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The truncation and approximation errors for the set of numerical solutions computed by methods based on the algorithms of different structure are calculated and analyzed for the case of the two-dimensional steady inviscid compressible flow.…

Numerical Analysis · Mathematics 2020-05-14 A. K. Alekseev , A. E. Bondarev

The issue of single-grid discretization error estimator, operating in the postprocessor mode, is addressed in the paper. An ensemble of numerical solutions, obtained using solvers of different accuracy, is shown to provide an upper estimate…

Computational Physics · Physics 2018-05-11 A. K. Alekseev , A. E. Bondarev , I. M. Navon

The Inverse Problem for the estimation of a point-wise approximation error occurring at the discretization and solving of the system of partial differential equations is addressed. The set of the differences between the numerical solutions…

Numerical Analysis · Mathematics 2021-01-05 Aleksey Alekseev , Alexander Bondarev

Rigorous assessment of uncertainty is crucial to the utility of DNS results. Uncertainties in the computed statistics arise from two sources: finite statistical sampling and the discretization of the Navier-Stokes equations. Due to the…

Fluid Dynamics · Physics 2015-06-17 Todd A. Oliver , Nicholas Malaya , Rhys Ulerich , Robert D. Moser

The numerical methods for differential equation solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods have the restricted class of…

Numerical Analysis · Mathematics 2023-07-03 Alexander Hvatov , Tatiana Tikhonova

Distances are pervasive in machine learning. They serve as similarity measures, loss functions, and learning targets; it is said that a good distance measure solves a task. When defining distances, the triangle inequality has proven to be a…

Machine Learning · Computer Science 2020-07-08 Silviu Pitis , Harris Chan , Kiarash Jamali , Jimmy Ba

The paper is concerned with a class of nonlinear free boundary problems, which are usually solved by variational methods based on primal (or primal-dual) variational settings. We deduce and investigate special relations (error identities).…

Analysis of PDEs · Mathematics 2017-03-01 Sergey Repin , Jan Valdman

We approximate the uniform measure on an equilateral triangle by a measure supported on $n$ points. We find the optimal sets of points ($n$-means) and corresponding approximation (quantization) error for $n\leq4$, give numerical…

Information Theory · Computer Science 2017-02-16 Carl P. Dettmann , Mrinal Kanti Roychowdhury

In backward error analysis, an approximate solution to an equation is compared to the exact solution to a nearby modified equation. In numerical ordinary differential equations, the two agree up to any power of the step size. If the…

Numerical Analysis · Mathematics 2022-07-21 Robert I McLachlan , Christian Offen

The maximum entropy principle is a powerful tool for solving underdetermined inverse problems. This paper considers the problem of discretizing a continuous distribution, which arises in various applied fields. We obtain the approximating…

Numerical Analysis · Mathematics 2020-08-05 Ken'ichiro Tanaka , Alexis Akira Toda

We consider elliptic variational inequalities generated by obstacle type problems with thin obstacles. For this class of problems, we deduce estimates of the distance (measured in terms of the natural energy norm) between the exact solution…

Analysis of PDEs · Mathematics 2018-09-18 Darya E. Apushkinskaya , Sergey I. Repin

How good is a triangulation as an approximation of a smooth curved surface or manifold? We provide bounds on the {\em interpolation error}, the error in the position of the surface, and the {\em normal error}, the error in the normal…

Computational Geometry · Computer Science 2019-11-11 Marc Khoury , Jonathan Richard Shewchuk

In this study, we employ Euler's method and Richardson's extrapolation to solve a triple integral, which is then transformed into a third-order initial value problem. Our objective is to resolve the computational challenges associated with…

Numerical Analysis · Mathematics 2026-02-17 Shubhangini Gupta , Prashant Sharma , Tamal Pramanick

Steplength thresholds for invariance preserving of three types of discretization methods on a polyhedron are considered. For Taylor approximation type discretization methods we prove that a valid steplength threshold can be obtained by…

Dynamical Systems · Mathematics 2016-09-06 Zoltán Horváth , Yunfei Song , and Tamás Terlaky

We introduce remarkable upper bounds for the interpolation error constants on triangles, which are sharp and given by simple formulas. These constants are crucial in analyzing interpolation errors, particularly those associated with the…

Numerical Analysis · Mathematics 2025-07-18 Kenta Kobayashi

This paper presents a unified metric-based framework for triangle geometric inequalities using barycentric coordinates. By interpreting classical inequalities as squared distances between points(a process termed metricization)we derive and…

Metric Geometry · Mathematics 2025-06-13 Xi Feng

The paper is concerned with a free boundary problem generated by the biharmonic operator and an obstacle. The main goal is to deduce a fully guaranteed upper bound of the difference between the exact minimizer u and any function…

Analysis of PDEs · Mathematics 2020-12-30 Darya E. Apushkinskaya , Sergey I. Repin

If several independent algorithms for a computer-calculated quantity exist, then one can expect their results (which differ because of numerical errors) to follow approximately Gaussian distribution. The mean of this distribution,…

General Mathematics · Mathematics 2017-07-03 Andrej Liptaj

Exponential integrability properties of numerical approximations are a key tool for establishing positive rates of strong and numerically weak convergence for a large class of nonlinear stochastic differential equations. It turns out that…

Numerical Analysis · Mathematics 2020-08-10 Martin Hutzenthaler , Arnulf Jentzen , Xiaojie Wang

In this paper, we propose two techniques to estimate the magnitude of a machine-zero residual for a given problem, which is the smallest possible residual that can be achieved when we solve a system of discretized equations. We estimate the…

Numerical Analysis · Mathematics 2020-07-15 Hiroaki Nishikawa
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