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What is called "numerical reproducibility" is the problem of getting the same result when the scientific computation is run several times, either on the same machine or on different machines, with different types and numbers of processing…

Numerical Analysis · Computer Science 2014-05-20 Nathalie Revol , Philippe Théveny

We consider numerical solution of elliptic problems with heterogeneous diffusion coefficients containing thin highly conductive structures. Such problems arise e.g. in fractured porous media, reinforced materials, and electric circuits. The…

Numerical Analysis · Mathematics 2020-07-22 Fredrik Hellman , Axel Målqvist , Siyang Wang

The generalization of (super)integrable Euclidean classical Hamiltonian systems to the two-dimensional sphere and the hyperbolic space by preserving their (super)integrability properties is reviewed. The constant Gaussian curvature of the…

Mathematical Physics · Physics 2019-07-16 Angel Ballesteros , Alfonso Blasco , Francisco J. Herranz

Hybrid spectral-spatial representations are introduced to rapidly calculate periodic scalar and dyadic Green's functions of the Helmholtz equation for 2D and 3D configurations with a 1D (linear) periodicity. The presented schemes work…

Computational Physics · Physics 2015-05-13 Derek Van Orden , Vitaliy Lomakin

In this paper, we propose an incremental abstraction method for dynamically over-approximating nonlinear systems in a bounded domain by solving a sequence of linear programs, resulting in a sequence of affine upper and lower hyperplanes…

Optimization and Control · Mathematics 2020-04-06 Syed M. Hassaan , Mohammad Khajenejad , Spencer Jensen , Qiang Shen , Sze Zheng Yong

We present an approach to accelerate real-space electronic structure methods several fold, without loss of accuracy, by reducing the dimension of the discrete eigenproblem that must be solved. To accomplish this, we construct an efficient,…

Computational Physics · Physics 2018-05-01 Qimen Xu , Phanish Suryanarayana , John E. Pask

Classical algorithms in numerical analysis for numerical integration (quadrature/cubature) follow the principle of approximate and integrate: the integrand is approximated by a simple function (e.g. a polynomial), which is then integrated…

Numerical Analysis · Mathematics 2018-06-15 Yuji Nakatsukasa

Many parallel algorithms which solve basic problems in computer science use auxiliary space linear in the input to facilitate conflict-free computation. There has been significant work on improving these parallel algorithms to be in-place,…

Data Structures and Algorithms · Computer Science 2025-03-11 Chase Hutton , Adam Melrod

Two fundamental difficulties are encountered in the numerical evaluation of time-dependent layer potentials. One is the quadratic cost of history dependence, which has been successfully addressed by splitting the potentials into two parts -…

Numerical Analysis · Mathematics 2018-11-06 Leslie Greengard , Shidong Jiang , Jun Wang

We consider integration of functions with values in a partially ordered vector space, and two notions of extension of the space of integrable functions. Applying both extensions to the space of real valued simple functions on a measure…

Functional Analysis · Mathematics 2021-10-18 Arnoud van Rooij , Willem van Zuijlen

This paper introduces a new discrete fracture model accounting for non-isothermal compositional multiphase Darcy flows and complex networks of fractures with intersecting, immersed and non immersed fractures. The so called…

Numerical Analysis · Mathematics 2017-07-13 Feng Xing , Roland Masson , Simon Lopez

The need for efficient normal integration methods is driven by several computer vision tasks such as shape-from-shading, photometric stereo, deflectometry, etc. In the first part of this survey, we select the most important properties that…

Computer Vision and Pattern Recognition · Computer Science 2017-09-19 Yvain Quéau , Jean-Denis Durou , Jean-François Aujol

The efficient evaluation of high-dimensional integrals is of importance in both theoretical and practical fields of science, such as data science, statistical physics, and machine learning. However, exact computation methods suffer from the…

Statistics Theory · Mathematics 2017-12-15 Radislav Vaisman , Robert Salomone , Dirk P. Kroese

These notes are concerned with harmonic and holomorphic functions on Euclidean spaces, using quaternions and Clifford algebras in higher dimensions. The main themes are weak solutions, the mean-value property, and subharmonicity.

Classical Analysis and ODEs · Mathematics 2007-05-23 Stephen Semmes

The solutions to many problems in the mathematical, computational, and physical sciences often involve multidimensional integrals. A direct numerical evaluation of the integral incurs a computational cost that is exponential in the number…

Statistical Mechanics · Physics 2026-04-15 Ryan T. Grimm , Alexander J. Staat , Joel D. Eaves

Traditional problems in computational geometry involve aspects that are both discrete and continuous. One such example is nearest-neighbor searching, where the input is discrete, but the result depends on distances, which vary continuously.…

Computational Geometry · Computer Science 2023-08-21 Ahmed Abdelkader , David M. Mount

Implicitly described domains are a well established tool in the simulation of time dependent problems, e.g. using level-set methods. In order to solve partial differential equations on such domains, a range of numerical methods was…

Numerical Analysis · Computer Science 2016-01-16 Christian Engwer , Andreas Nüßing

In this paper we analyze the approximation of multivariate integrals over the Euclidean plane for functions which are analytic. We show explicit upper bounds which attain the exponential rate of convergence. We use an infinite grid with…

Numerical Analysis · Mathematics 2018-03-19 Dong T. P. Nguyen , Dirk Nuyens

Additional integral inequalities are obtained for integrals of the differences of subharmonic functions by Borel measures on balls in a multidimensional Euclidean space. These integrals are still estimated from above through the Nevanlinna…

Complex Variables · Mathematics 2021-07-20 B. N. Khabibullin

It is often possible to perform reduced order modelling by specifying linear subspace which accurately captures the dynamics of the system. This approach becomes especially appealing when linear subspace explicitly depends on parameters of…

Machine Learning · Computer Science 2026-04-17 Vladimir Fanaskov , Vladislav Trifonov , Alexander Rudikov , Ekaterina Muravleva , Ivan Oseledets