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Hybrid classical-quantum communication networks

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arXiv 2025年

作者： Lukens, Joseph M. Peters, Nicholas A. Qi, Bing Elmore Family School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute West LafayetteIN47907 United States Quantum Information Science Section Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Research Technology Office and Quantum Collaborative Arizona State University TempeAZ85287 United States New York University Shanghai NYU-ECNU Institute of Physics NYU Shanghai 567 West Yangsi Road Shanghai200126 China State Key Laboratory of Precision Spectroscopy School of Physical and Material Sciences East China Normal University Shanghai200062 China

Over the past several decades, the proliferation of global classical communication networks has transformed various facets of human society. Concurrently, quantum networking has emerged as a dynamic field of research, driven by its potential applications in distributed quantum computing, quantum sensor networks, and secure communications. This prompts a fundamental question: rather than constructing quantum networks from scratch, can we harness the widely available classical fiber-optic infrastructure to establish hybrid quantum-classical networks? This paper aims to provide a comprehensive review of ongoing research endeavors aimed at integrating quantum communication protocols, such as quantum key distribution, into existing lightwave networks. This approach offers the substantial advantage of reducing implementation costs by allowing classical and quantum communication protocols to share optical fibers, communication hardware, and other network control resources—arguably the most pragmatic solution in the near term. In the long run, classical communication will also reap the rewards of innovative quantum communication technologies, such as quantum memories and repeaters. Accordingly, our vision for the future of the Internet is that of heterogeneous communication networks thoughtfully designed for the seamless support of both classical and quantum communications. © 2025, CC BY.

关键词： Quantum communication

A Conceptual Exploration of Generative AI-Induced Cognitive Dissonance and its Emergence in University-Level Academic Writing

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arXiv 2025年

作者： Seran, Carl Errol Tan, Myles Joshua Toledo Karim, Hezerul Abdul AlDahoul, Nouar Biology Program College of Arts and Sciences University of St. La Salle Bacolod Philippines Department of Natural Sciences College of Arts and Sciences University of St. La Salle Bacolod Philippines Faculty of Education University of the Philippines Open University Los Baños Philippines Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health and Health Professions College of Medicine University of Florida GainesvilleFL United States Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Yo-Vivo Corporation Bacolod Philippines Faculty of Engineering Multimedia University Persiaran Multimedia Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Abu Dhabi United Arab Emirates

The integration of Generative Artificial Intelligence (GenAI) intouniversity-level academic writing presents both opportunities and challenges,particularly in relation to cognitive dissonance (CD). This work explores howGenAI serves as both a trigger and amplifier of CD, as students navigateethical concerns, academic integrity, and self-efficacy in their writingpractices. By synthesizing empirical evidence and theoretical insights, weintroduce a hypothetical construct of GenAI-induced CD, illustrating thepsychological tension between AI-driven efficiency and the principles oforiginality, effort, and intellectual ownership. We further discuss strategiesto mitigate this dissonance, including reflective pedagogy, AI literacyprograms, transparency in GenAI use, and discipline-specific task *** approaches reinforce critical engagement with AI, fostering a balancedperspective that integrates technological advancements while safeguarding humancreativity and learning. Our findings contribute to ongoing discussions on AIin education, self-regulated learning, and ethical AI use, offering aconceptual framework for institutions to develop guidelines that align AIadoption with academic values. © 2025, CC BY.

关键词： Generative adversarial networks

A Sustainable Manufacturing Paradigm to Address Grand Challenges in Sustainability and Climate Change

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ACS Sustainable Resource Management

