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arXiv 2023年

作者： Zhang, Yue Peng, Chengtao Wang, Qiuli Song, Dan Li, Kaiyan Kevin Zhou, S. the School of Biomedical Engineering Division of Life Sciences and Medicine University of Science China Anhui Hefei230026 China Suzhou Institute for Advance Research USTC Suzhou Jiangsu215123 China Anhui Hefei230026 China Suzhou Institute for Advance Research USTC Suzhou Jiangsu215123 China the Key Laboratory of Precision and Intelligent Chemistry USTC Anhui Hefei230026 China Institute of Computing Technology CAS China University of Science and Technology of China Anhui Hefei230026 China the 7T Magnetic Resonance Translational Medicine Research Center Department of Radiology Southwest Hospital Army Medical University Third Military Medical University Chongqing400038 China the School of Electrical and Information Engineering Tianjin University Tianjin300072 China

Multi-modal medical images provide complementary soft-tissue characteristics that aid in the screening and diagnosis of diseases. However, limited scanning time, image corruption and various imaging protocols often result in incomplete multi-modal images, thus limiting the usage of multi-modal data for clinical purposes. To address this issue, in this paper, we propose a novel unified multimodal image synthesis method for missing modality imputation. Our method overall takes a generative adversarial architecture, which aims to synthesize missing modalities from any combination of available ones with a single model. To this end, we specifically design a Commonality- and Discrepancy-Sensitive Encoder for the generator to exploit both modality-invariant and specific information contained in input modalities. The incorporation of both types of information facilitates the generation of images with consistent anatomy and realistic details of the desired distribution. Besides, we propose a Dynamic Feature Unification Module to integrate information from a varying number of available modalities, which enables the network to be robust to random missing modalities. The module performs both hard integration and soft integration, ensuring the effectiveness of feature combination while avoiding information loss. Verified on two public multi-modal magnetic resonance datasets, the proposed method is effective in handling various synthesis tasks and shows superior performance compared to previous methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

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Beating the break-even point with autonomous quantum error correction

arXiv

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arXiv 2025年

作者： Li, Yi Mei, Qingyuan Jie, Qing-Xuan Cai, Weizhou Li, Yue Liu, Zhiyuan Chen, Zi-Jie Xie, Zihan Cheng, Xu Zhao, Xingyu Luo, Zhenghao Zhang, Mengxiang Zou, Xu-Bo Zou, Chang-Ling Lin, Yiheng Du, Jiangfeng Laboratory of Spin Magnetic Resonance School of Physical Sciences University of Science and Technology of China Hefei230026 China Anhui Province Key Laboratory of Scientific Instrument Development and Application University of Science and Technology of China Hefei230026 China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China Anhui Province Key Laboratory of Quantum Network University of Science and Technology of China Hefei230026 China National Advanced Talent Cultivation Center for Physics University of Science and Technology of China Hefei230026 China Hefei National Laboratory University of Science and Technology of China Hefei230088 China Anhui Province Engineering Research Center for Quantum Precision Measurement Hefei230088 China Institute of Quantum Sensing School of Physics Zhejiang University Hangzhou310027 China

Quantum error correction (QEC) [1, 2] is essential for practical quantum computing, as it protects fragile quantum information from errors by encoding it in high-dimensional Hilbert spaces. Conventional QEC protocols [3, 4] typically require repeated syndrome measurements, real-time feedback, and the use of multiple physical qubits for encoding. Such implementations pose significant technical complexities, particularly for trapped-ion systems, with high demands on precision and scalability. Here, we realize autonomous QEC [5–9] with a logical qubit encoded in multiple internal spin states of a single trapped ion [10–12], surpassing the break-even point for qubit lifetime. Our approach leverages engineered spin-motion couplings to transfer error-induced entropy into motional modes, which are subsequently dissipated through sympathetic cooling with an ancilla ion, fully eliminating the need for measurement and feedback. By repetitively applying this autonomous QEC protocol under injected low-frequency noise, we extend the logical qubit lifetime to approximately 11.6 ms, substantially outperforming lifetime for both the physical qubit (0.9 ms) and the uncorrected logical qubit (0.8 ms), thereby beating the break-even point with autonomous protection of quantum information without measurement [13–16] or post-selection [17, 18]. This work presents an efficient approach to fault-tolerant quantum computing that harnesses the intrinsic multi-level structure of trapped ions, providing a distinctive path toward scalable architectures and robust quantum memories with reduced overhead. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

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Generic detection-based error mitigation using quantum autoencoders

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Physical Review A 2021年第4期103卷 L040403-L040403页

