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We propose a geometric numerical analysis of SDEs admitting Lie symmetries which allows us to individuate a symmetry adapted coordinates system where the given SDE has notable invariant properties. An approximation scheme preserving the…

Probability · Mathematics 2020-08-04 Francesco C. De Vecchi , Andrea Romano , Stefania Ugolini

The task of integrating a large number of independent ODE systems arises in various scientific and engineering areas. For nonstiff systems, common explicit integration algorithms can be used on GPUs, where individual GPU threads…

Mathematical Software · Computer Science 2016-11-09 Kyle E Niemeyer , Chih-Jen Sung

This paper concerns the numerical procedure for solving hybrid optimal control problems with sliding modes. The proposed procedure has several features which distinguishes it from the other procedures for the problem. First of all a sliding…

Optimization and Control · Mathematics 2021-01-18 Radoslaw Pytlak , Damian Suski

We develop continuous-stage Runge-Kutta methods based on weighted orthogonal polynomials in this paper. There are two main highlighted merits for developing such methods: Firstly, we do not need to study the tedious solution of…

Numerical Analysis · Mathematics 2025-07-23 Wensheng Tang

A method of exact all-order summation of leading infrared logarithms in two dimensional massless $\Phi^4$-type non-renormalizable effective field theories (EFTs) is developed. The method is applied to the ${\rm O}(N)$-symmetric EFT, which…

High Energy Physics - Phenomenology · Physics 2019-04-05 Jonas Linzen , Maxim V. Polyakov , Kirill M. Semenov-Tian-Shansky , Nika S. Sokolova

A recently developed high-order implicit shock tracking (HOIST) framework for resolving discontinuous solutions of inviscid, steady conservation laws [41, 43] is extended to the unsteady case. Central to the framework is an optimization…

Numerical Analysis · Mathematics 2022-01-26 Andrew Shi , Per-Olof Persson , Matthew Zahr

In this paper we analyze several new methods for solving nonconvex optimization problems with the objective function formed as a sum of two terms: one is nonconvex and smooth, and another is convex but simple and its structure is known.…

Optimization and Control · Mathematics 2014-06-25 A. Patrascu , I. Necoara

Edge detection (ED) is a fundamental perceptual process in computer vision, forming the structural basis for high-level reasoning tasks such as segmentation, recognition, and scene understanding. Despite substantial progress achieved by…

Computer Vision and Pattern Recognition · Computer Science 2026-02-12 Hao Shu

This work gives the asymptotic error distribution of the stochastic Runge--Kutta (SRK) method of strong order $1$ applied to Stratonovich-type stochastic differential equations. For dealing with the implicitness introduced in the diffusion…

Numerical Analysis · Mathematics 2025-08-05 Diancong Jin

In eXplainable Constraint Solving (XCS), it is common to extract a Minimal Unsatisfiable Subset (MUS) from a set of unsatisfiable constraints. This helps explain to a user why a constraint specification does not admit a solution. Finding…

Artificial Intelligence · Computer Science 2024-12-19 Ignace Bleukx , Hélène Verhaeghe , Bart Bogaerts , Tias Guns

In this paper, we study symmetric integrators for solving second-order ordinary differential equations on the basis of the notion of continuous-stage Runge-Kutta-Nystrom methods. The construction of such methods heavily relies on the…

Numerical Analysis · Mathematics 2024-12-20 Wensheng Tang , Jingjing Zhang

Classical convergence theory of Runge-Kutta methods assumes that the time step is small relative to the Lipschitz constant of the ordinary differential equation (ODE). For stiff problems, that assumption is often violated, and a problematic…

Numerical Analysis · Mathematics 2026-05-05 Steven B. Roberts , David Shirokoff , Abhijit Biswas , Benjamin Seibold

In this note we discuss the construction of high order asymptotic preserving numerical schemes for the Boltzmann equation. The methods are based on the use of Implicit-Explicit (IMEX) Runge-Kutta methods combined with a penalization…

Numerical Analysis · Mathematics 2012-02-24 Giacomo Dimarco , Lorenzo Pareschi

We advocate a new approach of addressing hidden structure problems and finding efficient quantum algorithms. We introduce and investigate the Hidden Symmetry Subgroup Problem (HSSP), which is a generalization of the well-studied Hidden…

Quantum Physics · Physics 2014-07-11 Thomas Decker , Gábor Ivanyos , Miklos Santha , Pawel Wocjan

We suggest a novel approach for the efficient and reliable approximation of the Pareto front of sufficiently smooth unconstrained bi-criteria optimization problems. Optimality conditions formulated for weighted sum scalarizations of the…

Optimization and Control · Mathematics 2020-04-24 Matthias Bolten , Onur Tanil Doganay , Hanno Gottschalk , Kathrin Klamroth

Motivated by studies on fully discrete numerical schemes for linear hyperbolic conservation laws, we present a framework on analyzing the strong stability of explicit Runge-Kutta (RK) time discretizations for semi-negative autonomous linear…

Numerical Analysis · Mathematics 2018-11-28 Zheng Sun , Chi-Wang Shu

The finite element method is a well-established method for the numerical solution of partial differential equations (PDEs), both linear and nonlinear. However, the repeated reassemblage of finite element matrices for nonlinear PDEs is…

Numerical Analysis · Mathematics 2022-09-12 Yannis Voet

A fourth-order finite volume embedded boundary (EB) method is presented for the unsteady Stokes equations. The algorithm represents complex geometries on a Cartesian grid using EB, employing a technique to mitigate the "small cut-cell"…

Numerical Analysis · Mathematics 2022-09-08 Nathaniel Overton-Katz , Xinfeng Gao , Stephen Guzik , Oscar Antepara , Daniel T. Graves , Hans Johansen

We consider Hamiltonian systems driven by multi-dimensional Gaussian processes in rough path sense, which include fractional Brownian motions with Hurst parameter $H\in(1/4,1/2]$. We indicate that the phase flow preserves the symplectic…

Numerical Analysis · Mathematics 2018-03-20 Jialin Hong , Chuying Huang , Xu Wang

This thesis examines the empirical mode decomposition (EMD), a method for decomposing multicomponent signals, from a modern, both theoretical and practical, perspective. The motivation is to further formalize the concept and develop new…

Numerical Analysis · Mathematics 2023-02-08 Laslo Hunhold
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