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arXiv 2023年

作者： Ghosh, Subhendu B. Chowdhury, Snehasish Roy Gupta, Tathagata Bhowmik, Anandamay Das Saha, Sutapa Bhattacharya, Some Sankar Guha, Tamal Physics and Applied Mathematics Unit Indian Statistical Institute 203 B.T. Road Kolkata700108 India Department of Astrophysics and High Energy Physics S. N. Bose National Center for Basic Sciences Block JD Sector III Salt Lake Kolkata700106 India International Centre for Theory of Quantum Technologies University of Gdansk Wita Stwosza 63 Gdansk80-308 Poland QICI Quantum Information and Computation Initiative Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong

Discrimination of quantum states under local operations and classical communication (LOCC) is an intriguing question in the context of local retrieval of classical information, encoded in the multipartite quantum systems. All the local quantum state discrimination premises, considered so far, mimic a basic communication set-up, where the spatially separated decoding devices are independent of any additional input. Here, exploring a generalized communication scenario we introduce a framework for input-dependent local quantum state discrimination, which we call local random authentication (LRA). Referring to the term nonlocality, often used to indicate the impossibility of local state discrimination, we coin the term conditional nonlocality for the impossibility associated with the task LRA. We report that conditional nonlocality necessitates the presence of entangled states in the ensemble, a feature absent from erstwhile nonlocality arguments based on local state discrimination. Conversely, all the states in a complete basis set being entangled implies conditional nonlocality. However, the impossibility of LRA also exhibits more conditional nonlocality with less entanglement. The relation between the possibility of LRA and local state discrimination for sets of multipartite quantum states, both in the perfect and conclusive cases, has also been established. The results highlight a completely new aspect of the interplay between the security of information in a network and quantum entanglement under the LOCC paradigm. © 2023, CC BY.

关键词： Quantum entanglement

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SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： de Franca, F.O. Virgolin, M. Kommenda, M. Majumder, M.S. Cranmer, M. Espada, G. Ingelse, L. Fonseca, A. Landajuela, M. Petersen, B. Glatt, R. Mundhenk, N. Lee, C.S. Hochhalter, J.D. Randall, D.L. Kamienny, P. Zhang, H. Dick, G. Simon, A. Burlacu, B. Kasak, Jaan Machado, Meera Wilstrup, Casper Cavaz, W.G.L. Federal University of ABC Santo Andre Brazil Evolutionary Intelligence group Centrum Wiskunde and Informatica Science Park Amsterdam Netherlands University of Applied Sciences Upper Austria Hagenberg Austria Computational Health Informatics Program Boston Children’s Hospital Harvard Medical School Boston USA Center for Computational Astrophysics Flatiron Institute and Department of Astrophysical Sciences of Princeton University USA LASIGE Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Computational Engineering Division Lawrence Livermore National Laboratory Livermore USA Department of Mechanical Engineering University of Utah Utah USA Meta FAIR France Victoria University of Wellington School of Engineering and Computer Science New Zealand University of otago Department of Information Science New Zealand Institut für Angewandte Physik Universität TübingenMax Planck Institute for Intelligent Systems Tübingen Germany Abzu AI Orient Plads 1 Nordhavn Denmark

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main promise of this approach is that it may return an interpretable model that can be insightful to users, while maintaining high accuracy. The current standard for benchmarking these algorithms is SRBench, which evaluates methods on hundreds of datasets that are a mix of real-world and simulated processes spanning multiple domains. At present, the ability of SRBench to evaluate interpretability is limited to measuring the size of expressions on real-world data, and the exactness of model forms on synthetic data. In practice, model size is only one of many factors used by subject experts to determine how interpretable a model truly is. Furthermore, SRBench does not characterize algorithm performance on specific, challenging sub-tasks of regression such as feature selection and evasion of local minima. In this work, we propose and evaluate an approach to benchmarking SR algorithms that addresses these limitations of SRBench by 1) incorporating expert evaluations of interpretability on a domain-specific task, and 2) evaluating algorithms over distinct properties of data science tasks. We evaluate 12 modern symbolic regression algorithms on these benchmarks and present an in-depth analysis of the results, discuss current challenges of symbolic regression algorithms and highlight possible improvements for the benchmark itself. Authors

