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Chiral quasi-bound states in the continuum

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arXiv 2020年

作者： Overvig, Adam Yu, Nanfang Alù, Andrea Photonics Initiative Advanced Science Research Center The Graduate Center The City University of New York United States Department of Applied Physics and Applied Mathematics Columbia University United States Physics Program Graduate Center City University of New York United States

Quasi-bound states in the continuum (q-BICs) are resonant states of suitably tailored nanostructures with long optical lifetimes controlled by symmetry-breaking perturbations. While in planarized ultrathin devices the resulting Fano resonance is limited to linear polarization, we show here that chiral perturbations extend q-BIC concepts to arbitrary elliptical polarizations. Using geometric phase engineering, we realize metasurfaces with ultrasharp Fano spectral features that can shape the impinging wavefront with near-unity efficiency, while at the same time precisely filtering their spectral content. Copyright © 2020, The Authors. All rights reserved.

关键词： Polarization

Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion

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arXiv 2022年

作者： Maama, Mohamed Jasra, Ajay Ombao, Hernando Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

In this paper we consider Bayesian parameter inference for partially observed fractional Brownian motion (fBM) models. The approach we follow is to time-discretize the hidden process and then to design Markov chain Monte Carlo (MCMC) algorithms to sample from the posterior density on the parameters given data. We rely on a novel representation of the time discretization, which seeks to sample from an approximation of the posterior and then corrects via importance sampling;the approximation reduces the time (in terms of total observation time T) by O(T). This method is extended by using a multilevel MCMC method which can reduce the computational cost to achieve a given mean square error (MSE) versus using a single time discretization. Our methods are illustrated on simulated and real data. Copyright © 2022, The Authors. All rights reserved.

关键词： Mean square error

AMUSE: Empowering Users for Cost-Aware Offloading with Throughput-Delay Tradeoffs

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AMUSE: Empowering Users for Cost-Aware Offloading with Throu...

IEEE INFOCOM Conference

作者： Youngbin Im Carlee Joe-Wong Sangtae Ha Soumya Sen Ted "Taekyoung" Kwon Mung Chiang School of Computer Science and Engineering Seoul National University Seoul Korea Program in Applied and Computational Mathematics Princeton University Princeton NJ USA Department of Electrical Engineering Princeton University Princeton NJ USA

ISBN: (纸本)9781467359443

Mobile users face a tradeoff between cost, through-put, and delay in making their offloading decisions. To navigate this tradeoff, we propose AMUSE (Adaptive bandwidth Management through USer-Empowerment), a practical, cost-aware WiFi offloading system that takes into account a user's throughput-delay tradeoffs and cellular budget constraint. Based on predicted future usage and WiFi availability, AMUSE decides which applications to offload to what times of the day. To practically enforce the assigned rate of each TCP application, we introduce a receiver-side TCP bandwidth control algorithm that adjusts the rate by controlling the TCP advertisement window from the user side. We implement AMUSE on Windows 7 tablets and evaluate its effectiveness with 3G and WiFi usage data obtained from a trial with 25 mobile users. Our results show that AMUSE improves user utility.

关键词： tradeoffs UNLOADING Wi-Fi third generation rate control

Learning from 2D: machine learning of 3D effective properties of heterogeneous materials based on 2D microstructure sections

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arXiv 2023年

作者： Hu, Guangyu Latypov, Marat I. Department of Materials Science and Engineering University of Arizona TucsonAZ85721 United States Graduate Interdisciplinary Program in Applied Mathematics University of Arizona TucsonAZ85721 United States

Microstructure–property relationships are key to effective design of structural materials for advanced applications. Advances in computational methods enabled modeling microstructure-sensitive properties using 3D models (e.g., finite elements) based on microstructure representative volumes. 3D microstructure data required as input to these models are typically obtained from either 3D characterization experiments or digital reconstruction based on statistics from 2D microstructure images. In this work, we present machine learning (ML) approaches to modeling effective properties of heterogeneous materials directly from 2D microstructure sections. To this end, we consider statistical learning models based on spatial correlations and convolutional neural networks as two distinct ML strategies. In both strategies, models are trained on a dataset of synthetically generated 3D microstructures and their properties obtained from micromechanical 3D simulations. Upon training, the models predict properties from 2D microstructure sections. The advantage of the presented models is that they only need 2D sections, whose experimental acquisition is more accessible compared to 3D characterization. Furthermore, the present models do not require digital reconstruction of 3D microstructures. © 2023, CC BY.

关键词： Microstructure

A Neural Network-Based Approach to Normality Testing for Dependent Data

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arXiv 2023年

作者： Kim, Minwoo Genton, Marc G. Huser, Raphaël Castruccio, Stefano Department of Statistics Pusan National University Korea Republic of Statistics program King Abdullah University of Science and Technology Saudi Arabia Department of Applied and Computational Mathematics and Statistics University of Notre Dame United States

There is a wide availability of methods for testing normality under the assumption of independent and identically distributed data. When data are dependent in space and/or time, however, assessing and testing the marginal behavior is considerably more challenging, as the marginal behavior is impacted by the degree of dependence. We propose a new approach to assess normality for dependent data by non-linearly incorporating existing statistics from normality tests as well as sample moments such as skewness and kurtosis through a neural network. We calibrate (deep) neural networks by simulated normal and non-normal data with a wide range of dependence structures and we determine the probability of rejecting the null hypothesis. We compare several approaches for normality tests and demonstrate the superiority of our method in terms of statistical power through an extensive simulation study. A real world application to global temperature data further demonstrates how the degree of spatio-temporal aggregation affects the marginal normality in the data. © 2023, CC BY.

