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SSRN 2023年

作者： Huang, Xiaowei Feng, Shiguang Li, Lvzhou Institute of Quantum Computing and and Software School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China

Connectivity is a fundamental structural property of matroids, and has been studied algorithmically over 50 years. To the best of our knowledge, the classical query complexity lower bound and the quantum complexity for this problem have not been considered. Thus, in this paper we are devoted to addressing these issues, and our contributions are threefold as follows:(i) First, we prove that the randomized query complexity of determining whether a matroid is connected is $\Omega(n^2)$ and thus the algorithm proposed by Cunningham is optimal in classical computing. (ii) Second, we present a quantum algorithm with $O(n^{3/2})$ queries, which exhibits provable quantum speedups over classical ones.(iii) Third, we prove that any quantum algorithm requires $\Omega(n)$ queries, which indicates that quantum algorithms can achieve at most a quadratic speedup over classical ones. Therefore, we have a relatively comprehensive understanding of the potential of quantum computing in determining the connectedness of matroids. © 2023, The Authors. All rights reserved.

关键词： quantum theory

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Recent Advances in quantum computing for Drug Discovery and Development

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IEEE Nanotechnology Magazine 2023年第2期17卷 26-30页

作者： Wang, Pei-Hua Chen, Jen-Hao Yang, Yu-Yuan Lee, Chien Tseng, Yufeng Jane Chung Yuan Christian University Quantum Information Center Taoyuan City320314 Taiwan National Taiwan University College of Electrical Engineering and Computer Science Graduate Institute of Biomedical Electronics and Bioinformatics Taipei10617 Taiwan Chunghwa Telecom Co. Ltd. Taipei Taiwan National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan National Center for Theoretical Sciences Physics Division Taipei10617 Taiwan National Taiwan University Center for Quantum Science and Engineering Taipei10617 Taiwan

Drug discovery and development is a time-consuming and cost-intensive process. computer-aided drug design can speed up the timeline and reduce costs by decreasing the number of necessary biochemical experiments. The number of studies using quantum computing to solve problems in drug development has been increasing in recent years. In this review, we briefly introduce the main steps in drug discovery and development and how computers help to find potential drug candidates. Recent studies of quantum computing in drug development based on the structure of target proteins are listed chronologically. They include protein structure prediction, molecular docking, quantum simulation, and quantitative structure-activity relationship (QSAR) models. Current quantum devices are still susceptible to noise and error but are well suited for hybrid quantum-classical algorithms. The quantum advantage is demonstrated on hybrid systems and quantum-inspired devices such as quantum annealers. We hope to see more applications of quantum computing in the field of drug discovery and development.

关键词： Proteins

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Arbitrary unitary transformation over time-binned optical modes and the demonstration of superadditive communication 5

Arbitrary unitary transformation over time-binned optical mo...

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quantum computing, Communication, and Simulation V 2025

作者： Cui, Chaohan Basani, Jasvith Raj Postlewaite, Jack Saif, Babak N. Fan, Linran Waks, Edo Guha, Saikat Department of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States James C. Wyant College of Optical Sciences University of Arizona TucsonAZ85721 United States Institute for Research in Electronics and Applied Physics Joint Quantum Institute University of Maryland College ParkMD20742 United States NASA Goddard Space Flight Center 8800 Greenbelt Road GreenbeltMD20771 United States Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78758 United States

ISBN: (纸本)9781510685307

Programmable linear optical unitary transformation across many temporal modes is an enabling technology of far-reaching impact, with applications ranging from joint-detection receivers with quantum-limited communication capacity, generating temporally entangled squeezed light for quantum-enhanced photonic sensors, generating photonic cluster states for quantum computation to all-optical machine learning on native optically-encoded information. To date, implementing arbitrary temporal-mode unitary operations across N optical temporal modes usually involves a complex setup of a temporal-to-spatial mode sorter and an extensive mesh of O(N2) beamsplitters and phase shifters. Here, we present a more compact and scalable optical circuit that only iterates O(N) optical elements and O(N) time-dependent controls to perform any unitary transformation on N temporal modes on demand. We have successfully demonstrated a 16-mode optical Hadamard transform using this approach, achieving superadditive communication in photon-starved regimes. Its performance surpasses that of individual symbol-by-symbol measurements by leveraging collective quantum measurement across the 16 temporal modes. © 2025 SPIE.