关键词： Benchmarking

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Persistent flat band splitting and strong selective band renormalization in a kagome magnet thin film

arXiv

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arXiv 2024年

作者： Ren, Zheng Huang, Jianwei Tan, Hengxin Biswas, Ananya Pulkkinen, Aki Zhang, Yichen Xie, Yaofeng Yue, Ziqin Chen, Lei Xie, Fang Allen, Kevin Wu, Han Ren, Qirui Rajapitamahuni, Anil Kundu, Asish K. Vescovo, Elio Kono, Junichiro Morosan, Emilia Dai, Pengcheng Zhu, Jian-Xin Si, Qimiao Minár, Ján Yan, Binghai Yi, Ming Department of Physics and Astronomy Rice University HoustonTX77005 United States Department of Condensed Matter Physics Weizmann Institute of Science Rehovot Israel New Technologies-Research Center University of West Bohemia Plzeň301 00 Czech Republic Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States National Synchrotron Light Source II Brookhaven National Lab UptonNY United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Chemistry Rice University HoustonTX77005 United States Theoretical Division Center for Integrated Nanotechnologies Los Alamos National Laboratory Los AlamosNM United States

Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary FemXn (X=Sn, Ge;m:n = 3:1, 3:2, 1:1) family and the rare earth RMn6Sn6 (R = rare earth) family, where their kagome flat bands are calculated to be near the Fermi level in the paramagnetic phase. While partially filling a kagome flat band is predicted to give rise to a Stoner-type ferromagnetism, experimental visualization of the magnetic splitting across the ordering temperature has not been reported for any of these systems due to the high ordering temperatures, hence leaving the nature of magnetism in kagome magnets an open question. Here, we probe the electronic structure with angle-resolved photoemission spectroscopy in a kagome magnet thin film FeSn synthesized using molecular beam epitaxy. We identify the exchange-split kagome flat bands, whose splitting persists above the magnetic ordering temperature, indicative of a local moment picture. Such local moments in the presence of the topological flat band are consistent with the compact molecular orbitals predicted in theory. We further observe a large spin-orbital selective band renormalization in the Fe dxy+dx2-y2spin majority channel reminiscent of the orbital selective correlation effects in the iron-based superconductors. Our discovery of the coexistence of local moments with topological flat bands in a kagome system echoes similar findings in magic-angle twisted bilayer graphene, and provides a basis for theoretical effort towards modeling correlation effects in magnetic flat band systems. © 2024, CC BY.

关键词： Iron-based Superconductors

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Surveying Cyber Threat Intelligence and Collaboration: A Concise Analysis of Current Landscape and Trends

Surveying Cyber Threat Intelligence and Collaboration: A Con...

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IEEE International Conference on Cloud Computing Technology and science (CloudCom)

作者： Panagiotis Radoglou-Grammatikis Elisavet Kioseoglou Dimitrios Asimopoulos Miltiadis Siavvas Ioannis Nanos Thomas Lagkas Vasileios Argyriou Konstantinos E. Psannis Sotirios Goudos Panagiotis Sarigiannidis Department of Electrical and Computer Engineering Campus ZEP Kozani University of Western Macedonia Kozani Greece William Gladstone 31 K3Y Ltd Sofia Bulgaria MetaMind Innovations P.C. Kila Kozani Greece Centre for Research and Technology Hellas/Information Technologies Institute Thessaloniki Greece Sidroco Holdings Ltd Nicosia Cyprus Department of Computer Science Kavala Campus International Hellenic University Kavala Greece Department of Networks and Digital Media Kingston University London Surrey UK Department of Applied Informatics School of Information Sciences University of Macedonia Thessaloniki Greece School of Physics Aristotle University of Thessaloniki Thessaloniki Greece

The evolution of cyberattacks has been significantly impacted by the rise of Artificial Intelligence (AI). In particular, AI-driven attacks leverage Machine Learning (ML) and Deep Learning (DL) methods to automate tasks like identifying vulnerabilities, crafting convincing phishing emails, and evading conventional security measures. These cyberattacks can adapt in real time, making them more elusive and challenging to detect. Furthermore, AI has enabled the development of AI-powered malware that can learn and evolve, making it even more dangerous. As AI continues to evolve, both attackers and defenders are engaged in a relentless arms race, with cybersecurity professionals striving to harness AI for threat detection and response while cybercriminals seek to exploit AI’s capabilities for their malicious purposes. This ongoing battle underscores the need for proactive and adaptive cybersecurity strategies to mitigate the evolving threats posed by AI-driven cyberattacks. Based on the aforementioned remarks, it is evident that efficient and adaptable countermeasures are necessary. In this paper, we focus our attention on Cyber Threat Intelligence (CTI) mechanisms. CTI is the process of collecting, analysing, and sharing information about potential cybersecurity threats to help organisations proactively defend against cyberattacks. In particular, after providing an overview of the CTI use cases, a brief analysis of existing solutions follows, highlighting the current trends and directions for future work in this research field.

