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Related papers: Gaussian Beam Methods for the Helmholtz Equation

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This paper develops some interior penalty $hp$-discontinuous Galerkin ($hp$-DG) methods for the Helmholtz equation in two and three dimensions. The proposed $hp$-DG methods are defined using a sesquilinear form which is not only…

Numerical Analysis · Mathematics 2009-07-21 Xiaobing Feng , Haijun Wu

We present a ray-based finite element method (ray-FEM) by learning basis adaptive to the underlying high-frequency Helmholtz equation in smooth media. Based on the geometric optics ansatz of the wave field, we learn local dominant ray…

Numerical Analysis · Mathematics 2016-09-01 Jun Fang , Jianliang Qian , Leonardo Zepeda-Núñez , Hongkai Zhao

In this article, we consider the stochastic wave equation in spatial dimension $d=1$, with linear term $\sigma(u)=u$ multiplying the noise. This equation is driven by a Gaussian noise which is white in time and fractional in space with…

Probability · Mathematics 2023-07-04 Raluca M. Balan , Jingyu Huang , Xiong Wang , Panqiu Xia , Wangjun Yuan

The accuracy of Bayesian inference can be negatively affected by the use of inaccurate forward models. In the case of gravitational-wave inference, accurate but computationally expensive waveform models are sometimes substituted with faster…

Instrumentation and Methods for Astrophysics · Physics 2024-04-02 Miaoxin Liu , Xiao-Dong Li , Alvin J. K. Chua

We report on a new class of exact solutions of the scalar Helmholtz equation obtained by carefully engineering the form of the angular spectrum of a Bessel beam. We consider in particular the case in which the angular spectrum of such…

Optics · Physics 2023-07-19 Marco Ornigotti , Andrea Aiello

A generalized finite element method is proposed for solving a heterogeneous reaction-diffusion equation with a singular perturbation parameter $\varepsilon$, based on locally approximating the solution on each subdomain by solution of a…

Numerical Analysis · Mathematics 2024-07-25 Chupeng Ma , Jens Markus Melenk

Gaussian process is a theoretically appealing model for nonparametric analysis, but its computational cumbersomeness hinders its use in large scale and the existing reduced-rank solutions are usually heuristic. In this work, we propose a…

Machine Learning · Statistics 2015-11-25 Leo L. Duan , Xia Wang , Rhonda D. Szczesniak

The frozen Gaussian approximation (FGA) is an effective tool for modeling high frequency wave propagation. In previous works, the convergence of the FGA has established for strict hyperbolic systems. In this work, we derive the frozen…

Mathematical Physics · Physics 2019-11-04 James Hateley , Xu Yang

We show that $k$-means (Lloyd's algorithm) is obtained as a special case when truncated variational EM approximations are applied to Gaussian Mixture Models (GMM) with isotropic Gaussians. In contrast to the standard way to relate $k$-means…

Machine Learning · Statistics 2019-06-07 Jörg Lücke , Dennis Forster

In this paper, we develop a computational multiscale to solve the parabolic wave approximation with heterogeneous and variable media. Parabolic wave approximation is a technique to approximate the full wave equation. One benefit of the…

Numerical Analysis · Mathematics 2021-04-07 Eric Chung , Yalchin Efendiev , Sai-Mang Pun , Zecheng Zhang

We study the total mass of high points in a random model for the Riemann-Zeta function. We consider the same model as in [8], [2], and build on the convergence to 'Gaussian' multiplicative chaos proved in [14]. We show that the total mass…

Probability · Mathematics 2019-06-24 Louis-Pierre Arguin , Lisa Hartung , Nicola Kistler

We consider the problem of spherical Gaussian Mixture models with $k \geq 3$ components when the components are well separated. A fundamental previous result established that separation of $\Omega(\sqrt{\log k})$ is necessary and sufficient…

Machine Learning · Computer Science 2020-06-22 Jeongyeol Kwon , Constantine Caramanis

We propose a generalized finite element method for the strongly damped wave equation with highly varying coefficients. The proposed method is based on the localized orthogonal decomposition introduced and is designed to handle independent…

Numerical Analysis · Mathematics 2020-11-09 Per Ljung , Axel Målqvist , Anna Persson

A crucial role in the theory of uncertainty quantification (UQ) of PDEs is played by the regularity of the solution with respect to the stochastic parameters; indeed, a key property one seeks to establish is that the solution is holomorphic…

Analysis of PDEs · Mathematics 2022-09-21 Euan A. Spence , Jared Wunsch

Gaussian variational approximations are widely used for summarizing posterior distributions in Bayesian models, especially in high-dimensional settings. However, a drawback of such approximations is the inability to capture skewness or more…

Methodology · Statistics 2026-04-02 Lucas Kock , Linda S. L. Tan , Prateek Bansal , David J. Nott

In this paper, we investigate the approximation problem for functions in Gaussian Sobolev spaces $W^s_p(\mathbb{R}^d, \gamma)$ of smoothness $s > 0$, where the approximation error is measured in the Gaussian Lebesgue space…

Functional Analysis · Mathematics 2026-04-21 Van Kien Nguyen

We revisit the $k$-Hessian eigenvalue problem on a smooth, bounded, $(k-1)$-convex domain in $\mathbb R^n$. First, we obtain a spectral characterization of the $k$-Hessian eigenvalue as the infimum of the first eigenvalues of linear…

Analysis of PDEs · Mathematics 2021-09-28 Nam Q. Le

We determine the exact minimax rate of a Gaussian sequence model under bounded convex constraints, purely in terms of the local geometry of the given constraint set $K$. Our main result shows that the minimax risk (up to constant factors)…

Statistics Theory · Mathematics 2022-11-08 Matey Neykov

In this paper we investigate staggered discontinuous Galerkin method for the Helmholtz equation with large wave number on general quadrilateral and polygonal meshes. The method is highly flexible by allowing rough grids such as the…

Numerical Analysis · Mathematics 2019-04-30 Lina Zhao , Eun-Jae Park , Eric Chung

A local convergence analysis of the Gauss-Newton method for solving injective-overdetermined systems of nonlinear equations under a majorant condition is provided. The convergence as well as results on its rate are established without a…

Optimization and Control · Mathematics 2013-03-21 Max Leandro Nobre Goncalves
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