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Optica Quantum 2.0 Conference and Exhibition, Quantum 2.0

作者： Oliver, Richard Blau, Miri Ji, Xingchen Gutiérrez-Jáuregui, Ricardo Asenjo-Garcia, Ana Lipson, Michal Gaeta, Alexander L. Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States Department of Electrical Engineering Columbia University New YorkNY10027 United States Department of Physics Columbia University New YorkNY10027 United States

We propose multipartite Bragg-scattering to perform all-to-all transformation among N frequency modes, realizing a bosonic N-level system. We demonstrate the N = 3 case illustrating a pathway towards scalability for f... 详细信息

ISBN: (纸本)9781957171272

关键词： Fiber Bragg gratings Four wave mixing Phase matching Quantum information Single mode fibers Superconducting nanowire single photon detectors

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On the Computational Determination of the Third Focus of the Cartesian Oval 32

On the Computational Determination of the Third Focus of the...

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32nd Telecommunications Forum, TELFOR 2024

作者： Malesevic, Branko Rosic, Aleksandra Banjac, Bojan Micovic, Milos University of Belgrade School of Electrical Engineering Department of Applied Mathematics Bulevar kralja Aleksandra 73 Belgrade11000 Serbia University of Belgrade Faculty of Mathematics Department of Algebra and Mathematical Logic Studentski trg 16 Belgrade11000 Serbia University of Novi Sad Computer Graphics Chair Faculty of Technical Sciences Trg Dositeja Obradovica 16 Novi Sad21000 Serbia Intens Doo Bulevar Evrope 28 Novi Sad21000 Serbia School of Electrical Engineering University of Belgrade Science and Research Centre Department of Applied Mathematics Bulevar kralja Aleksandra 73 Belgrade11000 Serbia

ISBN: (纸本)9798350391053

In this paper, the correctness of the algebraic determination of the coordinate of the third focus of the Cartesian oval is examined and analysed. This analysis is necessary because the process includes solving systems with a large number of multivariate polynomial equations using the computer algebra system Maple. The paper also considers the difficulties and limitations of using computers in determining the coordinate of the third focus. © 2024 IEEE.

关键词： Polynomials

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Net Load Forecast based on Behind-the-Meter Disaggregation of Smart Meter Data 57

Net Load Forecast based on Behind-the-Meter Disaggregation o...

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57th Annual Conference on Information Sciences and Systems, CISS 2023

作者： Jia, Mian Pu, Kang Zhao, Yue Stony Brook University Department of Applied Mathematics and Statistics Stony BrookNY11794 United States Stony Brook University Department of Electrical and Computer Engineering Stony BrookNY11794 United States

ISBN: (纸本)9781665451819

As the penetration of behind-the-meter (BTM) rooftop solar energies continues to increase in power distribution systems, it is of paramount importance for load serving entities and system operators to forecast net loads in the system. In this paper, novel algorithms for training high-performance predictors for day-ahead net load forecasting are developed. Importantly, the overall method only utilizes metered net load data and does not require any monitoring data of solar generation. Methodologically, the net load data trace is disaggregated into estimated BTM solar and load traces, based on which separate predictors are then trained for solar generation and load forecasting exploiting their distinct natures, respectively. For solar generation forecasting, time data, weather forecast, and potentially solar irradiance forecast are used as input features of the predictor. For load forecasting, time data, weather forecast, and judiciously chosen load data in the recent past are used as input features of the predictor. The two predictors' outputs are combined to produce the final net load forecast. The developed method is comprehensively evaluated based on two real-world smart meter data sets from Ithaca, NY and Clifton park, NY, respectively. High accuracy of day-ahead net load forecast is demonstrated. © 2023 IEEE.

关键词： Smart meters

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Inverse Contextual Bandits: Learning How Behavior Evolves over Time 39

Inverse Contextual Bandits: Learning How Behavior Evolves ov...

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39th International Conference on Machine Learning, ICML 2022

作者： HÃ¼yÃ¼k, Alihan Jarrett, Daniel van der Schaar, Mihaela Department of Applied Mathematics and Theoretical Physics University of Cambridge United Kingdom Department of Electrical Engineering University of California Los Angeles United States

