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Introduction to Computational Quantum Chemistry for Computer Scientists

Introduction to Computational Quantum Chemistry for Computer...

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Ito, Yasuaki Tsuji, Satoki Fujii, Haruto Suzuki, Kanta Yokogawa, Nobuya Nakano, Koji Kasagi, Akihiko Hiroshima Univ Grad Sch Adv Sci & Technol Kagamiyama 1-4-1 Higashihiroshima 7398527 Japan Fujitsu Ltd Comp Lab Kamikodanaka 4-1-1Nakahara Ku Kawasaki Kanagawa 2118588 Japan

ISBN: (纸本)9798350364613;9798350364606

Computational quantum chemistry is a theoretical approach that utilizes the principles of quantum mechanics to perform computations on the electronic structure of molecules and atoms. This method enables the prediction of properties such as molecular structure, energy, electron orbitals, and electron density. In the field of the first principles, or ab initio, which relies solely on computation and not on experimental data, mathematical understanding allows even those without a background in chemistry to perform molecular orbital computations. The computation of quantum chemistry is computationally intensive, making them highly applicable in the field of high-performance computing. However, initiating quantum chemistry can be challenging for newcomers due to the numerous specialized terms and complex equations from quantum mechanics and chemistry. Therefore, this paper aims to provide a clear and accessible compilation of the fundamental and essential algorithm of the Hartree-Fock method, from theory to implementation. The goal is to offer the minimum required knowledge, in an approachable manner, serving as a starting point for those interested in computational quantum chemistry.

关键词： Computational quantum chemistry ab initio Hartree-Fock method SCF method

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Quantum-Classical-Quantum Workflow in Quantum-HPC Middleware with GPU Acceleration 1

Quantum-Classical-Quantum Workflow in Quantum-HPC Middleware...

引用

1st international conference on Quantum Communications, Networking, and computing, QCNC 2024

作者： Chen, Kuan-Cheng Li, Xiaoren Xu, Xiaotian Wang, Yun-Yuan Liu, Chen-Yu Imperial College London Centre for Quantum Engineering LondonSW7 2BX United Kingdom Imperial College London Department of Materials LondonSW7 2BX United Kingdom University of Waterloo Department of Physics and Astronomy WaterlooON N2L 3G1 Canada NVIDIA Corp. Taipei114 Taiwan Graduate Institute of Applied Physics National Taiwan University Taipei10663 Taiwan

ISBN: (纸本)9798350366778

Achieving high-performance computation on quantum systems is challenging, requiring integration between quantum and classical computing resources. This study presents a distribution-aware Quantum-Classical-Quantum (QCQ) architecture that combines advanced quantum software frameworks with high-performance classical computing to improve quantum simulations for materials and condensed matter physics, including the prediction of quantum phase transitions. The architecture employs Variational Quantum Eigensolver (VQE) algorithms on Quantum Processing Units (QPUs) for efficient quantum state preparation, and Tensor Network states and Quantum Convolutional Neural Networks (QCNNs) on classical hardware for state classification. Utilizing the cuQuantum SDK and PennyLane's Lightning plugin, the QCQ architecture achieves up to tenfold increases in computational speed for complex phase transition classification tasks compared to traditional CPU-based methods, demonstrating 99.5% accuracy in predicting phase transitions in models like the transverse field Ising and XXZ systems. This framework integrates quantum algorithms, machine learning, and Quantum-HPC capabilities, offering transformative insights into the behavior of quantum systems across different scales. As quantum hardware continues to improve, the QCQ framework will play a crucial role in realizing the full potential of quantum computing by seamlessly integrating distributed quantum resources with state-of-the-art classical computing infrastructure. © 2024 ieee.

关键词： Quantum computers

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Multiple distributed Generator Allocation for Energy Loss Reduction Considering Practical Load Models: A Hybrid Approach 1

Multiple Distributed Generator Allocation for Energy Loss Re...

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1st international conference on Innovative Sustainable Technologies for Energy, Mechatronics and Smart systems, IstEMS 2024

作者： Pawar, Abhilasha Viral, R.K. Bansal, Mohit Amity School of Engineering and Technology Department of Electrical and Electronics Engineering Uttar Pradesh Noida India G.L. Bajaj Institute of Technology and Management Department of Electrical and Electronics Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350384246

This research paper suggests novel hybrid methods for the distributed generators (DGs) allocation in distribution network to minimize system loss. The proposed methods employ JAYA optimization algorithm in combination with Analytical and Non-linear Programming (NLP) methods to find out the appropriate sites and capacity of DGs. The JAYA algorithm has been employed to identify the optimal locations of DGs, while the sizes are determined using the analytical and NLP methods in the two hybrid methods, respectively. The validity of the study is established by conducting experiments on ieee 33-bus radial distribution networks, considering both time-invariant and time-variant loads. The attained results are then meticulously compared with conventional methods to ensure their accuracy and reliability. Additionally, the effect of practical load models on the proposed methods is analyzed. The results of the tests demonstrate the efficacy of the hybrid methods in recognizing the suitable locations and most favorable mix of different types of DGs for beneficial allocation, leading to reduced energy loss. © 2024 ieee.

