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We examine the effect of accuracy of high-order spectral element methods, with or without adaptive mesh refinement (AMR), in the context of a classical configuration of magnetic reconnection in two space dimensions, the so-called…

Fluid Dynamics · Physics 2009-11-13 D. Rosenberg , A. Pouquet , P. D. Mininni

We design an optical feedback network making use of machine learning techniques and demonstrate via simulations its ability to correct for the effects of turbulent propagation on optical modes. This artificial neural network scheme only…

Signal Processing · Electrical Eng. & Systems 2018-06-22 Sanjaya Lohani , Ryan T. Glasser

This work introduces an Adaptive Mesh Refinement (AMR) strategy for the topology optimization of structures made of discrete geometric components using the geometry projection method. Practical structures made of geometric shapes such as…

Optimization and Control · Mathematics 2020-04-22 Shanglong Zhang , Arun L. Gain , Julian A. Norato

I consider techniques for Berger-Oliger adaptive mesh refinement (AMR) when numerically solving partial differential equations with wave-like solutions, using characteristic (double-null) grids. Such AMR algorithms are naturally recursive,…

General Relativity and Quantum Cosmology · Physics 2015-03-13 Jonathan Thornburg

We present a novel energy-based numerical analysis of semilinear diffusion-reaction boundary value problems. Based on a suitable variational setting, the proposed computational scheme can be seen as an energy minimisation approach. More…

Numerical Analysis · Mathematics 2022-02-16 Mario Amrein , Pascal Heid , Thomas P. Wihler

This research presents the development of an innovative algorithm tailored for the adaptive sampling of residual points within the framework of Physics-Informed Neural Networks (PINNs). By addressing the limitations inherent in existing…

Machine Learning · Computer Science 2023-06-16 Shikhar Nilabh , Fidel Grandia

Parametric mathematical models such as parameterizations of partial differential equations with random coefficients have received a lot of attention within the field of uncertainty quantification. The model uncertainties are often…

Numerical Analysis · Mathematics 2023-09-20 Philipp A. Guth , Vesa Kaarnioja

The advent of robust, reliable and accurate higher order Godunov schemes for many of the systems of equations of interest in computational astrophysics has made it important to understand how to solve them in multi-scale fashion. This is so…

Astrophysics · Physics 2015-06-24 Dinshaw Balsara

When numerically solving partial differential equations, for a given problem and operating condition, adaptive mesh refinement (AMR) has proven its efficiency to automatically build a discretization achieving a prescribed accuracy at low…

Numerical evolution of the spherically symmetric, massive Klein-Gordon field is presented using a new adaptive mesh refinement (AMR) code with fourth order discretization in space and time, along with compactification in space. The system…

High Energy Physics - Theory · Physics 2009-11-11 Peter Csizmadia

For quasi-linear interface problems with discontinuous diffusion coefficients, the nonconvex objective functional often leads to optimization stagnation in randomized neural network approximations. This paper Proposes a…

Numerical Analysis · Mathematics 2026-02-06 Siyuan Lang , Zhiyue Zhang

We propose an adaptive mesh refinement strategy for immersed isogeometric analysis, with application to steady heat conduction and viscous flow problems. The proposed strategy is based on residual-based error estimation, which has been…

We explicitly demonstrate that current numerical relativity techniques are able to accurately evolve black hole binaries with mass ratios of the order of 1000:1. This proof of principle is relevant for future third generation (3G)…

General Relativity and Quantum Cosmology · Physics 2023-04-19 Carlos O. Lousto , James Healy

We present a new set of 95 numerical relativity simulations of non-precessing binary black holes (BBHs). The simulations sample comprehensively both black-hole spins up to spin magnitude of 0.9, and cover mass ratios 1 to 3. The simulations…

General Relativity and Quantum Cosmology · Physics 2016-10-17 Tony Chu , Heather Fong , Prayush Kumar , Harald P. Pfeiffer , Michael Boyle , Daniel A. Hemberger , Lawrence E. Kidder , Mark A. Scheel , Bela Szilagyi

Neural Radiance Field (NeRF) is a representation for 3D reconstruction from multi-view images. Despite some recent work showing preliminary success in editing a reconstructed NeRF with diffusion prior, they remain struggling to synthesize…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Chieh Hubert Lin , Changil Kim , Jia-Bin Huang , Qinbo Li , Chih-Yao Ma , Johannes Kopf , Ming-Hsuan Yang , Hung-Yu Tseng

Template matching is a fundamental task in computer vision and has been studied for decades. It plays an essential role in manufacturing industry for estimating the poses of different parts, facilitating downstream tasks such as robotic…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Zhirui Gao , Renjiao Yi , Zheng Qin , Yunfan Ye , Chenyang Zhu , Kai Xu

We present an adaptive refinement algorithm for T-splines on unstructured 2D meshes. While for structured 2D meshes, one can refine elements alternatingly in horizontal and vertical direction, such an approach cannot be generalized directly…

Numerical Analysis · Mathematics 2022-05-03 Roland Maier , Philipp Morgenstern , Thomas Takacs

Second order accurate Cartesian grid methods have been well developed for interface problems in the literature. However, it is challenging to develop third or higher order accurate methods for problems with curved interfaces and internal…

Numerical Analysis · Mathematics 2022-06-14 Zhilin Li , Kejia Pan , Juan Ruiz

The quasicontinuum approximation is a method to reduce the atomistic degrees of freedom of a crystalline solid by piecewise linear interpolation from representative atoms that are nodes for a finite element triangulation. In regions of the…

Numerical Analysis · Mathematics 2015-05-13 Marcel Arndt , Mitchell Luskin

The premise of our work is deceptively familiar: A black box $f(\cdot)$ has altered an image $\mathbf{x} \rightarrow f(\mathbf{x})$. Recover the image $\mathbf{x}$. This black box might be any number of simple or complicated things: a…

Computer Vision and Pattern Recognition · Computer Science 2018-04-25 Peyman Milanfar
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