Understanding a decision-maker's priorities by observing their behavior is critical for transparency and accountability in decision processes-such as in healthcare. Though conventional approaches to policy learning almost invariably assume stationarity in behavior, this is hardly true in practice: Medical practice is constantly evolving as clinical professionals fine-tune their knowledge over time. For instance, as the medical community's understanding of organ transplantations has progressed over the years, a pertinent question is: How have actual organ allocation policies been evolving? To give an answer, we desire a policy learning method that provides interpretable representations of decision-making, in particular capturing an agent's non-stationary knowledge of the world, as well as operating in an offline manner. First, we model the evolving behavior of decision-makers in terms of contextual bandits, and formalize the problem of Inverse Contextual Bandits (ICB). Second, we propose two concrete algorithms as solutions, learning parametric and nonparametric representations of an agent's behavior. Finally, using both real and simulated data for liver transplantations, we illustrate the applicability and explainability of our method, as well as benchmarking and validating its accuracy. Copyright Â© 2022 by the author(s)

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A chattering free consensus controller for multiple Lur'e systems with a non-autonomous leader and directed switching topology

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Science China(Technological Sciences) 2023年第4期66卷 1110-1118页

作者： WANG PeiJun YU WenWu WEN GuangHui YU XingHuo HUANG TingWen School of Mathematics and Statistics Anhui Normal UniversityWuhu 241000China Anhui Province Engineering Laboratory of Intelligent Robot's Information Fusion and Control Anhui Normal UniversityWuhu 241000China School of Mathematics Frontiers Science Center for Mobile Information Communication and SecuritySoutheast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 21111lChina Department of Electrical Engineering Nantong UniversityNantong 226019China Department of Systems Science School of MathematicsSoutheast UniversityNanjing 210096China School of Engineering RMIT UniversityMelbourne VIC 3001Australia Science Program Texas A&M University at QatarDoha 23874Qatar

Achieving asymptotical cooperative goal for multi-agent systems(MASs)with non-autonomous leaders(i.e.,leaders with nonzero inputs)is a critical but challenging *** approach is to use discontinuous controllers which may cause chattering phenomenon in practical *** to achieve the asymptotical goal via a chattering free cooperative controller remains to be open so *** this paper,an adaptive continuous controller is designed to achieve zero error consensus tracking in multiple Lur’e systems with a non-autonomous leader under directed switching ***,an unknown input observer(UIO)based on relative outputs is given to estimate the relative full *** an adaptive continuous controller is designed by introducing a decay function which remains positive into the term that plays the role of eliminating the impacts of leader’s nonzero ***,by using multiple Lyapunov functions(MLFs)technique,it is proven that zero error consensus tracking can be achieved if the average dwell time(ADT)is greater than a positive ***,theoretical result is verified by performing simulations on Chua’s *** with existing work,the proposed controller can not only achieve asymptotical consensus,but also is chattering free.

关键词： multi-agent system consensus chattering free non-autonomous leader directed switching topology

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Estimation of Time-Varying Graph Topologies from Graph Signals 48

Estimation of Time-Varying Graph Topologies from Graph Signa...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Liu, Yuhao Cui, Chen Ajirak, Marzieh Djurić, Petar M. Stony Brook University Department of Applied Mathematics and Statistics Stony BrookNY11794 United States Stony Brook University Department of Electrical and Computer Engineering Stony BrookNY11794 United States

ISBN: (纸本)9781728163277

In science and engineering, we often deal with signals that are acquired from time-varying systems represented by dynamic graphs. We observe these signals, and the interest is in finding the time-varying topology of the graphs. We propose two Bayesian methods for estimating these topologies without assuming any specific functional relationships among the signals on the graphs. The two methods exploit Gaussian processes, where the first method uses the length scale of the kernel and relies on variational inference for optimization, and the second method is based on derivatives of the functions and Monte Carlo sampling. Both methods estimate the time-varying topologies of the graphs sequentially. We provide numerical tests that show the performance of the methods in two settings. © 2023 IEEE.

关键词： estimation of topology Monte Carlo sampling sequential estimation time-varying graphs variational inference

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Learning-based Real-time Outage Location Identification in Power Distribution Systems with Sparse Sensors 14

Learning-based Real-time Outage Location Identification in P...

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14th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Pu, Kang Xu, Ce Zhao, Yue Stony Brook University Department of Applied Mathematics and Statistics Stony BrookNY11794 United States Stony Brook University Department of Electrical and Computer Engineering Stony BrookNY11794 United States