ACS Sustainable Resource Management 2024年第11期1卷 2334-2337页

作者： Haihui Pu Jinrui Zhang Chao Liang Mark C. Hersam Stuart J. Rowan Wei Chen Santanu Chaudhuri Elizabeth A. Ainsworth DoKyoung Lee Jonathan Claussen Yuxin Chen Rebecca Willett Jennifer B. Dunn Junhong Chen Pritzker School of Molecular Engineering University of Chicago Chicago Illinois 60637 United States Chemical Sciences and Engineering Division Physical Sciences and Engineering Directorate Argonne National Laboratory Lemont Illinois 60439 United States Department of Chemical and Biological Engineering Northwestern University Evanston Illinois 60208 United States Institute for Sustainability and Energy at Northwestern Northwestern University Evanston Illinois 60208 United States Department of Materials Science and Engineering Department of Chemistry and Department of Electrical and Computer Engineering Northwestern University Evanston Illinois 60208 United States Department of Chemistry University of Chicago Chicago Illinois 60637 United States Department of Mechanical Engineering Northwestern University 2145 Sheridan Road Evanston Illinois 60208 United States Department of Civil Materials and Environmental Engineering Chemical Engineering and Department of Chemistry University of Illinois Chicago Chicago Illinois 60439 United States USDA Agricultural Research Service Global Change and Photosynthesis Research Unit Urbana Illinois 61801 United States Department of Crop Sciences and Institute for Sustainability Energy & Environment University of Illinois at Urbana-Champaign Champaign Illinois 61801 United States Department of Mechanical Engineering Iowa State University Ames Iowa 50011 United States Department of Computer Science University of Chicago Chicago Illinois 60637 United States Department of Statistics University of Chicago Chicago Illinois 60637 United States

Adopting a holistic approach to manufacturing that strikes a balance between economic, ecological, and social viability and well-being has the potential to address the grand challenge of climate ch...

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Can Personalized Medicine Coexist with Health Equity? Examining the Cost Barrier and Ethical Implications

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arXiv 2024年

作者： Francisco, Kishi Kobe Yee Apuhin, Andrane Estelle Carnicer Tan, Myles Joshua Toledo Byers, Mickael Cavanaugh Maravilla, Nicholle Mae Amor Tan Karim, Hezerul Abdul AlDahoul, Nouar Biology Program College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health & Health Professions College of Medicine University of Florida GainesvilleFL United States Department of Natural Sciences College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Yo-Vivo Corporation Negros Occidental Bacolod City Philippines Department of Civil and Coastal Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Faculty of Engineering Multimedia University Selangor Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Saadiyat Marina District Abu Dhabi United Arab Emirates

Personalized medicine (PM) promises to transform healthcare by providingtreatments tailored to individual genetic, environmental, and lifestylefactors. However, its high costs and infrastructure demands raise concernsabout exacerbating health disparities, especially between high-income countries(HICs) and low- and middle-income countries (LMICs). While HICs benefit fromadvanced PM applications through AI and genomics, LMICs often lack theresources necessary to adopt these innovations, leading to a wideninghealthcare divide. This paper explores the financial and ethical challenges ofPM implementation, with a focus on ensuring equitable access. It proposesstrategies for global collaboration, infrastructure development, and ethicalframeworks to support LMICs in adopting PM, aiming to prevent furtherdisparities in healthcare accessibility and outcomes. © 2024, CC BY.

关键词： Personalized medicine

Single molecule superradiance for optical cycling

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arXiv 2023年

作者： Dickerson, Claire E. Alexandrova, Anastassia N. Narang, Prineha Philbin, John P. Department of Chemistry and Biochemistry University of California Los Angeles Los AngelesCA90095 United States Division of Physical Sciences College of Letters and Science University of California Los Angeles Los AngelesCA90095 United States Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States

Herein, we show that single molecules containing multiple optical cycling centers (CaO moieties) can exhibit superradiant phenomena. We demonstrate the accuracy of the Frenkel exciton model at describing these superradiant states via comparisons to high-level electronic structure methods. We then rationally design molecules with superradiant properties optimized for laser cooling. Lastly, we demonstrate how multi-photon superradiant phenomena can occur in these novel molecular systems. © 2023, CC BY-NC-ND.

关键词： Electronic structure

Giant Electroresistance Switching of Two-dimensional Ferroelectric α-In2Se3on p+-Si

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Giant Electroresistance Switching of Two-dimensional Ferroel...