作者： Xiao-Ming Zhang Weicheng Kong Muhammad Usman Farooq Man-Hong Yung Guoping Guo Xin Wang Department of Physics City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong SAR China Origin Quantum Computing Company Limited Hefei Anhui 230088 China Department of Mathematics City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong SAR China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and Technology Shenzhen 518055 China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei Anhui 230026 China City University of Hong Kong Shenzhen Research Institute Shenzhen Guangdong 518057 China

Efficient error-mitigation techniques demanding minimal resources is key to quantum information processing. We propose a generic protocol to mitigate quantum errors using detection-based quantum autoencoders. In our protocol, the quantum data are compressed into a latent subspace while leaving errors outside, the latter of which is then removed by a measurement and postselection. Compared to previously developed methods, our protocol on the one hand requires no extra qubits, and on the other hand it has a near-optimal denoising power, in which under reasonable requirements all errors detected outside of the latent subspace can be removed, while those inside the subspace cannot be removed by any means. Our detection-based quantum autoencoders are therefore particularly useful for near-term quantum devices in which controllable qubits are limited while noise reduction is important.

关键词： Machine learning Quantum control Quantum information processing

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Querying a matrix through matrix-vector products 46

Querying a matrix through matrix-vector products

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46th International Colloquium on Automata, Languages, and Programming, ICALP 2019

作者： Sun, Xiaoming Woodruff, David P. Yang, Guang Zhang, Jialin CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Carnegie Mellon University PittsburghPA United States Institute of Computing Technology Chinese Academy of Sciences Beijing China Conflux Beijing China

ISBN: (纸本)9783959771092

We consider algorithms with access to an unknown matrix M ∈ Fn×d via matrix-vector products, namely, the algorithm chooses vectors v1,..., vq, and observes Mv1,..., Mvq. Here the vi can be randomized as well as chosen adaptively as a function of Mv1,..., Mvi−1. Motivated by applications of sketching in distributed computation, linear algebra, and streaming models, as well as connections to areas such as communication complexity and property testing, we initiate the study of the number q of queries needed to solve various fundamental problems. We study problems in three broad categories, including linear algebra, statistics problems, and graph problems. For example, we consider the number of queries required to approximate the rank, trace, maximum eigenvalue, and norms of a matrix M;to compute the AND/OR/Parity of each column or row of M, to decide whether there are identical columns or rows in M or whether M is symmetric, diagonal, or unitary;or to compute whether a graph defined by M is connected or triangle-free. We also show separations for algorithms that are allowed to obtain matrix-vector products only by querying vectors on the right, versus algorithms that can query vectors on both the left and the right. We also show separations depending on the underlying field the matrix-vector product occurs in. For graph problems, we show separations depending on the form of the matrix (bipartite adjacency versus signed edge-vertex incidence matrix) to represent the graph. Surprisingly, this fundamental model does not appear to have been studied on its own, and we believe a thorough investigation of problems in this model would be beneficial to a number of different application areas. © Xiaoming Sun, David P. Woodruff, Guang Yang, and Jialin Zhang;licensed under Creative Commons License CC-BY

关键词： Matrix algebra

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arXiv

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arXiv 2024年

作者： Ren, Yingying Li, Qiuli Guo, Yangyang Pedrycz, Witold Xing, Lining Liu, Anfeng Song, Yanjie School of Computer Electronics and Information Guangxi University Nanning China Guangxi Key Laboratory of Multimedia Communications and Network Technology China Key Laboratory of Parallel Distributed and Intelligent Computing Guangxi University China School of Systems Science Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Poland Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer Istanbul Turkey School of Electronic Engineering Xidian University Xian China School of Electronic Engineering Central South University Changsha China National Engineering Research Center of Maritime Navigation System Dalian Maritime University Dalian China

With the rapid development of the satellite industry, the information transmission network based on communication satellites has gradually become a major and important part of the future satellite ground integration network. However, the low transmission efficiency of the satellite data relay back mission has become a problem that is currently constraining the construction of the system and needs to be solved urgently. Effectively planning the task of satellite ground networking by reasonably scheduling resources is crucial for the efficient transmission of task data. In this paper, we hope to provide a task execution scheme that maximizes the profit of the networking task for satellite ground network planning considering feeding mode (SGNPFM). To solve the SGNPFM problem, a mixed-integer planning model with the objective of maximizing the gain of the link-building task is constructed, which considers various constraints of the satellite in the feed-switching mode. Based on the problem characteristics, we propose a distance similarity-based genetic optimization algorithm (DSGA), which considers the state characteristics between the tasks and introduces a weighted Euclidean distance method to determine the similarity between the tasks. To obtain more high-quality solutions, different similarity evaluation methods are designed to assist the algorithm in intelligently screening individuals. The DSGAalso uses an adaptive crossover strategy based on similarity mechanism, which guides the algorithm to achieve efficient population search. In addition, a task scheduling algorithm considering the feed-switching mode is designed for decoding the algorithm to generate a highquality scheme. The results of simulation experiments show that the DSGA can effectively solve the SGNPFM problem. Compared to other algorithms, the proposed algorithm not only obtains higher quality planning schemes but also has faster algorithm convergence speed. The proposed algorithm improves data trans

关键词： Profitability

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A Blockchain-based Fast Authentication and Collaborative Video data Forwarding Scheme for Vehicular networks

A Blockchain-based Fast Authentication and Collaborative Vid...

