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Local conformal symmetry is usually considered to be an approximate symmetry of nature, which is explicitly and badly broken. Arguments are brought forward here why it has to be turned into an exact symmetry that is spontaneously broken. As…

General Relativity and Quantum Cosmology · Physics 2015-03-18 Gerard T. Hooft

This work proposes and analyzes a fully discrete numerical scheme for solving the Landau-Lifshitz-Gilbert (LLG) equation, which achieves fourth-order spatial accuracy and third-order temporal accuracy.Spatially, fourth-order accuracy is…

Numerical Analysis · Mathematics 2025-10-30 Changjian Xie , Cheng Wang

Choosing the optimization algorithm that performs best on a given machine learning problem is often delicate, and there is no guarantee that current state-of-the-art algorithms will perform well across all tasks. Consequently, the more…

Optimization and Control · Mathematics 2024-06-25 Måns Williamson , Monika Eisenmann , Tony Stillfjord

We consider finite element approximations of ill-posed elliptic problems with conditional stability. The notion of {\emph{optimal error estimates}} is defined including both convergence with respect to mesh parameter and perturbations in…

Numerical Analysis · Mathematics 2024-03-25 Erik Burman , Mihai Nechita , Lauri Oksanen

Tight bounds for several symmetric divergence measures are derived in terms of the total variation distance. It is shown that each of these bounds is attained by a pair of 2 or 3-element probability distributions. An application of these…

Information Theory · Computer Science 2016-11-17 Igal Sason

The Exact Matching (EM) problem asks whether there exists a perfect matching which uses a prescribed number of red edges in a red/blue edge-colored graph. While there exists a randomized polynomial-time algorithm for the problem, only some…

Data Structures and Algorithms · Computer Science 2025-10-15 Nicolas El Maalouly , Kostas Lakis

Existing performance measures rank delineation algorithms inconsistently, which makes it difficult to decide which one is best in any given situation. We show that these inconsistencies stem from design flaws that make the metrics…

Computer Vision and Pattern Recognition · Computer Science 2019-12-02 Leonardo Citraro , Mateusz Koziński , Pascal Fua

We develop efficient and high-order accurate finite difference methods for elliptic partial differential equations in complex geometry in the Difference Potentials framework. The main novelty of the developed schemes is the use of local…

Numerical Analysis · Mathematics 2023-06-28 Qing Xia

This work aims at making a comprehensive contribution in the general area of parametric inference for discretely observed diffusion processes. Established approaches for likelihood-based estimation invoke a time-discretisation scheme for…

Methodology · Statistics 2024-01-30 Yuga Iguchi , Alexandros Beskos , Matthew M. Graham

This dissertation is concerned with understanding and analyzing some of the effects of diffraction in the near field. The contributions of homogeneous and of evanescent waves to two-dimensional near-field diffraction patterns of scalar…

Optics · Physics 2007-05-23 Marek W. Kowarz

In this work we develop and analyze an adaptive finite element method for efficiently solving electrical impedance tomography -- a severely ill-posed nonlinear inverse problem for recovering the conductivity from boundary voltage…

Numerical Analysis · Mathematics 2019-05-16 Bangti Jin , Yifeng Xu , Jun Zou

This paper deals with the Darcy-Forchheimer problem with two kinds of boundary conditions. We discretize the system by using the finite element methods and we propose two iterative schemes to solve the discrete problems. The well-posedness…

Numerical Analysis · Mathematics 2021-11-23 Toni Sayah

New implicit and implicit-explicit time-stepping methods for the wave equation in second-order form are described with application to two and three-dimensional problems discretized on overset grids. The implicit schemes are single step,…

Numerical Analysis · Mathematics 2024-04-24 Allison M. Carson , Jeffrey W. Banks , William D. Henshaw , Donald W. Schwendeman

With the widespread deployment of large-scale prediction systems in high-stakes domains, e.g., face recognition, criminal justice, etc., disparity in prediction accuracy between different demographic subgroups has called for fundamental…

Machine Learning · Computer Science 2021-06-15 Jianfeng Chi , Yuan Tian , Geoffrey J. Gordon , Han Zhao

Ando's surface roughness model is applied to metallic nanowires and extended beyond small roughness size and infinite barrier limit approximations for the wavefunction overlaps, such as the Prange-Nee approximation. Accurate and fast…

Mesoscale and Nanoscale Physics · Physics 2016-06-23 Kristof Moors , Bart Sorée , Wim Magnus

A new highly accurate numerical approximation scheme based on a Gauss type Clenshaw-Curtis Quadrature for Fredholm integral equations of the second kind, whose kernel is either discontinuous or not smooth along the main diagonal, is…

Numerical Analysis · Mathematics 2025-10-20 Sheon-Young Kang , Israel Koltracht , George Rawitscher

We discuss goal-oriented adaptivity in the frame of conforming finite element methods and plain convergence of the related a posteriori error estimator for different general marking strategies. We present an abstract analysis for two…

Numerical Analysis · Mathematics 2024-07-30 Valentin Helml , Michael Innerberger , Dirk Praetorius

The paper discusses the relationships between electrical and affine differential geometry quantities, establishing a link between frequency and time derivatives of voltage, through the utilization of affine geometric invariants. Based on…

Differential Geometry · Mathematics 2024-09-26 Ali Alshawabkeh , Georgios Tzounas , Angel Molina-Garcia , Federico Milano

Kernel techniques are among the most popular and flexible approaches in data science allowing to represent probability measures without loss of information under mild conditions. The resulting mapping called mean embedding gives rise to a…

Machine Learning · Statistics 2024-11-27 Linda Chamakh , Zoltan Szabo

Defects in crystalline materials control the properties of materials, and their characterization focuses our strategies to optimize performance. Electron microscopy has served as the backbone of our understanding of defect structure and…

Materials Science · Physics 2019-03-19 Daniel S. Gianola , T. Ben Britton , Stefan Zaefferer
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