关键词： Nonlinear programming

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A Virtual Sink-based strategy for Reducing the Funneling Effect in ieee 802.15.4 DSME Networks 18

A Virtual Sink-based Strategy for Reducing the Funneling Eff...

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18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Gonzalez, Ivonne Andrea Mantilla Turau, Volker Hamburg Univ Technol Inst Telemat Hamburg Germany

ISBN: (纸本)9781665495127

The MAC protocol ieee 802.15.4 DSME has features for WSNs to support exigent requirements such as high reliability and adaptability to dynamic traffic. This work introduces the concept of a virtual sink, which comprises the sink and its 1-hop neighbors, a.k.a. satellites, as the core of a strategy to alleviate the burden caused by the funneling effect in data collection scenarios. Our strategy enables the coexistence of a centralized scheduling algorithm at the virtual sink and a decentralized scheduling algorithm for the remaining nodes of the network. Through a simulative assessment, we compare the performance of the virtual sink-based strategy with the status quo of DSME via a decentralized slot scheduler TPS. Results show an improvement of the network throughput of up to 38% and a reduction of the energy consumption of about 30% at satellites.

关键词： Funneling effect ieee 802.15.4 DSME virtual sink heuristic scheduling algorithm.

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Modular Platform For Collaborative, distributed sensor Fusion 14

Modular Platform For Collaborative, Distributed Sensor Fusio...

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14th ACM/ieee international conference on Cyber-Physical systems (ICCPS) part of CPS-IoT Week

作者： Spencer, R. Zelter, Nate Hunt, David Angell, Kristen Pajic, Miroslav Duke Univ Durham NC 27706 USA

ISBN: (纸本)9798400700361

Leading autonomous vehicle (AV) platforms and testing infrastructures are, unfortunately, proprietary and closed-source. Thus, it is difficult to evaluate how well safety-critical AVs perform and how safe they truly are. Similarly, few platforms exist for much-needed multi-agent analysis. To provide a starting point for analysis of sensor fusion and collaborative & distributed sensing, we design an accessible, modular sensing platform with AVstack [9]. We build collaborative and distributed camera-radar fusion algorithms and demonstrate an evaluation ecosystem of AV datasets, physics-based simulators, and hardware in the physical world. This three-part ecosystem enables testing next-generation configurations that are prohibitively challenging in existing development platforms.

关键词： Ecosystems

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Solar Irradiance Forecasting Utilizing distributed and Federated Learning 25

Solar Irradiance Forecasting Utilizing Distributed and Feder...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zhang, Hao Yan, Ke College of Information Engineering China Jiliang University Hangzhou China China Jiliang University National University of Singapore Singapore

ISBN: (纸本)9798350330014

Photovoltaic energy generation and prediction are crucial for the integration between solar plants and smart grid. Accurate solar radiation prediction is one of the most important research topics for solar energy generation. Existing deep learning methods require sufficient data for training for achieving the desired results. In traditional deep learning modeling, the data sets required for model training usually come from various data in different regions and organizations, and it is difficult to ensure data security and privacy protection. Federated learning can effectively utilize the data optimization model while ensuring data security and privacy, but there is still the risk of privacy leakage by analyzing the parameters uploaded by the client. To effectively utilize data optimization models while ensuring data security and privacy, we propose a method based on a federated learning framework and N-BEATS to achieve interpretable time series prediction of solar irradiance. The model builds the N-BEATS model on the solar irradiance datasets of multiple institutions in a distributed method, does not share local data to protect institutional data privacy, the concept of differential privacy (DP) is introduced, Gaussian noise is added to the parameters of the client before the server-side aggregation processing, the model parameters of each distributed node are collected through TCP communication for federated average, and the parameters are returned to each distributed node. The experimental results show that compared with other deep learning models, the model has better prediction accuracy under the premise of ensuring data security and privacy. © 2023 ieee.