ISBN: (纸本)9781665455541

Real-time identification of outage locations in power distribution systems is an essential task for utilities to mitigate the negative impact of power system outages. In this paper, a learning-based model-assisted method is developed for identifying outage locations in power distribution systems in real time. Notably, the method utilizes primarily only a) sparsely located supervisory control and data acquisition (SCADA) measurements, and potentially b) last gasp signals from a small number of smart meters. The method exploits offline training of outage location predictors based on data simulated with synthetically generated load profiles and outage scenarios. The trained predictors can then be used in an online fashion to accurately identify outage locations in new scenarios in real time. With physical-model-based network partitioning, the offline learning is decoupled into training predictors for much smaller sub-regions so that the learning efficiency is much improved. Importantly, the trained predictors based only on SCADA measurements and entropy loss functions can be integrated with smart meter last gasp signals, without toss of any optimality, regardless of smart meter locations, outage scenarios, and performance evaluation metrics. Evaluation of the method based on real-world power distribution feeder and load data demonstrates high accuracy in outage location identification even using SCADA measurements only. We then demonstrated how having just a handful of smart meters with last gasp capabilities can further improve the outage location accuracy significantly. © 2023 IEEE.

关键词： Smart meters

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MEAN FIELD GAMES WITH COMMON NOISE VIA MALLIAVIN CALCULUS

arXiv

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arXiv 2024年

作者： Tangpi, Ludovic Wang, Shichun Princeton University Department of Operations Research and Financial Engineering and Program in Computational and Applied Mathematics United States

We present a simpler proof of the existence of equilibria for a class of mean field games with common noise, where players interact through the conditional law given the current value of the common noise rather than its entire path. By extending a compactness criterion for Malliavin-differentiable random variables to processes, we establish existence of strong equilibria, where the conditional law and optimal control are adapted to the common noise filtration and defined on the original probability space. Notably, our approach only requires measurability of the drift and cost functionals with respect to the state *** Codes 91A16, 60H07 Copyright © 2024, The Authors. All rights reserved.

关键词： Cost functions

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Inferring System and Optimal Control Parameters of Closed-Loop Systems from Partial Observations 63

Inferring System and Optimal Control Parameters of Closed-Lo...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Geadah, Victor Arbelaiz, Juncal Ritz, Harrison Daw, Nathaniel D. Cohen, Jonathan D. Pillow, Jonathan W. Princeton University Department of Mechanical and Aerospace Engineering PrincetonNJ United States Princeton University Program in Applied and Computational Mathematics PrincetonNJ United States Princeton Neuroscience Institute Princeton University PrincetonNJ United States

ISBN: (纸本)9798350316339

We consider the joint problem of system identification and inverse optimal control for discrete-time stochastic Linear Quadratic Regulators. We analyze finite and infinite time horizons in a partially observed setting, where the state is observed noisily. To recover closed-loop system parameters, we develop inference methods based on probabilistic statespace model (SSM) techniques. First, we show that the system parameters exhibit non-identifiability in the infinite-horizon from closed-loop measurements, and we provide exact and numerical methods to disentangle the parameters. Second, to improve parameter identifiability, we show that we can further enhance recovery by either (1) incorporating additional partial measurements of the control signals or (2) moving to the finitehorizon setting. We further illustrate the performance of our methodology through numerical examples. © 2024 IEEE.

关键词： Stochastic systems

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Optimal Resource Allocation for NOMA Wireless Networks

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Computers, Materials & Continua 2023年第2期74卷 3249-3261页

作者： Fahad R.Albogamy M.A.Aiyashi Fazirul Hisyam Hashim Imran Khan Bong Jun Choi Turabah University College Computer Sciences ProgramTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics Jazan UniversityJazanP.O.Box 218Saudi Arabia Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra Malaysia(UPM)43400SerdangMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarP.O.Box 814Pakistan School of Computer Science and Engineering Soongsil UniversitySeoulKorea

The non-orthogonal multiple access(NOMA)method is a novel multiple access technique that aims to increase spectral efficiency(SE)and accommodate enormous user ***-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information,and multi-user detection algorithms,such as successive interference cancellation(SIC),are performed at the receiving end to demodulate the necessary user *** its basic signal waveform,like LTE baseline,could be based on orthogonal frequency division multiple access(OFDMA)or discrete Fourier transform(DFT)-spread OFDM,NOMA superimposes numerous users in the power *** contrast to the orthogonal transmission method,the nonorthogonal method can achieve higher spectrum ***,it will increase the complexity of its *** power allocation techniques will have a direct impact on the system’s *** a result,in order to boost the system capacity,an efficient power allocation mechanism must be *** research developed an efficient technique based on conjugate gradient to solve the problem of downlink power *** major goal is to maximize the users’maximum weighted sum *** suggested algorithm’s most notable feature is that it converges to the global optimal *** compared to existing methods,simulation results reveal that the suggested technique has a better power allocation capability.

关键词： Non-orthogonalmultiple access wireless networks power domain 5G networks

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