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Geometric energy transfer in a Stückelberg interferometer of two parametrically coupled mechanical modes

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arXiv 2018年

作者： Fu, Hao Gong, Zhi-cheng Mao, Tian-hua Shen, Cheng-yu Sun, Chang-pu Yi, Su Li, Yong Cao, Geng-yu State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan430071 China University of Chinese Academy of Sciences Beijing100190 China Graduate School of the China Academy of Engineering Physics Beijing100193 China Beijing Computational Science Research Center Beijing100193 China CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China School of Physics & CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing100190 China

Geometric phase, which is acquired after a system undergoing cyclic evolution in the Hilbert space, is believed to be noise-resilient because it depends only on the global properties of the evolution path. Here, we report geometric control of energy transfer between two parametrically coupled mechanical modes in an optomechanical system. The parametric pump is controlled along a closed loop to implement geometric Stückelberg interferometry of mechanical motion, in which the dynamical phase is eliminated using the Hahn-echo technique. We demonstrate that the interference based solely on the geometric phase is robust against certain noises. And, more remarkably, we show that the all-geometric approach can achieve a high energy-transfer rate that is comparable to those using conventional dynamical protocols. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy transfer

RETRACTED ARTICLE: Prewitt Logistic Deep Recurrent Neural Learning for Face Log Detection by Extracting Features from Images

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Arabian Journal for science and engineering 2021年第2期48卷 2589-2589页

作者： Krishnan Nair, Sreekumar Chinnappan, Sathiya Kumar Dubey, Anil Kumar Subburaj, Arjun Subramaniam, Shanthi Balasubramaniam, Vivekanandam Sengan, Sudhakar Department of Computer Science and Engineering School of Computing SRM Institute of Science and Technology Kattankulathur India Department of Computational Intelligence School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Computer Science and Engineering ABES Engineering College Ghaziabad Uttar Pradesh India Tranxit Technology Solutions Private Limited Chennai India Department of Computer Science and Engineering Kongu Engineering College Perundurai India Faculty of Computer Science and Multimedia Lincoln University College Kota Bharu Malaysia Department of Computer Science and Engineering PSN College of Engineering and Technology Tirunelveli India

Integrating educational theories with virtual reality: Enhancing engineering education and VR laboratories

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Social sciences and Humanities Open 2024年 10卷

作者： Abbas Shah, Syed Faisal Mazhar, Tehseen Shahzad, Tariq khan, Muhammad Amir Ghadi, Yazeed Yasin Hamam, Habib Department of Computer Science & Information Technology Virtual University of Pakistan Lahore 54000 Pakistan Department of Computer Science and information Technology School Education Department Government of Punjab Layyah 31200 Pakistan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal 57000 Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam 40450 Malaysia Department of Computer Science and Software Engineering Al Ain University Abu Dhabi 12555 United Arab Emirates Faculty of Engineering University de Moncton Moncton E1A3E9 NB Canada Department of Electrical and Electronic Engineering Sciences University of Johannesburg Johannesburg 2006 South Africa International Institute of Technology and Management (IITG) Av. Grandes Ecoles BP Libreville 1989 Gabon Bridges for Academic Excellence - Spectrum Tunis Tunisia

Immersive technologies, including virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR), create realistic digital experiences by overlaying digital elements. This study aims to highlight the benefits of utilizing VR technology in education, particularly in universities and higher education institutions, by integrating VR with educational theories to create engaging and interactive learning experiences that enhance understanding and retention. This review includes a comprehensive analysis of 103 works, synthesizing existing literature to evaluate the suitability of various educational approaches and theories for implementation in VR-based educational applications. The findings emphasize VR's potential to transform learning by providing immersive experiences that bridge different domains and encourage engagement. By integrating learning theory into VR development, meaningful learning environments can be created, improving student understanding and retention across diverse learning settings. The study concludes that the combination of technology and educational theories provides a novel approach to motivate students and foster deep learning in VR laboratories. © 2024 The Authors

关键词： Augmented reality Educational theories engineering education Immersive technology Interactive learning VR laboratories