引用

IEEE/IFIP International Conference on Embedded and Ubiquitous computing, EUC

作者： Weihui Qiu Xin Yang Ming Wei Wei Ren Tianqing Zhu School of Computer Science China University of Geosciences Wuhan P.R. China Wuhan Institute of Marine Electric Propulsion CSSC P.R. China Key Laboratory of Network Assessment Technology CAS Chinese Academy of Sciences Institute of Information Engineering Beijing P.R. China Guizhou Provincial Key Laboratory of Public Big Data Guizhou University Guiyang P.R. China

ISBN: (纸本)9781665400374

Internet of Things (IoT) current present two trends with respect to ubiquity and mobility. The number of devices increases remarkably and most forthcoming devices are mobile, e.g., Internet of Vehicles (IoV). In large scale mobile IoT, the management of device identification, fast authentication, and certification of public keys experiences upcoming difficulties. Centralized security architecture may not be suitable and in contrast cross-domain security architecture will tackle the ubiquity and mobility better. We note that blockchain is a new decentralized architecture equipped with basic cryptographic settings, which provides new tools such as token and guarantees many security properties such as block integrity. In this paper we design a blockchain-based fast authentication video data forwarding scheme for IoV. Compared with existing protocols, it has the advantages of decentralization, high authentication efficiency, strong trust, and resistance to common attacks. We evaluate our scheme with real experiments over Hyperledger Fabric and the authentication delay is manageable (e.g, 4 seconds in IoV).

关键词： Resistance Protocols Authentication Public key Computer architecture Near field communication Ubiquitous computing

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Modeling the Correlations of Relations for Knowledge Graph Embedding

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Journal of Computer science & technology 2018年第2期33卷 323-334页

作者： Ji-Zhao Zhu Yan-Tao Jia Jun Xu Jian-Zhong Qiao Xue-Qi Cheng College of Computer Science and Engineering Northeastern University Shenyang 110169 China Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing 110190 China

Knowledge graph embedding, which maps the entities and relations into low-dimensional vector spaces, has demonstrated its effectiveness in many tasks such as link prediction and relation extraction. Typical methods include TransE, TransH, and TransR. All these methods map different relations into the vector space separately and the intrinsic correlations of these relations are ignored. It is obvious that there exist some correlations among relations because different relations may connect to a common entity. For example, the triples （Steve Jobs, PlaceOfBrith, California） and （Apple Inc., Location, California） share the same entity California as their tail entity. We analyze the embedded relation matrices learned by TransE/TransH/TransR, and find that the correlations of relations do exist and they are showed as low-rank structure over the embedded relation matrix. It is natural to ask whether we can leverage these correlations to learn better embeddings for the entities and relations in a knowledge graph. In this paper, we propose to learn the embedded relation matrix by decomposing it as a product of two low-dimensional matrices, for characterizing the low-rank structure. The proposed method, called TransCoRe （Translation-Based Method via Modeling the Correlations of Relations）, learns the embeddings of entities and relations with translation-based framework. Experimental results based on the benchmark datasets of WordNet and Freebase demonstrate that our method outperforms the typical baselines on link prediction and triple classification tasks.

关键词： knowledge graph embedding low-rank matrix decomposition

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Mesh Variational Autoencoders with Edge Contraction Pooling

Mesh Variational Autoencoders with Edge Contraction Pooling

引用

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Yu-Jie Yuan Yu-Kun Lai Jie Yang Qi Duan Hongbo Fu Lin Gao Institute of Computing Technology CAS Beijing Key Laboratory of Mobile Computing and Pervasive Device School of Computer Science and Informatics Cardiff University UK SenseTime Research City University of Hong Kong Shenzhen Research Institute of Big Data Shenzhen

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

3D shape analysis is an important research topic in computer vision and graphics. While existing methods have generalized image-based deep learning to meshes using graph-based convolutions, the lack of an effective pooling operation restricts the learning capability of their networks. In this paper, we propose a novel pooling operation for mesh datasets with the same connectivity but different geometry, by building a mesh hierarchy using mesh simplification. For this purpose, we develop a modified mesh simplification method to avoid generating highly irregularly sized triangles. Our pooling operation effectively encodes the correspondence between coarser and finer meshes in the hierarchy. We then present a variational auto-encoder (VAE) structure with the edge contraction pooling and graph-based convolutions, to explore probability latent spaces of 3D surfaces and perform 3D shape generation. Our network requires far fewer parameters than the original mesh VAE and thus can handle denser models thanks to our new pooling operation and convolutional kernels. Our evaluation also shows that our method has better generalization ability and is more reliable in various applications, including shape generation and shape interpolation.

