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We present a hierarchical approach for enhancing the robustness of numerical solvers for modelling radiative MHD flows in multi-dimensions. This approach is based on clustering the entries of the global Jacobian in a hierarchical manner…

Mathematical Physics · Physics 2009-11-10 A. A. Hujeirat

Recently a method for adiabatic quantum computation has been proposed and there has been considerable speculation about its efficiency for NP-complete problems. Heuristic arguments in its favor are based on the unproven assumption of an…

Quantum Physics · Physics 2007-05-23 Mary Beth Ruskai

The Newmark/Newton-Raphson (NNR) method is widely employed for solving nonlinear dynamic systems. However, the current NNR method exhibits limited applicability in complex nonlinear dynamic systems, as the acquisition of the Jacobian matrix…

Computational Engineering, Finance, and Science · Computer Science 2025-06-17 Yifan Jiang , Yuhong Jin , Lei Hou , Yi Chen , Andong Cong

We study composite optimization problems in which the smooth part of the objective function is \( p \)-times continuously differentiable, where \( p \geq 1 \) is an integer. Higher-order methods are known to be effective for solving such…

Optimization and Control · Mathematics 2025-03-04 Yassine Nabou

This paper addresses the problem of solving nonlinear systems in the context of symmetric quantum signal processing (QSP), a powerful technique for implementing matrix functions on quantum computers. Symmetric QSP focuses on representing…

Quantum Physics · Physics 2023-07-25 Yulong Dong , Lin Lin , Hongkang Ni , Jiasu Wang

We study the differentiability of the metric and other fields at any of the horizons of the \emph{most generic} multi center Reissner-Nordstrom black hole solutions in $d \ge 5$ and of multi center $M2$ brane solutions. Most generic means…

High Energy Physics - Theory · Physics 2014-07-22 Chethan N Gowdigere

We introduce an inertial quasi-Newton Forward-Backward Splitting Algorithm to solve a class of monotone inclusion problems. While the inertial step is computationally cheap, in general, the bottleneck is the evaluation of the resolvent…

Optimization and Control · Mathematics 2024-03-18 Shida Wang , Jalal Fadili , Peter Ochs

In Part V of this study, we presented an original Lagrangian approach for computing the dynamic characteristics along stationary rays, by solving the linear, second-order Jacobi differential equation, considering four sets of initial…

Geophysics · Physics 2020-03-24 Igor Ravve , Zvi Koren

Newton's method for solving the matrix equation $F(X)\equiv AX-XX^TAX=0$ runs up against the fact that its zeros are not isolated. This is due to a symmetry of $F$ by the action of the orthogonal group. We show how differential-geometric…

Numerical Analysis · Mathematics 2010-03-11 P. -A. Absil , M. Ishteva , L. De Lathauwer , S. Van Huffel

We present an efficient algorithm to compute the induced norms of finite-horizon Linear Time-Varying (LTV) systems. The formulation includes both induced $\mathcal{L}_2$ and terminal Euclidean norm penalties. Existing computational…

Systems and Control · Electrical Eng. & Systems 2020-11-03 Jyot Buch , Murat Arcak , Peter Seiler

This work introduces a new higher-order accurate super compact (HOSC) finite difference scheme for solving complex unsteady three-dimensional (3D) non-Newtonian fluid flow problems. As per the author's knowledge, the proposed scheme is the…

Fluid Dynamics · Physics 2024-07-30 Ashwani Punia , Rajendra K. Ray

This paper concerns developing a numerical method of the Newton type to solve systems of nonlinear equations described by nonsmooth continuous functions. We propose and justify a new generalized Newton algorithm based on graphical…

Optimization and Control · Mathematics 2010-09-03 T. Hoheisel , C. Kanzow , B. S. Mordukhovich , H. Phan

As we all known, the nonnegative matrix factorization (NMF) is a dimension reduction method that has been widely used in image processing, text compressing and signal processing etc. In this paper, an algorithm for nonnegative matrix…

Numerical Analysis · Mathematics 2013-05-27 Shu-Zhen Lai , Hou-Biao Li , Zu-Tao Zhang

In this paper, by combining the algorithm New Q-Newton's method - developed in previous joint work of the author - with Armijo's Backtracking line search, we resolve convergence issues encountered by Newton's method (e.g. convergence to a…

Optimization and Control · Mathematics 2022-09-13 Tuyen Trung Truong

In this paper, we consider an unconstrained optimization model where the objective is a sum of a large number of possibly nonconvex functions, though overall the objective is assumed to be smooth and convex. Our bid to solving such model…

Optimization and Control · Mathematics 2022-03-15 Xi Chen , Bo Jiang , Tianyi Lin , Shuzhong Zhang

We present a fast Jacobi-like algorithm for computing the eigenvalues, and optionally the eigenvectors, of a real normal matrix. The method gains a computational advantage by using Paardekooper's method for skew-symmetric matrices The…

Numerical Analysis · Mathematics 2026-05-27 Simon Mataigne , P. -A. Absil

We propose an automatic algorithm for 3D inverse electromagnetic scattering based on the combination of topological derivatives and regularized Gauss-Newton iterations. The algorithm is adapted to decoding digital holograms. A hologram is a…

Optics · Physics 2019-04-01 A. Carpio , T. G. Dimiduk , F. Le Louer , M. L. Rapun

Let $K$ be a number field and let $C/K$ be a curve of genus 2 with Jacobian variety $J$. In this paper, we study the canonical height $\hat{h} \colon J(K) \to \mathbb R$. More specifically, we consider the following two problems, which are…

Number Theory · Mathematics 2016-12-14 J. Steffen Müller , Michael Stoll

The paper starts with a concise description of the recently developed semismooth* Newton method for the solution of general inclusions. This method is then applied to a class of variational inequalities of the second kind. As a result, one…

Optimization and Control · Mathematics 2020-07-23 Helmut Gfrerer , Jiri V. Outrata , Jan Valdman

A new variant of Newton's method for empirical risk minimization is studied, where at each iteration of the optimization algorithm, the gradient and Hessian of the objective function are replaced by robust estimators taken from existing…

Machine Learning · Statistics 2023-07-18 Eirini Ioannou , Muni Sreenivas Pydi , Po-Ling Loh