A Brief Review of Explainable Artificial Intelligence in Healthcare

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arXiv 2023年

作者： Sadeghi, Zahra Alizadehsani, Roohallah Cifci, Mehmet Akif Kausar, Samina Rehman, Rizwan Mahanta, Priyakshi Bora, Pranjal Kumar Almasri, Ammar Alkhawaldeh, Rami S. Hussain, Sadiq Alatas, Bilal Shoeibi, Afshin Moosaei, Hossein Hladík, Milan Nahavandi, Saeid Pardalos, Panos M. Institute for Big Data Analytics Faculty of Computer Science Dalhousie University Canada Deakin University Geelong Australia The Institute of Computer Technology Tu Wien University Vienna1040 Austria University of Kotli Azad Jammu and Kashmir Azad Kashmir Kotli Pakistan Centre for Computer Science and Applications Dibrugarh University Assam India Department of Management Information Sys Al-Balqa Applied University Salt19117 Jordan Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Examination Branch Dibrugarh University Assam Dibrugarh India Department of Software Eng. Firat University Elazig23100 Turkey Data Science and Computational Intelligence Institute University of Granada Spain Department of Informatics Faculty of Science Jan Evangelista Purkyně University in Ústí nad Labem Czech Republic Department of Applied Mathematics School of Computer Science Faculty of Mathematics and Physics Charles University Prague Czech Republic Harvard Paulson School of Engineering and Applied Sciences Harvard University AllstonMA02134 United States Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville32611 United States

XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-stakes decision-making situations, such as medical domain have increased the demand for transparency and explainability since wrong predictions may have severe consequences. Model explainability and interpretability are vital successful deployment of AI models in healthcare practices. AI applications' underlying reasoning needs to be transparent to clinicians in order to gain their trust. This paper presents a systematic review of XAI aspects and challenges in the healthcare domain. The primary goals of this study are to review various XAI methods, their challenges, and related machine learning models in healthcare. The methods are discussed under six categories: Features-oriented methods, global methods, concept models, surrogate models, local pixel-based methods, and human-centric methods. Most importantly, the paper explores XAI role in healthcare problems to clarify its necessity in safety-critical applications. The paper intends to establish a comprehensive understanding of XAI-related applications in the healthcare field by reviewing the related experimental results. To facilitate future research for filling research gaps, the importance of XAI models from different viewpoints and their limitations are investigated. © 2023, CC BY-NC-ND.

关键词： Decision making

Single Relaxation Time and Multiple Revised Matrix Lattice Boltzmann Simulations of Forced Isotropic Turbulence

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SSRN

SSRN 2022年

作者： Abdel Kareem, Waleed Sayed Asinari, Pietro Succi, Sauro Izawa, Seiichiro Fukunishi, Yu Department of Mathematics Faculty of Science Suez University Suez Egypt Academy of Scientific Research & Technology 101 Al Kasr El Aini Cairo Egypt Department of Energetics Politecnico di Torino Torino10129 Italy Instituto per le Applicazioni del Calcolo CNR Via dei Taurini 19 Roma00185 Italy Department of Mechanical Engineering and Sciences University of Toyama Japan Institute of Computational Fluid Dynamics 1-16-5 Haramachi Meguro-ku Tokyo152-0011 Japan

The single relaxation time (SRT) and the revised matrix (RM) lattice Boltzmann models are compared for simulations of three dimensional forced isotropic turbulence with resolutions of 128 3 and 256 3 , respectively. The forcing technique by Guo et al.[1] is applied with the two models using the same parameters and conditions. Some new aspects and results have been confirmed such as the superiority of the MRT model to simulate forced turbulence and using the Courant-Friedichs-Lewy condition (CFL) [2] by multiplying the velocity input with the coefficient CFL © 2022, The Authors. All rights reserved.

关键词： Turbulence

Blinking coupling enhances network synchronization

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Physical Review E 2022年第5期105卷 054304-054304页

作者： Fatemeh Parastesh Karthikeyan Rajagopal Sajad Jafari Matjaž Perc Eckehard Schöll Department of Biomedical Engineering Amirkabir University of Technology (Tehran Polytechnic) Iran Center for Nonlinear Systems Chennai Institute of Technology India Health Technology Research Institute Amirkabir University of Technology (Tehran Polytechnic) Iran Faculty of Natural Sciences and Mathematics University of Maribor Koroška Cesta 160 2000 Maribor Slovenia Department of Medical Research China Medical University Hospital China Medical University Taichung 404332 Taiwan Complexity Science Hub Vienna Josefstädterstraße 39 1080 Vienna Austria Institut für Theoretische Physik Technische Universität Berlin Hardenbergstrasse 36 D-10623 Berlin Germany Bernstein Center for Computational Neuroscience Berlin Humboldt-Universität D-10115 Berlin Germany Potsdam Institute for Climate Impact Research Telegrafenberg A 31 D-14473 Potsdam Germany

This paper studies the synchronization of a network with linear diffusive coupling, which blinks between the variables periodically. The synchronization of the blinking network in the case of sufficiently fast blinking is analyzed by showing that the stability of the synchronous solution depends only on the averaged coupling and not on the instantaneous coupling. To illustrate the effect of the blinking period on the network synchronization, the Hindmarsh-Rose model is used as the dynamics of nodes. The synchronization is investigated by considering constant single-variable coupling, averaged coupling, and blinking coupling through a linear stability analysis. It is observed that by decreasing the blinking period, the required coupling strength for synchrony is reduced. It equals that of the averaged coupling model times the number of variables. However, in the averaged coupling, all variables participate in the coupling, while in the blinking model only one variable is coupled at any time. Therefore, the blinking coupling leads to an enhanced synchronization in comparison with the single-variable coupling. Numerical simulations of the average synchronization error of the network confirm the results obtained from the linear stability analysis.