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Landau Polaritons in the Ultrastrong and Superstrong Coupling Regime in a Multimode Terahertz Photonic-Crystal Cavity

Landau Polaritons in the Ultrastrong and Superstrong Couplin...

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International Conference on Infrared and Millimeter Waves

作者： Fuyang Tay Ali Mojibpour Stephen Sanders Shuang Liang Hongjing Xu Geoff C. Gardner Andrey Baydin Michael J. Manfra Alessandro Alabastri David Hagenmüller Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley–Curl Institute Rice University Houston TX USA Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Department of Physics and Astronomy Rice University Houston TX USA Smalley–Curl Institute Rice University Houston TX USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA ISIS (UMR 7006) Université de Strasbourg and CNRS Strasbourg France Department of Materials Science and NanoEngineering Rice University Houston TX USA

We have demonstrated ultrastrong and superstrong coupling of a Landau-quantized two-dimensional electron gas in GaAs with a multiple-mode three-dimensional terahertz photonic-crystal cavity. The cavity had an asymmetric design such that the real-space profiles of photonic modes depended on the electric field polarization. Terahertz magnetospectroscopy experiments with polarized radiation clearly showed that the degree of hybridization of multiple cavity modes is a function of the spatial overlap of the photonic modes. These findings can be utilized for the dynamical tuning of multimode light–matter interactions, which can lead to the development of novel terahertz devices.

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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction

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Scientific Reports 2025年第1期15卷 1-11页

作者： Huang, Kuo-Yang Hsu, Ying-Lin Chung, Che-Liang Chen, Huang-Chi Horng, Ming-Hwarng Lin, Ching-Hsiung Liu, Ching-Sen Xu, Jia-Lang Division of Chest Medicine Department of Internal Medicine Changhua Christian Hospital Changhua Taiwan Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan Ph.D. Program in Medical Biotechnology National Chung Hsing University Taichung Taiwan Institute of Statistics National Chung Hsing University Taichung Taiwan Division of Chest Medicine Department of Internal Medicine Yuanlin Christian Hospital Changhua Taiwan Department of Applied Mathematics National Chung Hsing University Taichung Taiwan Department of Computer Science and Information Engineering Chaoyang University of Technology Taichung Taiwan

The advancement of the Internet of Medical Things (IoMT) has revolutionized data acquisition and processing in critical care settings. Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. The system was deployed on edge devices to enable on-site inference with minimal latency. Among the evaluated models, Random Forest and XGBoost, the latter demonstrated superior predictive performance under both holdout and tenfold cross-validation schemes. Notably, the edge-based architecture reduced server data transmissions by 83.33%, while improving system stability, resilience, and sustainability. This paper details the model evaluation and demonstrates the feasibility and efficiency of edge intelligence in ventilator weaning decision support. © The Author(s) 2025.

关键词： Clinical decision support system Edge-computing Extubation Internet of medical things Machine learning

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Mutation adaptive cuckoo search hybridized naked mole rat algorithm for industrial engineering problems

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Scientific Reports 2025年第1期15卷 1-35页

作者： Salgotra, Rohit Singh, Supreet Verma, Pooja Abualigah, Laith Gandomi, Amir H Faculty of Physics and Applied Computer Science / Centre of Excellence in Artificial Intelligence AGH University of Krakow Kraków Poland Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia School of Computer Science UPES Uttarakhand Dehradun India Department of Computer Science & IT Kathua Campus University of Jammu J & K India Al al-Bayt University Computer Science Department Mafraq Jordan University Research and Innovation Center (EKIK) Óbuda University Bécsi út 96/B Budapest 1034 Hungary Department of Computer Science Khazar University Mahsati 41 Baku Azerbaijan

Cuckoo Search (CS) is a popular algorithm used to solve numerous challenging problems. In the present work, a novel variant of CS is presented to eliminate its shortcomings. The proposed algorithm is hybridized with the naked mole rat algorithm (NMRA) to enhance the exploitative behavior of CS, and is called Mutated Adaptive Cuckoo Search Algorithm (MaCN). This new algorithm has self-adaptive properties and its key feature is to divide the solutions into multiple sections, which are often called sub-swarms. In addition, a bare-bones search mechanism is also added to enhance exploration. The use of adaptive inertia weights helps optimize the switching probability, an important CS parameter that helps to achieve a balanced operation. The proposed MaCN algorithm is tested on CEC 2005 and CEC 2014 benchmark problems. Comparative studies showed that MaCN delivers promising results in solving CEC competition benchmark problems compared to JADE, success history-based adaptive DE (SHADE), LSHADE-SPACMA and self-adaptive DE (SaDE), among others. In addition to numerical benchmarks, MaCN is used to solve the industrial engineering frame structure and a comparison with hybridization of particle swarm with passive congregation (PSOPC), shuffled frog leaping algorithm hybrid with invasive weed optimization (SFLAIWO), particle swarm ant colony optimization (PSOACO), early strategy with DE (ES-DE), and others show its superiority. In addition, the Wilcoxon rankum and the Freidmann test statistically prove the significance of the proposed MaCN algorithm. MaCN was found to score first rank for the benchmarks. The application of the MaCN algorithm to solve the design problems of the suggests that the best new results are obtained for all test cases. © The Author(s) 2025.

