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Origin Pilot: A quantum operating system for effecient usage of quantum resources

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arXiv 2021年

作者： Kong, Weicheng Wang, Junchao Han, Yongjian Wu, Yuchun Zhang, Yu Dou, Menghan Fang, Yuan Guo, Guoping Origin Quantum Computing Company Limited Hefei230026 China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China School of Computer Science and Technology University of Science and Technology of China Hefei230027 China

The operating system is designed to manage the hardware and software resources of a computer. With the development of quantum computing, the management of quantum resources and cooperation between quantum systems and other computing resources (e.g. CPU, GPU and FPGA etc.) become the key challenge for the application of quantum computing to solve real world problems. In this paper we propose a quantum operating system, Origin Pilot. Origin Pilot includes the module of quantum task scheduling, quantum resource management, quantum program compilation and qubits' automatic calibration. With these modules, Origin Pilot can manage the quantum computing resources and solve the multi-quantum processor scheduling problem. It can also allow the parallel execution of multiple quantum programs and calibrate the quantum resource effectively. Thus, the performance of resources is guaranteed and the resource utilization is improved. By comparing the results with and without Origin Pilot, we evaluate the impact on a quantum circuit's fidelity of qubits mapping algorithm. We also evaluate the effectiveness of automatic calibration and parallel execution of multi-quantum processors. Finally, Origin Pilot can be easily customized for hybrid computing resources. © 2021, CC BY-NC-SA.

关键词： Scheduling

Pushing AI to wireless network edge: An overview on integrated sensing, communication, and computation towards 6G

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arXiv 2022年

作者： Zhu, Guangxu Lyu, Zhonghao Jiao, Xiang Liu, Peixi Chen, Mingzhe Xu, Jie Cui, Shuguang Zhang, Ping Shenzhen Research Institute of Big Data Shenzhen518172 China Shenzhen518172 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables33146 United States State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China Peng Cheng Laboratory Shenzhen518066 China

Pushing artificial intelligence (AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things (AIoT) in the sixth-generation (6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the huge amount of data scattered at wireless network edge. In general, realizing edge intelligence corresponds to the process of sensing, communication, and computation, which are coupled ingredients for data generation, exchanging, and processing, respectively. However, conventional wireless networks design the sensing, communication, and computation separately in a task-agnostic manner, which encounters difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications such as auto-driving. This thus prompts a new design paradigm of seamless integrated sensing, communication, and computation (ISCC) in a task-oriented manner, which comprehensively accounts for the use of the data in the downstream AI applications. In view of its growing interest, this article provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art development, and shedding light on the road ahead. Copyright © 2022, The Authors. All rights reserved.

关键词： Artificial intelligence

Acousto-drag photovoltaic effect by piezoelectric integration of two-dimensional semiconductors

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arXiv 2023年

作者： Gu, Jiaming Mou, Yicheng Ma, Jianwen Chen, Haonan Zhang, Chuanxin Wang, Yuxiang Wang, Jiayu Guo, Hangwen Shi, Wu Yuan, Xiang Jiang, Xue Ta, Dean Shen, Jian Zhang, Cheng State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Center for Biomedical Engineering School of Information Science and Technology Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China Shanghai Qi Zhi Institute Shanghai200232 China State Key Laboratory of Precision Spectroscopy East China Normal University Shanghai200241 China School of Physics and Electronic Science East China Normal University Shanghai200241 China Collaborative Innovation Center of Advanced Microstructures Nanjing210093 China

Light-to-electricity conversion is crucial for energy harvesting and photodetection, requesting efficient electron-hole pair separation to prevent recombination. Traditional junction-based mechanisms using built-in electric fields fail in non-barrier regions. Homogeneous material harvesting under photovoltaic effect is appealing but only realized in non-centrosymmetric systems via bulk photovoltaic effect. Here we report the realization of photovoltaic effect by employing surface acoustic waves (SAW) to generate zero-bias photocurrent in a conventional layered semiconductor MoSe2. SAW induces periodic modulation to electronic bands and drags the photoexcited pairs toward the travelling direction. The photocurrent is extracted by a local barrier. The separation of generation and extraction processes suppresses recombination and yields large nonlocal photoresponse. We distinguish acousto-electric drag and electron-hole pair separation effect by fabricating devices of different configurations. The acousto-drag photovoltaic effect, enabled by piezoelectric integration, offers an efficient light-to-electricity conversion method, independent of semiconductor crystal symmetry. © 2023, CC BY.

