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arXiv 2021年

作者： Bajaj, Shivam Torng, Eric Bopardikar, Shaunak D. Moll, Alexander Von Weintraub, Isaac Garcia, Eloy Casbeer, David W. the Department of Electrical and Computer Engineering Michigan State University United States the Department of Computer Science and Engineering Michigan State University United States Control Science Center Air Force Research Laboratory

We consider a perimeter defense problem in a planar conical environment in which a single vehicle, having a finite capture radius, aims to defend a concentric perimeter from mobile intruders. The intruders are arbitrarily released at the circumference of the environment and they move radially toward the perimeter with fixed speed. We present a competitive analysis approach to this problem by measuring the performance of multiple online algorithms for the vehicle against arbitrary inputs, relative to an optimal offline algorithm that has information about entire input sequence in advance. In particular, we establish two necessary conditions on the parameter space to guarantee (i) finite competitiveness of any algorithm and (ii) a competitive ratio of at least 2 for any algorithm. We then design and analyze three online algorithms and characterize parameter regimes in which they have finite competitive ratios. Specifically, our first two algorithms are provably 1, and 2-competitive, respectively, whereas our third algorithm exhibits different competitive ratios in different regimes of problem parameters. Finally, we provide a numerical plot in the parameter space to reveal additional insights into the relative performance of our algorithms. © 2021, CC BY.

关键词： Network security

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Study of Helicopter Optimal Autorotation Landing Procedure in Tail Rotor Drive Failure

Study of Helicopter Optimal Autorotation Landing Procedure i...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Yan, Xufei Chen, Renliang Zhu, Shiqiang Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics College of Aeronautics Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

This paper investigates the optimal landing trajectory and control procedure when a helicopter undergoes autorotation due to tail rotor drive failure (TRDF), in which an optimal control methodology is proposed. First, a helicopter flight dynamics model with TRDF was developed. Then, the autorotation in TRDF was converted to be a nonlinear optimal control problem, solved by direct node collocation method and sequential quadratic programming algorithm. Finally, a model helicopter (Z11) with single main rotor and tail rotor was used to demonstrate the proposed approach. An optimal autorotation landing procedure in TRDF was determined accordingly. Results indicate that the airframe will immediately respond to the excess torque generated by the main rotor via yawing, sideslip and rolling when TRDF occurs. The pilot is recommended to shut down the engine and perform a series of critical operations to stabilize the violent yaw and roll movements. In addition, flight test data were used to validate the numerical simulations of autorotation landing. The proposed optimal control approach provides a useful tool to investigate helicopter TRDF autorotation landing procedure. © 2022 IEEE.

关键词： Helicopters

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Ambient Infrared Solar Energy Harvesting Using Log-Periodic Optical Rectenna at 28.3 THz

Ambient Infrared Solar Energy Harvesting Using Log-Periodic ...

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Mediterrannean Microwave Symposium (MMS)

作者： Ali Yahyaoui Ahmad Elsharabasy Fahad Al-Qahtani Mohammed Aseeri Hatem Rmili Taoufik Aguili Communications Systems Laboratory (SysCom) University of Tunis El Manar (UTM) National Engineering School of Tunis (ENIT) Tunis Tunisia Electrical and Computer Engineering Department McMaster University Hamilton ON Canada Electrical and Computer Engineering Department Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia Next Generation Connectivity and Wireless Sensors Institute King Abdulaziz City of Science and Technology (KACST) Riyadh Saudi Arabia K. A. CARE Energy Research and Innovation Center King Abdulaziz University Jeddah Saudi Arabia

This work presents the conception and design of log-periodic nano-antenna for the infrared IR solar energy harvesting applications. The suggested nano-antenna contain three layers. The first layer contains two arms of the log-periodic nano-antenna made of gold (Au), the second is a quartz substrate and finally, the ground layer is a gold (Au) plane reflector. The analysis of the proposed nano-antenna is performed using FDTD technique in the range of frequencies [28 to 29 THz]. A huge parametric study was performed to optimize the different parameters (thickness of the arms, teeth angle, number of teeth, substrate thickness, solid angles, and inner radius) of the nano-antenna. With the optimized design parameters, the structure captures a maximum electric field E at the hotspot point of around 800 V/m. The optimized geometry and shape of the presented structure make it a suitable choice to design a metal-insulator-metal (MIM) rectifier system in order to harvest solar infrared IR energy with good performance in terms of E-field, current-voltage I/V, resistance, and responsivity.