2020 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2020

作者： Lee, Ko-Chun Retamal, Jose Ramon Duran Xue, Fei Cheng, Bin Tang, Hao-Ling Chiu, Ming-Hui Hu, Wei-Jin Wu, Chih-I Chen, Mei-Hsin Li, Lain-Jong Lien, Chen-Hsin He, Jr-Hau King Abdullah University of Science and Technology Electrical and Mathematical Science and Engineering Division Thuwal Saudi Arabia Institute of Electronics Engineering National Tsing Hua University Hsinchu300 Taiwan Physical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Shenyang National Laboratory for Materials Science Institute of Metal Research Chinese Academy of Sciences China Department of Electrical Engineering National Taiwan University Department of Electro-optical Engineering National Taipei University of Technology Department of Materials Science and Engineering University of New South Wales Australia

ISBN: (纸本)9781728142326

Recently, the demonstration of the ferroelectricity of phase In2Se3( -In2Se3) has opened new opportunities to develop two-dimensional small bandgap ferroelectric memories. Conventional ferroelectric hetero-junction memories have been widely studied but the performance is still limited by the large bandgap of oxide-based ferroelectric materials and limits the diode ON current and results in low ON/OFF ratio. Accordingly, we propose a novel resistive switching memory device based on the unique ferroelectric and semiconductor properties of -In2Se3. By forming the hetero-junction of -In2Se3 with the highly degenerated \mathrmp+ -Si substrate, we achieve a giant ferroelectric resistive ON/OFF ratio of 2.3 106. © 2020 IEEE.

关键词： Ferroelectricity

Complexity Analysis based on Parietal Fuzzy Entropy to Facilitate ADHD Diagnosis in Young Children

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Complexity Analysis based on Parietal Fuzzy Entropy to Facil...

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： I-Wen Huang Yu-Ci Jheng I-Chun Chen Li-Wei Ko Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan International Program in Interdisciplinary Neuroscience College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Physical Medicine and Rehabilitation Ton-Yen General Hospital Hsinchu Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Attention deficit hyperactivity disorder (ADHD) is the most common condition affecting the development of neurons in children. Therefore, early and accurate diagnosis of ADHD in young children is of paramount importance. In this study, the 8-channel wireless wearable EEG measurement device was employed to record EEG data from 30 children diagnosed with ADHD and 30 typical development (TD) young children aged 4-7 years. The data was collected both during rest and while the children performed a Kiddie Continuous Performance Test (K-CPT). We extract relative power spectral density (PSD) unaffected by factors like skull resistance and thickness. Additionally, a range of complex entropy values based on the time domain were extracted. These included sample entropy (SaEn), permutation entropy (PeEn), singular value decomposition entropy (SvdEn), and fuzzy entropy (FuEn). We compare the performance of k-Nearest Neighbors (kNN), Support Vector Machine (SVM), and XGBoost, and utilized the sequential forward selection (SFS) feature selection method in the wrapper approach. Through this process, the study identified the most effective EEG data segments and feature subsets. The findings indicated that using a combination of resting and K-CPT EEG data yielded greater discriminability. Notably, the study found that extracting beta power from the right occipital lobe along with fuzzy entropy from the parietal lobe resulted in optimal accuracy of 90% in distinguishing between children with ADHD and TD children. These outcomes highlight the potential of relative PSD and complexity metrics to support the clinical diagnosis of early ADHD. Furthermore, these metrics may contain unique neurobiomarkers that could be valuable for devising early intervention strategies.

关键词： Support vector machines Performance evaluation Pediatrics Accuracy Aging Feature extraction Entropy Electroencephalography Complexity theory Time-domain analysis

Crystalline Complex Oxide Membrane: Sub-1 nm CET Dielectrics for 2D Transistors

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Crystalline Complex Oxide Membrane: Sub-1 nm CET Dielectrics...