关键词： Energy harvesting

Semi-vortex solitons and their excited states in spin-orbit-coupled binary bosonic condensates

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arXiv 2024年

作者： Deng, Haiming Li, Jinqing Chen, Zhaopin Liu, Yaohui Liu, Dong Jiang, Chunzhi Kong, Chao Malomed, Boris A. School of Physics and Electronic-Electrical Engineering Xiangnan University Chenzhou423000 China Microelectronics and Optoelectronics Technology Key Laboratory of Hunan Higher Education Xiangnan University Chenzhou423000 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University Chenzhou423000 China Physics Department Solid-State Institute Technion Haifa32000 Israel Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University Tel Aviv69978 Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

It is known that two-dimensional two-component fundamental solitons of the semi-vortex (SV) type, with vorticities (s+, s−) = (0, 1) in their components, are stable ground states (GSs) in the spin-orbit-coupled (SOC) binary Bose-Einstein condensate with the contact self-attraction acting in both components, in spite of the possibility of the critical collapse in the system. However, excited states (ESs) of the SV solitons, with the vorticity set (s+, s−) = (S+, S+ + 1) and S+ = 1, 2, 3, ..., are unstable in the same system. We construct ESs of SV solitons in the SOC system with opposite signs of the self-interaction in the two components. The main finding is stability of the ES-SV solitons, with the extra vorticity (at least) up to S+ = 6. The threshold value of the norm for the onset of the critical collapse, Nthr, in these excited states is higher than the commonly known critical value, Nc ≈ 5.85, associated with the single-component Townes solitons, Nthr increasing with the growth of S+. A velocity interval for stable motion of the GS-SV solitons is found too. The results suggest a solution for the challenging problem of the creation of stable vortex solitons with high topological charges. Copyright © 2024, The Authors. All rights reserved.

关键词： Excited states

SURE-based Stopping Strategy for Fine-tunable Supervised PET Image Denoising

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SURE-based Stopping Strategy for Fine-tunable Supervised PET...

2021 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2021

作者： Cui, Jianan Gong, Kuang Guo, Ning Wollenweber, Scott Jansen, Floris Liu, Huafeng Li, Quanzheng Zhejiang University State Key Laboratory of Modern Optical Instrumentation College of Optical Science and Engineering Hangzhou China Massachusetts General Hospital Harvard Medical School Center for Advanced Medical Computing and Analysis BostonMA United States Massachusetts General Hospital Harvard Medical School Gordon Center for Medical Imaging BostonMA United States Ge Healthcare Waukesha United States

ISBN: (纸本)9781665421133

Previously, based on the unsupervised deep learning method, conditional deep image prior (CDIP), we showed the possibility of finetuning during the testing phase after supervised learning. However, one barrier for CDIP finetuning is that it needs early stopping before the network output converges to the noise which is hard to determine. In this work, we proposed to construct the finetuning loss based on Stein's unbiased risk estimator (SURE), which can provide an unbiased estimation of the true mean square error (MSE). We demonstrated that using SURE-based finetuning loss, the network output can be close to the ground truth while not converging to the noise. Quantification results based on seven real patient datasets show that the proposed method is more stable during finetuning than CDIP. © 2021 IEEE.