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Versatile tape-drive target for high-repetition-rate laser-driven proton acceleration

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High Power Laser science and engineering 2023年第4期11卷 59-69页

作者： N.Xu M.J.V.Streeter O.C.Ettlinger H.Ahmed S.Astbury M.Borghesi N.Bourgeois C.B.Curry S.J.D.Dann N.P.Dover T.Dzelzainis V.Istokskaia M.Gauthier L.Giuffrida G.D.Glenn S.H.Glenzer R.J.Gray J.S.Green G.S.Hicks C.Hyland M.King B.Loughran D.Margarone O.McCusker P.McKenna C.Parisuaña P.Parsons C.Spindloe D.R.Symes F.Treffert C.A.J.Palmer Z.Najmudin John Adams Institute for Accelerator Science Blackett LaboratoryImperial College LondonLondonUK School of Maths and Physics Queen’s University BelfastBelfastUK Central Laser Facility STFC Rutherford Appleton LaboratoryDidcotUK SLAC National Accelerator Laboratory Menlo ParkUSA ELI Beamlines Centre Institute of PhysicsCASDolni BrezanyCzech Republic Faculty of Nuclear Sciences and Physical Engineering Czech Technical University in PraguePragueCzech Republic Department of Physics SUPAUniversity of StrathclydeGlasgowUK Department of Mechanical Engineering Stanford UniversityStanfordUSA Department of Applied Physics Stanford UniversityStanfordUSA Department of Electrical and Computer Engineering University of AlbertaEdmontonCanada Institut für Kernphysik Technische Universität DarmstadtDarmstadtGermany

We present the development and characterization of a high-stability,multi-material,multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 *** tape surface position was measured to be stable on the sub-micrometre scale,compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers(>kHz).Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended *** target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team,with the exception of tape replacement,producing the largest data-set of relativistically intense laser–solid foil measurements to *** tape drive provides robust targetry for the generation and study of high-repetitionrate ion beams using next-generation high-power laser systems,also enabling wider applications of laser-driven proton sources.

关键词： high-repetition-rate laser target laser-plasma acceleration proton generation tape-drive target

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State-space models are accurate and efficient neural operators for dynamical systems

arXiv

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arXiv 2024年

作者： Hu, Zheyuan Daryakenari, Nazanin Ahmadi Shen, Qianli Kawaguchi, Kenji Em Karniadakis, George Department of Computer Science National University of Singapore Singapore119077 Singapore Center for Biomedical Engineering School of Engineering Brown University ProvidenceRI02912 United States Division of Applied Mathematics Brown University ProvidenceRI02912 United States Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory RichlandWA United States

Physics-informed machine learning (PIML) has emerged as a promising alternative to classical methods for predicting dynamical systems, offering faster and more generalizable solutions. However, existing models, including recurrent neural networks (RNNs), transformers, and neural operators, face challenges such as long-time integration, long-range dependencies, chaotic dynamics, and extrapolation, to name a few. To this end, this paper introduces state-space models implemented in Mamba for accurate and efficient dynamical system operator learning. Mamba addresses the limitations of existing architectures by dynamically capturing long-range dependencies and enhancing computational efficiency through reparameterization techniques. To extensively test Mamba and compare against another 11 baselines, we introduce several strict extrapolation testbeds that go beyond the standard interpolation benchmarks. We demonstrate Mamba’s superior performance in both interpolation and challenging extrapolation tasks. Mamba consistently ranks among the top models while maintaining the lowest computational cost and exceptional extrapolation capabilities. Moreover, we demonstrate the good performance of Mamba for a real-world application in quantitative systems pharmacology for assessing the efficacy of drugs in tumor growth under limited data scenarios. Taken together, our findings highlight Mamba’s potential as a powerful tool for advancing scientific machine learning in dynamical systems modeling. (The code will be available at https://***/zheyuanhu01/State_ Space_Model_Neural_Operator upon acceptance.) © 2024, CC BY.