关键词： Higher order statistics

Adaptive tikhonov strategies for stochastic ensemble Kalman inversion

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arXiv 2021年

作者： Weissmann, Simon Chada, Neil K. Schillings, Claudia Tong, Xin T. Interdisciplinary Center for Scientific Computing University of Heidelberg Heidelberg69120 Germany Applied Mathematics and Computational Science Program King Abdullah University of Science and Technology Thuwal KSA 23955 Saudi Arabia Mannheim School of Computer Science and Mathematics University of Mannheim Mannheim68131 Germany Department of Mathematics National University of Singapore Singapore119077 Singapore

Ensemble Kalman inversion (EKI) is a derivative-free optimizer aimed at solving inverse problems, taking motivation from the celebrated ensemble Kalman filter. The purpose of this article is to consider the introduction of adaptive Tikhonov strategies for EKI. This work builds upon Tikhonov EKI (TEKI) which was proposed for a fixed regularization constant. By adaptively learning the regularization parameter, this procedure is known to improve the recovery of the underlying unknown. For the analysis, we consider a continuous-time setting where we extend known results such as well-posdeness and convergence of various loss functions, but with the addition of noisy observations. Furthermore, we allow a time-varying noise and regularization covariance in our presented convergence result which mimic adaptive regularization schemes. In turn we present three adaptive regularization schemes, which are highlighted from both the deterministic and Bayesian approaches for inverse problems, which include bilevel optimization, the MAP formulation and covariance learning. We numerically test these schemes and the theory on linear and nonlinear partial differential equations, where they outperform the non-adaptive TEKI and *** Codes 65M32, 60G35, 65C35, 70F17 Copyright © 2021, The Authors. All rights reserved.

关键词： Continuous time systems

AnisoGNN: graph neural networks generalizing to anisotropic properties of polycrystals

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arXiv 2024年

We present AnisoGNNs - graph neural networks (GNNs) that generalize predictions of anisotropic properties of polycrystals in arbitrary testing directions without the need in excessive training data. To this end, we develop GNNs with a physics-inspired combination of node attributes and aggregation function. We demonstrate the excellent generalization capabilities of AnisoGNNs in predicting anisotropic elastic and inelastic properties of two alloys. © 2024, CC BY.

关键词： Anisotropy

Irregular oscillatory patterns in the early-time region of coherent phonon generation in silicon

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Physical Review B 2017年第12期96卷 125204-125204页

作者： Yohei Watanabe Ken-ichi Hino Muneaki Hase Nobuya Maeshima Doctoral Program in Materials Science Graduate School of Pure and Applied Sciences University of Tsukuba Tsukuba Ibaraki 305-8573 Japan Division of Materials Science Faculty of Pure and Applied Sciences University of Tsukuba Tsukuba 305-8573 Japan Center for Computational Sciences University of Tsukuba Tsukuba 305-8577 Japan Division of Applied Physics Faculty of Pure and Applied Sciences University of Tsukuba Tsukuba 305-8573 Japan

Coherent phonon (CP) generation in an undoped Si crystal is theoretically investigated to shed light on unexplored quantum-mechanical effects in the early-time region immediately after the irradiation of ultrashort laser pulses. We examine time signals attributed to an induced charge density of an ionic core, placing the focus on the effects of the Rabi frequency Ω0cv on the signals; this frequency corresponds to the peak electric-field of the pulse. It is found that at specific Ω0cv's, where the energy of plasmon caused by photoexcited carriers coincides with the longitudinal-optical phonon energy, the energetically resonant interaction between these two modes leads to striking anticrossings, revealing irregular oscillations with anomalously enhanced amplitudes in the observed time signals. Also, the oscillatory pattern is subject to the Rabi flopping of the excited carrier density that is controlled by Ω0cv. These findings show that the early-time region is enriched with quantum-mechanical effects inherent in the CP generation, though experimental signals are more or less masked by the so-called coherent artifact due to nonlinear optical effects.

关键词： Electron-phonon coupling Optical phonons Plasma oscillations Ultrafast phenomena Elemental semiconductors Optical absorption spectroscopy

Singularities of quantum control landscapes

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Physical Review A 2012年第1期86卷 013405-013405页

作者： Re-Bing Wu Ruixing Long Jason Dominy Tak-San Ho Herschel Rabitz Department of Automation Tsinghua University Beijing 100084 China and Center for Quantum Information Science and Technology TNList Beijing 100084 China Department of Chemistry Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Quantum control landscape theory was formulated to assess the ease of finding optimal control fields in simulations and in the laboratory. The landscape is the observable as a function of the controls, and a primary goal of the theory is the analysis of landscape features. In what is referred to as the kinematic picture of the landscape, prior work showed that the landscapes are generally free of traps that could halt the search for an optimal control at a suboptimal observable value. The present paper considers the dynamical picture of the landscape, seeking the existence of singular controls, especially of a nonkinematic nature along with an assessment of whether they correspond to traps. We analyze the necessary and sufficient conditions for singular controls to be kinematic or nonkinematic critical solutions and the likelihood of their being encountered while maximizing an observable. An algorithm is introduced to seek singular controls on the landscape in simulations along with an associated Hessian landscape analysis. Simulations are performed for a large number of model finite-level quantum systems, showing that all the numerically identified kinematic and nonkinematic singular critical controls are not traps, in support of the prior empirical observations on the ease of finding high-quality optimal control fields.

关键词： QUANTUM theory LANDSCAPES COMPUTER simulation OPTIMAL control theory ALGORITHMS