International Electron Devices Meeting (IEDM)

作者： Jing-Kai Huang Yi Wan Junjie Shi Ji Zhang Zeheng Wang Zi-Liang Yang Bo-Chao Huang Ya-Ping Chiu Wenxuan Wang Ni Yang Yang Liu Chun-Ho Lin Xinwei Guan Long Hu Jack Yang Danyang Wang Vincent Tung Kourosh Kalantar-Zadeh Tom Wu Xiaotao Zu Liang Qiao Sean Li Lain-Jong Li School of Materials Science and Engineering University of New South Wales Sydney Australia Department of Mechanical Engineering The University of Hong Kong Hong Kong China School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia Department of Physics National Taiwan University Taipei Taiwan Physical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia School of Chemical Engineering University of New South Wales Sydney Australia School of Physics University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665489607

Atomically thin 2D semiconductors have been regarded as promising candidates for the channels in ultra-scaled transistors. Although high-performance 2D field-effect transistors (FETs) have been demonstrated, the integration with conventional high-κ gate insulators is yet to be improved for energy-efficient devices. Here, 2D FETs with sub-1 nm capacitance equivalent thickness (CET) are demonstrated through the integration of transferrable single-crystal SrTiO 3 thin dielectrics with a monolayer CVD MoS 2 , where the optimized SrTiO 3 gate stack exhibits a gate leakage far below the low-standby-power limit (1.5×10 -2 A/cm 2 ). The short-channel devices manifest good reliability and competitive performance characteristics, including the steep subthreshold swing (SS) down to ~75 mV dec -1 and a large ON/OFF current ratio of 10 6 .

关键词： Temperature measurement Performance evaluation Voltage measurement Field effect transistors Logic gates Dielectrics Sulfur

BENCHMARKING COMMUNITY DRUG RESPONSE PREDICTION MODELS: DATASETS, MODELS, TOOLS, AND METRICS FOR CROSS-DATASET GENERALIZATION ANALYSIS

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arXiv 2025年

作者： Partin, Alexander Vasanthakumari, Priyanka Narykov, Oleksandr Wilke, Andreas Koussa, Natasha Jones, Sara E. Zhu, Yitan Overbeek, Jamie C. Jain, Rajeev Fernando, Gayara Demini Sanchez-Villalobos, Cesar Garcia-Cardona, Cristina Mohd-Yusof, Jamaludin Chia, Nicholas Wozniak, Justin M. Ghosh, Souparno Pal, Ranadip Brettin, Thomas S. Weil, M. Ryan Stevens, Rick L. Division of Data Science and Learning Argonne National Laboratory LemontIL United States Frederick National Laboratory for Cancer Research Cancer Data Science Initiatives Cancer Research Technology Program FrederickMD United States Department of Statistics University of Nebraska–Lincoln LincolnNE United States Department of Electrical & Computer Engineering Texas Tech University LubbockTX United States Division of Computer Computational and Statistical Sciences Los Alamos National Laboratory Los AlamosNM United States Department of Computer Science The University of Chicago ChicagoIL United States

Deep learning (DL) and machine learning (ML) models have shown promise in drug response prediction (DRP), yet their ability to generalize across datasets remains an open question, raising concerns about their real-world applicability. Due to the lack of standardized benchmarking approaches, model evaluations and comparisons often rely on inconsistent datasets and evaluation criteria, making it difficult to assess true predictive capabilities. In this work, we introduce a benchmarking framework for evaluating cross-dataset prediction generalization in DRP models. Our framework incorporates five publicly available drug screening datasets, six standardized DRP models, and a scalable workflow for systematic evaluation. To assess model generalization, we introduce a set of evaluation metrics that quantify both absolute performance (e.g., predictive accuracy across datasets) and relative performance (e.g., performance drop compared to within-dataset results), enabling a more comprehensive assessment of model transferability. Our results reveal substantial performance drops when models are tested on unseen datasets, underscoring the importance of rigorous generalization assessments. While several models demonstrate relatively strong cross-dataset generalization, no single model consistently outperforms across all datasets. Furthermore, we identify CTRPv2 as the most effective source dataset for training, yielding higher generalization scores across target datasets. By sharing this standardized evaluation framework with the community, our study aims to establish a rigorous foundation for model comparison, and accelerate the development of robust DRP models for real-world applications. © 2025, CC BY.

关键词： Prediction models