关键词： Solar radiation

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A Logical Time-Triggered distributed computing Environment for Cyber-Physical systems with V2X Wireless Communication 1

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17th international conference on Information Technology and Applications, ICITA 2023

作者： Nakajima, Shunsuke Shimabukuro, Kenji Takehara, Eiya Yokoyama, Takanori Yoo, Myungryun WingArc1st Inc. Tokyo Japan BIGLOBE Inc. Tokyo Japan TOPPAN Edge Inc. Tokyo Japan Tokyo City University Tokyo Japan

ISBN: (数字)9789819983247

ISBN: (纸本)9789819983230

The paper presents a logical time-triggered distributed computing environment for cyber-physical systems utilizing V2X (Vehicle to Everything) wireless communication based on ieee802.11p protocol. Logical time-triggered processing realizes real-time distributed computing equivalent to the time-triggered architecture without time synchronization. We have developed a real-time operating system emulator running on Linux, which manages tasks based on EDF (Earliest Deadline First) scheduling with logical deadlines. We have also developed distributed computing middleware that manages logical time and timestamped messages and communication software that supports ieee802.11p. By using the distributed computing environment, logical time-triggered cyber-physical systems with ieee802.11p wireless communication can be developed without considering either timestamps or logical time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Real time systems

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stable Soft sensor Modeling for Industrial systems 7

Stable Soft Sensor Modeling for Industrial Systems

引用

ieee 7th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Cao, Liang Cao, Yankai Gopaluni, R. Bhushan Univ British Columbia Chem & Biol Engn Vancouver BC V6T 1Z3 Canada

ISBN: (纸本)9798350363029;9798350363012

Learning trustworthy models is essential for machine learning tasks, as many researchers have revealed the vulnerability of machine learning models, especially when the fundamental independent and identically distributed (IID) assumption is not satisfied. Building a trustworthy model is promising when training on big representative data but fails to work with limited data. In this paper, we focus on solving small sample problems and unstable prediction problems in machine learning. First, to deal with small sample problems, we propose using a uniform manifold approximation and projection (UMAP) algorithm to generate high-quality virtual samples. Then, with the generated big data and original small data, we use the stable learning method to achieve stable predictions. In addition to a detailed description of the UMAP algorithm and the stable learning algorithm, we also discuss the corresponding theoretical explanations and implementation details. Finally, several comparison studies are implemented on the Tennessee Eastman benchmark process to validate the effectiveness of the proposed method.

关键词： trustworthy model small sample UMAP stable learning soft sensor

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Review of Design Issues, Applications, and Architecture of Wireless sensor Networks 1

Review of Design Issues, Applications, and Architecture of W...

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1st international conference on Healthcare Innovations, Software and Engineering Technologies, HISET 2024

作者： Mishra, Anupama Swami Rama Himalayan University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350360707

The design and development of low-cost intelligent sensor networks has been made possible by recent advancements in wireless communications, signal processing, and embedded systems. sensor networks have a wide range of applications, including but not limited to health, military, home automation, agriculture, and disaster mitigation. Researchers are now addressing various technical difficulties specific to distinct application areas. This paper provides a comprehensive study of the design issues, applications, and architecture of wireless sensor networks. This paper aims to explore and analyze several technical elements of Wireless sensor Networks (WSNs) in order to give fundamental knowledge to the researchers and other readers. © 2024 ieee.

关键词： sensor nodes

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Design of Corpus distributed Retrieval System Based on Elasticsearch Search Engine 1

Design of Corpus Distributed Retrieval System Based on Elast...

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1st international conference on Software, systems and Information Technology, SSITCON 2024

作者： Cai, Chunpeng Bohai University College of Foreign Languages Jinzhou China

ISBN: (数字)9798350352931

ISBN: (纸本)9798350352931

Information retrieval is the best practice to solve information data overload. Elasticsearch is a distributed, high-performance elastic full-text search engine based on Lucene extension. Based on Elasticsearch framework, this paper studies the distributed retrieval of corpora to meet the needs of the research and use of corpora in the information age. The research content mainly includes four aspects: First, the Elasticsearch architecture is studied, including the functions and data operations of each layer. Then, the N-Gram linguistic statistical model is studied, based on the basic N-Gram model, Markov hypothesis is introduced to improve it, and the parameter estimation and data smoothing of the N-Gram model are studied. Then, a corpus distributed retrieval module is designed, including index creation, retrieval process design and highlighting design. Preferably, the system is tested and validated, including building test environments, functional testing, and compatibility testing. The test results show that the system achieves the expected goal and has high retrieval efficiency and accuracy. Research has found that a corpus distributed retrieval system designed based on Elasticsearch search engine has fast retrieval speed, good practicality, and reliability. © 2024 ieee.

关键词： Search engines

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