关键词： Hadamard transforms

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Smart Ports Solutions for Cargo Container Tracking and Vessel Traffic Counting Systems using IoT and Cloud computing 10

Smart Ports Solutions for Cargo Container Tracking and Vesse...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Priya, S. Sairam, A. Azath, H. Manivannan, S.K. Mohankumar, N. Vedasundara Vinayagam, P. Deemed To Be University Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Vit Bhopal University School of Computing Science and Engineering Bhopal India Faculty of Management Srm Institute of Science and Technology Chennai Tamil Nadu Kattankulathur India Symbiosis Institute of Technology Maharashtra Nagpur India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

This research examines current port operations that use Internet of Things (IoT) technologies for cargo container monitoring and vessel traffic counts. Effective port management is crucial for smooth commodities movement and congestion reduction as global commerce grows. Addressing these issues with IoT solutions is promising. It analyzes cargo container IoT sensors and devices for real-time location, condition, and security monitoring. These IoT-enabled containers provide port status data for better logistical planning and security. IoT devices are used to count and control vessel traffic in the research. Sensors and data analytics at important port locations provide real-time vessel tracking and traffic monitoring. This data improves safety and optimizes vessel traffic flow, lowering congestion and wait times. The pros and downsides of using IoT in port operations include data privacy, security, and infrastructure needs. Smart port technologies may enhance marine efficiency, cost savings, and sustainability. The IoT can revolutionize port operations, notably cargo container monitoring and vessel traffic counts. Port capacity, security, and the environmental and economic viability of worldwide trade may all be improved with the help of the IoT. © 2024 IEEE.

关键词： Internet of things

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Orbital angular momentum emission from a high quality factor photonic crystal ring

Orbital angular momentum emission from a high quality factor...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Lu, Xiyuan Wang, Mingkang Zhou, Feng Heuck, Mikkel Zhu, Wenqi Aksyuk, Vladimir A. Englund, Dirk R. Srinivasan, Kartik Microsystems and Nanotechnology Division NIST GaithersburgMD20899 United States Joint Quantum Institute University of Maryland College ParkMD20742 United States Department of Electrical and Photonics Engineering Technical University of Denmark Kgs. Lyngby2800 Denmark Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States

We provide quantitative understanding of orbital angular momentum (OAM) emission for whispering gallery modes in a microring, and achieve high-Q (105 to 106), high ejection efficiency (up to 90 %), and high-OAM number... 详细信息

ISBN: (纸本)9781957171258

关键词： Whispering gallery modes

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A Hybrid Feature Selection Framework for Predicting Students Performance

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computers, Materials & Continua 2022年第1期70卷 1893-1920页

作者： Maryam Zaffar Manzoor Ahmed Hashmani Raja Habib KS Quraishi Muhammad Irfan Samar Alqhtani Mohammed Hamdi High Performance Cloud Computing(HPC3) Department of Computer and Information SciencesUniversiti Teknologi PETRONAS32610SeriIskandarMalaysia Department of Computer Science and Information Technology University of LahorePakistan Department of Process Engineering Pakistan Institute of Engineering&Applied SciencesNiloreIslamabadPakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia College of Computer Science and Information Systems Najran University61441NajranSaudi Arabia

Student performance prediction helps the educational stakeholders to take proactive decisions and make interventions,for the improvement of quality of education and to meet the dynamic needs of *** selection of features for student’s performance prediction not only plays significant role in increasing prediction accuracy,but also helps in building the strategic plans for the improvement of students’academic *** are different feature selection algorithms for predicting the performance of students,however the studies reported in the literature claim that there are different pros and cons of existing feature selection algorithms in selection of optimal *** this paper,a hybrid feature selection framework(using feature-fusion)is designed to identify the significant features and associated features with target class,to predict the performance of *** main goal of the proposed hybrid feature selection is not only to improve the prediction accuracy,but also to identify optimal features for building productive strategies for the improvement in students’academic *** key difference between proposed hybrid feature selection framework and existing hybrid feature selection framework,is two level feature fusion technique,with the utilization of cosine-based ***,according to the results reported in existing literature,cosine similarity is considered as the best similarity measure among existing similarity *** proposed hybrid feature selection is validated on four benchmark datasets with variations in number of features and number of *** validated results confirm that the proposed hybrid feature selection framework performs better than the existing hybrid feature selection framework,existing feature selection algorithms in terms of accuracy,f-measure,recall,and *** reported in presented paper show that the proposed approach gives more than 90%accuracy on benchmark dataset that is better tha

关键词： Educational data mining feature selection hybrid feature selection

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Ultrafast dynamic pulsed beam steering using virtually imaged phased array

Ultrafast dynamic pulsed beam steering using virtually image...

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IEEE Photonics Conference (IPC)

作者： Suparna Seshadri Jie Wang Andrew M. Weiner School of Electrical and Computer Engineering and Purdue Quantum Science and Engineering Institute Purdue University West Lafayette Indiana USA

We present a technique for steering of pulsed optical beams in a dynamic fashion using virtually imaged phased array (VIPA). We demonstrate steering of an ultrashort pulse input across a 0.9 mm aperture in discrete ~1...