关键词： Synchronization

Traceable random numbers from a nonlocal quantum advantage

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arXiv 2024年

作者： Kavuri, Gautam A. Palfree, Jasper Reddy, Dileep V. Zhang, Yanbao Bienfang, Joshua C. Mazurek, Michael D. Alhejji, Mohammad A. Siddiqui, Aliza U. Cavanagh, Joseph M. Dalal, Aagam Abellán, Carlos Amaya, Waldimar Mitchell, Morgan W. Stange, Katherine E. Beale, Paul D. Brandão, Luís T.A.N. Booth, Harold Peralta, René Nam, Sae Woo Mirin, Richard P. Stevens, Martin J. Knill, Emanuel Shalm, Lynden K. Department of Physics University of Colorado BoulderCO80309 United States The National Institute of Standards and Technology BoulderCO80305 United States Quantum Information Science Section Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Joint Quantum Institute National Institute of Standards and Technology University of Maryland 100 Bureau Drive GaithersburgMD20899 United States Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Physical Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Quside Technologies S.L. Castelldefels Barcelona Spain ICFO-Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Castelldefels Barcelona08860 Spain ICREA - Institució Catalana de Recerca i Estudis Avançats Barcelona08010 Spain Department of Mathematics University of Colorado BoulderCO80309 United States GaithersburgMD20899 United States Information Technology Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Physical Measurement Laboratory National Institute of Standards and Technology BoulderCO80305 United States Center for Theory of Quantum Matter University of Colorado BoulderCO80305 United States Applied and Computational Mathematics Division National Institute of Standards and Technology BoulderCO80305 United States Quantum Engineering Initiative Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States

The unpredictability of random numbers is fundamental to both digital security [1, 2] and applications that fairly distribute resources [3, 4]. However, existing random number generators have limitations—the generation processes cannot be fully traced, audited, and certified to be unpredictable. The algorithmic steps used in pseudorandom number generators [5] are auditable, but they cannot guarantee that their outputs were a priori unpredictable given knowledge of the initial seed. Device-independent quantum random number generators [6–9] can ensure that the source of randomness was unknown beforehand, but the steps used to extract the randomness are vulnerable to tampering. Here, for the first time, we demonstrate a fully traceable random number generation protocol based on device-independent techniques. Our protocol extracts randomness from unpredictable non-local quantum correlations, and uses distributed intertwined hash chains to cryptographically trace and verify the extraction process. This protocol is at the heart of a public traceable and certifiable quantum randomness beacon that we have launched [10]. Over the first 40 days of operation, we completed the protocol 7434 out of 7454 attempts—a success rate of 99.7%. Each time the protocol succeeded, the beacon emitted a pulse of 512 bits of traceable randomness. The bits are certified to be uniform with error times actual success probability bounded by 2−64. The generation of certifiable and traceable randomness represents one of the first public services that operates with an entanglement-derived advantage over comparable classical approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Random number generation

Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots

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arXiv 2023年

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the education sector, identifying potential concerns and challenges. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within Generative AI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023, CC0.

关键词： Machine learning

Experimental self-characterization of quantum measurements

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arXiv 2019年

作者： Zhang, Aonan Xie, Jie Xu, Huichao Zheng, Kaimin Zhang, Han Poon, Yiu-Tung Vedral, Vlatko Zhang, Lijian National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences School of Physics Nanjing University Nanjing210093 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China Department of Mathematics Iowa State University AmesIA50011 United States Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China Center for Quantum Computing Peng Cheng Laboratory Shenzhen518055 China Atomic and Laser Physics Clarendon Laboratory University of Oxford Parks Road OxfordOX13PU United Kingdom Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 117543 Singapore

The accurate and reliable description of measurement devices is a central problem in both observing uniquely non-classical behaviors and realizing quantum technologies from powerful computing to precision metrology. To date quantum tomography is the prevalent tool to characterize quantum detectors. However, such a characterization relies on accurately characterized probe states, rendering reliability of the characterization lost in circular argument. Here we report a self-characterization method of quantum measurements based on reconstructing the response range of the measurement outcomes, eliminating the reliance on known states. We characterize two representative measurements implemented with photonic setups and obtain fidelities above 99.99% with the conventional tomographic reconstructions. This initiates range-based techniques in characterizing quantum systems and foreshadows novel device-independent protocols of quantum information applications. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum optics