关键词： Image denoising

Collision Attack Framework on RIPEMD-128

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Collision Attack Framework on RIPEMD-128

International Conference on Artificial Intelligence and advanced Manufacturing (AIAM)

作者： Jingyu Li Guang Zeng Yang Yang State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Force Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Information Engineering University Zhengzhou China Trusted Computing and Information Assurance Laboratory Institute of Software Chinese Academy of Sciences Beijing China

In the last few years, the hash functions are the very common and essential primitives implemented in lots of fields. RIPEMD-128, a member of MD-family hash function, has been found collisions on the full round. In this paper, we further analyze the property about the security against collision attack of RIPEMD-128. The collision attack framework for RIPEMD-128 is proposed in order to provide ideas for other hash functions. The framework consists of three parts namely choosing a message word difference insertion, constructing differential characteristics and collision search phase. Cryptographic techniques including message modification is also introduced to reduce the complexity.

关键词： Hash functions Complexity theory Cryptography Artificial intelligence

An landmark evaluation algorithm based on router identification and delay measurement 5th

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An landmark evaluation algorithm based on router identificat...

5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Ma, Te Liu, Fenlin Zhang, Fan Luo, Xiangyang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Science and Technology Institute Zhengzhou China

ISBN: (纸本)9783030242701

City-level landmarks serve as an important foundation for achieving city-level and higher-precision IP geolocation. On the basis of the feature that router host names in network-developed areas often imply geographical location information, this paper proposes a city-level landmark evaluation algorithm based on router identification. Firstly, router host name matching rules are formulated by using plenty of network topology information obtained through probing. Secondly, the matching rules are used to extract router host names;the geographical locations corresponding to routers are queried through the established geographical location dictionary;and the nearest router that can obtain a city-level location in the probing path is reserved. Finally, candidate landmarks are evaluated based on the rule that the physical distance between network entities is less than the delay conversion distance. The experimental results show that the proposed algorithm can effectively evaluate the reliability of landmarks: among the experimental results on 8000 network landmarks in 4 cities in the United states, compared with the typical database query-based landmark obtaining, the city-level accuracy rates of landmarks are increased by 4.4%, 6.85%, 4.35% and 7.05% respectively. © Springer Nature Switzerland AG 2019.

关键词： Location

Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

Cascaded adaptive aberration-eliminating multimode fiber imaging

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advanced Photonics 2025年第2期 135-143页

作者： Zhong Wen Qilin Deng Quanzhi Li Yizhou Tan Jingshan Zhong Chiming Zhang Jiahe Zhang Clemens F.Kaminski Ying Gu Xu Liu Qing Yang Zhejiang University College of Optical Science and Engineering State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University International Research Center for Advanced Photonics Zhejiang University ZJU-Hangzhou Global Scientific and Technological Innovation Center Chinese PLA General Hospital The First Medical Center Department of Laser Medicine Chinese PLA General Hospital Hainan HospitalLaser Medicine Center Zhejiang Laboratory Research Center for Intelligent Manufacturing Computing University of Cambridge Department of Chemical Engineering and Biotechnology

In vivo microscopic imaging inside a biological lumen such as the gastrointestinal tract, respiratory airways, or within blood vessels has faced significant technological challenges for decades. A promising candidate technology is the multimode fiber(MMF) endoscope, which enables minimally invasive diagnostics at a resolution reaching the cellular level. However, for in vivo imaging applications deep inside a biological lumen, sample-induced aberrations and the dynamic dispersion in the MMF make the MMF endoscope a chaotic system with many unknowns, where multiple minor fluctuations can couple and compound into intractable problems. We introduce a dynamically encoding, cascaded, optical, and ultrathin polychromatic light-field endoscopy(DECOUPLE) to tackle this challenge. DECOUPLE includes an adaptive aberration correction that can accurately track and control MMF behavior in the spatial-frequency domain to compensate for chaos introduced during complex dynamic imaging processes. We demonstrate the flexibility and practicality of DECOUPLE for noninvasive volumetric imaging in two colors for light passing through various highly aberrating samples including 120-μm-thick onion epidermal slices and 80-μm-thick layers of fat emulsions. To summarize, we represent a significant step toward practical in vivo imaging deep within biological tissue.

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