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We introduce an efficient algorithm for computing fractional integrals and derivatives and apply it for solving problems of the calculus of variations of fractional order. The proposed approximations are particularly useful for solving…

Numerical Analysis · Mathematics 2017-07-19 Salman Jahanshahi , Esmail Babolian , Delfim F. M. Torres , Alireza Vahidi

This paper proposes a new numerical method based on the Chebyshev wavelets (CWs) to solve the variable-order time fractional mobile-immobile advection-dispersion equation. To do this, a new operational matrix of variable-order fractional…

Numerical Analysis · Mathematics 2016-05-23 Mohammad Hossein Heydari

Approximation theorem is one of the most important aspects of numerical analysis that has evolved over the years with many different approaches. Some of the most popular approximation methods include the Lebesgue approximation theorem, the…

Numerical Analysis · Mathematics 2024-04-16 Ishmael N. Amartey

We give an algorithm for computing approximate PSD factorizations of nonnegative matrices. The running time of the algorithm is polynomial in the dimensions of the input matrix, but exponential in the PSD rank and the approximation error.…

Data Structures and Algorithms · Computer Science 2016-02-25 Amitabh Basu , Michael Dinitz , Xin Li

The inspiral of two compact objects in gravitational wave astronomy is described by a post-Newtonian expansion in powers of $(v/c)$. In most cases, it is believed that the post-Newtonian expansion is asymptotically divergent. A standard…

General Relativity and Quantum Cosmology · Physics 2011-12-15 Jérôme Carré , Edward K. Porter

Consider a rational family of planar rational curves in a certain region of interest. We are interested in finding an approximation to the implicit representation of the envelope. Since exact implicitization methods tend to be very costly,…

Numerical Analysis · Mathematics 2017-07-06 Oliver J D Barrowclough , Bert Jüttler , Tino Schulz

We present a new algorithm for finding isolated zeros of a system of real-valued functions in a bounded interval in $\mathbb{R}^n$. It uses the Chebyshev proxy method combined with a mixture of subdivision, reduction methods, and…

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

The ultimate goal of any numerical scheme for partial differential equations (PDEs) is to compute an approximation of user-prescribed accuracy at quasi-minimal computational time. To this end, algorithmically, the standard adaptive finite…

Numerical Analysis · Mathematics 2025-01-30 Philipp Bringmann , Michael Feischl , Ani Miraci , Dirk Praetorius , Julian Streitberger

In this article the error estimation of the moving least squares approximation is provided for functions in fractional order Sobolev spaces. The analysis presented in this paper extends the previous estimations and explains some unnoticed…

Numerical Analysis · Mathematics 2015-01-22 Davoud Mirzaei

Many high-dimensional uncertainty quantification problems are solved by polynomial dimensional decomposition (PDD), which represents Fourier-like series expansion in terms of random orthonormal polynomials with increasing dimensions. This…

Numerical Analysis · Mathematics 2018-04-06 Sharif Rahman

Estimating the Domain of Attraction (DA) of non-polynomial systems is a challenging problem. Taylor expansion is widely adopted for transforming a nonlinear analytic function into a polynomial function, but the performance of Taylor…

Systems and Control · Computer Science 2017-09-18 Dongkun Han , Dimitra Panagou

This work is concerned with approximating a trivariate function defined on a tensor-product domain via function evaluations. Combining tensorized Chebyshev interpolation with a Tucker decomposition of low multilinear rank yields function…

Numerical Analysis · Mathematics 2023-01-24 Sergey Dolgov , Daniel Kressner , Christoph Strössner

In the present paper, we consider large-scale differential Lyapunov matrix equations having a low rank constant term. We present two new approaches for the numerical resolution of such differential matrix equations. The first approach is…

Numerical Analysis · Mathematics 2017-05-30 M. Hached , K. Jbilou

When Newton's method, or Halley's method is used to approximate the $p${th} root of $1-z$, a sequence of rational functions is obtained. In this paper, a beautiful formula for these rational functions is proved in the square root case,…

Complex Variables · Mathematics 2012-09-18 Omran Kouba

We propose conformable Adomian decomposition method (CADM) for fractional partial differential equations (FPDEs). This method is a new Adomian decomposition method (ADM) based on conformable derivative operator (CDO) to solve FPDEs. At the…

General Mathematics · Mathematics 2017-04-11 Omer Acan , Dumitru Baleanu

There has recently been considerable interest in using a nonstandard piecewise approximation to formulate fractional order differential equations as difference equations that describe the same dynamical behaviour and are more amenable to a…

Numerical Analysis · Mathematics 2016-05-09 Christopher N Angstmann , Bruce I Henry , Anna V McGann

Sudakov form factors appear ubiquitously in factorized cross sections where they allow one to resum large logarithms to all orders in perturbation theory. Their exact evaluation requires numerical integrals over anomalous dimensions, which…

High Energy Physics - Phenomenology · Physics 2022-02-22 Markus A. Ebert

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

We obtain an expression for the error in the approximation of $f(A) \boldsymbol{b}$ and $\boldsymbol{b}^T f(A) \boldsymbol{b}$ with rational Krylov methods, where $A$ is a symmetric matrix, $\boldsymbol{b}$ is a vector and the function $f$…

Numerical Analysis · Mathematics 2023-11-07 Igor Simunec