable resource prices to maximize the social welfare. These challenges even escalate in dynamic edge-cloud networks where decisions should be generated as soon as each user arrives without future information. Therefore, we design a combinatorial auction for dynamic distributed DNN inference scheduling, named CADEC. CADEC first constructs a bid set for each user based on convex optimization theory for optimal solution searching. Next, prices of resources in the edge-cloud network are adjusted according to changes in supply-demand relationship, and whether to admit the request of each user is decided. Finally, the dynamic distributed inference scheduling decisions are generated through the primal-dual algorithm to maximize the social welfare. Theoretical analysis shows the good competitive ratio and polynomial time complexity of CADEC. Results of simulation experiments present that CADEC improves social welfare by up to 46% compared with state-of-the-art distributed DNN inference schemes. © 2002-2012 IEEE.

关键词： Convex optimization

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Energy Efficient Collaborative Federated Learning Design: A Graph Neural Network based Approach

Energy Efficient Collaborative Federated Learning Design: A ...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Nuocheng Yang Sihua Wang Mingzhe Chen Christopher G. Brinton Changchuan Yin Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

In this paper, we consider the design of an energy efficient collaborative federated learning (CFL) methodology where devices exchange their local FL parameters with a subset of their neighbors without reliance on a parameter server. In the considered model, mobile devices implement the designed CFL to train their local FL models using their own datasets over a realistic wireless network. Due to the limited wireless resources and user movements, each device may not be able to transmit its FL parameters with all neighboring devices. Therefore, each device must select a subset of devices to share its FL parameters and optimize the transmit power. This problem is formulated as an optimization problem, whose goal is to minimize CFL training energy consumption while satisfying the delay and CFL training loss requirements. To solve this problem, a two-stage solution is proposed. At the first stage, a graph neural network (GNN) based algorithm is proposed, which enables each device to individually determine the subset of devices to transmit FL parameters using its neighboring devices' location and connection information. Compared to standard iterative algorithms that need to iteratively optimize device connections and transmit power, the proposed GNN based method can directly obtain the optimal device connections without iterative optimization. Given the optimal device connections, at the second stage, each device can directly obtain the optimal transmit power. Simulation results show that the proposed algorithm can decrease energy consumption by up to 46% compared to the algorithm where each device will directly connect to its first and second nearest neighbors.

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Anti-JPEG Compression Steganography Based on the High Tense Region Locating Method

引用

Computers, Materials & Continua 2019年第4期59卷 199-214页

作者： Yang Wu Weiping Shang Jiahao Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002China School of Telecommunications Engineering Xidian UniversityXi’an710071China Zhuhai Campus of Beijing Normal University Zhuhai519000China

Robust data hiding techniques attempt to construct covert communication in a lossy public ***,the existing robust JPEG steganographic algorithms cannot overcome the side-information missing ***,this paper proposes a new robust JPEG steganographic algorithm based on the high tense region location method which needs no side-information of lossy ***,a tense region locating method is proposed based on the Harris-Laplacian feature ***,robust cover object generating processes are ***,the advanced embedding cost function is proposed.A series of experiments are conducted on various JPEG image sets and the results show that the proposed steganographic algorithm can resist JPEG compression efficiently with acceptable performance against steganalysis statistical detection libraries GFR(Gabor Filters Rich model)and DCTR(Discrete Cosine Transform Residual).

关键词： Robust data hiding steganography JPEG compression resistant Harris-Laplacian feature

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A new network intrusion detection system based on blockchain

引用

International Journal of Performability engineering 2019年第12期15卷 3187-3195页

作者： Fu, Jinhua Xu, Mixue Huang, Yongzhong Tao, Hongwei State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou450002 China

With the increasing application of computers and networks, several network security problems have emerged, and thus network intrusion detection systems have become the focus of network security research. In order to achieve the purpose of intrusion detection and protection, the traditional network intrusion detection system extracts features from the data of the network data stream according to the feature recognition algorithm and compares the extracted features with those in the training set to recognize the behavior. However, if a user wants to effectively detect malicious behaviors in the network, a large feature library is needed, and it cannot be shared with other users, which makes the quality of single user detection lower than the highest detection quality of the whole network. Blockchain, which is a new network system of decentralization, de-trust, tamper-proof, anti-counterfeiting, and traceability, plays an important role in the transmission and sharing of high-value data. In this paper, a new network intrusion detection system is designed based on blockchain, which can enable users to share feature libraries over the whole network by means of P2P network transmission. Meanwhile, its network structure and consensus algorithm are presented, and its security and performance are analyzed. Analysis results show that this system has lower false negative rates. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Intrusion detection

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Phase Reentrances and Solid Deformations in Confined Colloidal Crystals

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Physical Review Letters 2024年第1期132卷 018202-018202页

作者： Xiaoxia Li Huang Fang Krongtum Sankaewtong Minhuan Li Yanshuang Chen Jiping Huang Ran Ni Hajime Tanaka Peng Tan State Key Laboratory of Surface Physics and Department of Physics Fudan University Shanghai 200433 China Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China Chemical Engineering School of Chemical and Biomedical Engineering Nanyang Technological University 62 Nanyang Drive 637459 Singapore Department of Fundamental Engineering Institute of Industrial Science University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Research Center for Advanced Science and Technology University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8904 Japan

A simple geometric constraint often leads to novel, complex crystalline phases distinct from the bulk. Using thin-film charge colloidal crystals, a model system with tunable interactions, we study the effects of geometric constraints. Through a combination of experiments and simulations, we systematically explore phase reentrances and solid deformation modes concerning geometrical confinement strength, identifying two distinct categories of phase reentrances below a characteristic layer number, Nc: one for bcc bulk-stable and another for fcc bulk-stable systems. We further verify that the dominant thermodynamic origin is the nonmonotonic dependence of solids’ free energy on the degree of spatial confinement. Moreover, we discover transitions in solid deformation modes between interface-energy and bulk-energy dominance: below a specific layer number, Nk, geometric constraints generate unique soft deformation modes adaptive to confinement. These findings on the N-dependent thermodynamic and kinetic behaviors offer fresh insights into understanding and manipulating thin-film crystal structures.

关键词： Phase transitions by order Colloidal crystal Colloids

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