关键词： Recurrent neural networks

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Joint Transmit Precoding and Rate Allocation for Rate-Splitting Multiple Access Based Wireless Backhaul HetNets

Joint Transmit Precoding and Rate Allocation for Rate-Splitt...

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IEEE International Conference on Communications (ICC)

作者： Guangyuan Zheng Miaowen Wen Yingyang Chen Yik-Chung Wu H. Vincent Poor School of Electronic and Information Engineering South China University of Technology Guangzhou China College of Information Science and Technology Jinan University Guangzhou China Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Jinan University Guangzhou China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

In this paper, we investigate the application of rate-splitting multiple access (RSMA) in a two-tier wireless backhaul heterogeneous network (HetNet), where a macro base station (MBS) simultaneously transmits wireless access signals to macro-cell users (MCUs) and wireless backhaul signals to small base stations (SBSs) by leveraging RSMA. In order to improve the system spectral efficiency (SE) while guaranteeing the quality-of-service (QoS) of each user, we formulate an optimization problem to maximize the sum SE by jointly considering transmit precoding and rate allocation at the MBS and SBSs. To solve the formulated non-convex problem, we propose an iterative algorithm based on successive convex approximation (SCA). Simulation results show that the application of RSMA can achieve higher SE over conventional non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) under different network loads. In addition, RSMA has better flexibility than other benchmark schemes in meeting the increasing QoS requirements of users.

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Tractography with T1-weighted MRI and associated anatomical constraints on clinical quality diffusion MRI

arXiv

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arXiv 2024年

作者： Yu, Tian Li, Yunhe Kim, Michael E. Gao, Chenyu Yang, Qi Cai, Leon Y. Resnick, Susane M. Beason-Held, Lori L. Moyer, Daniel C. Schilling, Kurt G. Landman, Bennett A. Department of Computer Science Vanderbilt University NashvilleTN United States Department of Biomedical Engineering Vanderbilt University NashvilleTN United States Department of Electrical Engineering Vanderbilt University NashvilleTN United States Department of Radiology and Radiological Sciences Vanderbilt University NashvilleTN United States Vanderbilt University Institute of Imaging Science Vanderbilt University NashvilleTN United States Laboratory of Behavioral Neuroscience National Institute on Aging BaltimoreMD United States

Diffusion MRI (dMRI) streamline tractography, the gold standard for in vivo estimation of brain white matter (WM) pathways, has long been considered indicative of macroscopic relationships with WM microstructure. However, recent advances in tractography demonstrated that convolutional recurrent neural networks (CoRNN) trained with a teacher-student framework have the ability to learn and propagate streamlines directly from T1 and anatomical contexts. Training for this network has previously relied on high-resolution dMRI. In this paper, we generalize the training mechanism to traditional clinical resolution data, which allows generalizability across sensitive and susceptible study populations. We train CoRNN on a small subset of the Baltimore Longitudinal Study of Aging (BLSA), which better resembles clinical protocols. Then, we define a metric, termed the epsilon ball seeding method, to compare T1 tractography and traditional diffusion tractography at the streamline level. Under this metric, T1 tractography generated by CoRNN reproduces diffusion tractography with approximately two millimeters of error. © 2024, CC BY.