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quantum and classical query complexities for determining connectedness of matroids

arXiv

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arXiv 2023年

作者： Huang, Xiaowei Feng, Shiguang Li, Lvzhou Institute of Quantum Computing and and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China

Connectivity is a fundamental structural property of matroids, and has been studied algorithmically over 50 years. In 1974, Cunningham proposed a deterministic algorithm consuming O(n2) queries to the independence oracle to determine whether a matroid is connected. Since then, no algorithm, not even a random one, has worked better. To the best of our knowledge, the classical query complexity lower bound and the quantum complexity for this problem have not been considered. Thus, in this paper we are devoted to addressing these issues, and our contributions are threefold as follows: (i) First, we prove that the randomized query complexity of determining whether a matroid is connected is Ω(n2) and thus the algorithm proposed by Cunningham is optimal in classical computing. (ii) Second, we present a quantum algorithm with O(n3/2) queries, which exhibits provable quantum speedups over classical ones. (iii) Third, we prove that any quantum algorithm requires Ω(n) queries, which indicates that quantum algorithms can achieve at most a quadratic speedup over classical ones. Therefore, we have a relatively comprehensive understanding of the potential of quantum computing in determining the connectedness of matroids. © 2023, CC BY.

关键词： quantum theory

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quantum neural estimation of entropies

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Physical Review A 2024年第3期109卷 032431-032431页

作者： Ziv Goldfeld Dhrumil Patel Sreejith Sreekumar Mark M. Wilde School of Electrical and Computer Engineering Cornell University Ithaca New York 14850 USA Department of Computer Science Cornell University Ithaca New York 14850 USA Institute for Quantum Information RWTH Aachen University Aachen Germany

Entropy measures quantify the amount of information and correlation present in a quantum system. In practice, when the quantum state is unknown and only copies thereof are available, one must resort to the estimation of such entropy measures. Here we propose a variational quantum algorithm for estimating the von Neumann and Rényi entropies, as well as the measured relative entropy and measured Rényi relative entropy. Our approach first parametrizes a variational formula for the measure of interest by a quantum circuit and a classical neural network and then optimizes the resulting objective over parameter space. Numerical simulations of our quantum algorithm are provided, using a noiseless quantum simulator. The algorithm provides accurate estimates of the various entropy measures for the examples tested, which renders it a promising approach for usage in downstream tasks.

关键词： quantum algorithms & computation quantum information theory

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Machine and Deep Learning Dominate Recent Innovations in Sensors, Signals and Imaging Informatics

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Yearbook of Medical Informatics 2023年第1期32卷 282-285页

作者： Baumgartner, Christian Rittner, Leticia Deserno, Thomas M. Institute of Health Care Engineering with European Testing Center of Medical Devices Graz University of Technology Austria Medical Imaging Computing Lab (MICLab) School of Electrical and Computer Engineering University of Campinas Brazil Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School Braunschweig Germany

OBJECTIVES: This review presents research papers highlighting notable developments and trends in sensors, signals, and imaging informatics (SSII) in 2022. METHOD: We performed a bibliographic search in PubMed combining Medical Subject Heading (MeSH) terms and keywords to create particular queries for sensors, signals, and imaging informatics. Only papers published in journals containing greater than three articles in the search query were considered. Using a three-point Likert scale (1 = not include, 2 = perhaps include, 3 = include), we reviewed the titles and abstracts of all database results. Only articles that scored three times Likert scale 3, or two times Likert scale 3, and one time Likert scale 2 were considered for full paper review. On this pre-selection, only papers with a total of at least eight points of the three section co-editors were considered for external review. Based on the external reviewers, we selected the top two papers representing significant research in SSII. RESULTS: Among the 469 returned papers published in 2022 in the various areas of SSII, 90, 31, and 348 papers for sensors, signals, and imaging informatics, and then, the full review process selected the two best papers. From the 469 papers, the section co-editors identified 29 candidate papers with at least 8 Likert points in total, of which 9 were nominated as the best contributions after a full paper assessment. Five external reviewers evaluated the nominated papers, and the two highest-scoring papers were selected based on the overall scores of all external reviewers. A consensus of the International Medical Informatics Association (IMIA) Yearbook editorial board finally approved the nominated papers. Machine and deep learning-based techniques continue to be the dominant theme in this field. CONCLUSIONS: Sensors, signals, and imaging informatics is a dynamic field of intensive research with increasing practical applications to support medical decision-making on a personalized bas

关键词： Biomedical informatics deep learning machine learning personalized medicine

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