关键词： Three-dimensional displays Shape Strain Interpolation Neural networks Machine learning

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Field Test of Twin-Field Quantum key Distribution through Sending-or-Not-Sending over 428 km

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Physical Review Letters 2021年第25期126卷 250502-250502页

作者： Hui Liu Cong Jiang Hao-Tao Zhu Mi Zou Zong-Wen Yu Xiao-Long Hu Hai Xu Shizhao Ma Zhiyong Han Jiu-Peng Chen Yunqi Dai Shi-Biao Tang Weijun Zhang Hao Li Lixing You Zhen Wang Yong Hua Hongkun Hu Hongbo Zhang Fei Zhou Qiang Zhang Xiang-Bin Wang Teng-Yun Chen Jian-Wei Pan Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology ofChina Hefei Anhui 230026 People’s Republic of China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui 230026 People’s Republic of China Jinan Institute of Quantum Technology Jinan Shandong 250101 People’s Republic of China State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing 100084 People’s Republic of China Data Communication Science and Technology Research Institute Beijing 100191 People’s Republic of China QuantumCTek Corporation Limited Hefei Anhui 230088 People’s Republic of China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 People’s Republic of China Chongqing Optoelectronics Research Institute Chongqing 400060 People’s Republic of China

Quantum key distribution endows people with information-theoretical security in communications. Twin-field quantum key distribution (TF-QKD) has attracted considerable attention because of its outstanding key rates over long distances. Recently, several demonstrations of TF-QKD have been realized. Nevertheless, those experiments are implemented in the laboratory, and therefore a critical question remains about whether the TF-QKD is feasible in real-world circumstances. Here, by adopting the sending-or-not-sending twin-field QKD (SNS-TF-QKD) with the method of actively odd parity pairing (AOPP), we demonstrate a field-test QKD over 428 km of deployed commercial fiber and two users are physically separated by about 300 km in a straight line. To this end, we explicitly measure the relevant properties of the deployed fiber and develop a carefully designed system with high stability. The secure key rate we achieved breaks the absolute key rate limit of repeaterless QKD. The result provides a new distance record for the field test of both TF-QKD and all types of fiber-based QKD systems. Our work bridges the gap of QKD between laboratory demonstrations and practical applications and paves the way for an intercity QKD network with measurement-device-independent security.

关键词： Optical quantum information processing Quantum cryptography Quantum optics

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Match2: A Matching over Matching Model for Similar Question Identification

arXiv

引用

arXiv 2020年

作者： Wang, Zizhen Fan, Yixing Guo, Jiafeng Yang, Liu Zhang, Ruqing Lan, Yanyan Cheng, Xueqi Jiang, Hui Wang, Xiaozhao University of Chinese Academy of Sciences Beijing China CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Massachusetts Amherst MA United States Alibaba Group Beijing China

Community Question Answering (CQA) has become a primary means for people to acquire knowledge, where people are free to ask questions or submit answers. To enhance the efficiency of the service, similar question identification becomes a core task in CQA which aims to find a similar question from the archived repository whenever a new question is asked. However, it has long been a challenge to properly measure the similarity between two questions due to the inherent variation of natural language, i.e., there could be different ways to ask a same question or different questions sharing similar expressions. To alleviate this problem, it is natural to involve the existing answers for the enrichment of the archived questions. Traditional methods typically take a one-side usage, which leverages the answer as some expanded representation of the corresponding question. Unfortunately, this may introduce unexpected noises into the similarity computation since answers are often long and diverse, leading to inferior performance. In this work, we propose a two-side usage, which leverages the answer as a bridge of the two questions. The key idea is based on our observation that similar questions could be addressed by similar parts of the answer while different questions may not. In other words, we can compare the matching patterns of the two questions over the same answer to measure their similarity. In this way, we propose a novel matching over matching model, namely Match2, which compares the matching patterns between two question-answer pairs for similar question identification. Empirical experiments on two benchmark datasets demonstrate that our model can significantly outperform previous state-of-the-art methods on the similar question identification *** CONCEPTS •Information systems → Question answering;Copyright © 2020, The Authors. All rights reserved.

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