关键词： Magnetic resonance imaging

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Developing New Analysis Tools for Near Surface Radio-based Neutrino Detectors 38

Developing New Analysis Tools for Near Surface Radio-based N...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Barwick, Steven W. Anker, A. Baldi, P. Barwick, S.W. Beise, J. Besson, D.Z. Chen, P. Gaswint, G. Glaser, C. Hallgren, A. Hanson, J.C. Klein, S.R. Kleinfelder, S.A. Lahmann, R. Liu, J. Nam, J. Nelles, A. Paul, M.P. Persichilli, C. Plaisier, I. Rice-Smith, R. Tatar, J. Terveer, K. Wang, S.-H. Welling, C. Zhao, L. University of California Department of Physics and Astronomy IrvineCA United States Department of Physics and Astronomy University of California IrvineCA92697 United States Department of Information and Computer Science University of California IrvineCA92697 United States Uppsala University Department of Physics and Astronomy UppsalaSE-752 37 Sweden Department of Physics and Astronomy University of Kansas LawrenceKS66045 United States Department of Physics Leung Center for Cosmology and Particle Astrophysics National Taiwan University Taipei10617 Taiwan Whittier College Department of Physics WhittierCA90602 United States Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Electrical Engineering and Computer Science University of California IrvineCA92697 United States ECAP Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen91058 Germany Deutsches Elektronen-Synchrotron DESY Zeuthen15738 Germany Research Cyberinfrastructure Center University of California IrvineCA92697 United States The William H. Miller III Department of Physics & Astronomy Johns Hopkins University BaltimoreMD21218 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States

The ARIANNA experiment is an Askaryan radio detector designed to measure high-energy neutrino induced cascades within the Antarctic ice. Ultra-high-energy neutrinos above 1016 eV have an extremely low flux, so experimental data captured at trigger level need to be classified correctly to retain as much neutrino signal as possible. We first describe two new physics-based neutrino selection methods, or "cuts", (the updown and dipole cut) that extend the previously published analysis to a specialized ARIANNA station with 8 antenna channels, which is double the number used in the prior analysis. The new cuts produce a neutrino efficiency of > 95% per station-year of operation, while rejecting 99.93% of the background (corresponding to 53 remaining experimental background events). When the new cuts are combined with a previously developed cut using neutrino waveform templates, all background is removed at no change of efficiency. In addition, the neutrino efficiency is extrapolated to 1,000 station-years of operation, obtaining 91%. This work then introduces a new selection method (the deep learning cut) to augment the identification of neutrino events by using deep learning methods and compares the efficiency to the physics-based analysis. The deep learning cut gives 99% signal efficiency per station-year of operation while rejecting 99.997% of the background (corresponding to 2 remaining experimental background events), which are subsequently removed by the waveform template cut at no significant change in efficiency. The results of the deep learning cut were verified using measured cosmic rays which shows that the simulations do not introduce artifacts with respect to experimental data. The data driven results in this paper demonstrate that the background rejection and signal efficiency of near surface antennas meets the requirements of a large scale future array, as considered in baseline design of the radio component of IceCube-Gen2. © Copyright owned by the author(

关键词： Cosmic rays

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Data Tables and Best Practices for Post-2000 Nonlinear-Optical Materials and Measurements

Data Tables and Best Practices for Post-2000 Nonlinear-Optic...

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2023 Optica Nonlinear Optics Topical Meeting, NLO 2023

