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In the article we discuss the notion of the generalized invariant manifold introduced in our previous study. In the literature the method of the differential constraints is well known as a tool for constructing particular solutions for the…

Exactly Solvable and Integrable Systems · Physics 2021-07-08 I. T. Habibullin , A. R. Khakimova , A. O. Smirnov

In this paper, we first propose a general interpolation algorithm in a free module of a linearized polynomial ring, and then apply this algorithm to decode several important families of codes, Gabidulin codes, KK codes and MV codes. Our…

Networking and Internet Architecture · Computer Science 2011-04-21 Hongmei Xie , Zhiyuan Yan , Bruce W. Suter

Bilevel optimization has been widely used in decision-making process. However, there still lacks an efficient algorithm to determine an optimal solution of a bilevel optimization problem, especially for a large-size problem. To bridge the…

Optimization and Control · Mathematics 2016-05-18 Xuan Liu , Zuyi Li

We present an acceleration method for sequences of large-scale linear systems, such as the ones arising from the numerical solution of time-dependent partial differential equations coupled with algebraic constraints. We discuss different…

Numerical Analysis · Mathematics 2024-03-29 Margherita Guido , Daniel Kressner , Paolo Ricci

A systematic construction of higher order splines using two hierarchies of polynomials is presented. Explicit instructions on how to implement one of these hierarchies are given. The results are limited to interpolations on regular,…

Numerical Analysis · Computer Science 2009-05-25 Cristian Constantin Lalescu

A generalized matrix-pencil approach is proposed for the estimation of complex exponential components with segmented signal samples, which is very efficient and provides super-resolution estimations. It is applicable to the signals sampled…

Signal Processing · Electrical Eng. & Systems 2022-10-28 Jianping Wang , Alexander Yarovoy

This article presents a validation of a recently proposed strongly polynomial-time algorithm for the general linear programming problem. The proposed algorithm is an implicit reduction procedure that combines primal and dual linear…

Optimization and Control · Mathematics 2026-04-28 Samuel Awoniyi

We introduce a class of unconditionally energy stable, high order accurate schemes for gradient flows in a very general setting. The new schemes are a high order analogue of the minimizing movements approach for generating a time discrete…

Numerical Analysis · Mathematics 2020-02-11 Alexander Zaitzeff , Selim Esedoglu , Krishna Garikipati

We explore the utilization of higher-order discretization techniques in optimizing the gate count needed for quantum computer based solutions of partial differential equations. To accomplish this, we present an efficient approach for…

Quantum Physics · Physics 2024-12-30 Boris Arseniev , Dmitry Guskov , Richik Sengupta , Igor Zacharov

A method of finding general solutions of second-order nonlinear ordinary differential equations by extending the Prelle-Singer (PS) method is briefly discussed. We explore integrating factors, integrals of motion and the general solution…

Exactly Solvable and Integrable Systems · Physics 2009-11-10 V. K. Chandrasekar , M. Senthilvelan , M. Lakshmanan

This paper presents a general high-order kernel regularization technique applicable to all four integral operators of Calder\'on calculus associated with linear elliptic PDEs in two and three spatial dimensions. Like previous density…

Numerical Analysis · Mathematics 2021-03-02 Luiz M. Faria , Carlos Pérez-Arancibia , Marc Bonnet

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution times for complex problems. In this…

In this paper the performance of a parallel iterated Runge-Kutta method is compared versus those of the serial fouth order Runge-Kutta and Dormand-Prince methods. It was found that, typically, the runtime for the parallel method is…

Numerical Analysis · Mathematics 2016-01-12 Alejandra Gaitán Montejo , Octavio A. Michel-Manzo , César A. Terrero-Escalante

We introduce a novel technique for constructing higher-order variational integrators for Hamiltonian systems of ODEs. In particular, we are concerned with generating globally smooth approximations to solutions of a Hamiltonian system. Our…

Numerical Analysis · Mathematics 2015-03-17 Melvin Leok , Tatiana Shingel

Many applications modeled by polynomial systems have positive dimensional solution components (e.g., the path synthesis problems for four-bar mechanisms) that are challenging to compute numerically by homotopy continuation methods. A…

Algebraic Geometry · Mathematics 2007-05-23 Andrew J. Sommese , Jan Verschelde

Transformations of differential equations to other equivalent equations play a central role in many routines for solving intricate equations. A class of differential equations that are particularly amenable to solution techniques based on…

Classical Analysis and ODEs · Mathematics 2020-05-21 Winter Sinkala

Using geometric methods for linearizing systems of second order cubically semi-linear ordinary differential equations and third order quintically semi-linear ordinary differential equations, we extend to the fourth order by differentiating…

Classical Analysis and ODEs · Mathematics 2007-12-27 F. M. Mahomed , A. Qadir

We study numerical integration of smooth functions defined over the $s$-dimensional unit cube. A recent work by Dick et al. (2019) has introduced so-called extrapolated polynomial lattice rules, which achieve the almost optimal rate of…

Numerical Analysis · Mathematics 2020-07-15 Takashi Goda

We provide first the functional analysis background required for reduced order modeling and present the underlying concepts of reduced basis model reduction. The projection-based model reduction framework under affinity assumptions,…

Numerical Analysis · Mathematics 2023-08-30 Gianluigi Rozza , Martin Hess , Giovanni Stabile , Marco Tezzele , Francesco Ballarin

When writing programs, people have the ability to tackle a new complex task by decomposing it into smaller and more familiar subtasks. While it is difficult to measure whether neural program synthesis methods have similar capabilities, what…

Machine Learning · Computer Science 2023-10-31 Kensen Shi , Joey Hong , Manzil Zaheer , Pengcheng Yin , Charles Sutton