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We propose to accelerate a high order discontinuous Galerkin solver using neural networks. We include a corrective forcing to a low polynomial order simulation to enhance its accuracy. The forcing is obtained by training a deep fully…

Fluid Dynamics · Physics 2024-01-10 Fernando Manrique de Lara , Esteban Ferrer

In calculating integral or discrete transforms, use has been made of fast algorithms for multiplying vectors by matrices whose elements are specified as values of special (Chebyshev, Legendre, Laguerre, etc.) functions. The currently…

Numerical Analysis · Mathematics 2022-08-11 Andrew V. Terekhov

In this paper we present an algorithm for analog simulation of electronic circuits involving a spline Galerkin method with wavelet-based adaptive refinement. Numerical tests show that a first algorithm prototype, build within a productively…

Numerical Analysis · Mathematics 2016-04-27 Kai Bittner , Emira Dautbegovic

We describe the GPU implementation of shifted or multimass iterative solvers for sparse linear systems of the sort encountered in lattice gauge theory. We provide a generic tool that can be used by those without GPU programming experience…

High Energy Physics - Lattice · Physics 2011-02-16 Richard Galvez , Greg van Anders

The Uzawa algorithm is an iterative method for the solution of saddle-point problems, which arise in many applications, including fluid dynamics. Viewing the Uzawa algorithm as a fixed- point iteration, we explore the use of Anderson…

Numerical Analysis · Mathematics 2016-05-24 Nguyenho Ho , Sarah D. Olson , Homer F. Walker

Federated learning has emerged in the last decade as a distributed optimization paradigm due to the rapidly increasing number of portable devices able to support the heavy computational needs related to the training of machine learning…

Machine Learning · Computer Science 2024-10-10 Emanuel Buttaci , Giuseppe Carlo Calafiore

This paper studies the Craig variant of the Golub-Kahan bidiagonalization algorithm as an iterative solver for linear systems with saddle point structure. Such symmetric indefinite systems in 2x2 block form arise in many applications, but…

Computational Engineering, Finance, and Science · Computer Science 2018-08-24 Mario Arioli , Carola Kruse , Ulrich Ruede , Nicolas Tardieu

In this paper, we study the synthesis of Gegenbauer processes using the wavelet packets transform. In order to simulate a 1-factor Gegenbauer process, we introduce an original algorithm, inspired by the one proposed by Coifman and…

Statistics Theory · Mathematics 2016-08-16 Jérôme Collet , Jalal Fadili

The Landau gauge fixing algorithm in the new definition of gauge fields is presented. In this algorithm a new solver of the Poisson equations based on the Green's function method is used. Its numerical performance of the gauge fixing…

High Energy Physics - Lattice · Physics 2009-10-31 Hideo Nakajima , Sadataka Furui

This paper proposes and analyzes an accelerated inexact dampened augmented Lagrangian (AIDAL) method for solving linearly-constrained nonconvex composite optimization problems. Each iteration of the AIDAL method consists of: (i) inexactly…

Optimization and Control · Mathematics 2023-02-08 Weiwei Kong , Renato D. C. Monteiro

Based on the generalized Cayley transform, a family of conservative one-step schemes of the sixth order of accuracy for the Zakharov-Shabat system is constructed. The exponential integrator is a special case. Schemes based on rational…

Numerical Analysis · Mathematics 2020-11-24 Sergey Medvedev , Igor Chekhovskoy , Irina Vaseva , Mikhail Fedoruk

We propose a new quantum state reconstruction method that combines ideas from compressed sensing, non-convex optimization, and acceleration methods. The algorithm, called Momentum-Inspired Factored Gradient Descent (\texttt{MiFGD}), extends…

Quantum Physics · Physics 2022-03-24 Junhyung Lyle Kim , George Kollias , Amir Kalev , Ken X. Wei , Anastasios Kyrillidis

We calculate the perturbative corrections to fermion bilinears that are used in numerical simulations when extracting weak matrix elements using staggered fermions. This extends previous calculations of Golterman and Smit, and Daniel and…

High Energy Physics - Lattice · Physics 2014-11-17 Apoorva Patel , Stephen Sharpe

In this series of eight papers we present the applications of methods from wavelet analysis to polynomial approximations for a number of accelerator physics problems. In this part, assuming a sinusoidal field variation, we consider the…

Accelerator Physics · Physics 2007-05-23 Antonina N. Fedorova , Michael G. Zeitlin

Federated learning has attracted increasing attention with the emergence of distributed data. While extensive federated learning algorithms have been proposed for the non-convex distributed problem, federated learning in practice still…

Machine Learning · Computer Science 2023-03-10 Xidong Wu , Feihu Huang , Zhengmian Hu , Heng Huang

In this paper, we propose, analyze and demonstrate a dynamic momentum method to accelerate power and inverse power iterations with minimal computational overhead. The method can be applied to real diagonalizable matrices, is provably…

Numerical Analysis · Mathematics 2024-07-08 Christian Austin , Sara Pollock , Yunrong Zhu

The large-scale execution of quantum algorithms requires basic quantum operations to be implemented fault-tolerantly. The most popular technique for accomplishing this, using the devices that can be realised in the near term, uses…

This paper studies the commonly utilized windowed Anderson acceleration (AA) algorithm for fixed-point methods, $x^{(k+1)}=q(x^{(k)})$. It provides the first proof that when the operator $q$ is linear and symmetric the windowed AA, which…

Numerical Analysis · Mathematics 2025-08-01 Casey Garner , Gilad Lerman , Teng Zhang

We consider the aeroelastic simulation of flexible mechanical structures submerged in subsonic fluid flows at low Mach numbers. The nonlinear kinematics of flexible bodies are described in the total Lagrangian formulation and discretized by…

Numerical Analysis · Mathematics 2024-03-25 Jenny Schubert , Marc C. Steinbach , Christian Hente , David Märtins , Daniel Schuster

We propose a new algorithm for solving the graph-fused lasso (GFL), a method for parameter estimation that operates under the assumption that the signal tends to be locally constant over a predefined graph structure. Our key insight is to…

Machine Learning · Statistics 2015-06-02 Wesley Tansey , James G. Scott