作者： Vermeulen, Nathalie Espinosa, Daniel Ball, Adam Ballato, John Boucaud, Philippe Boudebs, Georges Campos, Cecília L.A.V. Dragic, Peter Gomes, Anderson S.L. Huttunen, Mikko J. Kinsey, Nathaniel Mildren, Rich Neshev, Dragomir Padilha, Lázaro Pu, Minhao Secondo, Ray Tokunaga, Eiji Turchinovich, Dmitry Yan, Jingshi Yvind, Kresten Dolgaleva, Ksenia Van Stryland, Eric W. IR-TONA Vrije Universiteit Brussel Pleinlaan 2 Brussel1050 Belgium School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada Dept. Of Electrical & Computer Engineering Virginia Commonwealth University RichmondVA23284 United States Dept of Materials Science and Engineering Clemson University ClemsonSC29634 United States Université Côte d’Azur CNRS CRHEA Rue Bernard Grégory Sophia-Antipolis06905 France Univ Angers LPHIA SFR MATRIX AngersF-49000 France Departamento de Física Universidade Federal de Pernambuco Recife-PE50670-901 Brazil Dept. Of Electrical & Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Tampere University Photonics Laboratory Physics Unit TampereFI-33014 Finland MQ Photonics Research Centre Macquarie University NSW2109 Australia Department of Electronic Materials Engineering Research School of Physics Australian National University CanberraACT2601 Australia Instituto de Fisica "Gleb Wataghin" Universidade Estadual de Campinas Campinas Sao Paulo13083-970 Brazil Department of Electrical and Photonics engineering Technical University of Denmark Kgs. LyngbyDK-2800 Denmark Department of Physics Faculty of Science Tokyo University of Science 1-3 Kagurazaka Shinjuku-ku Tokyo162-8601 Japan Fakultät für Physik Universität Bielefeld Universitätsstr. 25 Bielefeld33615 Germany CREOL The College of Optics and Photonics University of Central Florida OrlandoFL United States

ISBN: (纸本)9781957171234

On the occasion of 60 years of nonlinear-optical research, we present new data tables listing nonlinear-optical properties for different material categories as reported in the literature since 2000, and provide best practices for performing experiments. Optica Nonlinear Optics Topical Meeting 2023 © Optica Publishing Group 2023 © 2023 The Author(s)

关键词： Nonlinear optics

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architectures for Heterogeneous Quantum Error Correction Codes

arXiv

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arXiv 2024年

作者： Stein, Samuel Xu, Shifan Cross, Andrew W. Yoder, Theodore J. Javadi-Abhari, Ali Liu, Chenxu Liu, Kun Zhou, Zeyuan Guinn, Charles Ding, Yufei Ding, Yongshan Li, Ang Pacific Northwest National Laboratory RichlandWA United States Departments of Applied Physics Yale University New HavenCT United States Yale Quantum Institute Yale University New HavenCT United States Department of Computer Science Yale University New HavenCT United States IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY United States Department of Physics Princeton University PrincetonNJ United States Department of Computer Science & Engineering University of Califronia San Diego San DiegoCA United States Department of Electrical & Computer Engineering University of Washington WashingtonWA United States

Quantum Error Correction (QEC) is essential for future quantum computers due to its ability to exponentially suppress physical errors. The surface code is a leading error-correcting code candidate because of its local topological structure, experimentally achievable thresholds, and support for universal gate operations with magic states. However, its physical overhead scales quadratically with number of correctable errors. Conversely, quantum low-density parity-check (qLDPC) codes offer superior scaling but lack, on their own, a clear path to universal logical computation. Therefore, it is becoming increasingly evident that there are significant advantages to designing architectures using multiple codes. Heterogeneous architectures provide a clear path to universal logical computation as well as the ability to access different resource trade offs. To address this, we propose integrating the surface code and gross code using an ancilla bus for inter-code data movement. This approach involves managing trade-offs, including qubit overhead, a constrained instruction set, and gross code (memory) routing and management. While our focus is on the gross-surface code architecture, our method is adaptable to any code combination and the constraints generated by that specific architecture. Motivated by the potential reduction of physical qubit overhead, an ever important feature in the realization of fault tolerant computation, we perform the first full system study of heterogeneous error-correcting codes, discovering architectural trade-offs and optimizing around them. We demonstrate physical qubit reductions of up to 6.42× when executing an algorithm to a specific logical error rate, at the cost of up to a 3.43× increase in execution time. Copyright © 2024, The Authors. All rights reserved.

关键词： Qubits

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