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Many subsurface engineering applications involve tight-coupling between fluid flow, solid deformation, fracturing, and similar processes. To better understand the complex interplay of different governing equations, and therefore design…

We study adaptive approximation algorithms for general multivariate linear problems where the sets of input functions are non-convex cones. While it is known that adaptive algorithms perform essentially no better than non-adaptive…

Numerical Analysis · Mathematics 2019-03-27 Yuhan Ding , Fred J. Hickernell , Peter Kritzer , Simon Mak

This paper considers the problem of approximating the inverse of the wave-equation Hessian, also called normal operator, in seismology and other types of wave-based imaging. An expansion scheme for the pseudodifferential symbol of the…

Numerical Analysis · Mathematics 2015-03-17 Laurent Demanet , Pierre-David Létourneau , Nicolas Boumal , Henri Calandra , Jiawei Chiu , Stanley Snelson

In this chapter we survey two topics that have recently been investigated in frame theory. First, we give an overview of the class of scalable frames. These are (finite) frames with the property that each frame vector can be rescaled in…

Functional Analysis · Mathematics 2016-01-19 Kasso A. Okoudjou

A formalism for the study of highly interacting electronic systems is presented. The proposed scheme is based on two key concepts: composite operators and algebra constraints. Composite field operators, that naturally appear as a…

Strongly Correlated Electrons · Physics 2009-11-10 Ferdinando Mancini

The dynamics of anisotropic particles are dictated by forces and torques that can be challenging to mathematically represent in computer simulations. Several data-driven approaches have been developed to approximate these interactions, but…

Soft Condensed Matter · Physics 2025-12-19 Mohammadreza Fakhraei , Michaela Bush , Chris A. Kieslich , Michael P. Howard

In this paper we show that there is a link between approximate Bayesian methods and prior robustness. We show that what is typically recognized as an approximation to the likelihood, either due to the simulated data as in the Approximate…

Methodology · Statistics 2020-04-03 Chaitanya Joshi , Fabrizio Ruggeri

The motivation of this paper is the development of an optimisation method for solving optimisation problems appearing in Chebyshev rational and generalised rational approximation problems, where the approximations are constructed as ratios…

Optimization and Control · Mathematics 2020-11-06 R. Díaz Millán , Nadezda Sukhorukova , Julien Ugon

We prove new upper bounds on the number of representations of rational numbers $\frac{m}{n}$ as a sum of $4$ unit fractions, giving five different regions, depending on the size of $m$ in terms of $n$. In particular, we improve the most…

Number Theory · Mathematics 2020-12-14 Christian Elsholtz , Stefan Planitzer

Differentiable physics provides a new approach for modeling and understanding the physical systems by pairing the new technology of differentiable programming with classical numerical methods for physical simulation. We survey the rapidly…

Machine Learning · Computer Science 2021-09-17 Bharath Ramsundar , Dilip Krishnamurthy , Venkatasubramanian Viswanathan

In this work, we use rational approximation to improve the accuracy of spectral solutions of differential equations. When working in the vicinity of solutions with singularities, spectral methods may fail their propagated spectral rate of…

Numerical Analysis · Mathematics 2024-04-01 João Carrilho de Matos , José M. A. Matos , Maria João Rodrigues

We discuss some topics concerning rational approximations in Quantum Chromodynamics, especially those related with the mathematical theory of Pad\'e Approximants. We focus on two kind of problems: the first one related with meromorphic…

High Energy Physics - Phenomenology · Physics 2010-10-27 Pere Masjuan

The discrete Fourier transform is approximated by summing over part of the terms with corresponding weights. The approximation reduces significantly the requirement for computer memory storage and enhances the numerical computation…

Strongly Correlated Electrons · Physics 2015-03-19 Xin-Zhong Yan

For some typical and widely used non-convex half-quadratic regularization models and the Ambrosio-Tortorelli approximate Mumford-Shah model, based on the Kurdyka-\L ojasiewicz analysis and the recent nonconvex proximal algorithms, we…

Optimization and Control · Mathematics 2021-07-30 Shengxiang Deng , Ismail Ben Ayed , Hongpeng Sun

The Kripke semantics of various logics arises via categorical dualities between a category of relational frames and their maps, and a category of algebras and logical homomorphisms. When the relational frames are considered as computational…

Logic in Computer Science · Computer Science 2026-05-08 Piotr Kozicki , Alex Kavvos

In this paper, we construct a type of interacting particle systems to approximate a class of stochastic different equations whose coefficients depend on the conditional probability distributions of the processes given partial observations.…

Probability · Mathematics 2024-03-27 Kai Du , Yunzhang Li , Yuyang Ye

Physics-based reinforcement learning tasks can benefit from simplified physics simulators as they potentially allow near-optimal policies to be learned in simulation. However, such simulators require the latent factors (e.g. mass, friction…

Machine Learning · Computer Science 2022-02-14 Buddhika Laknath Semage , Thommen George Karimpanal , Santu Rana , Svetha Venkatesh

If we cannot obtain all terms of a series, or if we cannot sum up a series, we have to turn to the partial sum approximation which approximate a function by the first several terms of the series. However, the partial sum approximation often…

General Mathematics · Mathematics 2021-10-06 Shi-Lin Li , Yuan-Yuan Liu , Wen-Du Li , Wu-Sheng Dai

We obtain approximation results for general positive linear operators satisfying mild conditions, when acting on discontinuous functions and absolutely continuous functions having discontinuous derivatives. The upper bounds, given in terms…

Probability · Mathematics 2024-10-29 José A. Adell , P. Garrancho , F. J. Martínez-Sánchez

The numerical solution of partial differential equations on high-dimensional domains gives rise to computationally challenging linear systems. When using standard discretization techniques, the size of the linear system grows exponentially…

Numerical Analysis · Mathematics 2015-08-13 Daniel Kressner , Michael Steinlechner , Bart Vandereycken
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