关键词： CEC benchmark functions Cuckoo search Frame design problems Mutated cuckoo search Naked mole-rat algorithm

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Correction to: A Modified Anisotropic Diffusion Scheme for Signal-Dependent Noise Filtering

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Circuits, Systems, and Signal Processing 2024年第7期43卷 4220-4220页

作者： Ben Abdallah, Mariem Malek, Jihene Bajahzar, Abdullah Belmabrouk, Hafedh Faculty of Sciences Electronics and Microelectronics Laboratory University of Monastir Monastir Tunisia Department of Electronics Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia Department of Computer Science and Information College of Science Majmaah University Al-Majmaah Saudi Arabia Department of Physics College of Science Majmaah University Al-Majmaah Saudi Arabia

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

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International Conference on Smart Communications and Networking (SmartNets)

作者： Jessé Da Costa Rocha Marcela Alves de Souza Evelin Helena Silva Cardoso Nandamudi Vijaykumar Jasmine Priscyla Leite de Araújo Renato Lisboa Francês Graduate Program in Electrical Engineering Institute of Technology Federal University of Pará (UFPA) Belém Pará Brazil Information and Communication Technology Center Federal University of the South and Southeast of Para (Unifesspa) Marabá Pará Brazil Department of Computer Science Federal Rural University of the Amazon (UFRA) Capitão Poço Pará Brazil Coordination of Applied Research and Technological Development National Institute for Space Research (INPE) São Paulo Brazil

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics.

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Resource-efficient generalized quantum subspace expansion

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Physical Review applied 2025年第5期23卷 054021-054021页

作者： Bo Yang Nobuyuki Yoshioka Hiroyuki Harada Shigeo Hakkaku Yuuki Tokunaga Hideaki Hakoshima Kaoru Yamamoto Suguru Endo LIP6 Sorbonne Université 4 Place Jussieu 75005 Paris France Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan International Center for Elementary Particle Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Theoretical Quantum Physics Laboratory RIKEN Cluster for Pioneering Research Wako-shi Saitama 351-0198 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan Department of Applied Physics and Physico-Informatics Keio University Hiyoshi 3-14-1 Kohoku Yokohama 223-8522 Japan NTT Computer and Data Science Laboratories NTT Corporation 3-9-11 Midori-cho Musashino-shi Tokyo 180-8585 Japan Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka 560-8531 Japan Center for Quantum Information and Quantum Biology Osaka University 1-2 Machikaneyama Toyonaka Osaka 560-0043 Japan

Realizing practical quantum computing requires overcoming a number of computation errors and the limitation of device size, which have intensively been tackled by quantum error mitigation. As a unified approach of noise-agnostic quantum error mitigation, generalized quantum subspace expansion (GSE) has lately been proposed to be remarkably robust regarding stochastic and coherent errors, integrating quantum subspace expansion and virtual state purification. However, the requirement in GSE to perform entangled measurements between copies of the quantum states remains a significant drawback under the current situation of quantum devices with a restricted number of qubits and their connectivity. In this work, we propose “Dual-GSE,” a resource-efficient implementation of GSE to circumvent this overhead by constructing an ansatz of error-mitigated quantum states via dual-state purification without state copies. Remarkably, the proposed method can further simulate larger quantum systems beyond the size of available quantum hardware, achieved by a suitable ansatz construction inspired by the divide-and-conquer strategy that classically reintroduces the effect of entanglement. While classically forging the entanglement comes with additional cost, the total sampling overhead can be notably reduced by reuse of the same Pauli expectation values among divided-and-conquered subsystems. We comprehensively analyze the advantages and overhead of Dual-GSE and perform numerical simulations of the eight-qubit transverse-field Ising model under various setups. Our results demonstrate that Dual-GSE estimates the ground state energy with high accuracy under gate noise with low mitigation overhead and practical sampling cost.

关键词： Qubits

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